Developing A High Resolution Rusle Model In Qgis

Development of a high-resolution [10 meter] water erosion model in QGIS, with the help of Google Earth Engine and SAGA

What you'll learn

Land use and land cover classification with machine learning in Google Earth Engine

Random forests

Downloading and working with high resolution DEM (ALOS PALSAR)

Developing codes in Google Earth Engine for R factor

Downloading and working with global soil data (from FAO and ESDAC)

Working with SAGA (open source)

Dozens of tools in QGIS

Soil science theory

Erosion modeling theory and practice

RUSLE model

Open source platfroms

Requirements

Basic GIS knowledge

Preferable:Basic QGIS

Preferable:Basic Java Script

Description

Soil erosion remains one of the greatest threats to land productivity, sustainable agriculture, and environmental stability. In this hands-on course, you will learn how to develop a high-resolution (10-meter) RUSLE (Revised Universal Soil Loss Equation) model in QGIS using a powerful combination of SAGA GIS and Google Earth Engine (GEE).This course is designed for GIS professionals, environmental scientists, students, and planners who want to accurately model water-induced soil erosion with modern, open-source tools. You’ll learn how to calculate the five core RUSLE factors—R (rainfall erosivity), K (soil erodibility), LS (slope length and steepness), C (cover management), and P (support practice)—and integrate them into a single spatial erosion map.We’ll use Sentinel-2 imagery, ALOS PALSAR DEM, and field-proven methods to produce reliable, high-resolution results. You'll gain practical skills in:Terrain preprocessing and LS factor derivation in SAGAAccurate land use and land cover classification for the C factor in Google Earth Engine with Random ForestsAssigning soil and conservation values in QGIS and Google Earth ProCombining all layers to generate a final erosion risk mapWe will create our own maps and use global open-source data when it is available. By the end of the course, you’ll be able to create accurate erosion models for any region, using freely available global datasets and open-source GIS software. No need for expensive licenses—just results.This course is ideal for GIS analysts, environmental modelers, students, and professionals working in land degradation, agriculture, watershed management, or conservation.Whether you're focused on a specific region or working on global sustainability assessments, this course gives you the data, tools, and skills to model erosion accurately and effectively.

Overview

Section 1: Introduction

Lecture 1 Introduction to the course(Promo)

Lecture 2 Spatial alignment and parameters

Lecture 3 Data sources

Lecture 4 Softwares to use

Lecture 5 Download QGIS

Lecture 6 Start the QGIS project

Lecture 7 Study area shapefile - reproject into UTM

Section 2: SOIL AND SOIL EROSION. THEORY

Lecture 8 Soil

Lecture 9 Soil erosion

Lecture 10 Soil erosion prevention measures

Lecture 11 Different soil erosion models

Lecture 12 RUSLE model concept

Section 3: RUSLE FACTORS. THEORY

Lecture 13 LS FACTOR

Lecture 14 C FACTOR

Lecture 15 R FACTOR

Lecture 16 P FACTOR

Lecture 17 K FACTOR

Section 4: LS (SLOPE LENGTH). PRACTICE

Lecture 18 How to download ALOS PALSAR DEM

Lecture 19 Saving GeoTIFF in .sdat format in QGIS for SAGA

Lecture 20 Computing LS factor in SAGA

Lecture 21 Mosaic,clip and review LS map

Section 5: C(COVER FACTOR).PRACTICE

Lecture 22 The beginning of the code in GEE

Lecture 23 Computing indices

Lecture 24 Adding elevation and slope bands

Lecture 25 Ground control points collection

Lecture 26 Training and testing data

Lecture 27 K-Fold Cross Validation

Lecture 28 Final classification results and export map

Lecture 29 Assigning C-factor values to each LULC class

Section 6: R(RAINFALL EROSIVITY). PRACTICE

Lecture 30 GloREDa database

Lecture 31 Preparing the GloREDa map for a study area

Lecture 32 R factor in Google Earth Engine

Lecture 33 Resampling R factor from GEE in QGIS

Section 7: P(CONSERVATION PRACTICE). PRACTICE

Lecture 34 Download Google Earth Pro software

Lecture 35 P factor table

Lecture 36 Mapping and discovering conservation practice methods with Google Earth Pro

Lecture 37 Creating slope in % with 10 meter

Lecture 38 Slope reclassify with Raster Calculator

Lecture 39 Rasterize vector of P

Lecture 40 Combining practice raster with cropland-non cropland raster

Lecture 41 Final P-factor map

Section 8: K(SOIL ERODIBILITY).PRACTICE

Lecture 42 Download FAO soil data

Lecture 43 Computing K-factor for dominant soils in Excel

Lecture 44 Vector to raster K-factor

Lecture 45 Global Soil Erodibility map from ESDAC

Section 9: RUSLE MODEL FINAL MAPS IN QGIS

Lecture 46 4 RUSLE maps (models)

Lecture 47 Correcting extreme values and using percentile tool in QGIS

Lecture 48 Map presentation in QGIS from results

Section 10: MISCELLANEOUS

Lecture 49 The model accuracy and how to improve it

Environmental Scientists,Ecologists,Agronomists,Soil scientists,GIS students,Remote sensing students,Farmers,Conservation scientists,Land use planners,Forestry