Monitoring Spatio-Temporal Dynamics in the Eastern Plain Lakes of China Using Long-Term MODIS UNWI Index

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 4; p. 985
• Main Authors: Zhang, Lifu, Wang, Sa, Cen, Yi, Huang, Changping, Zhang, Hongming, Sun, Xuejian, Tong, Qingxi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Agrochemicals; Automation; Biodiversity; Chemical precipitation; Climate change; driving forces; Drought; Eastern Plain Lake region; Fertilizers; Freshwater resources; Lakes; MDD; MODIS; Monitoring; Remote sensing; spatio-temporal; Storage; Surface water; Sustainable development; Water area; Water shortages; United States > US; China; Oklahoma; Huai River
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14040985

Monitoring the spatio-temporal dynamics of the Eastern Plain Lake (EPL) is vital to the local environment and economy. However, due to the limitations and efficiency of traditional image formats in storing and processing large amounts of images and optimal threshold adjustments are often necessary for water/non-water separation based on traditional multi-band/spectral water indexes over large areas and in the long-term, previous studies have either been on a short period or mainly focused on water inundation dynamics of several lakes. To address these issues, a multi-dimensional dataset (MDD) storage format was used to efficiently organize more than ~7000 time series composite MODIS images. Furthermore, a universal normalized water index (UNWI) was developed based on full-spectrum information to simplify optimal threshold adjustments. Consequently, the present study analyzed the patterns of spatio-temporal water dynamic patterns and potential driving factors of inundation changes at large lakes (>5 km2) in the EPL during 2000–2020 through MDD and UNWI. In terms of annual inundation patterns, the numbers of lakes that experienced significant (p < 0.05) decreases (17 lakes) and increases (43 lakes) were highest for Class IV lakes among six geographical classes. Variation in intra-annual inundation in Classes I and II is correlated with consumption of chemical fertilizers (CCF), while precipitation accounted for the most change in lake area in Class III. This spatio-temporal analysis of lakes provides a necessary foundation for the sustainable development and continuous investigations of the EPL.