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#冲刺创作新星#PIE-engine APP 教程 ——太湖生态环境智能监测 原创
此星光明
发布于 2022-9-27 15:23
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本次开发教程是基于太湖生态环境智能监测系统，这个我们首先预加载我们所选的研究区，这次研究区是在太湖研究区，首秀按需要转化为几何，预加载持续时间，颜色图层预设，波段（MODIS、Landsat的QA波段去云函数）去云效果，然后UI界面的设定，这个界面非常长，所以设定了很多label标签、复选框、按钮和textbox，当然每一个部分都在一个面板，最后就是程序的嵌套和各个部分的，本此APP主要分为三个部分：第一部分就是太湖湖泊的监测、第二部分是基于Landsat数据月季年监测、第三部分太湖周围生态监测，最后是其它功能监测，这里每一个部分其实所用到的数据基本上上是相互独立的，这样有利于减少云计算的过程，减少运算压力。每一个部分都可以拿出来单独的使用，每一个部分都是一个单独的APP。
代码：
PIE-engine APP 教程 ——太湖生态环境智能监测系统/**
* @Name : 基于多源遥感的太湖生态环境智能监测系统
* @Time : 2020/7/21
* @Author : 中国矿业大学（北京）PIE小分队
* @Version : 1.0
* @E-mail : sun_yilin@yeah.net
* @Source
// 需要转换为geometry;
var lakes = pie.FeatureCollection("user/pieadmin/lakeDemo");
var XukouBay = lakes
.filter(pie.Filter.eq("NAME", "XukouBay"))
.first()
.geometry();
var EastLake = lakes
.filter(pie.Filter.eq("NAME", "EastLake"))
.first()
.geometry();
var ZhushanBay = lakes
.filter(pie.Filter.eq("NAME", "ZhushanBay"))
.first()
.geometry();
var WestLake = lakes
.filter(pie.Filter.eq("NAME", "WestLake"))
.first()
.geometry();
var SouthLake = lakes
.filter(pie.Filter.eq("NAME", "SouthLake"))
.first()
.geometry();
var MeiliangBay = lakes
.filter(pie.Filter.eq("NAME", "MeiliangBay"))
.first()
.geometry();
var GongBay = lakes.filter(pie.Filter.eq("NAME", "GongBay")).first().geometry();
var EntireLake = lakes
.filter(pie.Filter.eq("NAME", "EntireLake"))
.first()
.geometry();
var CentralLake = lakes
.filter(pie.Filter.eq("NAME", "CentralLake"))
.first()
.geometry();
var points = pie.FeatureCollection("user/pieadmin/lakeDemoPoints"); // 训练样本
var MOD11A2 = pie.ImageCollection("USGS/MOD11A2/006"); // 1km分辨率
Map.setCenter(120.22, 31.22, 10); // 太湖中心
var selectStartDate = "2020-08-01"; // 计算蓝藻水华初始时间
var selectEndDate = "2020-08-03";
var selectStartDate1 = "2016-05-01"; // 计算水域面积初始时间
var selectEndDate1 = "2020-09-30";
var selectStartDate2 = "2020-05-01"; // 影像显示初始时间
var selectEndDate2 = "2020-09-30";
var color1 = [
"#040274",
"#040281",
"#0502a3",
"#0502b8",
"#0502ce",
"#0502e6",
"#0602ff",
"#235cb1",
"#307ef3",
"#269db1",
"#30c8e2",
"#32d3ef",
"#3be285",
"#3ff38f",
"#86e26f",
"#3ae237",
"#b5e22e",
"#d6e21f",
"#fff705",
"#ffd611",
"#ffb613",
"#ff8b13",
"#ff6e08",
"#ff500d",
"#ff0000",
"#de0101",
"#c21301",
"#a71001",
"#911003",
];
var color2 = [
"#9AA5DF",
"#0602ff",
"#235cb1",
"#307ef3",
"#269db1",
"#30c8e2",
"#32d3ef",
"#3be285",
"#3ff38f",
"#86e26f",
];
var color3 = [
"#145999",
"#1b76cc",
"#1f86e6",
"#26aaea",
"#36b6eb",
"#4dc0eb",
"#60cfeb",
"#77daef",
"#b0dfef",
"#d1e5ee",
"#dce6f0",
"#e1e7f2",
"#dee6f1",
"#43c370",
"#44b772",
"#52c88e",
"#6fc993",
"#7ecb97",
"#acd2ad",
];
var color4 = [
"#145999",
"#1b76cc",
"#1f86e6",
"#26aaea",
"#36b6eb",
"#4dc0eb",
"#60cfeb",
"#77daef",
"#b0dfef",
"#d1e5ee",
"#dce6f0",
"#e1e7f2",
"#dee6f1",
"#43c370",
"#44b772",
"#52c88e",
"#6fc993",
"#7ecb97",
"#acd2ad",
"#d4c97a",
"#d0bc59",
"#d3b146",
"#c78f3c",
"#c3812d",
"#c5762b",
"#b95322",
"#ae4621",
"#ba6e78",
"#bc8fa9",
"#c7aac6",
"#dbcdde",
"#fffcff",
];
function generateVis(min, max, palette) {
var vis = {
min: min,
max: max,
palette: palette,
};
return vis;
}
function generateVisalg(min, max) {
return generateVis(min, max, color1);
}
function generateVisalgOccu(min, max) {
return generateVis(min, max, color2);
}
function addLegend(args) {
var title = args.title || "";
var labels = args.labels || [];
var step = args.step || 1;
var colors = args.colors || [];
// 图例
var data = {
title: title,
colors: colors,
labels: labels,
step: step,
};
var style = {
right: "100px",
bottom: "25px",
height: "70px",
width: "350px",
};
var legend = ui.Legend(data, style);
Map.addUI(legend);
}
function addLegendToMap(args) {
args["colors"] = color1;
addLegend(args);
}
function addOccuLegendToMap(args) {
args["colors"] = color2;
addLegend(args);
}
function addDem1LegendToMap(args) {
args["colors"] = color3;
addLegend(args);
}
function addDem2LegendToMap(args) {
args["colors"] = color4;
addLegend(args);
}
function addClassLegendToMap(args) {
var colors = ["#040274", "#269db1", "#3ae237", "#ff0000", "#911003"];
args["colors"] = colors;
addLegend(args);
}
var modisUtil = {
maskClouds: function (image) {
// 选择质量评估波段
var QA = image.select("state_1km");
// 1<<10表示二进制第10位，第10位表示有云
var bitMask = 1 << 10;
// 使得检测出含云像元置为0，进行掩膜去除含云
return image
.select([
"sur_refl_b01",
"sur_refl_b02",
"sur_refl_b05",
"sur_refl_b06",
"sur_refl_b07",
])
.updateMask(QA.bitwiseAnd(bitMask).eq(0));
},
getMOD09GA: function (startDate, endDate, roi) {
var MOD09GA = pie.ImageCollection("USGS/MOD09GA/006"); // 500米分辨率
var TerraGA = MOD09GA.filterDate(startDate, endDate) // 数据筛选
.filterBounds(roi)
.map(modisUtil.maskClouds);
return TerraGA;
},
// 大气校正步骤1
min567: function (image) {
var b05 = image.select("sur_refl_b05").multiply(0.0001); // 841-876nm, NIR(859)
var b06 = image.select("sur_refl_b06").multiply(0.0001); // 620-670nm, RED(645)
var b07 = image.select("sur_refl_b07").multiply(0.0001); // 1230-1250nm, SWIR1(1240)
var images = pie.ImageCollection().fromImages([b05, b06, b07]); // 重组影像
var min = images.min().rename("min"); // 获取最小值影像
return image.addBands(min);
},
// 大气校正步骤2
// multiply 0.0001 is needed because the data is scaled by 10000
jz: function (image) {
var b01 = image.select("sur_refl_b01").multiply(0.0001);
var b02 = image.select("sur_refl_b02").multiply(0.0001);
var b05 = image.select("sur_refl_b05").multiply(0.0001); // 841-876nm, NIR(859)
var min = image.select("min");
var b011 = b01.subtract(min); // 均减去min波段
var b021 = b02.subtract(min);
var b051 = b05.subtract(min);
return image.addBands(b011).addBands(b021).addBands(b051);
},
// 计算 FAI
funFAI: function (image) {
b02 = image.select("sur_refl_b02"); // 841-876nm, NIR(859)
b01 = image.select("sur_refl_b01"); // 620-670nm, RED(645)
b05 = image.select("sur_refl_b05"); // 1230-1250nm, SWIR1(1240)
var temp = b01.add(b05.subtract(b01).multiply(0.359663865546)); // 构建近红外波段
var Index = b02.subtract(temp).rename("FAI");
return Index;
},
// 建立 FAI 阈值掩膜.
