Max Multitemporal NDVI
//VERSION=3
//Basic initialization setup function
function setup() {
return {
//List of all bands, that will be used in the script, either for visualization or for choosing best pixel
input: [{
bands: [
"Red",
"NIR"
]
}],
//This can always be the same if one is doing RGB images
output: { bands: 4 },
mosaicking: "ORBIT"
}
}
/*
In this function we limit the scenes, which are used for processing.
These are based also on input variables.
E.g. if one sets date "2017-03-01" ("TO date") and cloud coverage filter 30%,
all scenes older than 2017-03-01 with cloud coverage 30% will be checked against
further conditions in this function (in this function it is currently limited to 3 months).
The more scenes there are, longer it will take to process the data.
After 60 seconds of processing, there will be a timeout.
*/
function preProcessScenes(collections) {
collections.scenes.orbits = collections.scenes.orbits.filter(function (orbit) {
var orbitDateFrom = new Date(orbit.dateFrom)
return orbitDateFrom.getTime() >= (collections.to.getTime() - 3 * 31 * 24 * 3600 * 1000);
})
return collections
}
function calcNDVI(sample) {
var denom = sample.Red + sample.NIR;
return ((denom != 0) ? (sample.NIR - sample.Red) / denom : NaN);
}
function evaluatePixel(samples) {
var max = Number.NEGATIVE_INFINITY;
for (let i = 0; i < samples.length; i++) {
var ndvi = calcNDVI(samples[i]);
max = ndvi > max ? ndvi : max;
}
let max_exists = 0;
if (isFinite(max)) {
max_exists = 1;
}
if (max < -1.1) { return [0, 0, 0, max_exists]; }
else if (max < - 0.2) { return [0.75, 0.75, 0.75, max_exists]; }
else if (max < - 0.1) { return [0.86, 0.86, 0.86, max_exists]; }
else if (max < 0) { return [1, 1, 0.88, max_exists]; }
else if (max < 0.025) { return [1, 0.98, 0.8, max_exists]; }
else if (max < 0.05) { return [0.93, 0.91, 0.71, max_exists]; }
else if (max < 0.075) { return [0.87, 0.85, 0.61, max_exists]; }
else if (max < 0.1) { return [0.8, 0.78, 0.51, max_exists]; }
else if (max < 0.125) { return [0.74, 0.72, 0.42, max_exists]; }
else if (max < 0.15) { return [0.69, 0.76, 0.38, max_exists]; }
else if (max < 0.175) { return [0.64, 0.8, 0.35, max_exists]; }
else if (max < 0.2) { return [0.57, 0.75, 0.32, max_exists]; }
else if (max < 0.25) { return [0.5, 0.7, 0.28, max_exists]; }
else if (max < 0.3) { return [0.44, 0.64, 0.25, max_exists]; }
else if (max < 0.35) { return [0.38, 0.59, 0.21, max_exists]; }
else if (max < 0.4) { return [0.31, 0.54, 0.18, max_exists]; }
else if (max < 0.45) { return [0.25, 0.49, 0.14, max_exists]; }
else if (max < 0.5) { return [0.19, 0.43, 0.11, max_exists]; }
else if (max < 0.55) { return [0.13, 0.38, 0.07, max_exists]; }
else if (max < 0.6) { return [0.06, 0.33, 0.04, max_exists]; }
else { return [0, 0.27, 0, max_exists]; }
}//VERSION=3
//Basic initialization setup function
function setup() {
return {
//List of all bands, that will be used in the script, either for visualization or for choosing best pixel
input: [{
bands: [
"Red",
"NIR",
]
}],
//This can always be the same if one is doing RGB images
output: [
{ id: "default", bands: 4 },
{ id: "index", bands: 1, sampleType: "FLOAT32" },
{ id: "eobrowserStats", bands: 2, sampleType: "FLOAT32" },
{ id: "dataMask", bands: 1 }
],
mosaicking: "ORBIT"
}
}
/*
In this function we limit the scenes, which are used for processing.
These are based also on input variables.
E.g. if one sets date "2017-03-01" ("TO date") and cloud coverage filter 30%,
all scenes older than 2017-03-01 with cloud coverage 30% will be checked against
further conditions in this function (in this function it is currently limited to 3 months).
The more scenes there are, longer it will take to process the data.
After 60 seconds of processing, there will be a timeout.
