Synergistic use of Landsat TM and SPOT5 imagery for object-based forest classification
نویسندگان
چکیده
منابع مشابه
Object-Based Classification of UltraCamD Imagery for Identification of Tree Species in the Mixed Planted Forest
This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...
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Introduction: Having accurate and up-to-date information on the status of land use and land cover change is a key point to protecting natural resources, sustainable agriculture management and urban development. Preparing the land cover and land use maps with traditional methods is usually time and cost consuming. Nowadays satellite imagery provides the possibility to prepare these maps in less ...
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this study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. to maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. two subsets of an ultracam d image were geometrically corrected using aero-triangulation method. some appropriate transformations were perfor...
متن کاملComparison of Pixel-based and Object-oriented Knowledge-based Classification Methods Using SPOT5 Imagery
Land cover mapping is very important for evaluating natural recourses, understanding the societal and business activities. The remote sensing techniques provide effective and efficient methods to create such maps. To high spatial resolution imagery such as SPOT5 imagery, the land cover classification precision will be improved with the knowledge, Digital Elevation Model (DEM) data and the spati...
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This paper focuses on an automated ANN classification system consisting of two modules: an unsupervised Kohonen’s Self-Organizing Mapping (SOM) neural network module, and a supervised Multilayer Perceptron (MLP) neural network module using the Backpropagation (BP) training algorithm. Two training algorithms were provided for the SOM network module: the standard SOM, and a refined SOM learning a...
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ژورنال
عنوان ژورنال: Journal of Applied Remote Sensing
سال: 2014
ISSN: 1931-3195
DOI: 10.1117/1.jrs.8.083550