mod_FAI: function (image) {
var FAI_threshold = image.select("FAI").rename("FAI_threshold");
FAI_threshold = FAI_threshold.updateMask(FAI_threshold.gte(-0.004));
return FAI_threshold;
},
// 统计发生频率
Binary: function (image) {
var algae = image.select("FAI").gte(-0.004).rename("alage"); // 大于等于-0.004为1，小于则为0
return image.addBands(algae);
},
//添加 IndexBands
addIndexBands: function (image) {
var FAI = modisUtil.funFAI(image);
return image.addBands(FAI);
},
};
var landsat8Util = {
// landsat8去云处理
removeCloud: function (image) {
// 数据去云处理
var qa = image.select("QA_PIXEL");
var cloudMask = qa
.bitwiseAnd(1 << 4)
.eq(0)
.and(qa.bitwiseAnd(1 << 3).eq(0));
return image.updateMask(cloudMask);
},
scaleImage: function (image) {
return image
.select(["B2", "B3", "B4", "B5", "B6", "B7"])
.multiply(0.0000275)
.subtract(0.2);
},
//加载Landsat 8 SR
alg: function (image) {
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var b6 = image.select("B6"); // swir1
// 计算ndvi
var lswi = b5.subtract(b6).divide(b5.add(b6)).clip(TH_boundary);
var fai = b5
.subtract(b4.add(b6.subtract(b4)).multiply(0.219895287958))
.clip(TH_boundary);
var alg = fai
.updateMask(fai.gte(0.05))
.updateMask(lswi.gte(0.63))
.rename("alg"); // 判定太湖蓝藻水华
return image.addBands(alg); // 添加蓝藻波段
},
turbidity: function (image) {
var b4 = image.select("B4");
var b3 = image.select("B3");
var tbd = b4
.subtract(b3)
.divide(b4.add(b3))
.power(2)
.multiply(3117.4)
.add(b4.subtract(b3).divide(b4.add(b3)).power(2).multiply(1083.6))
.add(106.17)
.rename("turbidity");
return image.addBands(tbd);
},
MD: function (image) {
var b4 = image.select("B4");
var b5 = image.select("B5");
//计算蓝藻密度
var md = b5
.divide(b4)
.power(2)
.multiply(1352)
.subtract(b5.divide(b4).multiply(159.08))
.add(192.87)
.rename("md");
return image.addBands(md);
},
cha: function (image) {
var b4 = image.select("B4");
var b5 = image.select("B5");
//计算叶绿素
var cha = b5.multiply(100.49).divide(b4).subtract(15.776).rename("cha");
return image.addBands(cha);
},
//ndvi
ndvi: function (image) {
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var ndvi = b5.subtract(b4).divide(b5.add(b4)).rename("ndvi");
return image.addBands(ndvi);
},
//fvc
fvc: function (image) {
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var ndvi = b5.subtract(b4).divide(b5.add(b4)).rename("ndvi");
// var ndvi_per = ndvi.reduceRegion(pie.Reducer.percentile([2, 98]), roi, 1000).get("ndvi");
// var ndvi_min = pie.Number(pie.Dictionary(ndvi_per).get("p2"));
// var ndvi_max = pie.Number(pie.Dictionary(ndvi_per).get("p98"));
var ndvi_min = ndvi.reduceRegion(pie.Reducer.min(), roi, 1000).get("ndvi");
ndvi_min = pie.Number(ndvi_min);
var ndvi_max = ndvi.reduceRegion(pie.Reducer.max(), roi, 1000).get("ndvi");
ndvi_max = pie.Number(ndvi_max);
var fvc = ndvi
.subtract(ndvi_min)
.divide(ndvi_max.subtract(ndvi_min))
.rename("fvc");
return image.addBands(fvc);
},
// wet
wet: function (image) {
var b2 = image.select("B2"); // blue
var b3 = image.select("B3"); // green
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var b6 = image.select("B6"); // swir1
var b7 = image.select("B7"); // swir1
var tem1 = b2.multiply(0.1511).add(b3.multiply(0.1973));
var tem2 = b4.multiply(0.3283).add(b5.multiply(0.3407));
var tem3 = b6.multiply(-0.7177).add(b7.multiply(-0.4559));
var wet_oli = tem1.add(tem2).subtract(tem3).rename("wet");
return image.addBands(wet_oli);
},
// ndbsi
ndbsi: function (image) {
var b2 = image.select("B2"); // blue
var b3 = image.select("B3"); // green
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var b6 = image.select("B6"); // swir1
// var b7 = image.select("B7"); // swir1
var tem1 = b6
.divide(b6.add(b5))
.multiply(2)
.subtract(b5.divide(b6.add(b5)))
.add(b3.divide(b3.add(b6)));
var tem2 = b6
.divide(b6.add(b5))
.multiply(2)
.add(b5.divide(b6.add(b5)))
.add(b3.divide(b3.add(b6)));
var ibi = tem1.divide(tem2);
var tem3 = b6.multiply(1.0).add(b4).subtract(b5.add(b2));
var tem4 = b6.multiply(1.0).add(b4).add(b5.add(b2));
var si = tem3.divide(tem4);
var ndbsi = ibi.add(si).divide(2).rename("ndbsi"); // get the ndbsi
return image.addBands(ndbsi);
},
//ndbi
ndbi: function (image) {
var b6 = image.select("B6");
var b5 = image.select("B5");
var ndbi = b6.subtract(b5).divide(b6.add(b5)).rename("ndbi");
return image.addBands(ndbi);
},
// evi
evi: function (image) {
var b2 = image.select("B2"); // blue
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var evi = b5
.subtract(b4)
.multiply(2.5)
.divide(b5.add(b4.multiply(6)).subtract(b2.multiply(7.5)).add(1))
.rename("evi");
return image.addBands(evi);
},
// mndwi
mndwi: function (image) {
var b6 = image.select("B6");
var b3 = image.select("B3");
var mndwi = b3.subtract(b6).divide(b3.add(b6)).rename("mndwi");
return image.addBands(mndwi);
},
// rvi
rvi: function (image) {
var b3 = image.select("B3"); // green
var b5 = image.select("B5"); // nir
var rvi = b3.divide(b5).rename("rvi");
return image.addBands(rvi);
},
// ndwi
ndwi: function (image) {
var b3 = image.select("B3"); // green
var b5 = image.select("B5"); // nir
var ndwi = b3.subtract(b5).divide(b3.add(b5)).rename("ndwi");
return image.addBands(ndwi);
},
trans: function (image) {
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
//计算叶绿素
//计算蓝藻密度
var alg = pie
.Image(-0.416)
.subtract(b5.log().multiply(0.587))
.subtract(b4.log().multiply(0.722));
var band = alg.exp().rename("trans"); // 计算指数并裁剪区域
return image.addBands(band); // 添加蓝藻波段
},
//加载Landsat 8 SR
ss: function (image) {
var b4 = image.select("B4"); // red
var b2 = image.select("B2"); // nir
//计算叶绿素
//计算蓝藻密度
var ss = b4.subtract(b2).divide(b4.add(b2)).rename("ss");
return image.addBands(ss); // 添加蓝藻波段
},
mndwiCa: function (image) {
var b4 = image.select("B4"); // red
var b5 = image.select("B5"); // nir
var b6 = image.select("B6"); // swir1
var b2 = image.select("B2"); // blue
var b3 = image.select("B3"); // green
var mndwi = b3.subtract(b6).divide(b3.add(b6)).rename("mndwi");
// var mask1 = mndwi.updateMask(mndwi.gt(ndvi).and(evi.lt(0.1))).rename('water');
return image.addBands(mndwi);
},
getLandsat8: function (startDate, endDate, roi, cloud = 30) {
var l8SR = pie.ImageCollection("LC08/02/SR");
var l8Col = l8SR
.filterDate(startDate, endDate)
.filterBounds(roi)
.filter(pie.Filter.lt("cloud_cover", cloud))
.map(landsat8Util.removeCloud)
.map(landsat8Util.scaleImage);
return l8Col;
},
};
function mergeMOD09GAData(startDate, endDate, roi, callback) {
var TerraGA = modisUtil.getMOD09GA(startDate, endDate, roi);
var dateList = TerraGA.reduceColumns(pie.Reducer.toList(), ["date"]);
dateList.getInfo(function (list) {
var dates = Array.from(new Set(list["list"]["date"]));
dates.sort();
callback(TerraGA, dates);
});
}
function globalTVDI(startDate, endDate, roi) {
// tvdi
var images = pie
.ImageCollection("BNU/GLOBAL_1KM_TVDI")
.filterBounds(roi)
.filterDate(startDate, endDate)
.select("B1")
.mean()
.clip(roi);
var tvdi = images.multiply(0.0001).rename("tvdi");
return tvdi;
}
function getDateList(startDate, endDate) {
var syear = parseInt(startDate.slice(0, 4)); // 获取起始日期前四位
var sother = startDate.slice(4, 10); // 获取起始日期后6位
var eyear = parseInt(endDate.slice(0, 4)); // 获取结束日期前四位
var eother = endDate.slice(4, 10); // 获取结束日期后6位
var dates = [];
if (syear > eyear) {
return dates;
}
for (var year = syear; year <= eyear; year++) {
dates.push({
start: year + sother,
end: year + eother,
});
}
return dates;
}
// UI界面
var panel = ui.Panel({
style: {
width: "400px"
},
}); // set the panel
var style1 = {"font-size": "20px", color: "green", "font-weight": "bold"}; // set the format
var style2 = {"font-size": "16px", color: "black", "font-weight": "bold"}; // set the format
var label1 = ui.Label("基于多源遥感的太湖生态环境智能监测系统 V1.0", style1); // edit the content
var label2 = ui.Label("制作人: PIE小分队.", style2);
var label3 = ui.Label("E-mail: sun_yilin@yeah.net.", style2);
panel.add(label1).add(label2).add(label3); // add the ui panel
// 设置目录
// 第一节，太湖湖泊监测
var labelA = ui.Label("一、太湖湖泊监测", {
"font-size": "20px",
"font-weight": "bold",
color: "red",
});
var labelA1 = ui.Label("1、基于MODIS数据逐日监测", {
"font-size": "18px",
"font-weight": "bold",
color: "red",
});
panel.add(labelA).add(labelA1);
// 1 选择区域
var label4 = ui.Label("1) 请选择一个区域", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
// 设置空的变量保存矢量.
var TH_boundary = [];
// Create a ui.Select widget for area selection.
