Vegetation Drought Vulnerability Mapping Using a Copula Model of Vegetation Index and Meteorological Drought Index

Jeongeun Won,Jiyu Seo,Okjeong Lee,Sangdan Kim,Jeonghoon Lee

doi:10.3390/rs13245103

Jeongeun Won, Jiyu Seo + Show 3 more

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https://doi.org/10.3390/rs13245103

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Abstract

Since vegetation is closely related to a variety of hydrological factors, the vegetation condition during a drought is greatly affected by moisture supply or moisture demand from the atmosphere. However, since feedback between vegetation and climate in the event of drought is very complex, it is necessary to construct a joint probability distribution that can describe and investigate the interrelationships between them. In other words, it is required to understand the interaction between vegetation and climate in terms of joint probability. In this study, the possibility of drought stress experienced by vegetation under various conditions occurring during drought was investigated by dividing drought into two aspects (atmospheric moisture supply and moisture demand). Meteorological drought indices that explain different aspects of drought and vegetation-related drought indexes that describe the state of vegetation were estimated using data remotely sensed by satellites in parts of Far East Asia centered on South Korea. Bivariate joint probability distribution modeling was performed from vegetation drought index and meteorological drought index using Copula. It was found that the relationship between the vegetation drought index and the meteorological drought index has regional characteristics and there is also a seasonal change. From the copula-based model, it was possible to quantify the conditional probability distribution for the drought stress of vegetation under meteorological drought scenarios that occur from different causes. Through this, by mapping the vulnerability of vegetation to meteorological drought in the study area, it was possible to spatially check how the vegetation responds differently depending on the season and meteorological causes. The probabilistic mapping of vegetation vulnerability to various aspects of meteorological drought may provide useful information for establishing mitigation strategies for ecological drought.

Highlights

Droughts are caused by changes in meteorological factors such as lack of precipitation or increase in evapotranspiration, and sometimes evolve into extreme events and become serious disasters that can have a significant impact on each area of the community, including water resources, environment, and ecology [1]
The purpose of this study is to spatially explore the extent to which vegetation responds to meteorological drought stress caused by insufficient precipitation or excessive evapotranspiration using a bivariate joint probability distribution modeling that combines drought information from SPI
The main purpose of this study was to identify the degree of vegetation vulnerability and vulnerable areas for various meteorological drought scenarios

Summary

Introduction

Droughts are caused by changes in meteorological factors such as lack of precipitation or increase in evapotranspiration, and sometimes evolve into extreme events and become serious disasters that can have a significant impact on each area of the community, including water resources, environment, and ecology [1]. Since data remotely sensed by satellites provide significant benefits in monitoring the temporal and spatial evolution of vegetation [5], vegetation indices such as the Normalized. Difference Vegetation Index (NDVI) have been widely used to assess drought effects on land vegetation. NDVI is one of the most commonly used indices for monitoring vegetation conditions worldwide [6]. In addition to the lack of water availability of vegetation due to drought, human activity associated with pest infestation, virus infection and wildfires can control vegetation conditions, so the sole use of NDVI can lead to confusion in drought impact analysis [10,11,12]. The Vegetation Health Index (VHI) [13], calculated as a combination of NDVI and Land Surface Temperature (LST), was proposed. VHI has been applied for monitoring vegetation drought in various studies [15,16,17,18]

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