tagee 0.1.0

A suite of terrain analysis tools for Google Earth Engine.

Google Earth Engine (GEE) is a high-performance cloud-based platform for processing geospatial data.

There is a myriad of processing toolboxes in GEE, but this repository/package aims to contribute to the GEE community for making terrain analysis seamlessly.

Installation

Terrain Analysis in Google Earth Engine (TAGEE) is a repository that contains the GEE Javascript code and a Python API implementation with reproducible examples for both.

You can use TAGEE in the Earth Engine code editor with a require statement.

var TAGEE = require('users/joselucassafanelli/TAGEE:TAGEE-functions');

Or install the Python package from pip:

pip install tagee

Additional examples information are below.

Feature Overview

Available terrain attributes:

Attribute	Unit	Description
Elevation	meter	Height of terrain above sea level
Slope	degree	Slope gradient
Aspect	degree	Compass direction
Hillshade	dimensionless	Brightness of the illuminated terrain
Northness	dimensionless	Degree of orientation to North
Eastness	dimensionless	Degree of orientation to East
Horizontal curvature	meter	Curvature tangent to the contour line
Vertical curvature	meter	Curvature tangent to the slope line
Mean curvature	meter	Half-sum of the two orthogonal curvatures
Minimal curvature	meter	Lowest value of curvature
Maximal curvature	meter	Highest value of curvature
Gaussian curvature	meter	Product of maximal and minimal curvatures
Shape Index	dimensionless	Continuous form of the Gaussian landform classification

The users are referred to Florinsky (2016) for mathematical concepts of geomorphometry, a historical overview of the progress of digital terrain modelling, and the notion of the topographic surface and its limitations.

Florinsky, Igor. Digital terrain analysis in soil science and geology. Academic Press, 2016.

Please, cite the following paper when using TAGEE:

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

Important note!

As TAGEE uses spheroidal geometries and elevation nodes from a 3x3 moving window to calculate partial derivatives and hence terrain attributes, the visualization of the outputs is affected by the scale, which require the adjustment of the histogram for proper visualization. This happens because GEE produces different pyramids from your data (from the local up to the global scale) and consequently the pixel size changes dynamically, affecting the range of the estimated attribute values. Until you specify your final resolution, say 30m/pixel, the pyramids will dynamically affect the visualization of an output for different visualizaiton scales. You can determine your final resolution by exporting the results to assets and importing back further processing or map composition.

Minimal reproducible example

OPEN THE EXAMPLE DIRECTLY IN THE GEE CODE EDITOR.

NOTE: Any Earth Engine user with the above link can use it to view and run the example code. However, you need to login.

Javascript

// Importing module

var TAGEE = require('users/joselucassafanelli/TAGEE:TAGEE-functions');

// World bounding box

var bbox = ee.Geometry.Rectangle({coords: [-180, -60, 180, 60], geodesic: false});

// Water mask

var hansen_2016 = ee.Image('UMD/hansen/global_forest_change_2016_v1_4').select('datamask');
var hansen_2016_wbodies = hansen_2016.neq(1).eq(0);
var waterMask = hansen_2016.updateMask(hansen_2016_wbodies);

// Loading SRTM 30 m

var demSRTM = ee.Image('USGS/SRTMGL1_003').clip(bbox).rename('DEM');

// Smoothing filter
var gaussianFilter = ee.Kernel.gaussian({
  radius: 3, sigma: 2, units: 'pixels', normalize: true
});

// Smoothing the DEM with the gaussian kernel.
var demSRTM = demSRTM.convolve(gaussianFilter).resample("bilinear");

// Terrain analysis

var DEMAttributes = TAGEE.terrainAnalysis(TAGEE, demSRTM, bbox).updateMask(waterMask);
print(DEMAttributes.bandNames(), 'Parameters of Terrain');

// Visualization

var vizVC = TAGEE.makeVisualization(DEMAttributes, 'VerticalCurvature', 'level2', bbox, 'rainbow');
Map.addLayer(vizVC, {}, 'VerticalCurvature');
Map.setCenter(0,0,2);

Example description

In the Javascript code editor https://code.earthengine.google.com/, it is necessary to import the module TAGEE-functions.

var TAGEE = require('users/joselucassafanelli/TAGEE:TAGEE-functions');

Then, you need to define the bounding box (study region limits) and import the Digital Elevation Model for terrain analysis (e.g. SRTM 30 m).