*/
function preProcessScenes(collections) {
collections.scenes.orbits = collections.scenes.orbits.filter(function (orbit) {
var orbitDateFrom = new Date(orbit.dateFrom)
return orbitDateFrom.getTime() >= (collections.to.getTime() - 3 * 31 * 24 * 3600 * 1000);
})
return collections
}
function calcNDVI(sample) {
var denom = sample.Red + sample.NIR;
return ((denom != 0) ? (sample.NIR - sample.Red) / denom : NaN);
}
function evaluatePixel(samples) {
var max = Number.NEGATIVE_INFINITY;
for (let i = 0; i < samples.length; i++) {
var ndvi = calcNDVI(samples[i]);
max = ndvi > max ? ndvi : max;
}
let max_exists = 0;
if (isFinite(max)) {
max_exists = 1;
}
let imgVals;
if (max < -1.1) { imgVals = [0, 0, 0]; }
else if (max < - 0.2) { imgVals = [0.75, 0.75, 0.75]; }
else if (max < - 0.1) { imgVals = [0.86, 0.86, 0.86]; }
else if (max < 0) { imgVals = [1, 1, 0.88]; }
else if (max < 0.025) { imgVals = [1, 0.98, 0.8]; }
else if (max < 0.05) { imgVals = [0.93, 0.91, 0.71]; }
else if (max < 0.075) { imgVals = [0.87, 0.85, 0.61]; }
else if (max < 0.1) { imgVals = [0.8, 0.78, 0.51]; }
else if (max < 0.125) { imgVals = [0.74, 0.72, 0.42]; }
else if (max < 0.15) { imgVals = [0.69, 0.76, 0.38]; }
else if (max < 0.175) { imgVals = [0.64, 0.8, 0.35]; }
else if (max < 0.2) { imgVals = [0.57, 0.75, 0.32]; }
else if (max < 0.25) { imgVals = [0.5, 0.7, 0.28]; }
else if (max < 0.3) { imgVals = [0.44, 0.64, 0.25]; }
else if (max < 0.35) { imgVals = [0.38, 0.59, 0.21]; }
else if (max < 0.4) { imgVals = [0.31, 0.54, 0.18]; }
else if (max < 0.45) { imgVals = [0.25, 0.49, 0.14]; }
else if (max < 0.5) { imgVals = [0.19, 0.43, 0.11]; }
else if (max < 0.55) { imgVals = [0.13, 0.38, 0.07]; }
else if (max < 0.6) { imgVals = [0.06, 0.33, 0.04]; }
else { imgVals = [0, 0.27, 0]; }
return {
default: imgVals.concat(max_exists),
index: [max],
eobrowserStats: [max, max_exists],
dataMask: [max_exists]
}
}//VERSION=3
//Basic initialization setup function
function setup() {
return {
//List of all bands, that will be used in the script, either for visualization or for choosing best pixel
input: [{
bands: [
"Red",
"NIR"
]
}],
//This can always be the same if one is doing RGB images
output: { bands: 1 },
mosaicking: "ORBIT"
}
}
/*
In this function we limit the scenes, which are used for processing.
These are based also on input variables.
E.g. if one sets date "2017-03-01" ("TO date") and cloud coverage filter 30%,
all scenes older than 2017-03-01 with cloud coverage 30% will be checked against
further conditions in this function (in this function it is currently limited to 3 months).
The more scenes there are, longer it will take to process the data.
After 60 seconds of processing, there will be a timeout.
*/
function preProcessScenes(collections) {
collections.scenes.orbits = collections.scenes.orbits.filter(function (orbit) {
var orbitDateFrom = new Date(orbit.dateFrom)
return orbitDateFrom.getTime() >= (collections.to.getTime() - 3 * 31 * 24 * 3600 * 1000);
})
return collections
}
function calcNDVI(sample) {
var denom = sample.Red + sample.NIR;
return ((denom != 0) ? (sample.NIR - sample.Red) / denom : NaN);
}
function evaluatePixel(samples) {
var max = Number.NEGATIVE_INFINITY;
for (let i = 0; i < samples.length; i++) {
var ndvi = calcNDVI(samples[i]);
max = ndvi > max ? ndvi : max;
}
return [max];
}Evaluate and Visualize
General description
The script evaluates the NDVI for each scene of the past month and returns the highest NDVI value for every pixel. In short, it returns the highest NDVI values of the past month for every pixel. The script runs on-the-fly, since it doesn’t require preprocessing. It can be used as a cloud free background or an input for further analysis, such as change detection and classification. Find out more.
Note that multi-temporal processing needs to be enabled for this script to run.
Author of the script
William Ray
Description of representative images
