iowa_yield_viz.js

var dataset = ee.FeatureCollection('TIGER/2018/Counties').filterMetadata('STATEFP', 'equals', '19');
var visParams = {
  palette: ['ffffcc', '238443'],
  min: 44.5,
  max: 234.7,
};

var stateDataset = ee.FeatureCollection('TIGER/2018/States').filterMetadata('STATEFP', 'equals', '19');

// Save county yield
var sorted_county_FP = [1,
 3,
 5,
 7,
 9,
 11,
 13,
 15,
 17,
 19,
 21,
 23,
 25,
 27,
 29,
 31,
 33,
 35,
 37,
 39,
 41,
 43,
 45,
 47,
 49,
 51,
 53,
 55,
 57,
 59,
 61,
 63,
 65,
 67,
 69,
 71,
 73,
 75,
 77,
 79,
 81,
 83,
 85,
 87,
 89,
 91,
 93,
 95,
 97,
 99,
 101,
 103,
 105,
 107,
 109,
 111,
 113,
 115,
 117,
 119,
 121,
 123,
 125,
 127,
 129,
 131,
 133,
 135,
 137,
 139,
 141,
 143,
 145,
 147,
 149,
 151,
 153,
 155,
 157,
 159,
 161,
 163,
 165,
 167,
 169,
 171,
 173,
 175,
 177,
 179,
 181,
 183,
 185,
 187,
 189,
 191,
 193,
 195,
 197];
 
var yield_data11 = [152.8,
 151.7,
 173.3,
 120.1,
 176.6,
 157.2,
 186.1,
 182.5,
 196.5,
 187.0,
 180.2,
 186.7,
 181.9,
 180.2,
 175.2,
 184.9,
 169.3,
 176.7,
 188.8,
 107.7,
 185.4,
 186.8,
 180.0,
 181.8,
 172.1,
 97.8,
 126.1,
 186.5,
 146.6,
 169.3,
 185.1,
 169.6,
 186.6,
 181.1,
 189.7,
 155.6,
 183.4,
 172.8,
 169.4,
 180.6,
 179.8,
 186.7,
 169.9,
 123.2,
 185.8,
 185.5,
 182.9,
 171.6,
 178.3,
 171.1,
 112.4,
 171.9,
 171.4,
 152.4,
 179.9,
 105.2,
 169.1,
 148.9,
 114.9,
 185.4,
 145.1,
 165.0,
 152.6,
 166.3,
 155.0,
 180.1,
 158.3,
 112.5,
 153.2,
 164.6,
 185.1,
 184.4,
 136.2,
 174.6,
 164.5,
 181.2,
 160.6,
 170.9,
 179.0,
 118.7,
 183.4,
 174.2,
 173.6,
 177.6,
 163.2,
 162.0,
 140.5,
 132.6,
 100.9,
 127.3,
 129.1,
 156.3,
 126.0,
 190.6,
 176.6,
 186.2,
 173.3,
 173.0,
 189.9];

