Hyperspectral Data for Land use/Land cover classification
نویسندگان
چکیده
منابع مشابه
Urban Land Cover Classification Using Hyperspectral Data
Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...
متن کاملPolyline Feature Extraction for Land Cover Classification using Hyperspectral Data
Prediction of landcover types from airborne/spaceborne sensors is an important classification problem in remote sensing. Due to recent advances in sensor technology, it is now possible to acquire hyperspectral data simultaneously in ∼200 bands, each of which measures the integrated response of a target over a narrow window of the electromagnetic spectrum. This unprecedented spectral resolution ...
متن کاملLand-use/Land-cover Classification with Multispectral and Hyperspectral EO-1 Data
We compared the capability of the Earth Observing-1 (EO-1) Hyperion hyperspectral (HS) data with that of the EO-1 Advanced Land Imager (ALI) multispectral (MS) data for discriminating different land-use and land-cover classes in Fremont, California. We designed a classification scheme of two levels with level I including general classes and level II including more specific classes. Classificati...
متن کاملArtificial Neural Network Approach for Land Cover Classification of Fused Hyperspectral and Lidar Data
Hyperspectral remote sensing images are consisted of several hundreds of contiguous spectral bands that can provide very rich information and has the potential to differentiate land cover classes with similar spectral characteristics. LIDAR data gives detailed height information and thus can be used complementary with Hyperspectral data. In this work, a hyperspectral image is combined with LIDA...
متن کاملIntegration of LiDAR and Hyperspectral Data for Land-cover Classification: A Case Study
In this paper, an approach is proposed to fuse LiDAR and hyperspectral data, which considers both spectral and spatial information in a single framework. Here, an extended self-dual attribute profile (ESDAP) is investigated to extract spatial information from a hyperspectral data set. To extract spectral information, a few well-known classifiers have been used such as support vector machines (S...
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ژورنال
عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2014
ISSN: 2194-9034
DOI: 10.5194/isprsarchives-xl-8-991-2014