Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery
Tracking cropland change and its spatiotemporal characteristics can provide a scientific basis for assessments of ecological restoration in reclamation areas. In 1998, an ecological restoration project (Converting Farmland to Lake) was launched in Dongting Lake, China, in which original lake areas r...
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doaj-8505fd1e7d29402f9ae04a7ca3b8b1f42020-11-25T01:36:36ZengMDPI AGRemote Sensing2072-42922019-05-011110123410.3390/rs11101234rs11101234Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat ImageryLihong Zhu0Xiangnan Liu1Ling Wu2Yibo Tang3Yuanyuan Meng4School of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaTracking cropland change and its spatiotemporal characteristics can provide a scientific basis for assessments of ecological restoration in reclamation areas. In 1998, an ecological restoration project (Converting Farmland to Lake) was launched in Dongting Lake, China, in which original lake areas reclaimed for cropland were converted back to lake or to poplar cultivation areas. This study characterized the resulting long-term (1998−2018) change patterns using the LandTrendr algorithm with Landsat time-series data derived from the Google Earth Engine (GEE). Of the total cropland affected, ~447.48 km<sup>2</sup> was converted to lake and 499.9 km<sup>2</sup> was converted to poplar cultivation, with overall accuracies of 87.0% and 83.8%, respectively. The former covered a wider range, mainly distributed in the area surrounding Datong Lake, while the latter was more clustered in North and West Dongting Lake. Our methods based on GEE captured cropland change information efficiently, providing data (raster maps, yearly data, and change attributes) that can assist researchers and managers in gaining a better understanding of environmental influences related to the ongoing conversion efforts in this region.https://www.mdpi.com/2072-4292/11/10/1234cropland change patternsLandTrendr algorithmLandsat time seriesGoogle Earth EngineDongting LakeChina |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lihong Zhu Xiangnan Liu Ling Wu Yibo Tang Yuanyuan Meng |
spellingShingle |
Lihong Zhu Xiangnan Liu Ling Wu Yibo Tang Yuanyuan Meng Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery Remote Sensing cropland change patterns LandTrendr algorithm Landsat time series Google Earth Engine Dongting Lake China |
author_facet |
Lihong Zhu Xiangnan Liu Ling Wu Yibo Tang Yuanyuan Meng |
author_sort |
Lihong Zhu |
title |
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery |
title_short |
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery |
title_full |
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery |
title_fullStr |
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery |
title_full_unstemmed |
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery |
title_sort |
long-term monitoring of cropland change near dongting lake, china, using the landtrendr algorithm with landsat imagery |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2019-05-01 |
description |
Tracking cropland change and its spatiotemporal characteristics can provide a scientific basis for assessments of ecological restoration in reclamation areas. In 1998, an ecological restoration project (Converting Farmland to Lake) was launched in Dongting Lake, China, in which original lake areas reclaimed for cropland were converted back to lake or to poplar cultivation areas. This study characterized the resulting long-term (1998−2018) change patterns using the LandTrendr algorithm with Landsat time-series data derived from the Google Earth Engine (GEE). Of the total cropland affected, ~447.48 km<sup>2</sup> was converted to lake and 499.9 km<sup>2</sup> was converted to poplar cultivation, with overall accuracies of 87.0% and 83.8%, respectively. The former covered a wider range, mainly distributed in the area surrounding Datong Lake, while the latter was more clustered in North and West Dongting Lake. Our methods based on GEE captured cropland change information efficiently, providing data (raster maps, yearly data, and change attributes) that can assist researchers and managers in gaining a better understanding of environmental influences related to the ongoing conversion efforts in this region. |
topic |
cropland change patterns LandTrendr algorithm Landsat time series Google Earth Engine Dongting Lake China |
url |
https://www.mdpi.com/2072-4292/11/10/1234 |
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