Indice_NDMI_NDRE_Cabuyaro_Sentinel.js

var geometry = 
    /* color: #d63000 */
    /* shown: false */
    ee.Geometry.Polygon(
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          [-72.82947920310157, 4.395339576565946],
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          [-72.85318987930437, 4.373591735130669],
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          [-72.85147326612332, 4.373313597735325],
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          [-72.8507544338784, 4.3700615220474734],
          [-72.85022872156878, 4.369719197506667],
          [-72.84928458345215, 4.36912013001256],
          [-72.84879105716949, 4.368339200650602],
          [-72.84782546311486, 4.368242920990585],
          [-72.84746068330169, 4.369002455781846],
          [-72.84676330885986, 4.369275246177067],
          [-72.84607129873852, 4.369047920614247],
          [-72.84555095064877, 4.368392688305174],
          [-72.84254687758076, 4.372800113041608],
          [-72.8392853125377, 4.377079141379587],
          [-72.83306258976528, 4.386514312395148]]]);

/*El siguiente script crea visualizaciones en video con los cambios en el terreno y enl indice NDVI,
que se presentan en una coleccion de imagenes multiespectrales Sentinel en un poligono 
creado por geometria que es un area de cultivo en Cabuyaro Meta*/

/*Traer la coleccion de imagenes Sentinel_2_HARMONIZED con un filtro de fechas del 2021-09-01 al 2023-10-30,
teniendo dos años del ciclo del año cacaotero para Colombia que inicia en el mes de octubre y 
finaliza en el mes de septiembre. Se aplica un filtro con los parametros de 
visualizacion en RGB y recortadas al area del poligono para cada una de las imagenes de la coleccion
al final se imprime la coleccion para saber cuantas imagnes tiene y se visualiza en el mapa*/

var coleccion = ee.ImageCollection('COPERNICUS/S2_HARMONIZED')
.filterBounds(geometry)
.filterDate('2018-09-01','2023-10-30')
.filterMetadata('CLOUDY_PIXEL_PERCENTAGE', 'less_than', 5)
.map(function(i){return i.select(['B2','B3','B4','B5','B8','B11']).clip(geometry)
  })
print('coleccion', coleccion)

var resampleBands = function(image) {
  var projection = image.select('B8').projection()
  var scale = image.select('B8').projection().nominalScale()
  var band5_resampled = image.select('B5').resample('bicubic').reproject({
    crs: projection,
    scale: scale
    })
  var band11_resampled = image.select('B11').resample('bicubic').reproject({
    crs: projection,
    scale: scale
    })
  return image.select(['B2', 'B3', 'B4', 'B8'])
  .addBands(band5_resampled)
  .addBands(band11_resampled)
  .clip(geometry)
  }
var resampledCollection = coleccion.map(resampleBands)

// print('Resampled Collection:', resampledCollection)

var visparam = {bands:['B4','B3','B2'], min: 513, max: 1385, gamma: 1.7}
Map.addLayer(resampledCollection, visparam, "RGB_coleccion")


/*Se define la variable gif para generar el video de visualizacion de la coleccion de imagenes en RGB
y se imprime donde se crea un enlace del video con la coleccion*/

// var gif = resampledCollection.getVideoThumbURL(visparam)
// print('video coleccion cabuyaro', gif)


/*Se define la variable de parametros para la generacion del indice NDVI para cada imagen de la 
coleccion y se crea la funcion de normalizacion diferenciada para el NDVI de cada imagen
recortada al area del poligono de la geometria dada, de igual forma se define una mascara para los 
valores de NDVI superiores a 0.5*/

// var parametrosndvi = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
// var ndvi = resampledCollection.map(function (c){return c.normalizedDifference(['B8','B4']).clip(geometry)})
// var vis = ndvi.map(function (f){return f.visualize(parametrosndvi)})
// var mask = ndvi.map(function (c){return c.visualize(parametrosndvi).mask(c.gte(0.3))})

/*Se realiza el mismo procedimiento para los otros indices SAVI, ARVI, EVI, NDMI, NDRE,GCI*/

// var parametrosavi = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
// var savi = resampledCollection.map(function (a){return a.expression('(1+L)*((nir-red)/(nir+red+L))',
//   {
//     nir : a.select('B8').divide(10000),
//     red : a.select('B4').divide(10000),
//     L : 0.5
//   }).clip(geometry)})
// var visavi = savi.map(function (a){return a.visualize(parametrosavi)})

// var parametrosarvi = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
// var arvi = resampledCollection.map(function (b){return b.expression('(nir-(2*red)+blue)/(nir+(2*red)+blue)',
//   {
//     nir : b.select('B8').divide(10000),
//     red : b.select('B4').divide(10000),
//     blue : b.select('B2').divide(10000),
//   }).clip(geometry)})
// var visarvi = arvi.map(function (b){return b.visualize(parametrosarvi)})