var yield_data12 =[104.4,
 109.8,
 153.6,
 44.5,
 114.8,
 129.3,
 126.4,
 147.1,
 133.3,
 140.4,
 148.2,
 122.0,
 134.8,
 105.3,
 120.4,
 158.9,
 124.8,
 158.7,
 125.8,
 76.7,
 170.1,
 152.9,
 139.6,
 131.3,
 129.0,
 52.4,
 61.2,
 129.8,
 143.7,
 160.9,
 149.4,
 166.6,
 151.0,
 123.2,
 150.0,
 131.2,
 124.6,
 161.5,
 113.4,
 138.0,
 143.3,
 163.6,
 130.9,
 132.0,
 137.8,
 146.1,
 151.4,
 135.7,
 114.6,
 150.9,
 102.8,
 132.4,
 127.3,
 113.0,
 164.6,
 116.0,
 124.2,
 162.9,
 85.3,
 161.6,
 101.4,
 133.0,
 115.1,
 157.6,
 128.8,
 131.4,
 115.1,
 67.3,
 132.0,
 152.6,
 159.8,
 169.6,
 116.2,
 170.6,
 110.1,
 165.3,
 149.1,
 131.9,
 152.3,
 71.6,
 130.7,
 131.7,
 137.8,
 143.2,
 157.6,
 160.2,
 91.7,
 87.3,
 110.3,
 92.6,
 103.5,
 132.1,
 55.7,
 149.2,
 161.1,
 140.6,
 134.8,
 143.1,
 153.7]
var yield_data13 =[137.8,
 147.6,
 162.1,
 109.1,
 157.1,
 163.7,
 166.1,
 154.2,
 175.1,
 168.8,
 160.5,
 179.2,
 132.6,
 136.5,
 159.5,
 169.7,
 163.1,
 185.1,
 171.8,
 126.5,
 167.2,
 181.2,
 185.6,
 157.8,
 145.3,
 146.7,
 131.2,
 184.7,
 165.4,
 162.4,
 196.0,
 166.4,
 181.2,
 170.0,
 179.6,
 159.9,
 137.9,
 180.8,
 130.1,
 135.0,
 169.9,
 156.6,
 177.1,
 160.4,
 159.1,
 155.4,
 177.7,
 165.9,
 173.2,
 158.8,
 145.5,
 181.1,
 179.3,
 156.7,
 167.7,
 144.1,
 178.6,
 158.5,
 117.9,
 190.5,
 140.9,
 168.6,
 156.4,
 163.2,
 171.0,
 164.1,
 175.2,
 115.3,
 154.0,
 158.3,
 195.3,
 182.0,
 154.5,
 168.8,
 188.9,
 163.8,
 143.6,
 179.4,
 158.5,
 121.1,
 142.6,
 167.8,
 182.6,
 194.1,
 137.2,
 158.7,
 136.2,
 137.0,
 144.1,
 150.4,
 146.7,
 159.0,
 125.1,
 137.6,
 149.1,
 181.8,
 164.2,
 150.7,
 168.8]
var yield_data14 = [169.3,
 169.9,
 175.6,
 170.9,
 185.5,
 185.4,
 165.2,
 180.9,
 159.0,
 169.3,
 172.1,
 167.7,
 189.6,
 188.6,
 173.7,
 184.1,
 168.3,
 183.6,
 157.6,
 162.2,
 166.3,
 176.7,
 197.0,
 183.0,
 195.5,
 184.2,
 164.0,
 174.9,
 199.0,
 157.9,
 184.9,
 165.0,
 170.9,
 162.8,
 165.8,
 191.5,
 181.2,
 182.4,
 176.1,
 173.1,
 173.9,
 166.3,
 161.1,
 196.6,
 164.4,
 176.9,
 189.9,
 192.1,
 188.9,
 191.5,
 200.9,
 184.6,
 180.1,
 193.2,
 176.6,
 200.6,
 176.1,
 188.2,
 153.7,
 172.9,
 171.4,
 189.9,
 171.6,
 190.5,
 184.9,
 175.1,
 156.6,
 175.7,
 163.1,
 188.1,
 180.3,
 175.4,
 182.4,
 164.6,
 187.3,
 174.8,
 181.4,
 169.1,
 188.4,
 166.4,
 179.8,
 194.5,
 185.2,
 187.4,
 169.9,
 182.7,
 178.8,
 176.1,
 192.2,
 195.2,
 169.9,
 191.3,
 171.9,
 190.0,
 172.7,
 174.0,
 177.5,
 181.5,
 169.4]
var yield_data15 = [176.5,
 169.6,
 175.4,
 154.3,
 189.8,
 187.5,
 192.9,
 192.3,
 203.1,
 191.6,
 202.7,
 193.3,
 194.7,
 195.4,
 193.7,
 188.8,
 196.9,
 209.6,
 202.8,
 152.4,
 202.8,
 193.2,
 188.2,
 199.1,
 182.4,
 142.4,
 162.7,
 195.8,
 176.0,
 194.5,
 197.0,
 203.3,
 191.8,
 196.5,
 200.2,
 179.9,
 189.0,
 199.9,
 179.2,
 198.1,
 201.2,
 199.3,
 189.5,
 178.4,
 202.1,
 194.8,
 203.1,
 199.3,
 190.6,
 198.9,
 168.2,
 187.1,
 186.6,
 181.0,
 199.0,
 145.1,
 189.2,
 181.7,
 154.8,
 196.0,
 169.6,
 190.3,
 178.1,
 194.9,
 NaN,
 202.1,
 169.0,
 NaN,
 185.2,
 177.7,
 205.2,
 204.7,
 165.8,
 197.5,
 203.6,
 205.5,
 187.0,
 204.0,
 197.8,
 147.8,
 204.8,
 195.9,
 195.3,
 201.9,
 188.0,
 189.5,
 NaN,
 NaN,
 158.3,
 159.3,
 170.3,
 195.0,
 158.0,
 201.0,
 203.6,
 185.6,
 202.3,
 202.1,
 198.4]
var yield_data16 = [190.3,
 187.4,
 205.1,
 186.3,
 206.1,
 199.9,
 206.4,
 208.4,
 210.6,
 205.6,
 201.1,
 207.3,
 207.3,
 203.1,
 195.9,
 215.3,
 193.6,
 219.7,
 206.6,
 163.9,
 202.0,
 210.3,
 213.8,
 213.5,
 204.0,
 188.7,
 181.1,
 202.3,
 210.0,
 188.0,
 211.5,
 198.5,
 202.5,
 196.3,
 204.8,
 180.8,
 205.5,
 198.5,
 198.2,
 209.0,
 200.3,
 208.0,
 204.6,
 199.0,
 202.2,
 206.1,
 216.0,
 210.6,
 202.1,
 214.7,
 197.0,
 189.0,
 201.3,
 208.6,
 204.7,
 194.6,
 200.3,
 200.2,
 174.6,
 206.9,
 185.5,
 204.7,
 198.0,
 211.3,
 188.4,
 199.1,
 184.5,
 180.0,
 185.5,
 203.0,
 210.7,
 203.7,
 185.8,
 196.0,
 209.2,
 206.8,
 199.8,
 210.4,
 213.2,
 179.5,
 214.3,
 216.0,
 215.3,
 212.2,
 211.9,
 208.4,
 159.9,
 183.0,
 189.0,
 196.9,
 184.6,
 208.2,
 174.5,
 200.8,
 197.9,
 210.7,
 203.7,
 191.5,
 200.2]
var yield_data17 = [175.2,
 179.9,
 190.5,
 170.0,
 211.2,
 215.3,
 209.2,
 192.4,
 212.7,
 221.3,
 187.9,
 211.4,
 195.1,
 211.3,
 197.4,
 222.3,
 208.9,
 203.7,
 194.4,
 NaN,
 197.3,
 213.6,
 213.3,
 221.9,
 187.2,
 107.3,
 NaN,
 218.0,
 200.1,
 196.2,
 215.1,
 210.1,
 207.6,
 203.4,
 206.1,
 204.5,
 202.2,
 217.3,
 197.6,
 194.6,
 200.2,
 213.7,
 193.2,
 196.4,
 201.7,
 200.9,
 215.7,
 216.7,
 202.1,
 204.6,
 165.5,
 213.1,
 217.0,
 176.4,
 205.6,
 178.0,
 217.4,
 216.6,
 NaN,
 218.9,
 173.1,
 177.2,
 185.7,
 222.4,
 190.1,
 213.4,
 196.0,
 169.9,
 199.1,
 206.8,
 213.8,
 211.6,
 193.1,
 195.4,
 193.0,
 190.9,
 200.3,
 195.8,
 215.1,
 167.8,
 194.5,
 220.0,
 207.1,
 220.7,
 200.3,
 220.6,
 175.0,
 147.9,
 128.2,
 153.0,
 183.2,
 220.4,
 NaN,
 197.9,
 210.7,
 199.7,
 200.5,
 198.5,
 206.9]
var yield_data18 =[149.5,
 171.6,
 198.4,
 NaN,
 180.0,
 214.6,
 206.2,
 193.7,
 212.4,
 207.1,
 193.1,
 211.3,
 193.3,
 208.4,
 169.5,
 222.3,
 184.4,
 213.3,
 192.9,
 161.8,
 158.5,
 201.5,
 210.9,
 214.0,
 174.0,
 NaN,
 172.5,
 224.8,
 195.4,
 160.4,
 211.8,
 155.8,
 200.1,
 184.4,
 204.3,
 195.1,
 201.3,
 225.2,
 192.2,
 188.9,
 176.7,
 216.6,
 176.0,
 189.7,
 185.5,
 162.3,
 222.2,
 211.7,
 202.4,
 218.6,
 198.8,
 212.3,
 208.9,
 203.7,
 180.2,
 201.3,
 215.4,
 196.5,
 NaN,
 193.0,
 167.8,
 207.7,
 190.2,
 226.0,
 NaN,
 193.3,
 181.4,
 167.0,
 191.5,
 209.6,
 201.6,
 180.2,
 188.1,
 157.9,
 213.8,
 179.2,
 186.2,
 NaN,
 218.7,
 153.3,
 213.5,
 214.0,
 189.1,
 211.9,
 192.3,
 224.3,
 154.4,
 155.8,
 180.9,
 NaN,
 163.6,
 214.3,
 171.6,
 188.1,
 180.8,
 198.1,
 219.3,
 180.0,
 180.5]