var places = {
EntireLake: EntireLake,
CentralLake: CentralLake,
EastLake: EastLake,
SouthLake: SouthLake,
WestLake: WestLake,
GongBay: GongBay,
MeiliangBay: MeiliangBay,
ZhushanBay: ZhushanBay,
XukouBay: XukouBay,
};
// 设置选择区域
var selectArea = ui.Select({
items: Object.keys(places),
placeholder: "Click on the select",
value: null,
multiple: false,
onChange: function (key) {
// 存储选择的矢量边界
TH_boundary = places[key];
return TH_boundary;
},
});
panel.add(label4).add(selectArea);
// 显示研究区
function clickBtn() {
Map.addLayer(
TH_boundary, {color: "FF0000", fillColor: "00000000", width: 1},
"roi"
);
}
var btShow = ui.Button({
label: "显示研究区",
type: "success",
onClick: clickBtn,
});
var btNotShow = ui.Button({
label: "不显示研究区",
type: "success",
});
var btnPanelShow = ui.Panel({
widgets: [btShow, btNotShow],
layout: ui.Layout.flow("horizontal"),
});
panel.add(btnPanelShow);
// 2 选择时间
// 开始时间
var label5 = ui.Label("2) 请输入研究时间", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
function inputSDatea(value) {
selectStartDate = value;
}
var textBox1a = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectStartDate, //输入显示框显示数值
onChange: inputSDatea,
disabled: false,
});
var textboxName1a = ui.Label("开始时间：");
var textboxPanel1a = ui.Panel({
widgets: [textboxName1a, textBox1a],
layout: ui.Layout.flow("horizontal"),
});
panel.add(label5).add(textboxPanel1a);
// 结束时间
function inputEDatea(value) {
selectEndDate = value;
}
var textBox2a = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectEndDate, //输入显示框显示数值
onChange: inputEDatea,
disabled: false,
});
var textboxName2a = ui.Label("结束时间：");
var textboxPanel2a = ui.Panel({
widgets: [textboxName2a, textBox2a],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2a);
// 水华面积计算
var label6 = ui.Label("3) 逐日水华监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btArea = ui.Button({
label: "计算每日水华面积",
type: "success",
onClick: function () {
print("开始蓝藻水华面积计算");
mergeMOD09GAData(
selectStartDate,
selectEndDate,
TH_boundary,
function (TerraGA, dates) {
var count_images = [];
for (var i = 0; i < dates.length; i++) {
var FAI_threshold = TerraGA.filter(pie.Filter.eq("date", dates[i]))
.map(modisUtil.min567)
.map(modisUtil.jz)
.map(modisUtil.addIndexBands)
.select("FAI")
.mosaic()
.clip(TH_boundary); // 镶嵌并裁剪
var areaPixel = FAI_threshold.gte(-0.004); // 统计方法2：生成二值影像
var countPixel = areaPixel.reduceRegion(
pie.Reducer.sum(),
TH_boundary,
500
); // 计算像素数之和
//设置图层显示属性
var visalg = generateVisalg(-0.004, 0.25);
Map.addLayer(
FAI_threshold.updateMask(areaPixel),
visalg,
dates[i],
false
); // 去云影像，绘制图层
count_images.push(countPixel); // 记录数量
print("日期：", dates[i]); // 输出日期
print("数量：", countPixel); // 打印结果
}
// Map.playLayersAnimation(dates, 0.5, 100); // 动画演示
// 显示图例
addLegendToMap({
title: "FAI",
labels: ["-0.004", "0.25"],
step: 1,
});
// 通过判断设置图表属性
if (TH_boundary == EntireLake) {
var line_a = {
title: "太湖水域蓝藻面积动态变化",
legend: ["蓝藻面积"],
xAxisName: "日期",
yAxisName: "蓝藻像元数量（500*500m）",
chartType: "line",
yMin: 0,
yMax: 25000, // 当显示为全部区域时，上限为25000
smooth: true,
};
} else {
var line_a = {
title: "太湖水域蓝藻面积动态变化",
legend: ["蓝藻像元数量"],
xAxisName: "日期",
yAxisName: "蓝藻像元数量（500*500m）",
chartType: "line",
yMin: 0,
yMax: 2000, // 当显示为部分区域时，上限为2000
smooth: true,
};
}
// 显示折线图
var countChart = ui.Chart.image(count_images, dates, line_a);
print(countChart);
print("结束蓝藻水华面积计算");
}
);
},
});
panel.add(label6).add(btArea);
// 时间范围内蓝藻频率图
var label7 = ui.Label("4) 水华发生频率", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btOccurency = ui.Button({
label: "计算频率影像",
type: "success",
onClick: function () {
print("开始蓝藻频率计算");
var TerraGA = modisUtil.getMOD09GA(
selectStartDate,
selectEndDate,
TH_boundary
);
var BinarySum = TerraGA.map(modisUtil.min567)
.map(modisUtil.jz)
.map(modisUtil.addIndexBands)
.map(modisUtil.Binary)
.select("alage")
.sum()
.clip(TH_boundary); //对影像集中的像素求和
//设置图层显示属性
var visalgOccu = generateVisalgOccu(1, 10);
Map.addLayer(BinarySum, visalgOccu, "Occurrence Frequency");
//地图上显示图例组件
addOccuLegendToMap({
title: "蓝藻出现频率",
labels: ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"],
step: 1,
});
print("结束蓝藻频率计算");
},
});
panel.add(label7).add(btOccurency);
// 蓝藻发生最早时间
function generateDateImageCollection(TerraGA, dates) {
var images = [];
for (var i = 0; i < dates.length; i++) {
var image = TerraGA.filter(pie.Filter.eq("date", dates[i]))
.mosaic()
.clip(TH_boundary);
image = modisUtil.funFAI(image);
image = modisUtil.mod_FAI(image);
var dateImage = image
.where(image.gte(-0.004), i + 1)
.rename("dateImage"); // 设置数据值
images.push(dateImage);
}
var imageCollection = pie.ImageCollection.fromImages(images);
return imageCollection;
}
var label71 = ui.Label("5) 水华发生起始时间", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btEarlyTime = ui.Button({
label: "计算起始时间影像",
type: "success",
onClick: function () {
print("开始计算蓝藻发生最早时间");
mergeMOD09GAData(
selectStartDate,
selectEndDate,
TH_boundary,
function (TerraGA, dates) {
var imageCollection = generateDateImageCollection(TerraGA, dates);
var earlyImage = imageCollection.select("dateImage").min(); // 获得最小值天数影像
//设置图层显示属性
var visalgOccu = generateVisalgOccu(1, 10);
Map.addLayer(earlyImage, visalgOccu, "earlyImage");
// 显示图例
addOccuLegendToMap({
title: "水华发生起始时间（天）",
labels: ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"],
step: 1,
});
print("结束计算蓝藻发生最早时间");
}
);
},
});
panel.add(label71).add(btEarlyTime);
// 蓝藻发生的截止时间
var label72 = ui.Label("6) 水华发生结束时间", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btLatestTime = ui.Button({
label: "计算结束时间影像",
type: "success",
onClick: function () {
print("开始计算蓝藻消失时间");
mergeMOD09GAData(
selectStartDate,
selectEndDate,
TH_boundary,
function (TerraGA, dates) {
var imageCollection = generateDateImageCollection(TerraGA, dates);
var latestImage = imageCollection.select("dateImage").max(); // 获得最小值天数影像
//设置图层显示属性
var visalgOccu = generateVisalgOccu(1, 10);
Map.addLayer(latestImage, visalgOccu, "latestImage");
// 显示图例
addOccuLegendToMap({
title: "水华发生结束时间（天）",
labels: ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"],
step: 1,
});
print("结束计算蓝藻消失时间");
}
);
},
});
panel.add(label72).add(btLatestTime);
// 蓝藻发生的持续时间
var label73 = ui.Label("7) 水华发生持续时间", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btDurationTime = ui.Button({
label: "计算水华持续时间影像",
type: "success",
onClick: function () {
print("开始计算蓝藻持续时间");
mergeMOD09GAData(
selectStartDate,
selectEndDate,
TH_boundary,
function (TerraGA, dates) {
var imageCollection = generateDateImageCollection(TerraGA, dates);
var earlyImage = imageCollection.select("dateImage").min(); // 获得最小值天数影像
var latesImage = imageCollection.select("dateImage").max(); // 获得最大值天数影像
var durationImage = latesImage.subtract(earlyImage); // 获得蓝藻持续时间
//设置图层显示属性
var visalgOccu = generateVisalgOccu(1, 10);
Map.addLayer(durationImage, visalgOccu, "durationImage");
// 显示图例
addOccuLegendToMap({
title: "水华发生持续时间（天）",
labels: ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"],
step: 1,
});
print("结束计算蓝藻持续时间");
}
);
},
});
panel.add(label73).add(btDurationTime);
// 等级显示及直方图计算
var label74 = ui.Label("8) 蓝藻水华等级显示及统计", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btHIS = ui.Button({
label: "显示水华等级",
type: "success",
onClick: function () {
print("开始水华等级显示");
mergeMOD09GAData(
selectStartDate,
selectEndDate,
TH_boundary,
function (TerraGA, dates) {
var image = TerraGA.filter(pie.Filter.eq("date", dates[0]))
.map(modisUtil.addIndexBands)
.select("FAI")
.mosaic()
.clip(TH_boundary);
print(dates[0] + "等级统计结果:");
// Create a VCI level (Lv.2 - Lv.6) classification function.
var VCIs = [
{name: "VCI_Lv1", min: -0.004, max: 0, palette: "#040274"},
{name: "VCI_Lv2", min: 0, max: 0.05, palette: "#269db1"},
{name: "VCI_Lv3", min: 0.05, max: 0.1, palette: "#3ae237"},
{name: "VCI_Lv4", min: 0.1, max: 0.15, palette: "#ff0000"},
{name: "VCI_Lv5", min: 0.15, max: null, palette: "#911003"},
];
var count_images = []; // 保存数量
print("统计结果输出：");
for (var i = 0; i < VCIs.length; i++) {
var vci_image = image.rename(VCIs[i].name);
if (VCIs[i].min !== null) {
vci_image = vci_image.updateMask(vci_image.gte(VCIs[i].min));
}
if (VCIs[i].max !== null) {
vci_image = vci_image.updateMask(vci_image.lt(VCIs[i].max));
}
var vci_image_count = vci_image.reduceRegion(
pie.Reducer.count(),
TH_boundary,
500
);
print(vci_image_count);
count_images.push(vci_image_count);
Map.addLayer(vci_image, {palette: VCIs[i].palette}, VCIs[i].name);
}
// 显示图例
addClassLegendToMap({
title: "VCI",
labels: ["VCI1", "VCI2", "VCI3", "VCI4", "VCI5"],
step: 1,
});
var labelui = ui.Label(dates[0] + "等级分类显示", {
"font-size": "22px",
"font-weight": "bold",
color: "black",
}); //ui界面添加标题
Map.addUI(labelui);
// 绘制表格
// 设置图表属性
if (TH_boundary == EntireLake) {
var line_a = {
title: "太湖水域蓝藻等级面积统计",
legend: ["蓝藻面积"],
xAxisName: "等级",
yAxisName: "蓝藻像元数量（500*500m）",
chartType: "line",
yMin: 0,
yMax: 5000, // 当显示为全部区域时，上限为40000
smooth: true,
};
} else {
var line_a = {
title: "太湖水域蓝藻等级面积统计",
legend: ["蓝藻面积"],
xAxisName: "等级",
yAxisName: "蓝藻像元数量（500*500m）",
chartType: "line",
yMin: 0,
yMax: 2000, // 当显示为部分区域时，上限为4000
// smooth: true
};
}
// 显示折线图
var labels = ["VCI1", "VCI2", "VCI3", "VCI4", "VCI5"];
var countChart = ui.Chart.image(count_images, labels, line_a); // 方法2
print(countChart);
print("结束水华等级显示");
}
);
},
});