// var parametroevi = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
// var evi = resampledCollection.map(function (g){return g.expression('(2.5)*((nir-red)/(nir+(red*C)-(B*blue)+L))',
//   {
//     nir : g.select('B8').divide(10000),
//     red : g.select('B4').divide(10000),
//     blue : g.select('B2').divide(10000),
//     C : 6,
//     B : 7.5,
//     L : 1
//   }).clip(geometry)})
// var visevi = evi.map(function (g){return g.visualize(parametroevi)})

var parametrosndmi = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
var ndmi = resampledCollection.map(function (j){return j.expression('((nir-swir)/(nir+swir))',
  {
    nir : j.select('B8').divide(10000),
    swir : j.select('B11').divide(10000),
    }).clip(geometry)})
var visndmi = ndmi.map(function (j){return j.visualize(parametrosndmi)})

var parametrosndre = {min:-0.5, max:0.9, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
var ndre = resampledCollection.map(function (k){return k.expression('((nir-rededge)/(nir+rededge))',
  {
    nir : k.select('B8').divide(10000),
    rededge : k.select('B5').divide(10000),
    }).clip(geometry)})
var visndre = ndre.map(function (k){return k.visualize(parametrosndre)})

// var parametrosgci = {min:-0.5, max:10, palette: ['blue', 'black', 'white', 'yellow', 'green', 'red']}
// var gci = resampledCollection.map(function (h){return h.expression('((nir)/(green))-(N)',
//   {
//     nir : h.select('B8').divide(10000),
//     green : h.select('B3').divide(10000),
//     N : 1,
//     }).clip(geometry)})
// var visgci = gci.map(function (h){return h.visualize(parametrosgci)})

/*Se establece la variable de visualizacion por imagenes por segundo y se crea la visualizacion del
video en la consola con la funcion ui.Thumbnail para los diferentes indices y se imprime para
ver los videos en consola*/

var viscontrol = {framesPerSecond: 2}
// var timeserie1 = ui.Thumbnail(vis, viscontrol)
// var timeserie2 = ui.Thumbnail(mask, viscontrol)
// var timeserie3 = ui.Thumbnail(visavi, viscontrol)
// var timeserie4 = ui.Thumbnail(visarvi, viscontrol)
// var timeserie5 = ui.Thumbnail(visevi, viscontrol)
var timeserie6 = ui.Thumbnail(visndmi, viscontrol)
var timeserie7 = ui.Thumbnail(visndre, viscontrol)
// var timeserie8 = ui.Thumbnail(visgci, viscontrol)

// print('ndvi', timeserie1)
// print('maskndvi', timeserie2)
// print('savi', timeserie3)
// print('arvi', timeserie4)
// print('evi', timeserie5)
print('ndmi', timeserie6)
print('ndre', timeserie7)
// print('gci', timeserie8)

// throw('stop')

/*Se adiciona a la coleccion de imagenes las bandas de los indices recortadas a la geometria,
se definen los parametros de visualizacion y se visualizan en el mapa que se 
genera de la coleccion de imagenes*/

var app = function (image){
  // var ndvi = image.normalizedDifference(["B8", "B4"])
  // var savi = image.expression('(1+L)*((nir-red)/(nir+red+L))',
  // {
  //   nir : image.select('B8').divide(10000),
  //   red : image.select('B4').divide(10000),
  //   L : 0.5
  // })
  // var arvi = image.expression('(nir-(2*red)+blue)/(nir+(2*red)+blue)',
  // {
  //   nir : image.select('B8').divide(10000),
  //   red : image.select('B4').divide(10000),
  //   blue : image.select('B2').divide(10000),
  // })
  //   var evi = image.expression('(2.5)*((nir-red)/(nir+(red*C)-(B*blue)+L))',
  // {
  //   nir : image.select('B8').divide(10000),
  //   red : image.select('B4').divide(10000),
  //   blue : image.select('B2').divide(10000),
  //   C : 6,
  //   B : 7.5,
  //   L : 1
  // })  
    var ndmi = image.expression('((nir-swir)/(nir+swir))',
    {
      nir : image.select('B8').divide(10000),
      swir : image.select('B11').divide(10000),
    })
    var ndre = image.expression('((nir-rededge)/(nir+rededge))',
    {
      nir : image.select('B8').divide(10000),
      rededge : image.select('B5').divide(10000),
    })
  // var gci = image.expression('((nir)/(green))-(N)',
  // {
  //   nir : image.select('B8').divide(10000),
  //   green : image.select('B3').divide(10000),
  //   N : 1
  // })
  
