论文信息 - Application of multispectral remote sensing technology in surface water body extraction

Application of multispectral remote sensing technology in surface water body extraction

This paper addresses an improved water-body extraction method by the multispectral remote sensing image of four-bands. Firstly, traditional multispectral water body extraction technologies are reviewed, and their features are compared. It shows that finding the most difference of the reflection ratio of the water body and the background is the core to improve the identification rate. Furthermore, combing data's feature of GF-01 and GF-02 satellites, an improved normalization index method by introducing the weighted average of the blue and green light bands was proposed. Finally, the comparative results illustrating the improvement of water body extraction are provided and analyzed.

[1] S. K. McFeeters. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[2] Rasmus Fensholt,et al. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery , 2014 .

[3] Hanqiu Xu. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[4] Zhang Bing,et al. Comparative Analysis of Automatic Water Identification Method Based on Multispectral Remote Sensing , 2011 .

[5] References , 1971 .

[6] N. Oppelt,et al. Remote sensing for lake research and monitoring – Recent advances , 2016 .

[7] Vittorio E. Brando,et al. Imaging Spectrometry of Water , 2002 .

[8] Laurence C. Smith,et al. Automated Image Registration for Hydrologic Change Detection in the Lake-Rich Arctic , 2008, IEEE Geoscience and Remote Sensing Letters.

[9] Zhang Guifang,et al. A Integrated Method for Water Body Detection and Delineation Using Landsat ETM+data , 2008 .

[10] B. Wylie,et al. Analysis of Dynamic Thresholds for the Normalized Difference Water Index , 2009 .

[11] Y. Ouma,et al. A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes: an empirical analysis using Landsat TM and ETM+ data , 2006 .