NEON_SJR_MODIS_LST.txt

//Pulling MODIS LST data for a collection of NEON points
//16 January 2024
//Cat Lippi
//Modded by S.J. Ryan, July 2024 for VByte Workshop

//Bring in MODIS LST imagery
var modis = ee.ImageCollection('MODIS/061/MOD11A2').filterDate('2018', Date.now());
var modis_lst = modis.select('LST_Day_1km');
var modis_lst_vis = {
  min: 13000.0,
  max: 16500.0,
  palette: [
    '040274', '040281', '0502a3', '0502b8', '0502ce', '0502e6',
    '0602ff', '235cb1', '307ef3', '269db1', '30c8e2', '32d3ef',
    '3be285', '3ff38f', '86e26f', '3ae237', 'b5e22e', 'd6e21f',
    'fff705', 'ffd611', 'ffb613', 'ff8b13', 'ff6e08', 'ff500d',
    'ff0000', 'de0101', 'c21301', 'a71001', '911003'
  ],
};

//Add MODIS imagery to map
Map.addLayer(modis_lst, modis_lst_vis,
    'MODIS LST', false);
    
    
// Rescale MODIS LST and convert to Celsius (C)
var modis_lst_C = modis_lst.map(function(image) {
  return image
    .multiply(0.02)
    .subtract(273.15)
    .copyProperties(image, ['system:time_start']);
});



///////////////////////////////////////////////////////////////////////////
//FUNCTIONS//
//////////////////////////////////////////////////////////////////////////
// Function to create buffer around each point
function bufferPoints(radius, bounds) {
  return function(pt) {
    pt = ee.Feature(pt);
    return bounds ? pt.buffer(radius).bounds() : pt.buffer(radius);
  };
}

///////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////

//Trying to export LST values for all NEON points at once
// Pull in points and make FeatureCollection
// Combine NEON points into one feature collection
var towers = ee.FeatureCollection([
  ee.Feature(ee.Geometry.Point([-81.99343, 29.68927]), {plot_id: 'OSBS'}),
  ee.Feature(ee.Geometry.Point([-71.28731, 44.06388]), {plot_id: 'BART'}),
  ee.Feature(ee.Geometry.Point([-78.07164, 39.06026]), {plot_id: 'BLAN'}),
  ee.Feature(ee.Geometry.Point([-76.56001, 38.89008]), {plot_id: 'SERC'}),
  ee.Feature(ee.Geometry.Point([-81.4362, 28.12504]), {plot_id: 'DSNY'}),
   ee.Feature(ee.Geometry.Point([-84.46861, 31.19484]), {plot_id: 'JERC'}),
    ee.Feature(ee.Geometry.Point([-83.50195, 35.68896]), {plot_id: 'GRSM'}),
     ee.Feature(ee.Geometry.Point([-80.52484, 37.37828]), {plot_id: 'MLBS'}),
      ee.Feature(ee.Geometry.Point([-72.17266, 42.5369]), {plot_id: 'HARV'}),
       ee.Feature(ee.Geometry.Point([-78.1395, 38.89292]), {plot_id: 'SCBI'}),
        ee.Feature(ee.Geometry.Point([-89.53725, 46.23388]), {plot_id: 'UNDE'}),
         ee.Feature(ee.Geometry.Point([-84.2826, 35.96412]), {plot_id: 'ORNL'}),
          ee.Feature(ee.Geometry.Point([-87.39327, 32.95046]), {plot_id: 'TALL'}),
]);

//Read in tick plots from 13 NEON sites
//Uploaded csv to Assets
//NOTE: Yours will be named for your asset collection, so change the below variable assignment
var tickplots = ee.FeatureCollection('projects/ee-sjryan3/assets/NEON_tickplots_13sites_utf8');


//view feature collections
Map.addLayer(towers, {color: 'Red'}, 'NEON Towers');
Map.addLayer(tickplots, {color: 'Green'}, 'NEON Tick Plots');


// Implement buffer function to make each point a 1km^2 polygon
var ptsbuff = towers.map(bufferPoints(500, true)); //true = square pixel
var tickbuff = tickplots.map(bufferPoints(500, true));

//Get zonal statistics
var towreduced = modis_lst_C.map(function(image){
  return image.reduceRegions({
    collection:ptsbuff, 
    reducer:ee.Reducer.mean(), 
    scale: 1000  //Resolution of MODIS LST (m)
  });
});

print(towreduced.limit(50));

var tickreduced = modis_lst_C.map(function(image){
  return image.reduceRegions({
    collection:tickbuff, 
    reducer:ee.Reducer.mean(), 
    scale: 1000   //Resolution of MODIS LST (m)
  });
});

print(tickreduced.limit(50));

// the resulting mean is a FeatureCollection
// so you can export it as a table
//NOTE: when you run the export script, it does not automatically write the file
//after running script, the task tab will highlight in the right GEE editor window
//need to click the run button under unsubmitted tasks for each csv file

Export.table.toDrive({
    collection: towreduced.flatten(), 
    description: 'NEON_towers_MODIS_LST_export', 
    folder: 'NEON_MODIS', 
    fileFormat: 'CSV'
})

Export.table.toDrive({
    collection: tickreduced.flatten(), 
    description: 'NEON_tickplots_MODIS_LST_export', 
    folder: 'NEON_MODIS', 
    fileFormat: 'CSV'
})
//var table = reduced.flatten();

// Print in console  
//print(table.limit(50));