用GEE进行Sen趋势分析，并MK检验，请写一个代码

好的，以下是基于Google Earth Engine的Sen趋势分析及MK检验的代码：

// 设置区域
var roi = ee.Geometry.Polygon(
  [[[-98.72, 34.33], [-98.72, 34.05], [-98.25, 34.05], [-98.25, 34.33]]], 
  null, 
  false
);

// 加载Landsat 5影像集
var collection = ee.ImageCollection('LANDSAT/LT05/C01/T1_SR')
  .filterDate('1984-01-01', '2011-12-31')
  .filterBounds(roi)
  .map(function(image) {
    return image.select('B1', 'B2', 'B3', 'B4', 'B5', 'B7')
      .multiply(0.0001)
      .copyProperties(image, ['system:time_start']);
  });

// 定义Sen趋势函数
var SenTrend = function(collection, band, startYear, endYear) {
  // 计算年份
  var years = ee.List.sequence(startYear, endYear);
  
  // 计算每个像素的趋势值
  var trend = collection.map(function(image) {
    var year = ee.Date(image.get('system:time_start')).get('year');
    var mask = image.select(band).mask();
    var value = image.select(band).multiply(mask);
    var normalized = value.divide(mask.reduceRegion({
      reducer: ee.Reducer.mean(),
      geometry: roi,
      scale: 30
    }).get(band));
    return normalized.set('system:time_start', image.get('system:time_start')).set('year', year);
  }).reduce(ee.Reducer.linearFit());
  
  // 计算趋势斜率
  var slope = trend.select('scale');
  
  // 按年份计算每个像素的趋势值
  var annualTrend = ee.ImageCollection.fromImages(
    years.map(function(year) {
      var annualImage = collection.filterDate(ee.Date.fromYMD(year, 1, 1), ee.Date.fromYMD(year, 12, 31)).mean();
      var annualMask = annualImage.select(band).mask();
      var annualValue = annualImage.select(band).multiply(annualMask);
      var annualNormalized = annualValue.divide(annualMask.reduceRegion({
        reducer: ee.Reducer.mean(),
        geometry: roi,
        scale: 30
      }).get(band));
      return annualNormalized.set('year', year);
    })
  );
  
  // 计算年均值
  var annualMean = annualTrend.reduce(ee.Reducer.mean());
  
  // 计算残差
  var residual = collection.map(function(image) {
    var year = ee.Date(image.get('system:time_start')).get('year');
    var mask = image.select(band).mask();
    var value = image.select(band).multiply(mask);
    var normalized = value.divide(mask.reduceRegion({
      reducer: ee.Reducer.mean(),
      geometry: roi,
      scale: 30
    }).get(band));
    var trendValue = annualMean.select('year', ee.String(year).cat('_mean')).rename('trend');
    var detrended = normalized.subtract(trendValue);
    return detrended.set('system:time_start', image.get('system:time_start')).set('year', year);
  });
  
  // 返回结果
  return {
    'slope': slope,
    'annual': annualTrend,
    'residual': residual
  };
};

// 运行Sen趋势分析
var trend = SenTrend(collection, 'B3', 1984, 2011);

// 计算MK检验
var MKTest = function(collection) {
  // 计算每个像素的趋势值
  var trends = collection.map(function(image) {
    var mask = image.mask();
    var value = image.multiply(mask);
    var normalized = value.divide(mask.reduceRegion({
      reducer: ee.Reducer.mean(),
      geometry: roi,
      scale: 30
    }).get('B3'));
    return normalized.set('system:time_start', image.get('system:time_start'));
  });
  
  // 计算趋势斜率
  var slopes = trends.map(function(image) {
    var year = ee.Date(image.get('system:time_start')).get('year');
    return image.select('B3').reduceRegion({
      reducer: ee.Reducer.linearFit(),
      geometry: roi,
      scale: 30
    }).get('scale').set('year', year);
  });
  
  // 计算MK检验
  var N = slopes.size();
  var S = ee.List.sequence(1, N).map(function(i) {
    return ee.List.sequence(i+1, N).map(function(j) {
      return ee.Algorithms.If(ee.Number(slopes.get(j)).subtract(slopes.get(i)).gt(0), 1, ee.Algorithms.If(ee.Number(slopes.get(j)).subtract(slopes.get(i)).lt(0), -1, 0));
    });
  }).flatten().reduce(ee.Reducer.sum());
  var varS = ee.Number(N*(N-1)*(2*N+5)).divide(18);
  var Z = ee.Number(S).divide(ee.Number(varS).sqrt());
  
  // 返回结果
  return {
    'slopes': slopes,
    'MK': Z
  };
};

// 运行MK检验
var test = MKTest(collection.select('B3').filterDate('1990-01-01', '2010-12-31'));

// 显示结果
print('Sen趋势斜率', trend.slope);
print('MK检验', test.MK);

这段代码实现了对Landsat 5影像集中某个区域的B3波段进行Sen趋势分析，并计算了1990年到2010年期间的MK检验。其中，Sen趋势分析使用了Google Earth Engine中的reduce()函数和reduceRegion()函数，MK检验则使用了Algorithms.If()函数和reduce()函数。