Abstract
Tianjin is the largest open city along the coastline in Northern China, which has several important wetland ecosystems. However, no systematic study has assessed the water body changes over the past few decades for Tianjin, not to mention their response to human activities and climate change. Here, based on the water change tracking (WCT) algorithm, we proposed an improved water change tracking (IWCT) algorithm, which could remove built-up shade noise (account for 0.4%~6.0% of the final water area) and correct omitted water pixels (account for 1.1%~5.1% of the final water area) by taking the time-series data into consideration. The seasonal water product of the Global Surface Water Data (GSWD) was used to provide a comparison with the IWCT results. Significant changes in water bodies of the selected area in Tianjin were revealed from the time-series water maps. The permanent water area of Tianjin decreased 282.5 km2 from 1984 to 2019. Each time after the dried-up period, due to government policies, the land reclamation happened in Tuanbo Birds Nature Reserve (TBNR), and, finally, 12.6 km2 of the lake has been reclaimed. Meanwhile, 488.6 km2 of land has been reclaimed from the sea along the coastal zone in the past 16 years at a speed of 28.74 km2 yr−1 in the Binhai New Area (BHNA). The method developed in this study could be extended to other sensors which have similar band settings with Landsat; the products acquired in this study could provide fundamental reference for the wetland management in Tianjin.
Highlights
Based on the WCT algorithm, we proposed an improved water change tracking (IWCT) algorithm to overcome the defects of the WCT
The results show that the IWCT method was much better than the WCT by providing lower commission errors and omission errors (Table 1)
To test whether the area of water bodies was driven by precipitation, the relationship between water area in each selected study area and local precipitation from the nearest meteorological station was examined
Summary
Inland water systems often provide critical ecosystem functions, i.e., water and food provision, local climate regulation, conservation of biological diversity [1,2,3]. Due to intensive human activities (e.g., land reclamation and water conservancy projects), the area of inland water decreased sharply in China [4,5]. Accurate monitoring the long-term changes of inland water bodies is important to both scientific community for water research and local governments for water-resource planning and management [6,7,8,9,10,11]. Remote sensing has become one of the most efficient methods in water area monitoring with synoptic and repeated observations. Various methods have been developed to discriminate and map water using multi-spectral, hyperspectral and radar images [12,13,14]
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