Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data

• Published in: Land (Basel) Vol. 5; no. 4; p. 44
• Main Authors: Zhai, Ruiting, Zhang, Chuanrong, Li, Weidong, Boyer, Mark A, Hanink, Dean
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2016
• Subjects: Environmental management; Land use; land use/cover change; Light intensity; logistic regression; Long Island Sound Watersheds; Markov chain; Markov chains; multi-layer perception; nighttime lights; Population density; Urban areas; Water pollution; Watersheds; Wildlife; USA, New England
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land5040044

The Long Island Sound Watersheds (LISW) are experiencing significant land use/cover change (LUCC), which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management. This paper modeled the LUCCs between 1996, 2001 and 2006 in the LISW in the New England region, which experienced an increase in developed area and a decrease of forest. The low-density development pattern played an important role in the loss of forest and the expansion of urban areas. The key driving forces were distance to developed areas, distance to roads, and social-economic drivers, such as nighttime light intensity and population density. In addition, this paper compared and evaluated two integrated LUCC models-the logistic regression-Markov chain model and the multi-layer perception-Markov chain (MLP-MC) model. Both models achieved high accuracy in prediction, but the MLP-MC model performed slightly better. Finally, a land use map for 2026 was predicted by using the MLP-MC model, and it indicates the continued loss of forest and increase of developed area.