Soil Moisture–Vegetation–Carbon Flux Relationship under Agricultural Drought Condition using Optical Multispectral Sensor
Open Access
- 24 April 2020
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 12 (9), 1359
- https://doi.org/10.3390/rs12091359
Abstract
Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO2) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO2 concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO2 flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO2 flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO2 (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO2 flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.Keywords
This publication has 39 references indexed in Scilit:
- Remote Sensing-based Agricultural Drought Monitoring using Hydrometeorological VariablesKSCE Journal of Civil Engineering, 2019
- Correlation analysis between Korean spring drought and large-scale teleconnection patterns for drought forecastingKSCE Journal of Civil Engineering, 2016
- Exploring spatiotemporal relationships among meteorological, agricultural, and hydrological droughts in Southwest ChinaStochastic Environmental Research and Risk Assessment, 2015
- Drought monitoring using a Soil Wetness Deficit Index (SWDI) derived from MODIS satellite dataAgricultural Water Management, 2014
- Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing dataRemote Sensing of Environment, 2013
- A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration IndexJournal of Climate, 2010
- Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparednessWater Resources Management, 2007
- Drought forecasting using stochastic modelsStochastic Environmental Research and Risk Assessment, 2005
- A Review of Twentieth-Century Drought Indices Used in the United StatesBulletin of the American Meteorological Society, 2002
- Global Drought Watch from SpaceBulletin of the American Meteorological Society, 1997