var yield_data19 = [176.6,
 NaN,
 187.2,
 166.8,
 216.0,
 197.6,
 205.1,
 194.8,
 212.5,
 218.9,
 190.8,
 209.5,
 198.8,
 219.7,
 200.3,
 193.7,
 191.8,
 208.9,
 212.1,
 NaN,
 185.5,
 197.5,
 196.1,
 234.7,
 195.0,
 160.0,
 NaN,
 204.6,
 176.9,
 170.0,
 216.4,
 NaN,
 200.5,
 202.9,
 202.7,
 NaN,
 201.4,
 209.8,
 196.7,
 198.2,
 193.3,
 200.2,
 NaN,
 164.5,
 194.2,
 198.7,
 NaN,
 190.6,
 185.5,
 209.3,
 162.7,
 181.3,
 203.0,
 175.5,
 198.7,
 172.5,
 223.7,
 174.6,
 NaN,
 186.6,
 175.7,
 189.9,
 170.7,
 221.9,
 202.9,
 194.5,
 203.9,
 162.3,
 204.8,
 173.2,
 204.9,
 182.5,
 191.4,
 198.3,
 217.8,
 NaN,
 196.7,
 208.0,
 200.3,
 NaN,
 220.6,
 189.3,
 217.3,
 192.2,
 189.3,
 204.8,
 161.7,
 168.9,
 171.0,
 176.5,
 NaN,
 178.9,
 151.5,
 202.9,
 198.8,
 200.4,
 218.2,
 196.5,
 197.0]


