PIE-Engine APP 京津冀地区的生态宜居性评价的系统(2018-2020年)

/**
 * @Name    :   基于PIE云平台的城市生态宜居性评价系统——以京津冀城市群为例
 * @Time    :   2021/8/21
 * @Author  :   中国石油大学（华东）牛转乾坤队
 * @Version :   1.0
 * @E-mail  :   genyunsun@163.com
 * @Source
var libs = require("https://pie-engine-static-data.s3.cn-northwest-1.amazonaws.com.cn/engine-studio-data/demoData.js");
// 利用计算的结果 统计各个区域的各个指标变化情况：
var staticData = libs.data;
// print(staticData)
//划定研究区域
var Province = pie.FeatureCollection("user/pieadmin/JJJ_Provinces");
var Cities = pie.FeatureCollection("user/pieadmin/JJJ_Cities");
var Countries = pie.FeatureCollection("user/pieadmin/JJJ_County");
var all_region = pie.FeatureCollection("user/pieadmin/JingJinJi");

//定义常量参数
var layerKey = null; // 地图层 layerkery
var roilayerKey = null; // 矢量图层 key
var selectTag = "EI";
var selectSenson = "spring";
var seasonindex = 0; //季节的索引值 ， 默认为0 ，春季
var environmetClass = 1; // 默认环境等级

var selectStartDate = "2020-3-1"; // 默认起始时间
var selectCode = "110101"; // 默认地区代码
var countyname = "北京市/东城区";
var selectYear = 2019; //通过滚动轴选择年份
var showLevel = 10; //  显示层级 ， 区域越大层级越小

var reduceScale = 1000; // 局部统计使用的尺度 ， 统计的区域越大， 尺度越大 ，防止内存不足
var staticType = "Season"; // 统计表的形式
var region_level = "District"; // 显示的区域级别  默认 Disrrict
var charttype = "bar";
var roi = null; // 显示的区域

Map.addLayer(
  Cities,
  { color: "#044b4b", fillColor: "#00000000", width: 1.5 },
  "Cities",
  false
);
Map.addLayer(
  Countries,
  { color: "#7b7b7b", fillColor: "#00000000", width: 1.0 },
  "Countries",
  false
);

var visAQI = {
  min: 0,
  max: 1,
  palette: [
    "#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 colors1 = [
  "#0602ff",
  "#235cb1",
  "#307ef3",
  "#269db1",
  "#30c8e2",
  "#32d3ef",
  "#3be285",
  "#3ff38f",
  "#86e26f",
  "#3ae237",
  "#b5e22e",
  "#d6e21f",
  "#fff705",
  "#ffd611",
  "#ffb613",
  "#ff8b13",
  "#ff6e08",
  "#ff500d",
  "#ff0000",
  "#de0101",
]; // 由绿到红
var colors2 = [
  "#ff6e08",
  "#ff8b13",
  "#ff9613",
  "#ffd611",
  "#fff705",
  "#d6e21f",
  "#b5e22e",
  "#3ae237",
  "#86e26f",
  "#3ff38f",
  "#3be285",
  "#32d3ef",
]; // 由红到绿

//获取指定的ROI数据
function getROI(code) {
  print(code, parseInt(code));
  if (region_level == "District") {
    var fCol = pie.FeatureCollection("NGCC/CHINA_COUNTY_BOUNDARY");
    showLevel = 10;
    reduceScale = 1000;
  } else if (region_level == "City") {
    var fCol = pie.FeatureCollection("NGCC/CHINA_CITY_BOUNDARY");
    showLevel = 7;
    reduceScale = 2000;
  } else if (region_level == "Province") {
    var fCol = pie.FeatureCollection("NGCC/CHINA_PROVINCE_BOUNDARY");
    showLevel = 6;
    reduceScale = 3000;
  }

  if (region_level == "All") {
    roi = all_region.first().geometry();
    showLevel = 5;
    reduceScale = 5000;
  } else {
    roi = fCol
      .filter(pie.Filter.eq("code", parseInt(code)))
      .first()
      .geometry();
  }
  if (roilayerKey != null) {
    Map.removeLayer(roilayerKey);
  }
  if (roi != null) {
    roilayerKey = Map.addLayer(
      roi,
      { color: "#ff0000", fillColor: "#00000000" },
      "roi"
    );
    Map.centerObject(roi, showLevel);
  }
  return roi;
}

