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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,215 @@ | ||
| // Example script showing how to create a box plot with outliers. | ||
| var s2 = ee.ImageCollection('COPERNICUS/S2_HARMONIZED'); | ||
| var geometry = ee.Geometry.Polygon([[ | ||
| [82.60642647743225, 27.16350437805251], | ||
| [82.60984897613525, 27.1618529901377], | ||
| [82.61088967323303, 27.163695288375266], | ||
| [82.60757446289062, 27.16517483230927] | ||
| ]]); | ||
|
|
||
| Map.addLayer(geometry, {color: 'red'}, 'Farm'); | ||
| Map.centerObject(geometry); | ||
| var rgbVis = {min: 0.0, max: 3000, bands: ['B4', 'B3', 'B2']}; | ||
|
|
||
| var filtered = s2 | ||
| .filter(ee.Filter.date('2017-01-01', '2018-01-01')) | ||
| .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 30)) | ||
| .filter(ee.Filter.bounds(geometry)); | ||
|
|
||
| // Write a function for Cloud masking | ||
| function maskS2clouds(image) { | ||
| var qa = image.select('QA60'); | ||
| var cloudBitMask = 1 << 10; | ||
| var cirrusBitMask = 1 << 11; | ||
| var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and( | ||
| qa.bitwiseAnd(cirrusBitMask).eq(0)); | ||
| return image.updateMask(mask).multiply(0.0001) | ||
| .select('B.*') | ||
| .copyProperties(image, ['system:time_start']); | ||
| } | ||
|
|
||
| var filtered = filtered.map(maskS2clouds); | ||
| // Write a function that computes NDVI for an image and adds it as a band | ||
| function addNDVI(image) { | ||
| var ndvi = image.normalizedDifference(['B8', 'B4']).rename('ndvi'); | ||
| return image.addBands(ndvi); | ||
| } | ||
|
|
||
| // Map the function over the collection | ||
| var withNdvi = filtered.map(addNDVI); | ||
|
|
||
| // Extract the values from each image | ||
| var values = withNdvi.map(function(image) { | ||
| var ndvi = image.select('ndvi'); | ||
|
|
||
| var allReducers = ee.Reducer.median() | ||
| .combine({reducer2: ee.Reducer.min(), sharedInputs: true} ) | ||
| .combine({reducer2: ee.Reducer.max(), sharedInputs: true} ) | ||
| .combine({reducer2: ee.Reducer.percentile([25]), sharedInputs: true} ) | ||
| .combine({reducer2: ee.Reducer.percentile([50]), sharedInputs: true} ) | ||
| .combine({reducer2: ee.Reducer.percentile([75]), sharedInputs: true} ) | ||
|
|
||
| var stats = ndvi.reduceRegion({ | ||
| reducer: allReducers, | ||
| geometry: geometry, | ||
| scale: 10}); | ||
| var date = image.date(); | ||
| var dateString = date.format('YYYY-MM-dd'); | ||
|
|
||
| var properties = { | ||
| 'date': dateString, | ||
| 'median': stats.get('ndvi_p50'), // median is 50th percentile | ||
| 'min': stats.get('ndvi_min'), | ||
| 'max': stats.get('ndvi_max'), | ||
| 'p25': stats.get('ndvi_p25'), | ||
| 'p50': stats.get('ndvi_p50'), | ||
| 'p75': stats.get('ndvi_p75'), | ||
| } | ||
| return ee.Feature(null, properties) | ||
|
|
||
| }) | ||
| // Remove null values | ||
| var values = values.filter(ee.Filter.notNull( | ||
| ['median', 'min', 'max', 'p25', 'p50', 'p75'])); | ||
| print(values) | ||
|
|
||
| // Format the results as a list of DataTable rows | ||
|
|
||
| // We need a list to map() over | ||
| var dateList = values.aggregate_array('date'); | ||
|
|
||
| // Helper function to format dates as per DataTable requirements | ||
| // Converts date strings | ||
| // '2017-01-01' becomes 'Date(2017,0,1)' | ||
| // month is indexed from 0 in Date String representation | ||
| function formatDate(date) { | ||
| var year = ee.Date(date).get('year').format() | ||
| var month = ee.Date(date).get('month').subtract(1).format() | ||
| var day = ee.Date(date).get('day').format() | ||
| return ee.String('Date(') | ||