sorted_county_FP = ee.List(sorted_county_FP)

yield_data11 = ee.List(yield_data11)
yield_data12 = ee.List(yield_data12)
yield_data13 = ee.List(yield_data13)
yield_data14 = ee.List(yield_data14)
yield_data15 = ee.List(yield_data15)
yield_data16 = ee.List(yield_data16)
yield_data17 = ee.List(yield_data17)
yield_data18 = ee.List(yield_data18)
yield_data19 = ee.List(yield_data19)

 
var dataset11 = dataset.map(function (img) {
  return img.set('Yield', yield_data11.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset12 = dataset.map(function (img) {
  return img.set('Yield', yield_data12.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset13 = dataset.map(function (img) {
  return img.set('Yield', yield_data13.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset14 = dataset.map(function (img) {
  return img.set('Yield', yield_data14.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset15 = dataset.map(function (img) {
  return img.set('Yield', yield_data15.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset16 = dataset.map(function (img) {
  return img.set('Yield', yield_data16.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset17 = dataset.map(function (img) {
  return img.set('Yield', yield_data17.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});

var dataset18 = dataset.map(function (img) {
  return img.set('Yield', yield_data18.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});
 
var dataset19 = dataset.map(function (img) {
  return img.set('Yield', yield_data19.get(sorted_county_FP.indexOf((ee.Number.parse(img.get('COUNTYFP'))))))
});

var image11 = ee.Image().float().paint(dataset11, 'Yield');
var image12 = ee.Image().float().paint(dataset12, 'Yield');
var image13 = ee.Image().float().paint(dataset13, 'Yield');
var image14 = ee.Image().float().paint(dataset14, 'Yield');
var image15 = ee.Image().float().paint(dataset15, 'Yield');
var image16 = ee.Image().float().paint(dataset16, 'Yield');
var image17 = ee.Image().float().paint(dataset17, 'Yield');
var image18 = ee.Image().float().paint(dataset18, 'Yield');
var image19 = ee.Image().float().paint(dataset19, 'Yield');


var countyOutlines = ee.Image().float().paint({
  featureCollection: dataset,
  color: 'black',
  width: 2
});
var stateOutlines = ee.Image().float().paint({
  featureCollection: stateDataset,
  color: 'black',
  width: 2
});

Map.setCenter(-93, 42, 7);
//Map.addLayer(ee.Image.constant(100), {palette: ['ffffcc']},'yellow')
//Map.addLayer(ee.Image.constant(100), {palette: ['black']},'black')
Map.addLayer(ee.Image.constant(100), {palette: ['white']},'white')

Map.addLayer(image11, visParams, 'yield-11');
Map.addLayer(image12, visParams, 'yield-12');
Map.addLayer(image13, visParams, 'yield-13');
Map.addLayer(image14, visParams, 'yield-14');
Map.addLayer(image15, visParams, 'yield-15');
Map.addLayer(image16, visParams, 'yield-16');
Map.addLayer(image17, visParams, 'yield-17');
Map.addLayer(image18, visParams, 'yield-18');
Map.addLayer(image19, visParams, 'yield-19');

//Map.addLayer(countyOutlines, {palette: ['238443']}, 'county outlines');
Map.addLayer(stateOutlines, {palette: ['004529']}, 'state outlines');

Map.addLayer(dataset, null, 'for Inspector', false);