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Global drought monitoring with big geospatial datasets using Google Earth Engine

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Abstract

Drought or dryness occurs due to the accumulative effect of certain climatological and hydrological variables over a certain period. Droughts are studied through numerically computed simple or compound indices. Vegetation condition index (VCI) is used for observing the change in vegetation that causes agricultural drought. Since the land surface temperature has minimum influence from cloud contamination and humidity in the air, so the temperature condition index (TCI) is used for studying the temperature change. Dryness or wetness of soil is a major indicator for agriculture and hydrological drought and for that purpose, the index, soil moisture condition index (SMCI), is computed. The deviation of precipitation from normal is a major cause for meteorological droughts and for that purpose, precipitation condition index (PCI) is computed. The years when the indices escalated the dryness situation to severe and extreme are pointed out in this research. Furthermore, an interactive dashboard is generated in the Google Earth Engine (GEE) for users to compute the said indices using country boundary, time period, and ecological mask of their choice: Agriculture Drought Monitoring. Apart from global results, three case studies of droughts (2002 in Australia, 2013 in Brazil, and 2019 in Thailand) computed via the dashboard are discussed in detail in this research.
RESEARCH ARTICLE
Global drought monitoring with big geospatial datasets using
Google Earth Engine
Ramla Khan
1
&Hammad Gilani
1
Received: 8 August 2020 /Accepted: 8 December 2020
#The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021
Abstract
Drought or dryness occurs due to the accumulative effect of certain climatological and hydrological variables over a certain
period. Droughts are studied through numerically computed simple or compound indices. Vegetation condition index (VCI) is
used for observing the change in vegetation that causes agricultural drought. Since the land surface temperature has minimum
influence from cloud contamination and humidity in the air, so the temperature condition index (TCI) is used for studying the
temperature change. Dryness or wetness of soil is a major indicator for agriculture and hydrological drought and for that purpose,
the index, soil moisture condition index (SMCI), is computed. The deviation of precipitation from normal is a major cause for
meteorological droughts and for that purpose, precipitation condition index (PCI) is computed. The years when the indices
escalated the dryness situation to severe and extreme are pointed out in this research. Furthermore, an interactive dashboard is
generated in the Google Earth Engine (GEE) for users to compute the said indices using country boundary, time period, and
ecological mask of their choice: Agriculture Drought Monitoring. Apart from global results, three case studies of droughts (2002
in Australia, 2013 in Brazil, and 2019 in Thailand) computed via the dashboard are discussed in detail in this research.
Keywords Global drought .Satellite data .Drought indices .Interactive dashboard .Google Earth Engine .Case studies
Introduction
The Intergovernmental Panel on Climate Change (IPCC) is
working diligently on finding solutions for the impacts of
climate change (Downing et al. 2003), which is a major issue
of the world and is spurred on by anthropogenic activities
(Vera et al. 2006). More frequent natural disasters and extreme
weather are also courtesy of climate change (Marengo et al.
2009).
Drought is one of the costliest natural disasters known to
mankind (Kogan 1997). It has four types: agriculture drought
(crops when impacted by the dryness), meteorological
drought (the precipitation recorded less than normal), hydro-
logical drought (low water level in streams, reservoirs, and
groundwater), and socio-economic drought (the livelihood
and economy getting impacted) (Khan et al. 2020)
Droughts do not occur abruptly but rather develops slowly
over time (Palmer 1965). Rise and fall in certain climatic or
hydro-meteorological indicators (air temperature, humidity,
groundwater table, surface runoff, land surface temperature,
transpiration, evapotranspiration, soil moisture, precipitation,
and heat level, etc.) can become the consequent cause of
drought in a region (Svoboda and Fuchs 2017;Khanetal.
2020).
Researchers suggest numerically calculated drought indi-
ces for investigating impacts of drought in a region. Indices
describe droughts qualitative state of a certain landscape for a
chosen time period and give a quantitative assessment of se-
verity and timespan of a drought (Svoboda and Fuchs 2017).
These indices are either computed from one hydro-meteoro-
logical/climatic variable or in combination (WMO and GWP
2016). Each of these indices has its own significance and plays
equally important roles in drought assessment (WMO 2012;
Svoboda and Fuchs 2017).
Droughts affect people from all walks of life. A farmer
perceives the drought as deficiency of moisture to his crops;
a hydrologist observes the declining datum in streams and
rivers while an economist would care for its effects on the
economy (Zargar et al. 2011;Palmer1965).
Responsible Editor: Philippe Garrigues
*Ramla Khan
ramla3903@gmail.com
1
Institute of Space Technology, Islamabad, Pakistan
https://doi.org/10.1007/s11356-020-12023-0
/ Published online: 4 January 2021
Environmental Science and Pollution Research (2021) 28:17244–17264
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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