panel.add(label74).add(btHIS);
// 基于Landsat系列数据进行月季年监测
var labelA2 = ui.Label("2、基于Landsat数据月季年监测", {
"font-size": "18px",
"font-weight": "bold",
color: "red",
});
panel.add(labelA2);
var label4A = ui.Label("1) 请选择一个区域", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var selectAreaA = ui.Select({
items: Object.keys(places),
placeholder: "点击选择",
value: null,
multiple: false,
onChange: function (key) {
// 存储选择的矢量边界
TH_boundary = places[key];
return TH_boundary;
},
});
panel.add(label4A).add(selectAreaA);
var btShowA = ui.Button({
label: "显示研究区",
type: "success",
onClick: clickBtn,
});
var btNotShowA = ui.Button({
label: "不显示研究区",
type: "success",
});
var btnPanelShowA = ui.Panel({
widgets: [btShowA, btNotShowA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(btnPanelShowA);
// 2 选择时间
// 开始时间
var selectStartDateA = "2020-06-01"; // 设置初始值
var selectEndDateA = "2020-09-31";
var label5A = ui.Label("2) 请输入研究时间及云量", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
function inputSDateA(value) {
selectStartDateA = value;
}
var textBox1A = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectStartDateA, //输入显示框显示数值
onChange: inputSDateA,
disabled: false,
});
var textboxName1A = ui.Label("开始时间：");
var textboxPanel1A = ui.Panel({
widgets: [textboxName1A, textBox1A],
layout: ui.Layout.flow("horizontal"),
});
panel.add(label5A).add(textboxPanel1A);
// 结束时间
function inputEDateA(value) {
selectEndDateA = value;
}
var textBox2A = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectEndDateA, //输入显示框显示数值
onChange: inputEDateA,
disabled: false,
});
var textboxName2A = ui.Label("结束时间：");
var textboxPanel2A = ui.Panel({
widgets: [textboxName2A, textBox2A],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2A);
// 筛选云量 输入数值
var textboxName2AA = ui.Label("输入云量：");
function funInputNumberA(value) {
selectNumA = value; // 设置云量值
}
var selectNumA = 20; // 设置起始输入数据
var inputNumberA = ui.InputNumber({
placeholder: "请输入云量",
value: selectNumA,
min: 0,
max: 100,
step: 1,
onChange: funInputNumberA,
disabled: false,
});
var textboxPanel2AA = ui.Panel({
widgets: [textboxName2AA, inputNumberA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2AA);
// 蓝藻水华计算
var label81 = ui.Label("3) 月季年蓝藻水华监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btALG = ui.Button({
label: "计算水华影像",
type: "success",
onClick: function () {
print("开始水华面积计算");
//设置图层显示属性
var visalg = generateVisalg(-0.5, 0.5);
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start;
var endDate = dateList[i].end;
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.alg);
var alg_mean = l8Col.select("alg").mean().clip(TH_boundary); // 求取平均值
var layerName = startDate + "_" + endDate + "alg"; // 设置图层名称
layerDate.push(year);
var count = alg_mean.reduceRegion(pie.Reducer.count(), TH_boundary, 30); // 统计数量
print(count);
counts.push(count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻动态变化",
legend: ["蓝藻"],
xAxisName: "日期",
yAxisName: "蓝藻数量",
chartType: "line",
yMin: 0,
yMax: 10000000,
smooth: true,
};
// 显示折线图
var chart = ui.Chart.image(counts, layerDate, line_a);
print(chart);
// 图例
addLegendToMap({
title: "FAI",
labels: ["0", "0.05", "0.1", "0.15", "0.20", "0.25"],
step: 30,
});
print("结束水华面积计算");
},
});
panel.add(label81).add(btALG);
// 蓝藻浑浊度计算
var label8 = ui.Label("4) 月季年蓝藻浑浊度监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btHZ = ui.Button({
label: "计算蓝藻浑浊度影像",
type: "success",
onClick: function () {
print("开始计算蓝藻浑浊度");
//加载Landsat 8 SR
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var dateList = getDateList(selectStartDateA, selectEndDateA);
//设置图层显示属性
var visalg = generateVisalg(0, 1000);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.turbidity);
var alg_mean = l8Col.select("turbidity").max().clip(TH_boundary); // 求取最大值
var layerName = startDate + "_" + endDate + "turbidity"; // 设置图层名称
layerDate.push(year);
var mean_count = alg_mean
.select("turbidity")
.reduceRegion(pie.Reducer.mean(), TH_boundary, 30); // 统计数量
counts.push(mean_count);
print(mean_count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 显示图例
addLegendToMap({
title: "浑浊度",
labels: ["优", "差"],
step: 12,
});
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻浑浊度动态变化",
legend: ["蓝藻浑浊度"],
xAxisName: "日期",
yAxisName: "浑浊度均值）",
chartType: "line",
yMin: 0,
yMax: 1000,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算蓝藻浑浊度");
},
});
panel.add(label8).add(btHZ);
// 蓝藻密度计算
var label9 = ui.Label("5) 月季年蓝藻密度监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btMD = ui.Button({
label: "计算蓝藻密度影像",
type: "success",
onClick: function () {
print("开始计算蓝藻密度");
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var dateList = getDateList(selectStartDateA, selectEndDateA);
//设置图层显示属性
var visalg = generateVisalg(0, 1000);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
//加载Landsat 8 SR
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.MD);
var alg_mean = l8Col.select("md").mean().clip(TH_boundary); // 求取平均值
var layerName = startDate + "_" + endDate + "md"; // 设置图层名称
layerDate.push(year);
var mean_count = alg_mean
.select("md")
.reduceRegion(pie.Reducer.mean(), TH_boundary, 30); // 统计数量
counts.push(mean_count);
print(mean_count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 显示图例
addLegendToMap({
title: "密度",
labels: ["低", "高"],
step: 30,
});
// 绘制表格
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻密度动态变化",
legend: ["蓝藻浑浊度"],
xAxisName: "日期",
yAxisName: "密度均值）",
chartType: "line",
yMin: 0,
yMax: 100000,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算蓝藻密度");
},
});
panel.add(label9).add(btMD);
// 计算叶绿素a
var label81 = ui.Label("6) 月季年叶绿素监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btChla = ui.Button({
label: "计算叶绿素影像",
type: "success",
onClick: function () {
print("开始计算叶绿素");
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
//设置图层显示属性
var visalg = generateVisalg(-50, 1000);
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
//加载Landsat 8 SR
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.cha);
var alg_mean = l8Col.select("cha").mean().clip(TH_boundary); // 求取平均值
var layerName = startDate + "_" + endDate + "cha"; // 设置图层名称
layerDate.push(year);
var mean_count = alg_mean
.select("cha")
.reduceRegion(pie.Reducer.mean(), TH_boundary, 30); // 统计数量
counts.push(mean_count);
print(mean_count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 显示图例
addLegendToMap({
title: "叶绿素",
labels: ["低", "高"],
step: 30,
});
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻叶绿素动态变化",
legend: ["蓝藻浑浊度"],
xAxisName: "日期",
yAxisName: "叶绿素均值）",
chartType: "line",
yMin: 0,
yMax: 1000,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算叶绿素");
},
});
panel.add(label81).add(btChla);
// 透明度反演
var label82 = ui.Label("7) 月季年透明度监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btParence = ui.Button({
label: "计算透明度影像",
type: "success",
onClick: function () {
print("开始计算透明度");
//加载Landsat 8 SR
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
//设置图层显示属性
var visalg = generateVisalg(0, 200);
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.trans);
var alg_mean = l8Col.select("trans").mean().clip(TH_boundary); // 求取平均值
var layerName = startDate + "_" + endDate + "trans"; // 设置图层名称
layerDate.push(year);
var mean_count = alg_mean
.select("trans")
.reduceRegion(pie.Reducer.mean(), TH_boundary, 30); // 统计数量
counts.push(mean_count);
print("均值：", mean_count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 显示图例
addLegendToMap({title: "透明度", labels: ["低", "高"], step: 30});
// 绘制表格
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻透明度动态变化",
legend: ["蓝藻透明度"],
xAxisName: "日期",
yAxisName: "透明度均值",
chartType: "line",
yMin: 0,
yMax: 1000,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算透明度");
},
});
panel.add(label82).add(btParence);
// 归一化悬浮物指数
var label83 = ui.Label("8) 月季年归一化悬浊物监测", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btSS = ui.Button({
label: "计算归一化悬浊物影像",
type: "success",
onClick: function () {
print("开始计算归一化悬浊物");
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
//设置图层显示属性
var visalg = generateVisalg(0, 1);
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.ss);
var alg_mean = l8Col.select("ss").mean().clip(TH_boundary); // 求取平均值
var layerName = startDate + "_" + endDate + "ss"; // 设置图层名称
layerDate.push(year);
var mean_count = alg_mean
.select("ss")
.reduceRegion(pie.Reducer.mean(), TH_boundary, 30); // 统计数量
counts.push(mean_count);
print(mean_count);
Map.addLayer(alg_mean, visalg, layerName); // 加载图层
}
// 显示图例
addLegendToMap({title: "归一化悬浊物", labels: ["低", "高"], step: 30});
// 绘制表格
// 设置图表属性
var line_a = {
title: "太湖水域蓝藻归一化悬浊物动态变化",
legend: ["归一化悬浊物"],
xAxisName: "日期",
yAxisName: "归一化悬浊物均值）",
chartType: "line",
yMin: 0,
yMax: 1,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算归一化悬浊物");
},
});
panel.add(label83).add(btSS);
// 计算水域面积变化
var label11 = ui.Label("8) 太湖水域面积", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btMJ = ui.Button({
label: "计算水域面积",
type: "success",
onClick: function () {
print("开始水华面积计算");
var waterArea = []; //存储面积
var yearDate = []; // 存储时间
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
TH_boundary,
selectNumA
);
l8Col = l8Col.map(landsat8Util.mndwiCa);
var mndwi_max = l8Col.select("mndwi").max().clip(TH_boundary);
var l8_water = mndwi_max.gt(0.1);