// 向地图中添加 图例 （颜色条）
function addMapLenged(INDEX) {
  var colors = colors1;
  switch (INDEX) {
    case "FVC":
      colors = colors2;
      break;
    case "MNDWI":
      colors = colors2;
      break;
    case "EI":
      colors = colors2;
      break;
  }
  var data = {
    title: INDEX,
    colors: colors,
    labels: ["0", "0.2", "0.4", "0.6", "0.8", "1.0"],
    step: 30,
  };
  var style = {
    right: "550px",
    bottom: "70px",
    height: "70px",
    width: "300px",
  };
  var legend = ui.Legend(data, style);
  Map.addUI(legend);
}

//地表温度反演
function LSTMap(image, roi) {
  var ndvi = image
    .expression("(B5-B4)/(B5+B4)", {
      B4: image.select("B4"),
      B5: image.select("B5"),
    })
    .rename("NDVI");
  var normalNdvi = ndvi.subtract(-0.3).divide(pie.Number(0.81).subtract(-0.3));
  var fv = normalNdvi.power(2.0).rename("fv");
  var a = pie.Number(0.025);
  var b = pie.Number(0.986);
  var EM = fv
    .multiply(a)
    .add(pie.Image(1).subtract(fv).multiply(0.02).add(pie.Image(b)))
    .rename("EMM");
  var thermal = image.select("B10").multiply(0.1);
  var EM_LOG = EM.log();
  var FenMU = thermal.divide(1.438).multiply(0.00115);
  var Fenmu2 = FenMU.multiply(EM_LOG).add(1.0);
  var LST = thermal.divide(Fenmu2).subtract(273.15).rename("LST");
  //计算最大值最小值
  var LST_max = LST.reduceRegion(pie.Reducer.max(), roi, reduceScale).get(
    "LST"
  );
  LST_max = pie.Number(LST_max);
  var LST_min = LST.reduceRegion(pie.Reducer.min(), roi, reduceScale).get(
    "LST"
  );
  LST_min = pie.Number(LST_min);
  var nORLST = LST.subtract(LST_min).divide(LST_max.subtract(LST_min));
  return nORLST;
}

//计算 MNDWI （水体分布）
function mNDWI(image, roi) {
  var b3 = image.select("B3");
  var b6 = image.select("B6");
  var mNDWI = b3.subtract(b6).divide(b3.add(b6)).rename("mNDWI");
  var mNDWI_max = mNDWI
    .reduceRegion(pie.Reducer.max(), roi, reduceScale)
    .get("mNDWI");
  mNDWI_max = pie.Number(mNDWI_max);
  var mNDWI_min = mNDWI
    .reduceRegion(pie.Reducer.min(), roi, reduceScale)
    .get("mNDWI");
  mNDWI_min = pie.Number(mNDWI_min);
  //归一化
  var nORmNDWI = mNDWI
    .subtract(mNDWI_min)
    .divide(mNDWI_max.subtract(mNDWI_min));
  return nORmNDWI;
}

// 植被覆盖度计算
function l8FVC(img, roi) {
  var B4 = img.select("B4");
  var B5 = img.select("B5");
  var NDVI = B5.subtract(B4).divide(B5.add(B4)).rename("NDVI");

  //4.计算京津冀范围FVC
  //计算区域内NDVI最大值
  var NDVI_max = NDVI.reduceRegion(pie.Reducer.max(), roi, reduceScale).get(
    "NDVI"
  );
  NDVI_max = pie.Number(NDVI_max);
  //计算区域内NDVI最小值
  var NDVI_min = NDVI.reduceRegion(pie.Reducer.min(), roi, reduceScale).get(
    "NDVI"
  );
  NDVI_min = pie.Number(NDVI_min);
  //反演区域植被覆盖度并加载
  var img_FVC = NDVI.subtract(NDVI_min).divide(NDVI_max.subtract(NDVI_min));
  return img_FVC;
}

//计算 NDBI  建筑物密度
function l8NDBI(img, roi) {
  var B5 = img.select("B5");
  var B6 = img.select("B6");
  var NDBI = B6.subtract(B5).divide(B6.add(B5)).rename("NDBI");

  //计算最大值最小值
  var NDBI_max = NDBI.reduceRegion(pie.Reducer.max(), roi, reduceScale).get(
    "NDBI"
  );
  NDBI_max = pie.Number(NDBI_max);
  var NDBI_min = NDBI.reduceRegion(pie.Reducer.min(), roi, reduceScale).get(
    "NDBI"
  );
  NDBI_min = pie.Number(NDBI_min);
  var nORNDBI = NDBI.subtract(NDBI_min).divide(NDBI_max.subtract(NDBI_min));
  return nORNDBI;
}

