Global drought monitoring with big geospatial datasets using Google Earth Engine

Area of Science:

• Environmental Science
• Climate Science
• Remote Sensing

Background:

• Droughts result from cumulative climatological and hydrological factors.
• Monitoring drought is crucial for agriculture and water resource management.
• Existing methods often lack comprehensive, accessible tools for real-time assessment.

Purpose of the Study:

• To develop and present a suite of drought indices for comprehensive drought monitoring.
• To create an interactive Google Earth Engine dashboard for calculating these indices.
• To analyze global drought patterns and present detailed case studies.

Main Methods:

• Computation of Vegetation Condition Index (VCI) for agricultural drought.
• Utilizing Temperature Condition Index (TCI) to assess land surface temperature anomalies.
• Calculating Soil Moisture Condition Index (SMCI) and Precipitation Condition Index (PCI) for hydrological and meteorological drought.
• Development of an interactive dashboard on Google Earth Engine for user-defined drought index computation.

Main Results:

• Identification of years with severe and extreme drought conditions globally.
• Demonstration of the dashboard's capability through case studies in Australia (2002), Brazil (2013), and Thailand (2019).
• The developed indices and dashboard provide a robust tool for agricultural drought monitoring.

Conclusions:

• The integrated approach using VCI, TCI, SMCI, and PCI offers a holistic view of drought conditions.
• The Google Earth Engine dashboard enhances accessibility for global drought monitoring and analysis.
• This research provides valuable insights and tools for mitigating drought impacts.