Map.addLayer(l8_water, {palette: "#0602ff"}, year + "water");
//根据计算的水体数据计算面积
var areaImage = mndwi_max.pixelArea().multiply(l8_water.gt(0.1));
var water = areaImage.reduceRegion(pie.Reducer.sum(), TH_boundary, 30);
var water_area = pie.Number(water.get("constant")).divide(1000000);
waterArea.push(water_area.getInfo()); // 保存面积,需用getInfo
yearDate.push(year); // 存储年份
print(
year + "水体面积是（单位：平方千米）: ",
pie.Number(water.get("constant")).divide(1000000)
); //进行单位换算
}
// 设置图表属性
var line_options = {
title: "太湖水域面积动态变化",
legend: ["水域面积"],
xAxis: yearDate,
xAxisName: "年",
yAxisName: "平方千米",
series: [waterArea],
chartType: "line",
};
//调用绘制折线图的方法
var chart = ui.Chart.array(line_options);
print(chart);
//动画显示
Map.playLayersAnimation(dates, 0.5, -1);
},
});
panel.add(label11).add(btMJ);
var label111 = ui.Label("9) 太湖水域温度", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btLST = ui.Button({
label: "计算水域温度",
type: "success",
onClick: function () {
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
//设置图层显示属性
var visalg = generateVisalg(0, 40);
var dateList = getDateList(selectStartDateA, selectEndDateA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
// 筛选影像
var rawLST = MOD11A2.filterDate(startDate, endDate)
.filterBounds(TH_boundary)
.select("LST_Day_1km")
.mean()
.clip(TH_boundary);
var lst = rawLST.select("LST_Day_1km").multiply(0.02).subtract(273.15);
var layerName = startDate + "_" + endDate + "LSTmean";
Map.addLayer(lst, visalg, layerName);
var mean = lst.reduceRegion(pie.Reducer.mean(), TH_boundary, 1000); // 统计温度均值
counts.push(mean);
layerDate.push(year);
}
// 显示图例
addLegendToMap({
title: "湖面温度",
labels: ["0", "10 ", " 20", "30"],
step: 12,
});
// 绘制表格
// 设置图表属性
var line_a = {
title: "太湖水域温度均值变化",
legend: ["温度均值"],
xAxisName: "年份",
yAxisName: "温度均值(℃)",
chartType: "line",
yMin: 0,
yMax: 40,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
},
});
panel.add(label111).add(btLST);
// 第二节，太湖周围生态监测
// 基于Landsat系列数据计算太湖周围生态指数
var labelB = ui.Label("二、太湖周围生态监测", {
"font-size": "20px",
"font-weight": "bold",
color: "red",
});
panel.add(labelB);
var label1B1 = ui.Label("1、指数计算", {
"font-size": "18px",
"font-weight": "bold",
color: "red",
});
panel.add(label1B1);
// 2 选择时间
// 开始时间
var selectStartDateAA = "2014-03-01"; // 设置初始值
var selectEndDateAA = "2020-10-31";
var label5AA = ui.Label("1) 请输入研究时间及缓冲距离", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
function inputSDateAA(value) {
selectStartDateAA = value;
}
var textBox1AA = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectStartDateAA, //输入显示框显示数值
onChange: inputSDateAA,
disabled: false,
});
var textboxName1AA = ui.Label("开始时间：");
var textboxPanel1AA = ui.Panel({
widgets: [textboxName1AA, textBox1AA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(label5AA).add(textboxPanel1AA);
// 结束时间
function inputEDateAA(value) {
selectEndDateAA = value;
}
var textBox2AA = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectEndDateAA, //输入显示框显示数值
onChange: inputEDateAA,
disabled: false,
});
var textboxName2AA = ui.Label("结束时间：");
var textboxPanel2AA = ui.Panel({
widgets: [textboxName2AA, textBox2AA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2AA);
//获取缓冲区
// 输入数值
var textboxName2AAA = ui.Label("请输入缓冲距离（km）：");
function funInputNumberAA(value) {
selectNumAA = value; // 设置值
}
var selectNumAA = 30; // 设置起始输入数据
var inputNumberAA = ui.InputNumber({
placeholder: "请输入缓冲距离",
value: selectNumAA,
min: 0,
max: 100,
step: 1,
onChange: funInputNumberAA,
disabled: false,
});
var textboxPanel2AA = ui.Panel({
widgets: [textboxName2AAA, inputNumberAA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2AA);
// 1缓冲区温度反演
var label11 = ui.Label("2) 温度显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btlst = ui.Button({
label: "计算温度",
type: "success",
onClick: function () {
print("开始计算温度");
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var layers = [];
//设置图层显示属性
var visalg = generateVisalg(0, 40);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
// 筛选影像
var rawLST = MOD11A2.filterDate(startDate, endDate)
.filterBounds(Th_buffer_dif)
.select("LST_Day_1km")
.mean()
.clip(Th_buffer_dif);
var lst = rawLST.select("LST_Day_1km").multiply(0.02).subtract(273.15);
var layerName = startDate + "_" + endDate + "mean";
layers.push(layerName);
Map.addLayer(lst, visalg, layerName);
var mean = lst.reduceRegion(pie.Reducer.mean(), Th_buffer_dif, 1000); // 统计温度均值
print(mean);
counts.push(mean);
layerDate.push(year);
}
// 显示图例
addLegendToMap({
title: "湖面温度",
labels: ["0", "10 ", " 20", "30", "40"],
step: 12,
});
// 绘制表格
// 设置图表属性
var line_a = {
title: "太湖水域周围" + selectNumAA + "km温度均值变化",
legend: ["温度均值(℃)"],
xAxisName: "年份",
yAxisName: "温度均值(℃)",
chartType: "line",
yMin: 0,
yMax: 40,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
//动画显示
Map.playLayersAnimation(layers, 0.5, -1);
print("结束计算温度");
},
});
panel.add(label11).add(btlst);
// 缓冲区绿度反演
var label12 = ui.Label("3) NDVI显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btNdvi = ui.Button({
label: "计算NDVI",
type: "success",
onClick: function () {
print("开始计算NDVI");
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var layers = [];
//设置图层显示属性
var visalg = generateVisalg(-1, 1);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
// 筛选影像
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
Th_buffer_dif,
20
);
l8Col = l8Col
.map(landsat8Util.ndvi)
.select("ndvi")
.max()
.clip(Th_buffer_dif);
var layerName = startDate + "_" + endDate + "mean";
layers.push(layerName);
Map.addLayer(l8Col, visalg, layerName);
var mean = l8Col
.select("ndvi")
.reduceRegion(pie.Reducer.mean(), Th_buffer_dif, 30); // 统计ndvi均值
print(mean);
counts.push(mean);
layerDate.push(year);
}
// 显示图例
addLegendToMap({
title: "NDVI",
labels: ["-1", "-0.5 ", " 0", "0.5", "1"],
step: 12,
});
// 设置图表属性
var line_a = {
title: "太湖水域周围" + selectNumAA + "kmNDVI均值变化",
legend: ["NDVI均值"],
xAxisName: "年份",
yAxisName: "NDVI均值",
chartType: "line",
yMin: 0,
yMax: 1,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
//动画显示
Map.playLayersAnimation(layers, 0.5, -1);
print("结束计算NDVI");
},
});
panel.add(label12).add(btNdvi);
// 计算植被覆盖度
var label121 = ui.Label("4) 植被覆盖度显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btfvc = ui.Button({
label: "计算FVC",
type: "success",
onClick: function () {
print("开始计算FVC");
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var layers = [];
//设置图层显示属性
var visalg = generateVisalg(0, 1);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
var startDate = dateList[0].start; // 组合开始日期
var endDate = dateList[0].end; // 组合结束日期
// 筛选影像
var l8Col = landsat8Util.getLandsat8(startDate, endDate, Th_buffer_dif, 20);
var ndvi = l8Col
.map(landsat8Util.ndvi)
.select("ndvi")
.max()
.clip(Th_buffer_dif);
var result = pie.Dictionary(
ndvi.reduceRegion(pie.Reducer.percentile([5, 95]), Th_buffer_dif, 30)
);
var ndvi_p5 = pie.Dictionary(result.get("ndvi")).getNumber("p5").getInfo();
//反演区域植被覆盖度并加载
var fvc = ndvi.subtract(ndvi_p5).divide(1.2).rename("fvc");
var layerName = startDate + "_" + endDate + "mean";
layers.push(layerName);
Map.addLayer(fvc.select("fvc"), visalg, layerName);
var mean = fvc
.select("fvc")
.reduceRegion(pie.Reducer.mean(), Th_buffer_dif, 30); // 统计ndvi均值
print("fvc均值：", mean);
// 显示图例
addLegendToMap({
title: "FVC",
labels: ["0", "0.2 ", " 0.4", "0.6", "0.8", "1"],
step: 12,
});
print("结束计算FVC");
},
});
panel.add(label121).add(btfvc);
// 计算湿度
var label13 = ui.Label("5) Wet显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btWet = ui.Button({
label: "计算Wet",
type: "success",
onClick: function () {
print("开始计算wet");
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
var layers = [];
//设置图层显示属性
var visalg = generateVisalg(-0.5, 0.5);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
// 筛选影像
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
Th_buffer_dif,
20
);
var wet = landsat8Util.wet(
l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7"]).mean()
);
wet = wet.select("wet").clip(Th_buffer_dif);
var layerName = startDate + "_" + endDate + "mean";
layers.push(layerName);
Map.addLayer(wet, visalg, layerName);
var mean = wet
.select("wet")
.reduceRegion(pie.Reducer.mean(), Th_buffer_dif, 30); // 统计WET均值
print("均值：", mean);
counts.push(mean);
layerDate.push(year);
}
// 显示图例
addLegendToMap({
title: "Wet",
labels: ["-0.5", "-0.25 ", " 0", "0.25", "0.5"],
step: 12,
});
// 设置图表属性
var line_a = {
title: "太湖水域周围" + selectNumAA + "kmWet均值变化",
legend: ["Wet均值"],
xAxisName: "年份",
yAxisName: "Wet均值",
chartType: "line",
yMin: -0.5,
yMax: 0.5,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
//动画显示
// Map.playLayersAnimation(layers, 0.5, -1);
print("结束计算Wet");
},
});
panel.add(label13).add(btWet);
// 城镇建筑指数
var label14 = ui.Label("6) NDBSI显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btNdbsi = ui.Button({
label: "计算NDBSI",
type: "success",
onClick: function () {
print("开始计算NDBSI");
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var layerDate = []; //存储年份
var counts = []; // 存储像元数量
//设置图层显示属性
var visalg = generateVisalg(-0.1, 1);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
// 筛选影像
var l8Col = landsat8Util.getLandsat8(
startDate,
endDate,
Th_buffer_dif,
selectNumA
);
l8Col = l8Col.select(["B2", "B3", "B4", "B5", "B6"]).mean();