// NO2 去云函数
function cloudMask(image) {
  var k = image.updateMask(image.select("cloud_fraction").lt(0.2));
  return k.select("tropospheric_NO2_column_number_density");
} //NO2 去云

function normalNO2(startDate, endDate, roi) {
  //加载对二氧化氮进行监测的近实时数据流产品数据
  var NO2cOLL = pie
    .ImageCollection("S5P/OFFL_L3_NO2")
    .filterBounds(roi)
    .filterDate(startDate, endDate);
  var NO2IMG = NO2cOLL.select([
    "tropospheric_NO2_column_number_density",
    "cloud_fraction",
  ]).map(cloudMask);
  NO2IMG = NO2IMG.mean().clip(roi).rename("NO2");
  var NO23_max = NO2IMG.reduceRegion(pie.Reducer.max(), roi, 7000).get("NO2");
  NO23_max = pie.Number(NO23_max);
  var NO23_min = NO2IMG.reduceRegion(pie.Reducer.min(), roi, 7000).get("NO2");
  NO23_min = pie.Number(NO23_min);
  var NORNO23 = NO2IMG.subtract(NO23_min).divide(NO23_max.subtract(NO23_min));
  return NORNO23;
}

// O3 去云函数
function cloudMask_O3(image) {
  var k = image.updateMask(image.select("cloud_fraction").lt(0.2));
  return k.select("O3_column_number_density");
}
function normalO3(startDate, endDate, roi) {
  var O3 = pie
    .ImageCollection("S5P/OFFL_L3_O3")
    .filterBounds(roi)
    .filterDate(startDate, endDate);
  var O33 = O3.select(["O3_column_number_density", "cloud_fraction"])
    .map(cloudMask_O3)
    .mean()
    .clip(roi)
    .rename("O3");
  var O33_max = O33.reduceRegion(pie.Reducer.max(), roi, 7500).get("O3");
  O33_max = pie.Number(O33_max);
  var O33_min = O33.reduceRegion(pie.Reducer.min(), roi, 7500).get("O3");
  O33_min = pie.Number(O33_min);
  var NORO33 = O33.subtract(O33_min).divide(O33_max.subtract(O33_min));
  return NORO33;
}

//SO2 去云
function cloudMask_SO2(image) {
  var k = image.updateMask(image.select("cloud_fraction").lt(0.2));
  return k.select("SO2_column_number_density");
}
function normalSO2(startDate, endDate, roi) {
  var SO2 = pie
    .ImageCollection("S5P/OFFL_L3_SO2")
    .filterBounds(roi)
    .filterDate(startDate, endDate);
  var SO23 = SO2.select(["SO2_column_number_density", "cloud_fraction"])
    .map(cloudMask_SO2)
    .mean()
    .clip(roi)
    .rename("SO2");
  var SO23_max = SO23.reduceRegion(pie.Reducer.max(), roi, 7500).get("SO2");
  SO23_max = pie.Number(SO23_max);
  var SO23_min = SO23.reduceRegion(pie.Reducer.min(), roi, 7500).get("SO2");
  SO23_min = pie.Number(SO23_min);

  //归一化
  var NORSO23 = SO23.subtract(SO23_min).divide(SO23_max.subtract(SO23_min));
  //加载春季SO2影像
  return NORSO23;
}

//CO 指标归一化
function normalCO(startDate, endDate, roi) {
  var CO3 = pie
    .ImageCollection("S5P/OFFL_L3_CO")
    .filterBounds(roi)
    .filterDate(startDate, endDate)
    .select("CO_column_number_density")
    .mean()
    .clip(roi)
    .rename("CO");
  var CO3_max = CO3.reduceRegion(pie.Reducer.max(), roi, 7500).get("CO");
  CO3_max = pie.Number(CO3_max);
  var CO3_min = CO3.reduceRegion(pie.Reducer.min(), roi, 7500).get("CO");
  CO3_min = pie.Number(CO3_min);
  var NORCO3 = CO3.subtract(CO3_min).divide(CO3_max.subtract(CO3_min));
  return NORCO3;
}
//计算空气质量
function normalAQI(startDate, endDate, roi) {
  var co = normalCO(startDate, endDate, roi);
  var so2 = normalSO2(startDate, endDate, roi);
  var o3 = normalO3(startDate, endDate, roi);
  var no2 = normalNO2(startDate, endDate, roi);
  var AQI5 = no2
    .multiply(0.25)
    .add(o3.multiply(0.25))
    .add(so2.multiply(0.25))
    .add(co.multiply(0.25))
    .rename("AQI5");
  //计算最大值最小值
  var AQI5_max = AQI5.reduceRegion(pie.Reducer.max(), roi, 7500).get("AQI5");
  AQI5_max = pie.Number(AQI5_max);
  var AQI5_min = AQI5.reduceRegion(pie.Reducer.min(), roi, 7500).get("AQI5");
  AQI5_min = pie.Number(AQI5_min);
  //归一化
  var NORAQI5 = AQI5.subtract(AQI5_min)
    .divide(AQI5_max.subtract(AQI5_min))
    .rename("NORAQI5");
  //加载夏季AQI影像
  return NORAQI5;
}

