Mapping Annual Land Use and Land Cover Changes in the Yangtze Estuary Region Using an Object-Based Classification Framework and Landsat Time Series Data

Jinquan Ai, Chao Zhang, Lijuan Chen and Dajun Li
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Jinquan Ai: Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
Chao Zhang: Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai 200241, China
Lijuan Chen: Key Laboratory of the Causes and Control of Atmospheric Pollution of Jiangxi Province, East China University of Technology, Nanchang 330013, China
Dajun Li: Faculty of Geomatics, East China University of Technology, Nanchang 330013, China

Sustainability, 2020, vol. 12, issue 2, 1-18

Abstract: A system understanding of the patterns, causes, and trends of long-term land use and land cover (LULC) change at the regional scale is essential for policy makers to address the growing challenges of local sustainability and global climate change. However, it still remains a challenge for estuarine and coastal regions due to the lack of appropriate approaches to consistently generate accurate and long-term LULC maps. In this work, an object-based classification framework was designed to mapping annual LULC changes in the Yangtze River estuary region from 1985–2016 using Landsat time series data. Characteristics of the inter-annual changes of LULC was then analyzed. The results showed that the object-based classification framework could accurately produce annual time series of LULC maps with overall accuracies over 86% for all single-year classifications. Results also indicated that the annual LULC maps enabled the clear depiction of the long-term variability of LULC and could be used to monitor the gradual changes that would not be observed using bi-temporal or sparse time series maps. Specifically, the impervious area rapidly increased from 6.42% to 22.55% of the total land area from 1985 to 2016, whereas the cropland area dramatically decreased from 80.61% to 55.44%. In contrast to the area of forest and grassland, which almost tripled, the area of inland water remained consistent from 1985 to 2008 and slightly increased from 2008 to 2016. However, the area of coastal marshes and barren tidal flats varied with large fluctuations.

Keywords: land use and land cover changes; long-term; Landsat time series; object-based image analysis; backdating; updating (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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