var ndbsi = landsat8Util.ndbsi(l8Col).select("ndbsi").clip(Th_buffer_dif);
var layerName = startDate + "_" + endDate + "mean";
Map.addLayer(ndbsi, visalg, layerName);
var mean = ndbsi.reduceRegion(pie.Reducer.mean(), Th_buffer_dif, 30); // 统计ndvi均值
print("均值：", mean);
counts.push(mean);
layerDate.push(year);
}
// 显示图例
addLegendToMap({
title: "NDBSI",
labels: ["0", "0.2 ", " 0.4", "0.6", "0.8", "1"],
step: 12,
});
// 设置图表属性
var line_a = {
title: "太湖水域周围" + selectNumAA + "kmNDBSI均值变化",
legend: ["Wet均值"],
xAxisName: "年份",
yAxisName: "NDBSI均值",
chartType: "line",
yMin: -0.1,
yMax: 1,
smooth: true,
};
// 显示折线图
var countChart = ui.Chart.image(counts, layerDate, line_a);
print(countChart);
print("结束计算NDBSI");
},
});
panel.add(label14).add(btNdbsi);
// 监督分类
// 第二节，土地利用监测
// 基于Landsat系列数据对太湖周边地区进行土地利用监测
var label1B2 = ui.Label("2、土地利用监测", {
"font-size": "18px",
"font-weight": "bold",
color: "red",
});
panel.add(label1B2);
function classifyLand(tag) {
Map.centerObject(EntireLake, 11);
var counts = []; // 存储像元数量
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(startDate, endDate, Th_buffer_dif, 10);
var image = l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7"]).median();
image = landsat8Util.ndvi(image);
image = landsat8Util.mndwi(image);
image = image.clip(Th_buffer_dif);
// 获得训练样本，并且按照8:2分成训练样本和验证样本
var sampleFeatureCollection = image.sampleRegions(
points,
["landcover"],
30
);
sampleFeatureCollection = sampleFeatureCollection.filter(pie.Filter.notNull(["B2",
"B3",
"B4",
"B5",
"B6",
"B7",
"ndvi",
"mndwi"
]))
sampleFeatureCollection = sampleFeatureCollection.randomColumn("random");
var sampleTrainingFeatures = sampleFeatureCollection.filter(
pie.Filter.lte("random", 0.8)
);
var sampleTestingFeatures = sampleFeatureCollection.filter(
pie.Filter.gt("random", 0.8)
);
var methods = {
rTrees: pie.Classifier.rTrees,
svm: pie.Classifier.svm,
normalBayes: pie.Classifier.normalBayes,
};
// 构建RT分类器，并训练数据
var classifer = methods[tag]().train(sampleTrainingFeatures, "landcover", [
"B2",
"B3",
"B4",
"B5",
"B6",
"B7",
"ndvi",
"mndwi",
]);
// 影像分类，并加载显示
var resultImage = image.classify(classifer, "classifyA");
// 形态学运算
resultImage = resultImage.focal_max(1); // 膨胀运算
resultImage = resultImage.focal_min(1); //腐蚀运算
var visParam = {
opacity: 1,
uniqueValue: "1,2,3,4,5",
palette: "#040274,#269db1,#3ae237,#ff0000,#911003",
};
Map.addLayer(resultImage, visParam, year + "-" + tag + "-Image");
Map.addLayer(
image, {min: 0, max: 0.3, bands: ["B4", "B3", "B2"]},
year + "-Original Image"
);
var counts = [];
for (var i = 1; i <= 5; i++) {
var areaImg = pie.Image().pixelArea();
var count = areaImg
.multiply(resultImage.eq(i))
.reduceRegion(pie.Reducer.sum(), Th_buffer_dif, 30); // 类别数量统计
counts.push(count);
}
// 设置图表属性
var line_a = {
title: dateList[i].start.slice(0, 4) + "年太湖水域周边地物面积统计",
legend: ["不同地物面积"],
xAxisName: "类别",
yAxisName: "面积（平方千米）",
chartType: "line",
yMin: 0,
yMax: 20000,
};
var labels = ["水体", "建设用地", "林地", "耕地", "裸地"];
var countChart = ui.Chart.image(counts, labels, line_a); // 方法2
print(countChart);
}
// 添加图例
addLegend({
title: "土地利用分类",
colors: ["#040274", "#269db1", "#3ae237", "#ff0000", "#911003"],
labels: ["水体", "建设用地", "林地", "耕地", "裸地"],
step: 1,
});
// 评估训练样本的精度
var checkM = classifer.confusionMatrix();
print("训练矩阵：", checkM);
print(
"训练矩阵-ACC系数：",
checkM.acc(),
"训练矩阵-Kappa系数：",
checkM.kappa()
);
// 评估验证样本的精度
var predictResult = sampleTestingFeatures.classify(
classifer,
"classification"
);
var errorM = predictResult.errorMatrix("landcover", "classification");
print("验证矩阵：", errorM);
print(
"验证矩阵-ACC系数：",
errorM.acc(),
"验证矩阵-Kappa系数：",
errorM.kappa()
);
}
// 城市建筑用地情况
var label15 = ui.Label("1) 随机森林分类", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btClass = ui.Button({
label: "开始分类",
type: "success",
onClick: function () {
// 获得样本点
print("开始随机森林分类");
classifyLand("rTrees");
print("结束随机森林分类");
},
});
panel.add(label15).add(btClass);
// 支持向量机分类
var label16 = ui.Label("2) 支持向量机分类", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btSVCClass = ui.Button({
label: "开始分类",
type: "success",
onClick: function () {
// 获得样本点
print("开始支持向量机分类");
classifyLand("svm");
print("结束支持向量机分类");
},
});
panel.add(label16).add(btSVCClass);
// 正太贝叶斯分类
var label17 = ui.Label("3) 正太贝叶斯分类", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
var btNBClass = ui.Button({
label: "开始分类",
type: "success",
onClick: function () {
// 获得样本点
print("开始正太贝叶斯分类");
classifyLand("normalBayes");
print("结束正太贝叶斯分类");
},
});
panel.add(label17).add(btNBClass);
// k-mean分类
var label18 = ui.Label("4) 非监督分类", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label18);
function clusterLand(tag) {
Map.centerObject(EntireLake, 11);
var Th_buffer_1km = EntireLake.buffer(selectNumAA * 1000);
var Th_buffer_dif = Th_buffer_1km.difference(EntireLake);
var dateList = getDateList(selectStartDateAA, selectEndDateAA);
// 筛选影像
for (var i = 0; i < dateList.length; i++) {
var startDate = dateList[i].start; // 组合开始日期
var endDate = dateList[i].end; // 组合结束日期
var year = new Date(startDate).getFullYear();
var l8Col = landsat8Util.getLandsat8(startDate, endDate, Th_buffer_dif, 10);
var image = l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7"]).median();
var ndvi = landsat8Util.ndvi(image).select("ndvi");
var mndwi = landsat8Util.mndwi(image).select("mndwi");
image = image.addBands(ndvi).addBands(mndwi).clip(Th_buffer_dif);
// 随机采集样本，30米下采集200个点分类
var training = image.sample(Th_buffer_dif, 30, "", "", 200);
var methods = {
kMeans: pie.Clusterer.kMeans,
em: pie.Clusterer.em,
};
// 创建分类器，并进行训练
var cluster = methods[tag](selectNumAAA).train(training);
// 分类数据并显示
var resultImage = image.cluster(cluster, "clusterA");
// 形态学运算
resultImage = resultImage.focal_max(1); // 膨胀运算
resultImage = resultImage.focal_min(1); //腐蚀运算
var visParam = {
opacity: 1,
classify: "0,1,2,3,4,5,6",
palette: "FF0000,00FFFF,00FF00,FF00FF,0000FF,FFFF00,FF8000,00AAFF",
};
Map.addLayer(resultImage, visParam, year + "-" + tag + "-resultImage", false);
var vis = {
min: 0,
max: 0.3,
opacity: 0.9,
bands: ["B4", "B3", "B2"],
};
Map.addLayer(image.select(["B4", "B3", "B2"]), vis, year + "-Landsat8 RGB", false);
}
}
//获取类别
// 输入数值
var textboxName2AAAA = ui.Label("请输入k：");
function funInputNumberAAA(value) {
selectNumAAA = value; // 设置值
}
var selectNumAAA = 2; // 设置起始输入数据
var inputNumberAAA = ui.InputNumber({
placeholder: "请输入k",
value: selectNumAAA,
min: 0,
max: 5,
step: 1,
onChange: funInputNumberAAA,
disabled: false,
});
var textboxPanel2AAA = ui.Panel({
widgets: [textboxName2AAAA, inputNumberAAA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel2AAA);
var btkmeanClass = ui.Button({
label: "k-means分类",
type: "success",
onClick: function () {
// 获得样本点
print("开始k-means分类");
clusterLand("kMeans");
print("结束k-means分类");
},
});
panel.add(btkmeanClass);
// 最大期望算法
var btemClass = ui.Button({
label: "最大期望算法",
type: "success",
onClick: function () {
// 获得样本点
print("开始最大期望分类");
clusterLand("em");
print("结束最大期望分类");
},
});
panel.add(btemClass);
// 第三节，其他功能
var labelC = ui.Label("三、其他功能", {
"font-size": "20px",
"font-weight": "bold",
color: "red",
});
panel.add(labelC);
var label510 = ui.Label("1) 请输入行政区划", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label510);
var label5101 = ui.Label(
"[注]：行政区划网址：http://www.mca.gov.cn/article/sj/xzqh/2020/", {
"font-size": "16px",
"font-weight": "bold",
color: "black"
}
);
panel.add(label5101);
// 单选按钮，选择省、城市、县
var selectDis = "县行政区划";
function funRadio(value) {
selectDis = value;
}
var radio = ui.Radio({
label: ["省行政区划", "县行政区划"],
value: selectDis,
onChange: funRadio,
disabled: false,
});
var textboxName31 = ui.Label("行政级别：");
var textboxPanel31 = ui.Panel({
widgets: [textboxName31, radio],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel31);
//定义常量参数
var layerKey = null;
var roiKey = null;
var selectCode = "110114";
// 输入行政区划
//获取指定的ROI数据
function getROI(code) {
if (selectDis == "县行政区划") {
var fCol = pie.FeatureCollection("NGCC/CHINA_COUNTY_BOUNDARY");
} else if (selectDis == "省行政区划") {
var fCol = pie.FeatureCollection("NGCC/CHINA_PROVINCE_BOUNDARY");
}
var roi = fCol
.filter(pie.Filter.eq("code", parseInt(code)))
.first()
.geometry();
if (roiKey != null) {
Map.removeLayer(roiKey);
}
var geometry = roi.centroid(); // 中心点
var roiPoint = pie.FeatureCollection(pie.Feature(geometry));
Map.addLayer(
roiPoint, {color: "00AAFF", fillColor: "00000000"},
"centroidPoint",
true
);
Map.centerObject(geometry, 10);
var label1a = ui.Label("行政区划代码:" + code, {
"font-size": "20px",
"font-weight": "bold",
color: "black",
});
Map.addUI(label1a);
roiKey = Map.addLayer(
roi, {color: "#ff0000", fillColor: "#00000000"},
"roi"
);
return roi;
}
function inputArea(value) {
if (value > 99999) {
selectCode = value;
var roi = getROI(selectCode);
print("行政区划的面积是（平方千米）：");
print(roi.area().divide(1000000)); // 计算面积
}
}
var textBox3 = ui.TextBox({
placeholder: "请输入行政区划编码",
value: selectCode,
onChange: inputArea,
disabled: false,
});
var textboxName3 = ui.Label("行政区划：");
var textboxPanel3 = ui.Panel({
widgets: [textboxName3, textBox3],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel3);
// 导出数据
function clickBtExpShp() {
var roi = getROI(selectCode);
Export.table({
collection: roi,
description: "ExportShp" + selectCode,
assetId: selectCode + "shp",
});
}
var btExpShp = ui.Button({