//计算生态环境质量
function cacluateEI(startDate, endDate, img, roi) {
  var fvc = l8FVC(img, roi);
  var lst = LSTMap(img, roi);
  var ndbi = l8NDBI(img, roi);
  var water = mNDWI(img, roi);
  if (selectYear == "2020") {
    var AQI = normalAQI(startDate, endDate, roi);
    var eI = fvc
      .multiply(0.2465)
      .subtract(ndbi.multiply(0.1308))
      .add(water.multiply(0.1863))
      .subtract(AQI.multiply(0.3688))
      .subtract(lst.multiply(0.0676))
      .rename("EI");
  } else {
    // 绿地0.4094，建筑0.2047，水0.2895，LST0.0965
    print("selectYear:", selectYear);
    var eI = fvc
      .multiply(0.4094)
      .subtract(ndbi.multiply(0.2047))
      .add(water.multiply(0.2895))
      .subtract(lst.multiply(0.0965))
      .rename("EI");
  }

  var eI_max = eI.reduceRegion(pie.Reducer.max(), roi, reduceScale).get("EI");
  eI_max = pie.Number(eI_max);
  var eI_min = eI.reduceRegion(pie.Reducer.min(), roi, reduceScale).get("EI");
  eI_min = pie.Number(eI_min);
  //归一化
  var norEI = eI
    .subtract(eI_min)
    .divide(eI_max.subtract(eI_min))
    .rename("norEI");
  return norEI.clip(all_region.first().geometry());
}

// 主函数 ， 控制整体流程
function cacluateVI(roi, startDate, tag) {
  //影像集合
  var endDate = pie.Date(startDate).advance(4, "month");
  var l8Col = pie
    .ImageCollection("LC08/01/T1_SR")
    .filterBounds(roi)
    .filterDate(startDate, endDate)
    .filter(pie.Filter.lt("cloudCover", 30));
  //通过日期过滤影像集合，并且计算指数
  l8Col = l8Col
    .select(["B2", "B3", "B4", "B5", "B6", "B7", "B10", "pixel_qa"])
    .map(function (image) {
      // Bits 3 and 5 are cloud shadow and cloud, respectively.
      var cloudShadowBitMask = 1 << 3;
      var cloudsBitMask = 1 << 5;
      // Get the pixel QA band.
      var qa = image.select("pixel_qa");
      // Both flags should be set to zero, indicating clear conditions.
      var mask = qa
        .bitwiseAnd(cloudShadowBitMask)
        .eq(0)
        .and(qa.bitwiseAnd(cloudsBitMask).eq(0));
      return image.updateMask(mask);
    });
  l8Col = l8Col.select(["B2", "B3", "B4", "B5", "B6", "B7", "B10"]);
  var l8image = l8Col.mean().clip(roi);

