A synergy cropland of China by fusing multiple existing maps and statistics

Accurate information on cropland extent is critical for scientific research and resource management. Several cropland products from remotely sensed datasets are available. Nevertheless, significant inconsistency exists among these products and the cropland areas estimated from these products differ...

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Main Authors: Lu, Miao, Wu, Wenbin, You, Liangzhi, Chen, Di, Zhang, Li, Yang, Peng, Tang, Huajun
Format: Journal Article
Language:Inglés
Published: MDPI 2017
Subjects:
Online Access:https://hdl.handle.net/10568/146209
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author Lu, Miao
Wu, Wenbin
You, Liangzhi
Chen, Di
Zhang, Li
Yang, Peng
Tang, Huajun
author_browse Chen, Di
Lu, Miao
Tang, Huajun
Wu, Wenbin
Yang, Peng
You, Liangzhi
Zhang, Li
author_facet Lu, Miao
Wu, Wenbin
You, Liangzhi
Chen, Di
Zhang, Li
Yang, Peng
Tang, Huajun
author_sort Lu, Miao
collection Repository of Agricultural Research Outputs (CGSpace)
description Accurate information on cropland extent is critical for scientific research and resource management. Several cropland products from remotely sensed datasets are available. Nevertheless, significant inconsistency exists among these products and the cropland areas estimated from these products differ considerably from statistics. In this study, we propose a hierarchical optimization synergy approach (HOSA) to develop a hybrid cropland map of China, circa 2010, by fusing five existing cropland products, i.e., GlobeLand30, Climate Change Initiative Land Cover (CCI-LC), GlobCover 2009, MODIS Collection 5 (MODIS C5), and MODIS Cropland, and sub-national statistics of cropland area. HOSA simplifies the widely used method of score assignment into two steps, including determination of optimal agreement level and identification of the best product combination. The accuracy assessment indicates that the synergy map has higher accuracy of spatial locations and better consistency with statistics than the five existing datasets individually. This suggests that the synergy approach can improve the accuracy of cropland mapping and enhance consistency with statistics.
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spelling CGSpace1462092025-02-19T13:42:22Z A synergy cropland of China by fusing multiple existing maps and statistics Lu, Miao Wu, Wenbin You, Liangzhi Chen, Di Zhang, Li Yang, Peng Tang, Huajun data fusion land-use mapping remote sensing cartography farmland land cover mapping synergism statistics Accurate information on cropland extent is critical for scientific research and resource management. Several cropland products from remotely sensed datasets are available. Nevertheless, significant inconsistency exists among these products and the cropland areas estimated from these products differ considerably from statistics. In this study, we propose a hierarchical optimization synergy approach (HOSA) to develop a hybrid cropland map of China, circa 2010, by fusing five existing cropland products, i.e., GlobeLand30, Climate Change Initiative Land Cover (CCI-LC), GlobCover 2009, MODIS Collection 5 (MODIS C5), and MODIS Cropland, and sub-national statistics of cropland area. HOSA simplifies the widely used method of score assignment into two steps, including determination of optimal agreement level and identification of the best product combination. The accuracy assessment indicates that the synergy map has higher accuracy of spatial locations and better consistency with statistics than the five existing datasets individually. This suggests that the synergy approach can improve the accuracy of cropland mapping and enhance consistency with statistics. 2017 2024-06-21T09:06:11Z 2024-06-21T09:06:11Z Journal Article https://hdl.handle.net/10568/146209 en Open Access MDPI Lu, Miao; Wu, Wenbin; You, Liangzhi; Chen, Di; Zhang, Li; Yang, Peng; and Tang, Huajun. 2017. A synergy cropland of China by fusing multiple existing maps and statistics. Sensors 17(7): 1613. https://doi.org/10.3390/s17071613
spellingShingle data fusion
land-use mapping
remote sensing
cartography
farmland
land cover mapping
synergism
statistics
Lu, Miao
Wu, Wenbin
You, Liangzhi
Chen, Di
Zhang, Li
Yang, Peng
Tang, Huajun
A synergy cropland of China by fusing multiple existing maps and statistics
title A synergy cropland of China by fusing multiple existing maps and statistics
title_full A synergy cropland of China by fusing multiple existing maps and statistics
title_fullStr A synergy cropland of China by fusing multiple existing maps and statistics
title_full_unstemmed A synergy cropland of China by fusing multiple existing maps and statistics
title_short A synergy cropland of China by fusing multiple existing maps and statistics
title_sort synergy cropland of china by fusing multiple existing maps and statistics
topic data fusion
land-use mapping
remote sensing
cartography
farmland
land cover mapping
synergism
statistics
url https://hdl.handle.net/10568/146209
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