label: "导出行政边界",
type: "success",
onClick: clickBtExpShp,
});
panel.add(btExpShp);
// 输入时间
// 开始时间
var label511 = ui.Label("2) 请输入查询时间", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
function inputSDate(value) {
selectStartDate2 = value;
}
var textBox11 = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectStartDate2, //输入显示框显示数值
onChange: inputSDate,
disabled: false,
});
var textboxName11 = ui.Label("开始时间：");
var textboxPanel1 = ui.Panel({
widgets: [textboxName11, textBox11],
layout: ui.Layout.flow("horizontal"),
});
panel.add(label511).add(textboxPanel1);
// 结束时间
function inputEDate(value) {
selectEndDate2 = value;
}
var textBox21 = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectEndDate2, //输入显示框显示数值
onChange: inputEDate,
disabled: false,
});
var textboxName21 = ui.Label("结束时间：");
var textboxPanel21 = ui.Panel({
widgets: [textboxName21, textBox21],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel21);
// 查询影像
var label19 = ui.Label("3) 显示数据", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
function changeSelect(value) {
var roi = getROI(selectCode);
print("选择的数据:" + value);
if (value == "Landsat8") {
var imageCollection = landsat8Util
.getLandsat8(selectStartDate2, selectEndDate2, roi, 100)
.select(["B4", "B3", "B2"]);
print("影像集合", imageCollection.limit(1));
print("影像数量", imageCollection.size());
var image_median = imageCollection.median().clip(roi);
print(image_median);
var vis = {
min: [0, 0, 0],
max: [20000, 20000, 20000],
opacity: 0.9,
bands: ["B4", "B3", "B2"],
};
Map.addLayer(image_median, vis, "Landsat8");
} else if (value == "GF1") {
var imageCollection = pie
.ImageCollection("GF1/L1A/WFV_SR")
.filterBounds(roi)
.filterDate(selectStartDate2, selectEndDate2)
.select(["B3", "B2", "B1"]);
print("影像集合", imageCollection.limit(1));
print("影像数量", imageCollection.size());
var image_median = imageCollection.median().clip(roi);
var vis = {min: 0, max: 0.3, opacity: 0.9, bands: ["B3", "B2", "B1"]};
Map.addLayer(image_median, vis, "GF1");
} else {
// 哨兵二号去云2
function removeCloud2(image) {
var qa = image.select("QA60");
var cloudBitMask = 1 << 10;
var cirrusBitMask = 1 << 11;
var mask = qa
.bitwiseAnd(cloudBitMask)
.eq(0)
.and(qa.bitwiseAnd(cirrusBitMask).eq(0));
return image.updateMask(mask);
}
var imageCollection = pie
.ImageCollection("S2/L1C")
.filterBounds(roi)
.filterDate(selectStartDate2, selectEndDate2)
.map(removeCloud2)
.select(["B4", "B3", "B2"]); // 真彩色
print("影像集合", imageCollection.limit(1));
print("影像数量", imageCollection.size());
var image_median = imageCollection.median().clip(roi);
var vis = {min: 0, max: 10000, opacity: 0.9, bands: ["B4", "B3", "B2"]};
Map.addLayer(image_median, vis, "Sentinel-2");
}
}
var selectId = ui.Select({
items: ["Landsat8", "Sentinel-2", "GF1"],
placeholder: "请选择",
value: "Landsat8",
multiple: false,
onChange: changeSelect,
});
panel.add(label19).add(selectId);
// 地形显示
var label20 = ui.Label("4) 地形显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label20);
var selectTag1A = "DEM"; // 设置初始值
// select
function changeSelect1A(value) {
selectTag1A = value;
var roi = getROI(selectCode);
var dem = pie
.ImageCollection("DEM/ASTGTM_003")
.filterBounds(roi)
.select("dem")
.mean()
.clip(roi);
var visParam;
if (value == "DEM") {
visParam = {
opacity: 0.8,
classify: "-100,0,100,200,300,400,500,600,700,800,900,1000,1100,1200,1300,1400,1500,1600,1700,1800,1900,2000,2100,2200,2300,2400,2500,2600,2700,2800,2900,3000,3100",
palette: "145999,1b76cc,1f86e6,26aaea,36b6eb,4dc0eb,60cfeb,77daef,b0dfef,d1e5ee,dce6f0,e1e7f2,dee6f1,43c370,44b772,52c88e," +
"6fc993,7ecb97,acd2ad,d4c97a,d0bc59,d3b146,c78f3c,c3812d,c5762b,b95322,ae4621,ba6e78,bc8fa9,c7aac6,dbcdde,fffcff",
};
Map.addLayer(dem, visParam, "DEM");
var mean = dem.select("dem").reduceRegion(pie.Reducer.mean(), roi, 30);
print("DEM均值：" + mean.get("dem").getInfo() + "m");
// 添加图例
addDem2LegendToMap({
title: "DEM",
labels: ["-100", "500", "1000", "1500", "2000", "2500", "3000"],
step: 100,
});
} else if (value == "坡向") {
var aspect = pie.Terrain.aspect(dem); // 计算坡向
visParam = {
opacity: 0.8,
classify: "0,10,20,30,40,50,60,70,80,90,100,110,120,130,140,150,160,170,180,190,200,210,220,230,240,250,260,270,280,290,300,310,320",
palette: "145999,1b76cc,1f86e6,26aaea,36b6eb,4dc0eb,60cfeb,77daef,b0dfef,d1e5ee,dce6f0,e1e7f2,dee6f1,43c370,44b772,52c88e," +
"6fc993,7ecb97,acd2ad,d4c97a,d0bc59,d3b146,c78f3c,c3812d,c5762b,b95322,ae4621,ba6e78,bc8fa9,c7aac6,dbcdde,fffcff",
};
Map.addLayer(aspect, visParam, "Aspect");
// 添加图例
addDem2LegendToMap({
title: "坡向",
labels: ["0", "50", "100", "150", "200", "250", "300"],
step: 10,
});
} else if (value == "坡度") {
var slope = pie.Terrain.slope(dem).multiply(180 / 3.1415926); // 计算坡度
visParam = {
opacity: 0.8,
classify: "0,10,20,30,40,50,60,70,80,90,100,110,120,130,140,150,160,170,180",
palette: "145999,1b76cc,1f86e6,26aaea,36b6eb,4dc0eb,60cfeb,77daef,b0dfef,d1e5ee,dce6f0,e1e7f2,dee6f1,43c370,44b772,52c88e," +
"6fc993,7ecb97,acd2ad",
};
Map.addLayer(slope, visParam, "slope");
// 添加图例
addDem1LegendToMap({
title: "坡度",
labels: ["0", "30", "60", "90", "120", "150", "180"],
step: 10,
});
} else {
var imageShade = pie.Terrain.hillShade(dem, 45, 315, 8); // 山体阴影
visParam = {
opacity: 0.8,
classify: "-1100,-800,-700,-600,-500,-400,-300,-200,-100,-50,-20,-10,-5,0,5,10,25,50,75,100,125,150,175,200,250,300,350,400,450,500,550,600,880",
palette: "145999,1b76cc,1f86e6,26aaea,36b6eb,4dc0eb,60cfeb,77daef,b0dfef,d1e5ee,dce6f0,e1e7f2,dee6f1,43c370,44b772,52c88e," +
"6fc993,7ecb97,acd2ad,d4c97a,d0bc59,d3b146,c78f3c,c3812d,c5762b,b95322,ae4621,ba6e78,bc8fa9,c7aac6,dbcdde,fffcff",
};
Map.addLayer(imageShade, visParam, "imageShade");
// 添加图例
addDem1LegendToMap({
title: "山体阴影",
labels: ["0", "50", "100", "150", "200", "250", "300"],
step: 10,
});
}
}
var select1A = ui.Select({
items: ["DEM", "坡向", "坡度", "山体阴影"],
placeholder: "请选择",
value: selectTag1A,
multiple: false,
onChange: changeSelect1A,
});
var selectName1A = ui.Label("选择地形：");
var selectPanel1A = ui.Panel({
widgets: [selectName1A, select1A],
layout: ui.Layout.flow("horizontal"),
});
panel.add(selectPanel1A);
//导出数据
function clickbtExport() {
print(selectTag1A);
var roi = getROI(selectCode);
var dem = pie
.ImageCollection("DEM/ASTGTM_003")
.filterBounds(roi)
.select("dem")
.mean()
.clip(roi);
var aspect = pie.Terrain.aspect(dem); // 计算坡向
var slope = pie.Terrain.slope(dem).multiply(180 / 3.1415926); // 计算坡度
var imageShade = pie.Terrain.hillShade(dem, 45, 315, 8); // 山体阴影
var config = {
DEM: dem,
坡度: slope,
坡向: aspect,
山体阴影: imageShade,
};
Export.image({
image: config[selectTag1A],
description: "ExportImage:" + selectTag1A,
assetId: "test",
region: roi,
scale: 30,
});
}
var btExport = ui.Button({
label: "导出数据",
type: "success",
onClick: clickbtExport,
});
panel.add(btExport);
// 指数计算
var label21 = ui.Label("5) 指数计算", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label21);
function changeSelect1B(value) {
selectTag1B = value;
var roi = getROI(selectCode);
var l8Col = landsat8Util.getLandsat8(
selectStartDate2,
selectEndDate2,
roi,
20
);
l8Col = l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7"]).median().clip(roi);
if (value == "ndvi") {
var ndvi = landsat8Util.ndvi(l8Col).select("ndvi");
//设置图层显示属性
var visalg = generateVisalg(-1, 1);
Map.addLayer(ndvi, visalg, "NDVI");
var mean = ndvi.select("ndvi").reduceRegion(pie.Reducer.mean(), roi, 30);
print("ndvi均值：" + mean.get("ndvi").getInfo());
// 显示图例
addLegendToMap({
title: "NDVI",
labels: ["-1", "-0.5 ", " 0", "0.5", "1"],
step: 30,
});
} else if (value == "fvc") {
var fvc = landsat8Util.fvc(l8Col).select("fvc");
var visalg = generateVisalg(0, 1);
Map.addLayer(fvc, visalg, "fvc");
var mean = fvc.select("fvc").reduceRegion(pie.Reducer.mean(), roi, 30);
print("fvc均值：" + mean.get("fvc").getInfo());
// 显示图例
addLegendToMap({
title: "fvc",
labels: ["0", "0.2 ", " 0.4", "0.6", "0.8", "1"],
step: 30,
});
} else if (value == "rvi") {
var rvi = landsat8Util.rvi(l8Col).select("rvi");
var visalg = generateVisalg(0, 1);
Map.addLayer(rvi, visalg, "rvi");
var mean = rvi.select("rvi").reduceRegion(pie.Reducer.mean(), roi, 30);
print("rvi均值：" + mean.get("rvi").getInfo());
// 显示图例
addLegendToMap({
title: "rvi",
labels: ["0", "0.2 ", " 0.4", "0.6", "0.8", "1"],
step: 30,
});
} else if (value == "evi") {
var evi = landsat8Util.evi(l8Col).select("evi");
//设置图层显示属性
var visalg = generateVisalg(-1, 1);
Map.addLayer(evi, visalg, "evi");
var mean = evi.select("evi").reduceRegion(pie.Reducer.mean(), roi, 30);
print("evi均值：" + mean.get("evi").getInfo());
// 显示图例
addLegendToMap({
title: "evi",
labels: ["-1", "-0.5 ", " 0", "0.5", "1"],
step: 30,
});
} else if (value == "wet") {
var wet = landsat8Util.wet(l8Col).select("wet");
var visalg = generateVisalg(-1, 1);
Map.addLayer(wet, visalg, "wet_oli");
var mean = wet_oli.select("wet").reduceRegion(pie.Reducer.mean(), roi, 30);
print("wet均值：" + mean.get("wet").getInfo());
// 显示图例
addLegendToMap({
title: "wet",
labels: ["-1", "-0.5 ", " 0", "0.5", "1"],
step: 30,
});
} else if (value == "ndbsi") {
var ndbsi = landsat8Util.ndbsi(l8Col).select("ndbsi");
var visalg = generateVisalg(0, 0.5);
Map.addLayer(ndbsi, visalg, "ndbsi");
var mean = ndbsi.select("ndbsi").reduceRegion(pie.Reducer.mean(), roi, 30);
print("ndbsi均值：" + mean.get("ndbsi").getInfo());