  switch (tag) {
    case "EI":
      var eImap = cacluateEI(startDate, endDate, l8image, roi);
      var viseImap = { min: 0, max: 0.85, palette: colors2 };
      layerKey = Map.addLayer(eImap, viseImap, "EI", true);
      addMapLenged("EI");
      break;
    case "FVC":
      var imgFVC = l8FVC(l8image, roi);
      layerKey = Map.addLayer(
        imgFVC,
        { min: 0, max: 0.9, palette: colors2 },
        "FVC",
        true
      );
      addMapLenged("FVC");
      break;
    case "LST":
      var imgLST = LSTMap(l8image, roi);
      layerKey = Map.addLayer(
        imgLST,
        { min: 0, max: 0.9, palette: colors },
        "LST",
        true
      );
      addMapLenged("LST");
      break;
    case "MNDWI":
      var imgMNDWI = mNDWI(l8image, roi);
      layerKey = Map.addLayer(
        imgMNDWI,
        { min: 0, max: 0.9, palette: colors2 },
        "MNDWI",
        true
      );
      addMapLenged("MNDWI");
      break;
    case "NDBI":
      var ndbiimg = l8NDBI(l8image, roi);
      //设置NDBI影像预览参数与颜色组合
      layerKey = Map.addLayer(
        ndbiimg,
        { min: 0, max: 0.9, palette: colors1 },
        "NDBI",
        true
      );
      addMapLenged("NDBI");
      break;
    case "SO2":
      var so2img = normalSO2(startDate, endDate, roi);
      layerKey = Map.addLayer(so2img, visAQI, "SO2", true);
      addMapLenged("SO2");
      break;
    case "NO2":
      var no2img = normalNO2(startDate, endDate, roi);
      layerKey = Map.addLayer(no2img, visAQI, "SO2", true);
      addMapLenged("SO2");
      break;
    case "CO":
      var coimg = normalCO(startDate, endDate, roi);
      layerKey = Map.addLayer(coimg, visAQI, "CO", true);
      addMapLenged("CO");
      break;
    case "O3":
      var o3img = normalO3(startDate, endDate, roi);
      layerKey = Map.addLayer(o3img, visAQI, "O3", true);
      addMapLenged("O3");
      break;
    case "AQI":
      var AQIimg = normalAQI(startDate, endDate, roi);
      layerKey = Map.addLayer(AQIimg, visAQI, "AQI Quality", true);
      addMapLenged("AQI");
      break;
  }
}

// 标题 Label
var label = ui.Label("生态宜居性评估系统-京津冀", {
  "font-size": "20px",
  color: "#00f",
  textAlign: "center",
});
// select 选择要计算的指标
function funCascader(value, selectData) {
  var index = parseInt(value.length);
  selectTag = value[index - 1];
  print("选择的指标为:", selectTag);
}

// 指标选择级联控件
var cascader = ui.Cascader({
  placeholder: "请选择",
  content: [
    {
      value: "FVC",
      label: "植被覆盖度",
    },
    {
      value: "MNDWI",
      label: "水体分布",
    },
    {
      value: "LST",
      label: "地表温度",
    },
    {
      value: "NDBI",
      label: "建筑物密度",
    },
    {
      value: "AQI",
      label: "空气质量",
      children: [
        {
          value: "SO2",
          label: "二氧化硫",
        },
        {
          value: "CO",
          label: "一氧化碳",
        },
        {
          value: "NO2",
          label: "二氧化氮",
        },
        {
          value: "O3",
          label: "臭氧",
        },
      ],
    },
    {
      value: "EI",
      label: "生态环境质量",
    },
  ],
  value: ["FVC"],
  style: { width: "220px" },
  onChange: funCascader,
});
var selectName = ui.Label("选择指标：");
var selectPanel = ui.Panel({
  widgets: [selectName, cascader],
  style: { left: "10px" },
  layout: ui.Layout.flow("horizontal"),
});

// 地区选择回调函数
function inputArea(codeList, nameList) {
  var index = nameList.length;
  if (index <= 0) {
    selectCode = "";
    countyname = "";
  } else {
    selectCode = nameList[index - 1].value;
    countyname = nameList[index - 1].label;
  }
}
// 地区选择级联控件
var cascader_region = ui.GeoCascader({
  // 可以通过init自定义显示内容
  init: {
    list: ["province", "city", "county"],
    province: ["河北省", "北京市", "天津市"],
  },
  placeholder: "请选择",
  onChange: inputArea,
});
var textboxName3 = ui.Label("行政区划：");
// 地区选择容器
var textboxPanel3 = ui.Panel({
  widgets: [textboxName3, cascader_region],
  style: { left: "10px", width: "400px" },
  layout: ui.Layout.flow("horizontal"),
});

// 确定显示级别 回调函数
var showLevelLabel = ui.Label("显示级别：");
function funRadio(value) {
  region_level = value;
}
// 计算区域 单选控件
var radio_region = ui.Radio({
  label: ["All", "Province", "City", "District"],
  value: "District",
  onChange: funRadio,
  disabled: false,
});
var show_level_Panel = ui.Panel({
  widgets: [showLevelLabel, radio_region],
  style: { left: "10px", width: "350px" },
  layout: ui.Layout.flow("horizontal"),
});

