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A Simple Approach for Guiding Classification of Forest and Crop from Remote Sensing Imagery: A Case Study of Suqian, China

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Geo-Informatics in Resource Management and Sustainable Ecosystem ( 2015, GRMSE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 569))

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Abstract

Basic scientific research of land cover in Suqian is fundamental to ensure the sustainability of land resource management. The major study is to monitor the confusable land cover types according to the remote sensing, and the integrated information. It supplies a new direction for integrating date sets and improves the monitor on land cover. It presents a simple fusion approach for integrating time series of the MODIS Vegetation Index products and Landsat TM data. The fusion supplies the prior probability to distinguish forest with crop for guiding supervised classification which served in monitoring forest quantities-increasing in future. The entire operation just uses primarily the fusion method from the fuzzy mathematics to achieve various kinds of information with some simple parameters. However, the fusion is a spatial feature classification conduced remote sensing training mask data blending the advantages of the phonological information, the feature characteristics and the spatial-temporal data.

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Acknowledgements

This study is supported partly by National Natural Science Foundation of China (41201485), Scientific Research Startup Foundation of Chuzhou University (2012qd17) and the Doctorate Fellowship Foundation of Nanjing Forestry University and the Graduate Education Innovation Project of Jiangsu Province.

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Authors and Affiliations

  1. Chuzhou University, Fengle Road 1528, Chuzhou, 239000, People’s Republic of China

    Ni Wang & Taisheng Chen

  2. College of Forest Resources and Environment, Nanjing Forestry University, Longpan Road 159, Nanjing, 210037, People’s Republic of China

    Ni Wang & Shikui Peng

Authors
  1. Ni Wang
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  2. Taisheng Chen
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  3. Shikui Peng
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Corresponding author

Correspondence to Ni Wang .

Editor information

Editors and Affiliations

  1. Wuhan University , Wuhan, China

    Fuling Bian

  2. Eastern Michigan University , Ypsilanti, China

    Yichun Xie

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Wang, N., Chen, T., Peng, S. (2016). A Simple Approach for Guiding Classification of Forest and Crop from Remote Sensing Imagery: A Case Study of Suqian, China. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_2

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  • DOI: https://doi.org/10.1007/978-3-662-49155-3_2

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  • Publisher Name: Springer, Berlin, Heidelberg

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