// 显示图例
addLegendToMap({
title: "ndbsi",
labels: ["0", "0.1", " 0.2", "0.3", "0.4"],
step: 30,
});
} else if (value == "ndbi") {
var ndbi = landsat8Util.ndbi(l8Col).select("ndbi");
var visalg = generateVisalg(-0.5, 0.5);
var ndbi = b6.subtract(b5).divide(b6.add(b5)).rename("ndbi");
Map.addLayer(ndbi, visalg, "ndbi");
var mean = ndbi.select("ndbi").reduceRegion(pie.Reducer.mean(), roi, 30);
print("ndbi均值：" + mean.get("ndbi").getInfo());
// 显示图例
addLegendToMap({
title: "ndbi",
labels: ["-0.5", "-0.25", " 0", "0.25", "0.5"],
step: 30,
});
} else if (value == "lai") {
//加载Terra星全球500m叶面积指数/FPAR 8天合成产品(MOD15A2H V6)
var images = pie
.ImageCollection("USGS/MOD15A2H/006")
.filterDate(selectStartDate2, selectEndDate2);
//选择LAI波段,计算LAI均值
var lai = images
.select("Lai_500m")
.map(function (image) {
return image.updateMask(image.lt(200));
})
.mean()
.clip(roi)
.rename("lai");
//设置图层显示属性
var visalg = generateVisalg(0, 100);
Map.addLayer(lai, visalg, "lai");
var mean = lai.select("lai").reduceRegion(pie.Reducer.mean(), roi, 500);
print("lai均值：" + mean.get("lai").getInfo());
// 显示图例
addLegendToMap({
title: "lai",
labels: ["0", "30 ", " 60", "90"],
step: 30,
});
} else if (value == "fpar") {
//加载Terra星全球500m叶面积指数/FPAR 8天合成产品(MOD15A2H V6)
var images = pie
.ImageCollection("USGS/MOD15A2H/006")
.filterDate(selectStartDate2, selectEndDate2);
//选择FPAR波段,计算FPAR均值
var fpar = images.select("Fpar_500m").mean().clip(roi).rename("fpar");
//设置图层显示属性
var visalg = generateVisalg(0, 100);
Map.addLayer(fpar, visalg, "fpar");
var mean = fpar.select("fpar").reduceRegion(pie.Reducer.mean(), roi, 500);
print("fpar均值：" + mean.get("fpar").getInfo());
// 显示图例
addLegendToMap({
title: "fpar",
labels: ["0", "30 ", " 60", "90"],
step: 30,
});
} else if (value == "lst") {
var lst = MOD11A2.filterDate(selectStartDate2, selectEndDate2)
.filterBounds(roi)
.select("LST_Day_1km")
.mean()
.multiply(0.02)
.subtract(273.15)
.clip(roi)
.rename("lst");
//设置图层显示属性
var visalg = generateVisalg(0, 30);
Map.addLayer(lst, visalg, "lst");
var mean = lst.select("lst").reduceRegion(pie.Reducer.mean(), roi, 1000);
print("lst均值：" + mean.get("lst").getInfo());
// 显示图例
addLegendToMap({
title: "温度",
labels: ["0", "10 ", " 20", "30"],
step: 30,
});
} else if (value == "tvdi") {
var image = globalTVDI(selectStartDate2, selectEndDate2, roi);
//设置图层显示属性
var visalg = generateVisalg(0, 1);
Map.addLayer(image, visalg, "tvdi");
var mean = image.reduceRegion(pie.Reducer.mean(), roi, 1000);
print("tvdi均值：", mean.get("tvdi"));
// 显示图例
addLegendToMap({
title: "tdvi",
labels: ["0", "0.2 ", " 0.4", "0.6", "0.8", "1"],
step: 30,
});
} else if (value == "ndwi") {
var ndwi = landsat8Util.ndwi(l8Col).select("ndwi");
var visalg = generateVisalg(-0.5, 0.5);
Map.addLayer(ndwi, visalg, "ndwi");
// 显示图例
addLegendToMap({
title: "ndwi",
labels: ["-0.5", "-0.25 ", " 0", "0.25", "0.5"],
step: 30,
});
} else if (value == "mndwi") {
var mndwi = landsat8Util.mndwi(l8Col).select("mndwi");
var visalg = generateVisalg(-0.5, 0.5);
Map.addLayer(mndwi, visalg, "mndwi");
// 显示图例
addLegendToMap({
title: "mndwi",
labels: ["-0.5", "-0.25 ", " 0", "0.25", "0.5"],
step: 30,
});
//根据计算的水体数据计算面积
var areaImage = mndwi
.select("water")
.pixelArea()
.multiply(mndwi.select("water").gt(0.1));
var water = areaImage.reduceRegion(pie.Reducer.sum(), roi, 30);
print(water);
print(
"水体面积是（单位：平方千米）: ",
pie.Number(water.get("constant").getInfo()).divide(1000000)
); //进行单位换算
}
}
var selectTag1B = "ndvi"; // 设置初值
var select1B = ui.Select({
items: [
"ndvi",
"rvi",
"evi",
"fvc",
"lai",
"fpar",
"wet",
"lst",
"ndbsi",
"ndbi",
"tvdi",
"mndwi",
"ndwi",
],
placeholder: "请选择",
value: selectTag1B,
multiple: false,
onChange: changeSelect1B,
});
var selectName1B = ui.Label("选择指数：");
var selectPanel1B = ui.Panel({
widgets: [selectName1B, select1B],
layout: ui.Layout.flow("horizontal"),
});
panel.add(selectPanel1B);
function clickbtExport1() {
print(selectTag1B);
var roi = getROI(selectCode);
var l8Col = landsat8Util.getLandsat8(
selectStartDate2,
selectEndDate2,
roi,
20
);
l8Col = l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7"]).median().clip(roi);
// tvdi
var tvdi = globalTVDI(selectStartDate2, selectEndDate2, roi);
// lst
var lst = MOD11A2.filterDate(selectStartDate2, selectEndDate2)
.filterBounds(roi)
.select("LST_Day_1km")
.mean()
.multiply(0.02)
.subtract(273.15)
.rename("lst")
.clip(roi);
// lai
//加载Terra星全球500m叶面积指数/FPAR 8天合成产品(MOD15A2H V6)
var images1 = pie
.ImageCollection("USGS/MOD15A2H/006")
.filterDate(selectStartDate2, selectEndDate2);
//选择LAI波段,计算LAI均值
var lai = images1
.select("Lai_500m")
.map(function (image) {
return image.updateMask(image.lt(200));
})
.mean()
.clip(roi)
.rename("lai");
// fpar
//选择FPAR波段,计算FPAR均值
var fpar = images1.select("Fpar_500m").mean().clip(roi).rename("fpar");
l8Col = landsat8Util.ndvi(l8Col);
l8Col = landsat8Util.wet(l8Col);
l8Col = landsat8Util.ndbsi(l8Col);
l8Col = landsat8Util.evi(l8Col);
l8Col = landsat8Util.mndwi(l8Col);
l8Col = landsat8Util.fvc(l8Col);
l8Col = landsat8Util.rvi(l8Col);
l8Col = landsat8Util.ndbi(l8Col);
l8Col = l8Col
.addBands(ndwi.rename("ndwi"))
.addBands(lst.rename("lst"))
.addBands(tvdi.rename("tvdi"))
.addBands(lai.rename("lai"))
.addBands(fpar.rename("fpar"));
//导出影像
Export.image({
image: l8Col.select(selectTag1B),
description: "ExportImage:" + selectTag1B,
assetId: "test",
region: roi,
scale: 30,
});
}
//导出数据
var btExport1 = ui.Button({
label: "导出数据",
type: "success",
onClick: clickbtExport1,
});
panel.add(btExport1);
// 回归分析
var label22 = ui.Label("6) 回归分析", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label22);
function changeCheckbox(value) {
var roi = getROI(selectCode);
print("开始回归分析");
// 裁剪
function clip(image) {
image = image.clip(roi);
return image;
}
var l8Col = landsat8Util.getLandsat8(
selectStartDate2,
selectEndDate2,
roi,
20
);
l8Col = l8Col
.select(["B2", "B3", "B4", "B5", "B6", "B7"])
.map(clip)
.map(landsat8Util.ndvi)
.map(landsat8Util.wet)
.map(landsat8Util.evi);
var visParam1 = {
min: [0, 0.5, 0],
max: [0.3, 2, 0.3],
opacity: 1,
bands: ["offset", "scale", "offset"],
};
var image1 = l8Col.select(["ndvi", "evi"]).reduce(pie.Reducer.linearFit()); // 回归算法
Map.addLayer(image1, visParam1, "linearFit");
print("结束回归分析");
}
var checkbox = ui.Checkbox({
label: ["ndvi", "evi", "wet"],
value: [],
disabled: [],
onChange: changeCheckbox,
});
panel.add(checkbox);
// 土地堵盖类型显示
var label23 = ui.Label("7) 土地覆盖类型显示", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label23);
function clickbtLandShow() {
var roi = getROI(selectCode);
//加载全球地表覆盖GlobeLand30数据
var sdate = new Date(selectStartDate2).getFullYear() + "-01-01"; // 获取起始日期前四位
var edate = new Date(selectEndDate2).getFullYear() + "-12-31"; // 获取结束日期前四位
var img = pie
.ImageCollection("NGCC/GLOBELAND30")
.filterBounds(roi)
.filterDate(sdate, edate)
.select("B1")
.mosaic()
.clip(roi);
//按不同地表覆盖类型值设定预览参数
var colors = [
"#00FF00",
"#00e900",
"#00dF00",
"#00ce00",
"#00ba00",
"#0002FF",
"#97FF00",
"#FF0000",
"#FFce00",
"#FFFFFF",
];
var visGL = {
uniqueValue: "10, 20, 30, 40, 50, 60, 70, 80, 90, 100",
palette: colors,
};
//加载显示影像
Map.addLayer(img, visGL, "img");
// 图例
addLegend({
title: "地表覆盖",
colors: colors,
labels: [
"耕地",
"林地",
"草地",
"灌木地",
"湿地",
"水体",
"苔原",
"人造地表",
"裸地",
"积雪",
],
step: 1,
});
}
var btLandShow = ui.Button({
label: "显示",
type: "success",
onClick: clickbtLandShow,
});
panel.add(btLandShow);
// 时间转换
var label24 = ui.Label("8) 时间转换", {
"font-size": "16px",
"font-weight": "bold",
color: "red",
});
panel.add(label24);
var selectStartDateAAA = "2021-06-30";
function inputSDateAAA(value) {
selectStartDateAAA = value;
}
var textBox1AAA = ui.DateSelect({
type: "date",
placeholder: "请输入数值",
value: selectStartDateAAA, //输入显示框显示数值
onChange: inputSDateAAA,
disabled: false,
});
var textboxName1AAA = ui.Label("输入转换日期：");
var textboxPanel1AAA = ui.Panel({
widgets: [textboxName1AAA, textBox1AAA],
layout: ui.Layout.flow("horizontal"),
});
panel.add(textboxPanel1AAA);
// 转换天数,输入数据为pieNumber类型
function convertYearToDay(dateStr) {
var now = new Date(dateStr);
var start = new Date(now.getFullYear(), 0, 0);
var diff = (now - start) + ((start.getTimezoneOffset() - now.getTimezoneOffset()) * 60 * 1000);
var oneDay = 1000 * 60 * 60 * 24;
var day = Math.floor(diff / oneDay);
return day;
}
function clickbtCon() {
var dateNum = convertYearToDay(selectStartDateAAA); //转换为1年中的某一天
print("转换后的天数：" + dateNum);
}
var btCon = ui.Button({
label: "转换",
type: "success",
onClick: clickbtCon,
});
panel.add(btCon);
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- 3250.
- 3251.
- 3252.
- 3253.
- 3254.
- 3255.
- 3256.
- 3257.
- 3258.
- 3259.
- 3260.
- 3261.
- 3262.
- 3263.
- 3264.
- 3265.
- 3266.
- 3267.
- 3268.
- 3269.
- 3270.
- 3271.
- 3272.
- 3273.
- 3274.
- 3275.
- 3276.
- 3277.
- 3278.
- 3279.
- 3280.
- 3281.
- 3282.
- 3283.
- 3284.
- 3285.
- 3286.
- 3287.
- 3288.
- 3289.
- 3290.
- 3291.
- 3292.
- 3293.
- 3294.
- 3295.
- 3296.
- 3297.
- 3298.
- 3299.
- 3300.
- 3301.
- 3302.
- 3303.
- 3304.
- 3305.
- 3306.
- 3307.
- 3308.
- 3309.
- 3310.
- 3311.
- 3312.
- 3313.
- 3314.
- 3315.
- 3316.
- 3317.
- 3318.
- 3319.
- 3320.
- 3321.
- 3322.
- 3323.
- 3324.
- 3325.
- 3326.
- 3327.
- 3328.
结果：
©著作权归作者所有，如需转载，请注明出处，否则将追究法律责任
已于2022-9-27 15:24:29修改
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