// TextBox
function seanson2Date(senson) {
  // 将季节转化为日期
  print("选择的季节是", senson);
  switch (senson) {
    case "spring":
      selectStartDate = selectYear + "-3-1";
      seasonindex = 0;
      break;
    case "summer":
      selectStartDate = selectYear + "-6-1";
      seasonindex = 1;
      break;
    case "fall":
      selectStartDate = selectYear + "-9-1";
      seasonindex = 2;
      break;
    case "winter":
      selectStartDate = selectYear + "-12-1";
      seasonindex = 3;
      break;
  }

  return selectStartDate;
}

//季节选择回调函数
function inputSDate(value) {
  selectSeason = value;
}

//季节选择列表控件
var selectSeason = ui.Select({
  items: ["spring", "summer", "fall", "winter"],
  placeholder: "请选择季节",
  value: selectSenson,
  onChange: inputSDate,
  disabled: false,
});
var textboxName1 = ui.Label("显示季节：");
var textboxPanel1 = ui.Panel({
  widgets: [textboxName1, selectSeason],
  style: { left: "10px", width: "300px" },
  layout: ui.Layout.flow("horizontal"),
});

//年份滑块
function yearSlide(value) {
  selectYear = value;
  print("选择年份为：", value);
}
//年份选择滑块
var yearSlider = ui.Slider({
  min: 2018,
  max: 2020,
  value: selectYear,
  step: 1,
  onChange: yearSlide,
  style: { bottom: "0px", width: "500px" },
});

var sliderLabel = ui.Label("年份:", { bottom: "-10px" });
var sliderPanel = ui.Panel({
  widgets: [sliderLabel, yearSlider],
  style: { width: "580px", height: "55px", bottom: "10px", left: "450px" },
  layout: ui.Layout.flow("horizontal"),
});
Map.addUI(sliderPanel);

// Button
function clickBtn() {
  print(
    "点击按钮，选择的参数是：",
    selectCode + ":" + selectTag + ":" + selectSenson
  );
  if (layerKey != null) {
    Map.removeLayer(layerKey);
    print("layerKey", layerKey);
  } //清空现有层
  roi = getROI(selectCode);
  var startdate = seanson2Date(selectSenson);
  cacluateVI(roi, startdate, selectTag);
}

function cancelclickBtn() {
  if (layerKey != null) {
    Map.removeLayer(layerKey);
  } //清空现有层
  if (roilayerKey != null) {
    Map.removeLayer(roilayerKey);
  }
  // DOM 操作：重启系统
  var restbtn = document.getElementsByClassName("toolButton")[3];
  restbtn.click();
  var runbtn = document.getElementsByClassName("toolButton")[2];
  runbtn.click();
}
var btn1 = ui.Button({
  label: "清空",
  style: { left: "40px" },
  onClick: cancelclickBtn,
});
var btn2 = ui.Button({
  label: "显示",
  type: "success",
  onClick: clickBtn,
  style: { left: "70px", top: "0px" },
});
var btnPanel = ui.Panel({
  widgets: [btn1, btn2],
  style: { left: "0px", top: "20px" },
  layout: ui.Layout.flow("horizontal"),
});

// 每个指标的逐季节平均值
var meanData = {
  FVC: [0.5, 0.68, 0.57, 0.39],
  LST: [0.71, 0.81, 0.64, 0.34],
  MNDWI: [0.27, 0.23, 0.25, 0.38],
  NDBI: [0.65, 0.43, 0.59, 0.65],
  AQI: [0.43, 0.4, 0.45],
  EI: [0.47, 0.55, 0.51, 0.49],
};
// seanson 转化为 索引

//统计部分
var staticIndes = ["MNDWI", "FVC", "NDBI"];
var staticLabel = ui.Label("统计指标:");
function staticIndex(value) {
  staticIndes = value;
  print("staticIndes", staticIndes);
}
var staticIndexcheckbox = ui.Checkbox({
  label: ["EI", "MNDWI", "FVC", "NDBI", "LST", "AQI"],
  value: staticIndes,
  style: { width: "220px" },
  onChange: staticIndex,
});

var staticIndexPanel = ui.Panel({
  widgets: [staticLabel, staticIndexcheckbox],
  style: { left: "10px" },
  layout: ui.Layout.flow("horizontal"),
});

var showsStyleLabel = ui.Label("图表类型:");
function showStyleFunRadio(value) {
  charttype = value;
  print("图表类型为:", charttype);
}
var showStyleradio = ui.Radio({
  label: ["bar", "column", "line"],
  value: "bar",
  onChange: showStyleFunRadio,
  disabled: false,
});
var showStyle_Panel = ui.Panel({
  widgets: [showsStyleLabel, showStyleradio],
  style: { left: "10px", width: "350px" },
  layout: ui.Layout.flow("horizontal"),
});

