13 October 2009 Automatic detection of LUCC based on SIFT
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74920E (2009) https://doi.org/10.1117/12.838660
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Land use cover change (LUCC) provide important information for environmental management and planning. It is one of the most prominent characteristics in globe environment change, and not only limited by natural factor, but also affected by the factor of social, economics, technique and histories. Traditionally, field surveys of land cover and land use are time consuming and costly and provide tabular statistics with out geographic location information. Remote sensing and GIS are the most modern technologies which have been widely used in the field of natural resource management and monitoring. Change detection in land use and updating information on the distribution and dynamics of land use have long term significance in policy making and scientific research. In this paper, we use multistpectral images of Spot period two different of time 2002 and 2007 for detection on LUCC base on Scale Invariant Feature Transform (SIFT) method. An automatic image matching technique based on SIFT was proposed by using the rotation and scale invariant property of SIFT. Keypoints are first extracted by searching over all scales and image locations, then the descriptors defined on the keypoint neighborhood are computed. The proposed algorithm is robust to translation, rotation, noise and scaling. Experimental results, urban is the most part of Huangpi area which have been changed.
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Keonuchan Ammala, Keonuchan Ammala, YaoLin Liu, YaoLin Liu, Ji Rong Tai, Ji Rong Tai, } "Automatic detection of LUCC based on SIFT", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74920E (13 October 2009); doi: 10.1117/12.838660; https://doi.org/10.1117/12.838660

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