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Abstract
The land type cover information has significantly important role to understand land type change and earth activities. Despite the availability of numerous high-resolution satellite data, very minimal number of land type change researches are available up till now due to the computational limitations. This study provides land type change mapping based on high-resolution (30 m) using high computing cloud base platform (google earth engine). The supervised classification training technique is being used in our study. We gathered the land cover type of two year (2016–2017) and addressed the transformations among them during these years. The study is based on four land cover types specifically water, urban land, forest and crop land. This method is provided to overcome the limitation of high computing platform and lack of the availability of high-resolution land cover change data.
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Acknowledgement
The National Natural Science Foundation of China (Nos. 41371371 and 41871296), Open Fund of Key Laboratory of Geographic Information Science (Ministry of Education) and East China Normal University (No. KLGIS2017A05).
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School of Remote Sensing and Engineering, Wuhan University, Wuhan, China
Yahya Ali Khan, Yuwei Wang & Zongyao Sha
- Yahya Ali Khan
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Correspondence toYahya Ali Khan.
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Eastern Michigan University, Ypsilanti, MI, USA
Yichun Xie
Hebei University of Engineering, Handan, China
Anbing Zhang
Hebei University of Engineering, Handan, Hebei, China
Haixin Liu
Hebei University of Engineering, Handan, China
Lili Feng
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Khan, Y.A., Wang, Y., Sha, Z. (2019). Land Cover Change Analysis in Wuhan, China Using Google Earth Engine Platform and Ancillary Knowledge. In: Xie, Y., Zhang, A., Liu, H., Feng, L. (eds) Geo-informatics in Sustainable Ecosystem and Society. GSES 2018. Communications in Computer and Information Science, vol 980. Springer, Singapore. https://doi.org/10.1007/978-981-13-7025-0_24
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