var timeSriesLabel = ui.Label("统计方式：");

function timeSriesFunRadio(value) {
  staticType = value;
  print("统计方式:", staticType);
}
var timeSriesradio = ui.Radio({
  label: ["Season", "TimeSeries"],
  value: "Season",
  onChange: timeSriesFunRadio,
  disabled: false,
});
var timeSries_Panel = ui.Panel({
  widgets: [timeSriesLabel, timeSriesradio],
  style: { left: "10px", width: "350px" },
  layout: ui.Layout.flow("horizontal"),
});

function btn_staticClearBtn() {
  var restbtn = document.getElementsByClassName("toolButton")[3];
  restbtn.click();
  var runbtn = document.getElementsByClassName("toolButton")[2];
  print(runbtn);
  runbtn.click();
}
var btn_static_clear = ui.Button({
  label: "清空",
  style: { left: "40px" },
  onClick: btn_staticClearBtn,
});

// 数据统计 按照季节进行柱状图统计：
// 调用绘制方法，输出图表显示在结果面板中
// 柱状图统计: 指定年份的季节性
function colum_static() {
  var col_data = [];
  for (var i = 0; i < staticIndes.length; i++) {
    col_data.push(
      staticData[String(selectCode)][String(selectYear)][staticIndes[i]]
    );
  }

  var chart_options = {};
  if (charttype == "bar") {
    chart_options = {
      title: countyname + " " + selectYear + "年" + "环境指标逐季节变化情况",
      legend: staticIndes,
      yAxis: ["spring", "summer", "fall", "winter"],
      xAxisName: "value",
      yAxisName: "季节",
      series: col_data,
      chartType: charttype,
    };
  } else if (charttype == "column" || charttype == "line") {
    chart_options = {
      title: countyname + " " + selectYear + "年" + "环境指标逐季节变化情况",
      legend: staticIndes,
      xAxis: ["spring", "summer", "fall", "winter"],
      xAxisName: "季节",
      yAxisName: "value",
      series: col_data,
      chartType: charttype,
    };
  }
  print(chart_options);
  var chart = ui.Chart.array(chart_options);
  chart.setStyle({
    width: "500px",
    height: "300px",
    top: "50px",
    right: "1px",
  });
  Map.addUI(chart);
}

// 时间序列统计
function time_static() {
  var years = ["2018", "2019", "2020"];
  var multiIndesData = [];
  for (var i = 0; i < staticIndes.length; i++) {
    var timeSeriesData = [];
    for (var j = 0; j < years.length; j++) {
      teamData = staticData[selectCode][years[j]][staticIndes[i]];

      timeSeriesData = timeSeriesData.concat(teamData);
    }
    multiIndesData.push(timeSeriesData);
  }

  var chart_options = {
    title: countyname + " " + "全时间序列" + "生态环境指标变化情况",
    legend: staticIndes,
    xAxis: [
      "2018春",
      "2018夏",
      "2018秋",
      "2018冬",
      "2019春",
      "2019夏",
      "2019秋",
      "2019冬",
      "2020春",
      "2020夏",
      "2020秋",
    ],
    xAxisName: "Time",
    yAxisName: "各个指标",
    series: multiIndesData,
    chartType: "line",
    smooth: true,
  };

  var chart = ui.Chart.array(chart_options);
  chart.setStyle({ width: "500px", top: "50px", right: "1px" });
  Map.addUI(chart);
}

// 根据EI 值对地区进行评级：
function classEI() {
  // 实际值减去平均值
  var subvalueEI =
    staticData[selectCode][selectYear]["EI"][seasonindex] -
    meanData["EI"][seasonindex];
  var sublist = [];
  if (parseFloat(subvalueEI) > 0.045) {
    // 大于一倍标准差
    environmetClass = 1;
  } else if (parseFloat(subvalueEI) > 0) {
    //大于均值
    environmetClass = 2;
  } else if (parseFloat(subvalueEI) > -0.045) {
    //小于均值
    environmetClass = 3;
  } else {
    environmetClass = 4;
  }
  //

  var subFVC =
    staticData[selectCode][selectYear]["FVC"][seasonindex] -
    meanData["FVC"][seasonindex];
  if (subFVC < -0.09) {
    sublist.push(["FVC", subFVC]);
  }
  var subLST =
    staticData[selectCode][selectYear]["LST"][seasonindex] -
    meanData["LST"][seasonindex];

