bands: ['B4', 'B3', 'B2'], }; // 2019 Jan var filtered = s2 .filter(ee.Filter.date('2019-01-01', '2019-02-01')) .filter(ee.Filter.bounds(geometry)) .select('B.*'); var before = filtered.median().clip(geometry); // Display the input composite. Map.addLayer(before, rgb...
创建多边形区域roi,用于限定分析的地理范围,并设置地图中心。 2. 加载Sentinel-2数据集 加载Sentinel-2数据集,选择特定波段,筛选日期,地理范围和云层覆盖。 3. 添加假彩色图层 使用Sentinel-2数据的特定波段创建假彩色图层,以更好地识别不同地表特征。 4. 计算NDWI 计算归一化差异水体指数,以识别水体。 5. 打印NDW...
1 is a dense cloud pixel 2 is a cirrus cloud pixel. If measurements are not available in one or several bands needed to calculate the cloud mask, the mask value is set to NODATA. After all filtering steps, the cloud mask is available at a spatial resolution of 60 m. It is then re...
clip(roi), {bands:['B8', 'B4', 'B3']}, 'false color composite', false); // 计算NDWI var ndwi = sen.normalizedDifference(['B3', 'B8']).rename('ndwi'); Map.addLayer(ndwi.clip(roi), [], 'ndwi', false); // 打印NDWI直方图 print( ui.Chart.image.histogram(ndwi, roi, 100) ...
Sentinel-2 carries the Multispectral Imager (MSI). This sensor delivers 13 spectral bands ranging from 10 to 60-meter pixel size. Its blue (B2), green (B3), red (B4), and near-infrared (B8) channels have a 10-meter resolution.
.map(function(img) {returnimg.updateMask(img.select(QA_BAND).gte(CLEAR_THRESHOLD)); }) .median();// Sentinel-2visualization parameters. var s2Viz= {bands: ['B4','B3','B2'], min: 0, max: 2500}; Map.addLayer(composite, s2Viz,'median composite'); Map.centerObject(ROI,11);...
Figure: Characteristics of the multispectral instrument (MSI) on board Sentinel-2 (https://www.mdpi.com/128566) S2 Super-resolution creates a 10 m resolution band for all the existing spectral bands with 20 m and 60 m using a trained convolutional neural network. This processing block's outpu...
composite from all the Sentinel-2 images acquired between June 2015 and October 2020. Both tasks were implemented using GEE, an efficient programming, processing and visualisation platform that allowed us to have free manipulation and access to all used LULC products and Sentinel-2 imagery, ...
2. 不同轨道数据拼接:sentinel1卫星的数据采集是通过不同的轨道进行的,不同轨道之间可能存在位置偏差和分辨率差异,当将这些数据拼接在一起时,由于数据之间的差异会导致条带问题的出现。 3. 数据预处理:在数据拼接之前,需要进行预处理操作,如辐射校正、大气校正、地形校正等,但不同数据之间预处理时所采用的方法和参...
It emerged that the false-color composition of the Sentinel-2 bands SWIR, NIR and RED allows water surfaces to be clearly distinguished from the other components of the river corridor. From the false-color composite images, it was possible to identify the three distinct flowing status of non-...