Mapping and spatiotemporal dynamics of land-use and land-cover change based on the Google Earth Engine cloud platform from Landsat imagery: A case study of Zhoushan Island, China.

Chao Chen, Xuebing Yang, Shenghui Jiang, Zhisong Liu

Abstract read

In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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2 · The registry

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2 citing papers in PubMed.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chao ChenSchool of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, 215009, PR China.

Xuebing YangSchool of Information Engineering, Zhejiang Ocean University, Zhoushan, 316022, PR China.

Shenghui JiangKey Lab of Submarine Geosciences and Prospecting Techniques, MOE and College of Marine Geoscience, Ocean University of China, Qingdao, 266100, PR China.

Zhisong LiuSchool of Information Engineering, Zhejiang Ocean University, Zhoushan, 316022, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Land resources are an essential foundation for socioeconomic development. Island land resources are limited, the type changes are particularly frequent, and the environment is fragile. Therefore, large-scale, long-term, and high-accuracy land-use classification and spatiotemporal characteristic analysis are of great significance for the sustainable development of islands. Based on the advantages of remote sensing indices and principal component analysis in accurate classification, and taking Zhoushan Archipelago, China, as the study area, in this work long-term satellite remote sensing data were used to perform land-use classification and spatiotemporal characteristic analysis. The classification results showed that the land-use types could be exactly classified, with the overall accuracy and Kappa coefficient greater than 94% and 0.93, respectively. The results of the spatiotemporal characteristic analysis showed that the built-up land and forest land areas increased by 90.00 km

Indexed as

GEELandsatLand use and land cover changeSpatio-temporal characteristicsZhoushan island

Identifiers

PMID37809681

DOI10.1016/j.heliyon.2023.e19654

PMCPMC10558908

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LicenceCC BY-NC-ND

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.