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A Fine-Scale Mangrove Map of China Derived from 2-Meter Resolution Satellite Observations and Field Data.

Authors :
Zhang, Tao
Hu, Shanshan
He, Yun
You, Shucheng
Yang, Xiaomei
Gan, Yuhang
Liu, Aixia
Kainz, Wolfgang
Source :
ISPRS International Journal of Geo-Information. Feb2021, Vol. 10 Issue 2, p92. 1p.
Publication Year :
2021

Abstract

Mangrove forests are important ecosystems in the coastal intertidal zone, but China's mangroves have experienced a large reduction in area from the 1950s, and the remaining mangrove forests are exhibiting increased fragmentation. A detailed mangrove dataset of China is crucial for mangrove ecosystem management and protection, but the fragmented mangrove patches are hardly mapped by medium resolution satellite imagery. To overcome these difficulties, we presented a fine-scale mangrove map for 2018 using the 2-meter resolution Gaofen-1 and Ziyuan-3 satellite imagery together with field data. We employed a hybrid method of object-based image analysis (OBIA), interpreter editing, and field surveying for mangrove mapping. The field survey route reached 9500 km, and 2650 patches were verified during the field work. Accuracy assessment by confusion matrix showed that the kappa coefficient reached 0.98, indicating a highly thematic accuracy of the mangrove dataset. Results showed the total area of mangrove forest in China for 2018 was 25,683.88 hectares, and approximately 91% of mangroves were found in the three provinces of Guangdong, Guangxi, and Hainan. About 64% of mangroves were distributed in or near the nature reserves established by national or local governments, which indicated that China's mangroves were well protected in recent years. The new fine-scale mangrove dataset was freely shared together with this paper, and it can be used by local authorities and research groups for mangrove management and ecological planning. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22209964
Volume :
10
Issue :
2
Database :
Academic Search Index
Journal :
ISPRS International Journal of Geo-Information
Publication Type :
Academic Journal
Accession number :
148977549
Full Text :
https://doi.org/10.3390/ijgi10020092