How to make Urban Sprawl Map 1990 - 2023 || Urban Growth || Urban Sprawl Map || Google Earth Engine скачать в хорошем качестве

How to make Urban Sprawl Map 1990 - 2023 || Urban Growth || Urban Sprawl Map || Google Earth Engine

This code is written in Google Earth Engine (GEE) JavaScript API and is used for analyzing urban expansion over a series of years using Landsat satellite imagery. Let's break down the code and understand its functionality: Variables and Functions: 1. *Year List:* ```javascript var yearList = [1990, 1995, 2000, 2005, 2010, 2015, 2020]; ``` This array contains the years for which the analysis will be performed. 2. *Filtering Function:* ```javascript function filterCol(col, roi, date) { return col.filterDate(date[0], date[1]).filterBounds(roi); } ``` This function filters a given image collection (`col`) based on a date range (`date`) and a region of interest (`roi`). 3. *Cloud Masking Functions:* Two functions, `cloudMaskTm` and `cloudMaskOli`, are defined for cloud masking in Landsat images. 4. *Composite Functions:* Two functions, `landsat457` and `landsat89`, are defined to create composite images for Landsat 4, 5, and 7 (for years before 2014) and Landsat 8 and 9 (for years from 2014 onward), respectively. 5. *Generate Image per Year Function:* ```javascript var builtCol = ee.ImageCollection(yearList.map(function (year) { // ... })); ``` This function generates a collection of images for each year using Landsat data, applies cloud masking, and calculates indices such as NDBI and MNDWI. It also adds these layers to the GEE map. Image Generation and Visualization: The code then goes through each year in `yearList`, decides which Landsat collection to use based on the year, generates a composite image, calculates indices, and visualizes the results on the map. Urban Expansion and Visualization: ```javascript var urbanExpansion = builtCol.select('built').min().set(dict); Map.addLayer(urbanExpansion, {}, 'Urban_expansion'); ``` This section creates an image representing the minimum built-up class value for each pixel over the years. The results are visualized on the map as "Urban Expansion." Legend and Visualization: ```javascript var legend = ui.Panel([ui.Label('Urban expansion')], ui.Panel.Layout.flow('vertical'), { position: 'bottomleft' }); yearList.map(function(year, index){ // ... }); Map.add(legend); ``` A legend is created and added to the map, showing the color-coded classes for each year of urban expansion. Area Chart: ```javascript var areaChart = ui.Chart.image.series(builtCol.select('area'), roi, ee.Reducer.sum(), 30, 'year') .setChartType('AreaChart') .setOptions({ title: 'Urban area (Ha)', hAxis: { title: 'Year' }, vAxis: { title: 'Area (Ha)' } }); print(areaChart); ``` This section generates and prints an area chart showing the change in urban area over the specified years. Summary: The code performs a comprehensive analysis of urban expansion over a series of years using Landsat satellite imagery. It involves filtering, cloud masking, index calculation, visualization, and charting to provide a detailed understanding of urban growth over time.