Drought Monitoring Using Standardized Precipitation Index (SPI) in Google Earth Engine скачать в хорошем качестве

Drought Monitoring Using Standardized Precipitation Index (SPI) in Google Earth Engine

Drought Monitoring Using Standardized Precipitation Index (SPI) in Google Earth Engine Is your region facing drought stress? 🌍 In this complete step-by-step tutorial, you’ll learn how to calculate and map the Standardized Precipitation Index (SPI) in Google Earth Engine (GEE) for effective drought monitoring and climate analysis. We will use satellite-based rainfall datasets such as CHIRPS and generate SPI maps (3-month, 6-month, 12-month) to assess drought severity from mild to extreme conditions. This tutorial is ideal for GIS students, researchers, hydrologists, climate analysts, and remote sensing professionals. 🔥 What You’ll Learn in This Video: ✔ What is Standardized Precipitation Index (SPI)? ✔ Types of Drought (Meteorological, Agricultural, Hydrological) ✔ How to Access CHIRPS Rainfall Data in GEE ✔ SPI Calculation Formula Explained ✔ SPI Time-Series Analysis ✔ Drought Severity Classification ✔ Visualizing SPI Maps in Google Earth Engine ✔ Exporting Results (GeoTIFF / CSV) ✔ Best Practices for Climate Studies 📊 Why SPI is Important? SPI is one of the most widely used drought indices worldwide because it: Standardizes rainfall anomalies Detects early drought signals Supports water resource planning Helps agricultural monitoring Assists climate risk assessment Using Google Earth Engine, you can process long-term rainfall datasets (1981–Present) efficiently in the cloud without downloading large data files. 🛰️ Dataset Used: CHIRPS Daily / Monthly Rainfall Data Google Earth Engine Climate Datasets 🎯 Who Should Watch? Remote Sensing Students GIS Analysts Climate Researchers Hydrology & Water Resource Experts Environmental Scientists Anyone working on drought assessment 📌 SEO Keywords: SPI in Google Earth Engine, drought monitoring GIS, Standardized Precipitation Index tutorial, CHIRPS rainfall GEE, SPI drought mapping, climate analysis using GEE, rainfall anomaly mapping, drought severity classification, remote sensing drought index. 🎓 Want Advanced Training? Join our live hands-on training on: ✔ Google Earth Engine ✔ Climate & Drought Analysis ✔ Machine Learning in GIS ✔ Time-Series Analysis Contact details are provided below. 👍 Support the Channel: Like 👍 Comment 💬 Subscribe 🔔 Share with researchers 🌍 #SPI #DroughtMonitoring #GoogleEarthEngine #RemoteSensing #GIS #ClimateAnalysis #CHIRPS #Geospatial #Hydrology