Lake water surface mapping in the Tibetan Plateau using the MODIS MOD09Q1 product

• Published in: Remote sensing letters Vol. 8; no. 3; pp. 224 - 233
• Main Authors: Lu, Shanlong, Jia, Li, Zhang, Lei, Wei, Yongping, Baig, Muhammad Hasan Ali, Zhai, Zhaokun, Meng, Jihua, Li, Xiaosong, Zhang, Guifang
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 04.03.2017; Taylor & Francis Ltd
• Subjects: Algorithms; China; Cryosphere; Cryospheres; data collection; Hydrosphere; Imaging; Lakes; Landsat; Mapping; moderate resolution imaging spectroradiometer; MODIS; Reflectance; Remote sensing; space and time; Spectroradiometers; surface area; surface water; surveys; thematic maps; China
• ISSN: 2150-704X; 2150-7058; 2150-7058
• DOI: 10.1080/2150704X.2016.1260178

The Tibetan Plateau (TP) has the largest number of inland lakes with the highest elevation on the planet. Mapping the distribution of lake water in space and time is crucial for scientific research of interactions among the regional cryosphere, hydrosphere, and atmosphere. In this study, a lake water surface mapping algorithm is developed for Moderate Resolution Imaging Spectroradiometer (MODIS) MOD09Q1 surface reflectance images, which is used to produce the 8-day lake water surface data set (lake water surface area larger than 1 km 2 ) of theTP (Qinghai-Tibet Plateau) for the period of 2000-2012. The accuracy analysis indicate that compared with water surface data of the 134 sample lakes extracted from the 30 m Landsat Thematic Mapper (TM) images, the average overall accuracy of the results is 91.81% with average commission and omission error of 3.26% and 5.38%; the results also show strong linear (the coefficient of determination R 2 is 0.9991) correlation with the global MODIS water mask data set with overall accuracy of 86.30%; and the lake area difference between the Second National Lake Survey and this study is only 4.74%, respectively. This study provides reliable data set for the lake change research of theTP in the recent decade.