Soil Moisture–Vegetation–Carbon Flux Relationship under Agricultural Drought Condition using Optical Multispectral Sensor

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 9; p. 1359
• Main Authors: Sur, Chanyang, Kang, Do-Hyuk, Lim, Kyoung Jae, Yang, Jae E., Shin, Yongchul, Jung, Younghun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2020
• Subjects: Agricultural drought; Albedo; Atmosphere; Carbon; Carbon dioxide; carbon dioxide flux; Correlation coefficient; Correlation coefficients; Depletion; Drought; Ecosystems; Extreme drought; Extreme values; Fluctuations; Flux; Hydrology; Hypotheses; Land surface temperature; Mathematical analysis; MODIS; Moisture content; optical multispectral sensor; Photosynthesis; Physical properties; Remote sensing; Respiration; Sensors; Soil moisture; Soils; Spectroradiometers; Studies; Temporal variations; Time lag; Vegetation; vegetation activity; Vegetation index; Water content; South Korea
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12091359

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.