| .cat(year) | ||
| .cat(', ') | ||
| .cat(month) | ||
| .cat(', ') | ||
| .cat(day) | ||
| .cat(ee.String(')')); | ||
| } | ||
|
|
||
| // We will compute the values to display whiskers | ||
| // at 1.5*(Inter-Quartile Range) | ||
| // If the minimum or maximum values fall outside | ||
| // if this range, they will be considered outliers. | ||
| var rowList = dateList.map(function(date) { | ||
| var f = values.filter(ee.Filter.eq('date', date)).first(); | ||
| var x = formatDate(date); | ||
| var median = f.getNumber('median'); | ||
| var p25 = f.getNumber('p25'); | ||
| var p50 = f.getNumber('p50'); | ||
| var p75 = f.getNumber('p75'); | ||
| // Compute min/max as the Inter-Quartile Range (IQR) | ||
| var min = ee.Number.expression('p25 - 1.5*(p75-p25)', { | ||
| p75: ee.Number(p75), | ||
| p25: ee.Number(p25)}) | ||
| var max = ee.Number.expression('p75 + 1.5*(p75-p25)', { | ||
| p75: ee.Number(p75), | ||
| p25: ee.Number(p25)}) | ||
| var minValue = f.getNumber('min'); | ||
| var maxValue = f.getNumber('max'); | ||
| // Add the outlier if they are outside of IQR | ||
| var minOutlier = ee.Algorithms.If(minValue.lt(min), minValue, null); | ||
| var maxOutlier = ee.Algorithms.If(maxValue.gt(max), maxValue, null); | ||
| var rowDict = { | ||
| c: [{v: x}, {v: median}, {v: minOutlier}, {v: maxOutlier}, {v: min}, {v: max}, | ||
| {v: p25}, {v: p50}, {v: p75}] | ||
| }; | ||
| return rowDict; | ||
| }); | ||
|
|
||
| print('Rows', rowList); | ||
|
|
||
| // We need to convert the server-side rowList object | ||
| // to client-side javascript object | ||
| // use evaluate() | ||
| rowList.evaluate(function(rowListClient) { | ||
| var dataTable = { | ||
| cols: [ | ||
| {id: 'x', type: 'date'}, | ||
| {id: 'median', type: 'number'}, | ||
| {id: 'minOutlier', type: 'number', role: 'interval'}, | ||
| {id: 'maxOutlier', type: 'number', role: 'interval'}, | ||
| {id: 'min', type: 'number', role: 'interval'}, | ||
| {id: 'max', type: 'number', role: 'interval'}, | ||
| {id: 'firstQuartile', type: 'number', role: 'interval'}, | ||
| {id: 'median', type: 'number', role: 'interval'}, | ||
| {id: 'thirdQuartile', type:'number', role: 'interval'}, | ||
|
|
||
| ], | ||
| rows: rowListClient | ||
| }; | ||
|
|
||
| var options = { | ||
| title:'NDVI Time-Series Box Plot with Outliers', | ||
| vAxis: { | ||
| title: 'NDVI', | ||
| gridlines: { | ||
| color: '#d9d9d9' | ||
| }, | ||
| minorGridlines: { | ||
| color: 'transparent' | ||
| }, | ||
| viewWindow: { | ||
| min: -0.2, | ||
| max: 1 | ||
| } | ||
| }, | ||
| hAxis: { | ||
| title: '', | ||
| format: 'YYYY-MMM', | ||
| viewWindow: { | ||
| min: new Date(2017, 0), | ||
| max: new Date(2018, 0) | ||
| }, | ||
| gridlines: { | ||
| color: '#d9d9d9' | ||
| }, | ||
| minorGridlines: { | ||
| color: 'transparent' | ||
| } | ||
| }, | ||
| legend: {position: 'none'}, | ||
| lineWidth: 1, | ||
| series: [{'color': '#D3362D'}], | ||
| interpolateNulls: true, | ||
| intervals: { | ||
| barWidth: 2, | ||
| boxWidth: 4, | ||
| lineWidth: 1, | ||
| style: 'boxes' | ||
| }, | ||
| interval: { | ||
| min: { | ||
| style: 'bars', | ||
| fillOpacity: 1, | ||
| color: '#777777' | ||
| }, | ||
| max: { | ||
| style: 'bars', | ||
| fillOpacity: 1, | ||
| color: '#777777' | ||
| }, | ||
| minOutlier: { | ||
| style: 'points', | ||
| pointSize: 2 | ||
| }, | ||
| maxOutlier: { | ||
| style: 'points', | ||
| pointSize: 2 | ||
| }, | ||
| }, | ||
| chartArea: {left:100, right:100} | ||
| }; | ||
|
|
||
| var chart = ui.Chart(dataTable, 'LineChart', options); | ||
| print(chart); | ||
| }); | ||
|
|
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