导读：

1. 创建和探索如何读取一个假彩色无云的Landsat合成影像；

2.计算归一化燃烧指数；

3.定位变化的区域；

4.生成变更图并使用阈值对变更进行分类。

一、准备影像

1.1 select 用法

 1.2 多时相配准、辐射大气校正

这里用的LANDSAT/LC08/C02/T1_L2数据集。

二、创建假彩色合成影像

var visParam = { 'bands': ['swir2', 'nir', 'red'], 
    'min': 7750, 
    'max': 22200 
}; 
Map.addLayer(preImage, visParam, 'pre'); 
Map.addLayer(postImage, visParam, 'post'); 

Q: 调色板中的'min' 和'max'参数的值是怎么确定的？

三、代码

//----------------------------Section 1 ------------------------------------
var landsat8 = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
    .select( ['SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7'], 
    ['blue', 'green', 'red', 'nir', 'swir1', 'swir2'] ); 
    

var point = ee.Geometry.Point([-123.64, 42.96]); 
Map.centerObject(point, 11); 

var preImage = landsat8.filterBounds(point) 
    .filterDate('2013-06-01', '2013-06-30') 
    .sort('CLOUD_COVER', true) 
    .first(); 
print('preImage',preImage);

 
var postImage = landsat8.filterBounds(point)
    .filterDate('2020-06-01', '2020-06-30') 
    .sort('CLOUD_COVER', true) 
    .first(); 
print('postImage', postImage);

//----------------------------Section 2 ------------------------------------
var visParam = { 'bands': ['swir2', 'nir', 'red'], 
    'min': 7750, 
    'max': 22200 
}; 
Map.addLayer(preImage, visParam, 'pre'); 
Map.addLayer(postImage, visParam, 'post'); 

//----------------------------Section 3 计算NBR------------------------------------
// Calculate NBR. 
var nbrPre = preImage.normalizedDifference(['nir', 'swir2']) .rename('nbr_pre'); 
var nbrPost = postImage.normalizedDifference(['nir', 'swir2']) .rename('nbr_post');

//----------------------------Section 4 Single Date Transformation------------------------------------
// 2-date change. 
var diff = nbrPost.subtract(nbrPre).rename('change'); 
var palette = [ 
    '011959', '0E365E', '1D5561', '3E6C55', '687B3E', '9B882E', 'D59448', 'F9A380', 'FDB7BD', 'FACCFA' 
]; 
var visParams = { 
    palette: palette, 
    min: -0.2, 
    max: 0.2 
}; 
Map.addLayer(diff, visParams, 'change'); 


//----------------------------Section 5 lassify change --------------------------------------
var thresholdGain = 0.10; 
var thresholdLoss = -0.10; 
var diffClassified = ee.Image(0); 
diffClassified = diffClassified.where(diff.lte(thresholdLoss), 2); 
diffClassified = diffClassified.where(diff.gte(thresholdGain), 1); 
print('diffClassified', diffClassified);
var changeVis = { 
    palette: 'fcffc8,2659eb,fa1373', 
    min: 0, 
    max: 2 
}; 
Map.addLayer(diffClassified.selfMask(), changeVis, 'change classified by threshold');