  // image = image.addBands(ndvi.rename("NDVI"))
  // image = image.addBands(savi.rename("SAVI"))
  // image = image.addBands(arvi.rename("ARVI"))
  // image = image.addBands(evi.rename("EVI"))
  image = image.addBands(ndmi.rename("NDMI"))
  image = image.addBands(ndre.rename("NDRE")) 
  // image = image.addBands(gci.rename("GCI"))
  
  return image.clip(geometry)}
  
var coleccion1 = resampledCollection.map(app)

print('coleccion1', coleccion1)

// var visParams = {bands:["NDVI"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
// Map.addLayer(coleccion1, visParams, "NDVI_coleccion")

// var visParams1 = {bands:["SAVI"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
// Map.addLayer(coleccion1, visParams1, "SAVI_coleccion")

// var visParams2 = {bands:["ARVI"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
// Map.addLayer(coleccion1, visParams2, "ARVI_coleccion")

// var visParams3 = {bands:["EVI"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
// Map.addLayer(coleccion1, visParams3, "EVI_coleccion")

var visParams4 = {bands:["NDMI"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
Map.addLayer(coleccion1, visParams4, "NDMI_coleccion")

var visParams5 = {bands:["NDRE"], min: -0.5, max:0.9, palette: ["blue", "black", "white", "yellow", "green", "red"]}
Map.addLayer(coleccion1, visParams5, "NDRE_coleccion")

// var visParams6 = {bands:["GCI"], min: -0.5, max:10, palette: ["blue", "black", "white", "yellow", "green", "red"]}
// Map.addLayer(coleccion1, visParams6, "GCI_coleccion")

Map.centerObject(geometry,14)

/*Se imprime la coleccion con las bandas adicionadas de los indices y se genera un video de
visualizacion de los cambios de cada indice en la coleccion de imagenes mediante un enlace*/

// var gif1 = coleccion1.getVideoThumbURL(visParams)
// print('video coleccion ndvi cabuyaro', gif1)

// var gif2 = coleccion1.getVideoThumbURL(visParams1)
// print('video coleccion savi cabuyaro', gif2)

// var gif3 = coleccion1.getVideoThumbURL(visParams2)
// print('video coleccion arvi cabuyaro', gif3)

// var gif4 = coleccion1.getVideoThumbURL(visParams3)
// print('video coleccion evi cabuyaro', gif4)

// var gif5 = coleccion1.getVideoThumbURL(visParams4)
// print('video coleccion ndmi cabuyaro', gif5)

// var gif6 = coleccion1.getVideoThumbURL(visParams5)
// print('video coleccion ndre cabuyaro', gif6)

// var gif7 = coleccion1.getVideoThumbURL(visParams6)
// print('video coleccion gci cabuyaro', gif7)

/*Se crea una etiqueta a partir de un punto que se defina mediante un click en el mapa
la cual va a presentar la grafica de los indices de vegetacion para el sitio que se define en el click*/

var lon = ui.Label()
var lat = ui.Label()

Map.onClick(function(click){
  lon.setValue('Longitud: '+ click.lon.toFixed(2))
  lat.setValue('Latitud: '+ click.lat.toFixed(2))
  var punto = ee.Geometry.Point(click.lon, click.lat)
  var dibujo = ui.Map.Layer(punto)
  Map.layers().set(1, ui.Map.Layer(punto, {color: 'white', pointSize: 10}))
  Map.centerObject(punto, 16)
    var grafico = ui.Chart.image
    .series({
      imageCollection: coleccion1.select("NDMI","NDRE"),
      // imageCollection: coleccion1.select("NDVI","SAVI","ARVI","EVI","NDMI","NDRE","GCI"),
      region: punto, 
      reducer: ee.Reducer.mean(), 
      scale: 10,
      xProperty: 'system:time_start'
    })
    .setSeriesNames(["NDVI","NDRE"])
    // .setSeriesNames(["NDVI","SAVI","ARVI","EVI","NDMI","NDRE","GCI"])
    .setOptions({
      title: 'Distribución de valores índice de vegetación',
      vAxis: {title: 'Valores índices de vegetación'},
      hAxis: {title: 'Mes/Año'},
      lineWidth: 2,
      colors: ['red','green'],
      // colors: ['red', 'green', 'blue', 'yellow', 'purple', 'black', 'orange'],
      curveType: 'function'
     })
  var panel = ui.Panel({widgets: grafico, layout: ui.Panel.Layout.Flow('vertical'), 
  style:{width: '500px', position: 'bottom-left'}
})
Map.widgets().set(2, panel)

  
})