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https://code.earthengine.google.com/6b8092646f132a13435cba982dccbb05 * One goal is to create a chart of the change in NIRv vegetation index over. Another goal is to use the "linearFit" expression for these two variables: NIRv vegetation index and time (in years.) * I am getting an error message for the linearFit function because it says that the 'system:time_start' property isn't a band I can use. How can I revise the code to get the offset and slope for this relationship? function addNIRv(image) { var nir = image.select('SR_B4'); var red = image.select('SR_B3'); var ndvi = image.normalizedDifference(['SR_B4', 'SR_B3']).rename('NDVI'); var nirv = ndvi.multiply(nir).rename('NIRv'); return image.addBands([ndvi, nirv]); } var withNIRv = dataset.map(addNIRv); // Compute mean NIRv for the year var mean_NIRv = withNIRv.select('NIRv').mean().clip(geometry); //geometry for forest plot var BH1_AS = ee.Geometry.Point(-76.376, 42.35778333); // Note that GEE likes coordinates as long, lat var BH1_AS_buffer = BH1_AS.buffer({'distance': 30}); // Plots are 40 by 40, so a 30 meter buffer should cover the entire plot var stats = mean_NIRv.reduceRegions({ collection: ee.FeatureCollection(BH1_AS_buffer), reducer: ee.Reducer.mean(), scale: 30, // meters crs: 'EPSG:32618' }); //Calculating year wise Nirv var year = ee.List.sequence(2011,2019); var year_func = function(y){ var range = ee.Filter.calendarRange (y, y, 'year'); return withNIRv.select('NIRv').filter(range).mean().set ('Year', y) }; var yearwise_nirv = ee.ImageCollection(year.map(year_func)); print (yearwise_nirv); Map.addLayer (yearwise_nirv) //Creating time-series chart: var chart = ui.Chart.image.series ({ imageCollection: yearwise_nirv, region: BH1_AS_buffer, reducer: ee.Reducer.mean(), scale: 30, xProperty: 'Year' }).setOptions ({title: "NIRv over time", trendlines: { 0:{ color: 'CC0000' } }, hAxis: {title: 'Time of the year', format: 'year'} }); print (chart); var linearFit = dataset.select(['system:time_start', 'mean_NIRv']) .reduce(ee.Reducer.linearFit()); Map.addLayer(linearFit, {min: 0, max: [-0.9, 8e-5, 1], bands: ['scale', 'offset', 'scale']}, 'fit'); print(linearFit);

https://code.earthengine.google.com/6b8092646f132a13435cba982dccbb05 * One goal is to create a chart of the change in NIRv vegetation index over. Another goal is to use the "linearFit" expression for these two variables: NIRv vegetation index and time (in years.) * I am getting an error message for the linearFit function because it says that the 'system:time_start' property isn't a band I can use. How can I revise the code to get the offset and slope for this relationship? function addNIRv(image) { var nir = image.select('SR_B4'); var red = image.select('SR_B3'); var ndvi = image.normalizedDifference(['SR_B4', 'SR_B3']).rename('NDVI'); var nirv = ndvi.multiply(nir).rename('NIRv'); return image.addBands([ndvi, nirv]); } var withNIRv = dataset.map(addNIRv); // Compute mean NIRv for the year var mean_NIRv = withNIRv.select('NIRv').mean().clip(geometry); //geometry for forest plot var BH1_AS = ee.Geometry.Point(-76.376, 42.35778333); // Note that GEE likes coordinates as long, lat var BH1_AS_buffer = BH1_AS.buffer({'distance': 30}); // Plots are 40 by 40, so a 30 meter buffer should cover the entire plot var stats = mean_NIRv.reduceRegions({ collection: ee.FeatureCollection(BH1_AS_buffer), reducer: ee.Reducer.mean(), scale: 30, // meters crs: 'EPSG:32618' }); //Calculating year wise Nirv var year = ee.List.sequence(2011,2019); var year_func = function(y){ var range = ee.Filter.calendarRange (y, y, 'year'); return withNIRv.select('NIRv').filter(range).mean().set ('Year', y) }; var yearwise_nirv = ee.ImageCollection(year.map(year_func)); print (yearwise_nirv); Map.addLayer (yearwise_nirv) //Creating time-series chart: var chart = ui.Chart.image.series ({ imageCollection: yearwise_nirv, region: BH1_AS_buffer, reducer: ee.Reducer.mean(), scale: 30, xProperty: 'Year' }).setOptions ({title: "NIRv over time", trendlines: { 0:{ color: 'CC0000' } }, hAxis: {title: 'Time of the year', format: 'year'} }); print (chart); var linearFit = dataset.select(['system:time_start', 'mean_NIRv']) .reduce(ee.Reducer.linearFit()); Map.addLayer(linearFit, {min: 0, max: [-0.9, 8e-5, 1], bands: ['scale', 'offset', 'scale']}, 'fit'); print(linearFit);