  if (subLST > 0.08) {
    sublist.push(["LST", subLST]);
  }
  var subNDBI =
    staticData[selectCode][selectYear]["NDBI"][seasonindex] -
    meanData["NDBI"][seasonindex];
  if (subNDBI > 0.12) {
    sublist.push(["NDBI", subNDBI]);
  }
  var subMNDWI =
    staticData[selectCode][selectYear]["MNDWI"][seasonindex] -
    meanData["MNDWI"][seasonindex];
  if (subMNDWI < -0.1) {
    sublist.push(["MNDWI", subMNDWI]);
  }

  if (selectYear == "2020") {
    var subAQI =
      staticData[selectCode][selectYear]["AQI"][seasonindex] -
      meanData["AQI"][seasonindex];
    if (subAQI > 0.1) {
      sublist.push(["AQI", subAQI]);
    }
  }
  return sublist;
}

// 统计各个指标数据并给出建议
function suggestPart() {
  var index2char = {
    FVC: "植被密度, ",
    NDBI: "建筑物/裸地密度, ",
    MNDWI: "水体数量, ",
    LST: "地表温度, ",
    AQI: "空气质量, ",
  };
  var indesQuality = classEI();
  // var classENV = indesQuality[indesQuality.length-1]     // 环境等级
  var sign = "";
  var strindes = "";
  for (var k = 0; k < indesQuality.length; k++) {
    var index = indesQuality[k][0]; //  每种标识
    charindex = index2char[index];
    strindes += charindex;
    var indexsubvalue = indesQuality[k][1];
    if (indexsubvalue > 0) {
      sign = sign + index + "高于预警值，";
    } else {
      sign = sign + index + "低于预警值，";
    }
  }
  environmetClasstoChart = ["优", "良", "中(预警)", "差"];
  var signChart = "目前该地区:" + sign + "建议加强对" + strindes + "的管理";
  if (parseInt(indesQuality.length) < 1) {
    signChart = "目前该地区各生态环境指标正常";
  }
  var suggestTable = ui.Table({
    items: [
      {
        name: countyname,
        time: selectYear + " " + selectSenson,
        result: "生态宜居性为: " + environmetClasstoChart[environmetClass - 1],
        info: signChart,
      },
    ],
    columns: [
      {
        title: "地区",
        key: "name",
        width: "100px",
        align: "center",
      },
      {
        title: "时间",
        key: "time",
        width: "100px",
        align: "center",
      },
      {
        title: "评估结果",
        key: "result",
        width: "100px",
        align: "center",
      },
      {
        title: "建议",
        key: "info",
        width: "200px",
        align: "center",
      },
    ],
  });
  return suggestTable;
}

// 宜居性评估结果 表
function btn_staticclickBtn() {
  if (staticType == "Season") {
    colum_static();
  } else if (staticType == "TimeSeries") {
    time_static();
  }
  var suggestTable = suggestPart();
  var suggestPanel = ui.Panel({
    widgets: [suggestTable],
    style: {
      width: "500px",
      right: "5px",
      top: "380px",
      border: "4px double #0bcbfb",
    },
  });
  Map.addUI(suggestPanel);
}

// 统计按钮
var btn_static_success = ui.Button({
  label: "统计",
  type: "success",
  onClick: btn_staticclickBtn,
  style: { left: "70px", top: "0px" },
});
var btnPanel_s = ui.Panel({
  widgets: [btn_static_clear, btn_static_success],
  style: { left: "0px", top: "10px" },
  layout: ui.Layout.flow("horizontal"),
});

//统计部分控件容器
var staticPanel = ui.Panel({
  widgets: [staticIndexPanel, showStyle_Panel, timeSries_Panel, btnPanel_s],
  style: {
    left: "3px",
    width: "350px",
    height: "250px",
    top: "5px",
    border: "1px double #ababab",
  },
  layout: ui.Layout.flow("vertical"),
});
var mapPanel = ui.Panel({
  widgets: [
    selectPanel,
    textboxPanel3,
    show_level_Panel,
    textboxPanel1,
    btnPanel,
  ],
  style: {
    left: "3px",
    width: "350px",
    height: "300px",
    top: "10px",
    border: "1px double #ababab",
  },
  layout: ui.Layout.flow("vertical"),
});

// 整体的控件容器
var panel_control = ui.Panel({
  widgets: [label, mapPanel, staticPanel],
  style: {
    width: "370px",
    height: "350px",
    left: "40px",
    top: "50px",
    backgroundColor: "#fff",
    border: "3px solid #00afaf",
  },
});
Map.addUI(panel_control);