SRT - Spatial Reduction Tool

SRT is a collector and spatial reducer of data from GEE available dataset. It allows you to calculate the spatial mean and standard deviation from several dataset inside each feature of a feature collection ('MapUnit' in the example).

The dataset collected are:

• DEM: USGS/SRTMGL1_003
• temperature: MODIS/006/MOD11A1
• precipitation: UCSB-CHG/CHIRPS/DAILY
• ndvi: LANDSAT/LE07/C01/T1_32DAY_NDVI

The SRT is structured in 5 separated functions which can be run separately or simultanously:

• SRTtemperature()
• SRTgeomorphometry()
• SRTcurvature()
• SRTprecipitation()
• SRTndvi()

The SRT requires a polygons collection which represents the mapping units where the datsets have been spatially reduced to mean and std.

The outputs are 5 feature collections which contains several columns:

Function	Column name	Description
SRTgeomorphometry	Elev	Elevation
	Slope	Slope
	Asp	Aspect
	Hill	Hillshade
	Nss	Northness
	Ess	Eastness
	SIdx	Shape Index
	Rlf	Relative relief
SRTcurvature	HCv	Horizontal curvature
	VCv	Vertical curvature
	MCv	Mean curvature
	MinCv	Minimal curvature
	MaxCv	Maximal curvature
	GCv	Gaussian curvature
SRTprecipitation	RnSum	Annual precipitation averaged over a number of years
	RnMax	Max daily precipitation of one year averaged over a number of years
	RnStd	Std daily precipitation of one year averaged over a number of years
	RnMed	Average daily precipitation of one year averaged over a number of years
SRTtemperature	TMed	Average daily mean temperature of one year averaged over a number of years
	TStd	Std daily mean temperature of one year averaged over a number of years
	TMax	Max daily mean temperature of one year averaged over a number of years
SRTndvi	NDVI	32days NDVI averaged over a number of years

Most of the variables derived from the DEM have been calculated using TAGEE function:

Safanelli, J.L.; Poppiel, R.R.; Ruiz, L.F.C.; Bonfatti, B.R.; Mello, F.A.O.; Rizzo, R.; Demattê, J.A.M. Terrain Analysis in Google Earth Engine: A Method Adapted for High-Performance Global-Scale Analysis. ISPRS Int. J. Geo-Inf. 2020, 9, 400. DOI: https://doi.org/10.3390/ijgi9060400

Example of application

link to example

//generate table
var geom=ee.Geometry.BBox(94.1329327392578,25.514028970276666,94.5339337158203,25.890203351903423);
var MapUnit=geom.coveringGrid(geom.projection(),1000);
Map.addLayer(MapUnit,{},'units');

//import tool
var SRT = require('users/giacomotitti/SRT:SRTfunctions');

//temperature
var temperature = SRT.SRTtemperature(MapUnit,2000,2021,30);//mapping unit, start date, end date, scale
print(temperature,'temperature');

//geomorphometry
var geomorphometry = SRT.SRTgeomorphometry(MapUnit,1000,30);//mapping unit, buffer radius for relief, scale
print(geomorphometry,'geomorphometry');

//geomorph
var curvature = SRT.SRTcurvature(MapUnit,30);//mapping unit, scale
print(curvature,'curvature');

// precipitation
var precipitation = SRT.SRTprecipitation(MapUnit,1991,2020,30);//mapping unit, start date, end date, scale
print(precipitation,'precipitation');

//ndvi
var ndvi = SRT.SRTndvi(MapUnit,2011,2020,30);//mapping unit, start date, end date, scale
print(ndvi,'ndvi');

//Display
Map.setCenter(94.33, 25.74, 10);
var display = function(collection,name){
var imaged = collection.reduceToImage({
properties: [name],
reducer: ee.Reducer.first()});
Map.addLayer(imaged,{},name)};

display(ndvi,'NDVI_mean');
display(geomorphometry,'Slope_mean');
display(precipitation,'RnMax_mean');
display(temperature,'TMax_mean');

Contacts

For any request, comment and suggestion, please write to me: [email protected]