GEE图表：利用MODIS中ET数据进行时序图表的绘制

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发布于 2024-10-15 09:00:41

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发布于 2024-10-15 09:00:41

文章被收录于专栏：GEE数据专栏，GEE学习专栏，GEE错误集等专栏

简介

利用MODIS中ET数据进行时序图表的绘制

数据

MODIS/061/MOD16A2GF

MODIS/061/MOD16A2GF数据是一种由美国国家航空航天局（NASA）的MODIS卫星获取的遥感数据。该数据集提供了全球范围内的地表净初级生产力（GPP）和蒸散发（ET）的估算结果。

MOD16A2GF数据是通过使用高分辨率的植被指数（NDVI）和蒸汽压缩所得的气象数据来计算地表GPP和ET的。它还使用了地表温度和辐射数据来准确估计植物蒸腾和土壤蒸发的水分损失。

MOD16A2GF数据的空间分辨率为1千米，并且提供了逐日、逐月和逐年的数据。数据集包含了从2000年至今的数据，因此可以用于长期分析和趋势研究。

该数据集对于研究全球气候变化、生态系统健康状况和水资源管理等方面非常有用。它可以用于监测植被生长和生产力的变化，预测农作物收量和水资源的可持续利用。

MOD16A2GF数据可以在NASA的EOS数据中心获取，使用者可以根据自己的需求选择不同的时间范围和空间范围进行数据下载。数据以标准的GeoTIFF格式提供，可以与常见的GIS软件进行处理和分析。

函数

ui.Chart.image.series(imageCollection, region, reducer, scale, xProperty)

Generates a Chart from an ImageCollection. Plots derived values of each band in a region across images. Usually a time series.

X-axis: Image, labeled by xProperty value.
Y-axis: Band value.
Series: Band names.

Returns a chart.

Arguments:

imageCollection (ImageCollection):

An ImageCollection with data to be included in the chart.

region (Feature|FeatureCollection|Geometry):

The region to reduce.

reducer (Reducer, optional):

Reducer that generates the values for the y-axis. Must return a single value. Defaults to ee.Reducer.mean().

scale (Number, optional):

Scale to use with the reducer in meters.

xProperty (String, optional):

Property to be used as the label for each image on the x-axis. Defaults to 'system:time_start'.

Returns: ui.Chart

代码

//加载研究区域

var geometry = 
    /* color: #d63000 */
    /* shown: false */
    /* displayProperties: [
      {
        "type": "rectangle"
      }
    ] */
    ee.Geometry.Polygon(
        [[[104.87425659179613, 11.582757951758422],
          [104.87425659179613, 11.464344370353382],
          [105.04179809570238, 11.464344370353382],
          [105.04179809570238, 11.582757951758422]]], null, false);

//加载影像
var et = ee.ImageCollection("MODIS/061/MOD16A2GF")
.filterDate('2023', '2024')
.map(function(img){
  var bands = img.select('ET').multiply(0.1)
  return bands.rename('MODIS_ET')
  .copyProperties(img, img.propertyNames())
  })

//图标输出
print(
  ui.Chart.image.series(et, geometry, ee.Reducer.first(), 500, 'system:time_start')
  .setChartType('AreaChart')
  .setOptions({
    title: 'Evapotranspiration Chart', 
    vAxis: {title: 'ET (mm)'}, hAxis: {title: 'Date'},
    series: {0:{color: 'red', lineWidth: 4, pointSize: 5}}
    
    })
  )
  
//矢量集合测试图标

var cor2 = [
  [-114.26883939030296,42.52569509607107],
  [-114.26094296696311,42.52569509607107],
  [-114.26094296696311,42.53100829096698],
  [-114.26883939030296,42.53100829096698],
  [-114.26883939030296,42.52569509607107]
  ]

var pol1 = ee.Geometry.Polygon(cor2)

var cor3 = [
  [-114.22420743229515,42.58360981365639],
  [-114.2159676862014,42.58360981365639],
  [-114.2159676862014,42.58942360551128],
  [-114.22420743229515,42.58942360551128],
  [-114.22420743229515,42.58360981365639]
  ]
  
var pol2 = ee.Geometry.Polygon(cor3)

var geometry2 = ee.FeatureCollection([ee.Feature(pol1), ee.Feature(pol2)])




print(
  ui.Chart.image.seriesByRegion(et, geometry2, ee.Reducer.mean(),
  'MODIS_ET', 500, 'system:time_start', 'system:index')
  .setChartType('AreaChart')
  .setOptions({
    title: 'Evapotranspiration Comparison', 
    vAxis: {title: 'ET (mm)'}, hAxis: {title: 'Date'}, 
    series: {0:{color: 'orange', lineWidth: 4, pointSize: 5}, 
    1:{color: 'green', lineWidth: 4, pointSize: 5}}
    
    
    })
  )