Google Earth Engine（GEE）计算雷达植被指数RVI

今天来分享下如何在GEE中计算雷达植被指数，雷达植被指数（Radar vegetation index，RVI）是基于特征向量分解得到的参数，常用以描述植被的疏密程度。所使用的数据为COPERNICUS/S1_GRD，为哨兵1号合成孔径雷达 (SAR) 数据。
合成孔径雷达具有全天候、全天时对地观测的能力以及电磁散射矢量特性和微波穿透性等优势，可准确反演森林和农作物等植被的分布、结构及长势等信息
计算代码如下：

var roi =  ee.Geometry.Polygon(
        [[[116.98472978918164, 39.24615801205016],
          [116.98472978918164, 38.90714240105087],
          [117.60408403722852, 38.90714240105087],
          [117.60408403722852, 39.24615801205016]]], null, false);
Map.centerObject(roi,7) 
var styling = {color:"red",fillColor:"00000000"};

 // Load the Sentinel-1 ImageCollection, filter to Jun-Sep 2020 observations.
 var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD')
                   .filterDate('2020-01-01', '2020-12-30')
                   .filterBounds(roi)


 // Filter the Sentinel-1 collection by metadata properties.
 var vvVhIw = sentinel1
   // Filter to get images with VV and VH dual polarization.
   .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
   .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
   // Filter to get images collected in interferometric wide swath mode.
   .filter(ee.Filter.eq('instrumentMode', 'IW'));
 print(vvVhIw);
 var RVI = vvVhIw.map(function (image){
   var date = image.get('system:time_start');
   var rvi = image.expression('sqrt(vv/(vv + vh))*(vv/vh)',
     {'vv': image.select('VV'),
      'vh': image.select('VH')
     }

     );

     return rvi.set('system:time_start', date);

   });
 var imageVisParam = {"opacity":1,
                      "bands":["VV"],
                      "min":0.01548,
                      "max":0.46221,
                      "gamma":1};

 Map.addLayer(RVI.first().clip(roi), imageVisParam, 'RVI', false);

 // Plotting of the graph:
 var chart =
     ui.Chart.image.seriesByRegion(
           RVI,
           roi,
           // .filter(ee.Filter.eq('Field_ID', 10)),
           ee.Reducer.mean(),
           'VV',
           10,
           'system:time_start'
         )
         .setSeriesNames(['RVI'])
         .setOptions({
           title: 'RVI',
           hAxis: {title: 'Date', titleTextStyle: {italic: false, bold: true}},
           vAxis: {
             title: 'RVI',
             titleTextStyle: {italic: false, bold: true}
           },
           lineWidth: 5,
           colors: ['#fc0303'],
           curveType: 'function'
         });

 print(chart);

结果显示：

统计结果：
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