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Im, Jungho
Intelligent Remote sensing and geospatial Information Science (IRIS) Lab
Research Interests
  • Remote sensing, Geospatial modeling, Disaster monitoring and management, Climate change

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Short-Term Forecasting of Satellite-Based Drought Indices Using Their Temporal Patterns and Numerical Model Output

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Title
Short-Term Forecasting of Satellite-Based Drought Indices Using Their Temporal Patterns and Numerical Model Output
Author
Park, SuminIm, JunghoHan, DaehyeonRhee, Jinyoung
Issue Date
2020-11
Publisher
MDPI
Citation
REMOTE SENSING, v.12, no.21, pp.3499
Abstract
Drought forecasting is essential for effectively managing drought-related damage and providing relevant drought information to decision-makers so they can make appropriate decisions in response to drought. Although there have been great efforts in drought-forecasting research, drought forecasting on a short-term scale (up to two weeks) is still difficult. In this research, drought-forecasting models on a short-term scale (8 days) were developed considering the temporal patterns of satellite-based drought indices and numerical model outputs through the synergistic use of convolutional long short term memory (ConvLSTM) and random forest (RF) approaches over a part of East Asia. Two widely used drought indices-Scaled Drought Condition Index (SDCI) and Standardized Precipitation Index (SPI)-were used as target variables. Through the combination of temporal patterns and the upcoming weather conditions (numerical model outputs), the overall performances of drought-forecasting models (ConvLSTM and RF combined) produced competitive results in terms of r (0.90 and 0.93 for validation SDCI and SPI, respectively) and nRMSE (0.11 and 0.08 for validation of SDCI and SPI, respectively). Furthermore, our short-term drought-forecasting model can be effective regardless of drought intensification or alleviation. The proposed drought-forecasting model can be operationally used, providing useful information on upcoming drought conditions with high resolution (0.05 degrees).
URI
https://scholarworks.unist.ac.kr/handle/201301/48837
URL
https://www.mdpi.com/2072-4292/12/21/3499
DOI
10.3390/rs12213499
ISSN
2072-4292
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