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Google Earth Engine is a cloud-based geospatial analysis platform that enables users to visualize and analyze satellite images of our planet. Scientists and non-profits use Earth Engine for remote sensing research, predicting disease outbreaks, natural resource management, and more.
The use of remote sensing and GIS, is fairly basic for any hydrological/catchment study. The use of remote sensing information may require high computational processing abilities, which is not possible over any local computer. Google Earth Engine, not only allows cloud based computing but also provides access to big geospatial data and their visualization.
Abstract for Cloud Based Rainfall-Runoff Model
Abstract for Cloud Based Rainfall-Runoff Model
The capability of open-data sources in cloud computing was explored in rainfall–run-off modelling through the Soil Conservation Services curve number (SCS CN) model. The Google Earth Engine (GEE) has a petabytes catalogue of global remote sensing and GIS datasets, numerous functions and algorithms to manipulate and visualize datasets rapidly. In this study, an algorithm has been developed to prepare dynamic CN maps in GEE using OpenLandMap Soil Texture and MODIS land use/land cover (LULC) data through ternary function and climate hazards group infrared precipitation rainfall collection for input rainfall and creation of antecedent moisture condition. The capabilities of the developed algorithm were demonstrated for Shipra, Kuttiyadi and Bah river catchments in India. However, it can be used with different satellite data for estimating the run-off and impact of LULC change on run-off for any part of the world and any desired period. The developed algorithm not only utilizes GEF and the public archive database for estimating the run-off at basin/subbasin scales for the planning of water resources, but also provides a quick evaluation of the impact of LULC change on run-off over time.
Instructor :
Sukant Jain [ Hydrologist at Entura-Hydro Tasmania , Former Research Scientists at NIH, Bhopal ]
Pre-requisites :
No previous experience in Earth Engine or JavaScript is required for the workshop, but basic knowledge of any programming language is desirable.
Basic knowledge of Hydrology
Basic knowledge of Remote Sensing and/or GIS is highly desirable.
Before the workshop:
Participants are requested to be ready with a Google Earth Engine account well in advance, before the workshop (it may take upto four days to get a GEE account activated).
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