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我想使用监督分类对具有清晰时间模式的模式进行分类。例如，识别针叶林中的落叶乔木林分。NDVI 会随着时间的推移在落叶林中以应易于检测的规则模式变化。我假设有一种简单的方法可以将时间数据集展平为单个图像，以便可以在分类算法中使用该图像中的波段。也许使用.map(....)？

这是一些构建答案的代码：

var startDate = '2016-05-01';
var endDate = '2016-09-01';

var lng = -122.3424; var lat = 37.9344; //SF
var region = ee.Geometry.Point(lng, lat);

//Image Import
var l8 = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA')
.filterBounds(region)
.filterDate(startDate,endDate);

// NDVI temporal
var ndvi = l8.map(function(image) {
  var ndvi = image.normalizedDifference(['B5', 'B4']).rename("NDVI");
  return ndvi;
  });

Map.addLayer(ndvi,{},"NDVI Temporal"); // 8 images with 1 band

//NDVI FLATTENED??????? I want 1 image with 8 bands. The below code doesn't work...
var ndviFlat = ee.Image().addBands(ndvi.map(function(image){
  var temp = image.select("NDVI");  
  return temp;
  }));

从那里，我会将 ndviFlat 传递给.sampleRegions，它只适用于Imagesnot ImageCollections：

//Classification Model:
var points = ee.FeatureCollection([trainingPointsPos,trainingPointsNeg]).flatten(); 

var training = ndviFlat.sampleRegions({
  collection: points,
  properties: ['class'],
  scale: 30
});

var trained = ee.Classifier.randomForest(20).train(training, 'class', bands);
classified = regLayers.select(bands).classify(trained);
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1 回答 1

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这是一种方法：

var startDate = '2016-05-01';
var endDate = '2016-09-01';

var lng = -122.3424; 
var lat = 37.9344; //SF
var region = ee.Geometry.Point(lng, lat);

//Image Import
var l8 = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA')
  .filterBounds(region)
  .filterDate(startDate, endDate);

var empty = ee.Image();

// NDVI temporal
var ndvi = ee.Image(l8.iterate(function(image, previous) {
  var name = ee.String('NDVI_').cat(image.id());
  var ndvi = image.normalizedDifference(['B5', 'B4']).rename(name);
  return ee.Image(previous).addBands(ndvi);
}, empty));

// Remove the annoying non-band
ndvi = ndvi.select(ndvi.bandNames().remove('constant'));

Map.centerObject(region, 13);
Map.addLayer(ndvi, {}, 'ndvi');
于 2018-04-30T16:14:24.207 回答