The Vegetation Extraction and Hierarchical Classification using an IRS-1C LISS III Image
نویسندگان
چکیده
منابع مشابه
The Vegetation Extraction and Hierarchical Classification using an IRS-1C LISS III Image
Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The proposed method examines the complex process of land cover vegetation pattern classification using an IRS-1C LISS III image. Pre-processing was done by employing partial differential equation (PDE). Normalized differential vegetation index (NDVI) was applied to separate vegetation features from the ...
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Monitoring and tracking vegetation changes in vast and remote areas is a difficult task. Accurate extraction of existing vegetation is the primary step for better statistical assessment. An approach for vegetation mapping is proposed which automatically explores spectral characteristics of connected components in an image. Different frames of multi-spectral Indian Remote sensing IRS-1C LISS III...
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Abstract— Satellite Remote sensing with repetitive and pan viewing and multispectral capabilities, is a powerful tool for mapping and monitoring the ecological changes. Analysis of the remote sensing data is faced with a number of challenges ranging from type of sensors, number of sensors, spectral responses of satellite sensors, resolutions in different domains and qualitative and quantitati...
متن کاملLand Cover Classification Using IRS LISS III Image and DEM in a Rugged Terrain: A Case Study in Himalayas
Digital image classification is generally performed to produce land cover maps from remote sensing data, particularly for large areas. The performance of image classifiers that utilize only the remote sensing data may deteriorate, especially in mountainous regions, due to the presence of shadows of high peaks. In this study, a multisource classification approach to map land cover in Himalayan r...
متن کاملClassification of IRS LISS-III Images by using Artificial Neural Networks
The purpose of this paper is to classify the LISS-III satellite images into different classes as agriculture, urban and water body. Here pixel based classification is used to classify each pixel of the satellite image as belonging to one of those three classes. To perform this classification, a neural network back propagation technique is used. The neural network consists of three layers: Input...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2016
ISSN: 0975-8887
DOI: 10.5120/ijca2016912401