// World bounding box

var bbox = ee.Geometry.Rectangle({coords: [-180, -60, 180, 60], geodesic: false});

// Water mask

var hansen_2016 = ee.Image('UMD/hansen/global_forest_change_2016_v1_4').select('datamask');
var hansen_2016_wbodies = hansen_2016.neq(1).eq(0);
var waterMask = hansen_2016.updateMask(hansen_2016_wbodies);

// Loading SRTM 30 m

var demSRTM = ee.Image('USGS/SRTMGL1_003').clip(bbox).rename('DEM');

// Smoothing filter
var gaussianFilter = ee.Kernel.gaussian({
  radius: 3, sigma: 2, units: 'pixels', normalize: true
});

// Smoothing the DEM with the gaussian kernel.
var demSRTM = demSRTM.convolve(gaussianFilter).resample("bilinear");

Finally, you can run the TAGEE module for calculating the terrain attributes.

// Terrain analysis

var DEMAttributes = TAGEE.terrainAnalysis(TAGEE, demSRTM, bbox).updateMask(waterMask);
print(DEMAttributes.bandNames(), 'Parameters of Terrain');

List (13 elements){
0: Elevation
1: Slope
2: Aspect
3: Hillshade
4: Northness
5: Eastness
6: HorizontalCurvature
7: VerticalCurvature
8: MeanCurvature
9: GaussianCurvature
10: MinimalCurvature
11: MaximalCurvature
12: ShapeIndex}

TAGEE has an additional feature for making the visualization easier and adapated to a dynamic scale (legend), once the pixel distances for the derivatives calculations are influenced by the visualization level. The legend limits are estimated by the 5th and 95th percentiles existing within the bounding box.

// Visualization

var vizVC = TAGEE.makeVisualization(DEMAttributes, 'VerticalCurvature', 'level2', bbox, 'rainbow');
Map.addLayer(vizVC, {}, 'VerticalCurvature');
Map.setCenter(0,0,2);

For the function makeVisualization, you need to specify:

• Attributes in multiband object
• Attribute name (string, e.g. 'VerticalCurvature')
• Visualization level (string, e.g. 'level2')
• Bounding box object
• Color pallete (string, e.g. 'rainbow')

The visualization levels are:

Visualization level	Pixel resolution (m)
'level0'	157000
'level1'	78000
'level2'	39000
'level3'	20000
'level4'	10000
'level5'	5000
'level6'	2000
'level7'	1000
'level8'	611
'level9'	306
'level10'	153
'level11'	76
'level12'	38
'level13'	19
'level14'	10
'level15'	5

Available color palettes: 'rainbow', 'inferno', 'cubehelix', 'red2green', 'green2red', 'elevation', 'aspect' and 'hillshade'.

Python API

The Python TAGEE package is implemented very similarly to the JS version.

# import & initialize the earth engine API
import ee
ee.Initialize()

# import relevant function
from tagee import terrainAnalysis

# set up a smoothed DEM
gaussianFilter = ee.Kernel.gaussian(
  radius=3, sigma=2, units='pixels', normalize=True
)
srtmSmooth = ee.Image("USGS/SRTMGL1_003").convolve(gaussianFilter).resample("bilinear")

# Calculate terrain metrics over a given geometry. You must provide a geometry
# in the terrainAnalysis call.
geom = ee.FeatureCollection(ee.Geometry.Rectangle(-111, 40, -110.9, 40.1))
terrainMetrics = terrainAnalysis(srtmSmooth, geom.geometry())

# Summarize the metrics in the geometry
reduction = terrainMetrics.reduceRegions(
  geom,
  ee.Reducer.median()
)

print(reduction.getInfo())

For any request, comment and suggestion, please send me a email (my github nickname at gmail.com)