the reflectance spectrum of green leaves is considerably affected by their biochemical and biophysical properties. it is possible to extract biochemical information from a continuous vegetation spectrum produced using hyperspectral sensors. the numerous absorption features present in the vegetation spectrum carry a considerable amount of information related to the content and the structure of t...

abstract the amount of needed fertilizer in agricultural soils depends to the type of crop. absence of enough fertilizer may cause in tensions in plants and consequently result in decrease in amount of product. according to the agricultural literature, soils containing total nitrogen amounts (n %) between 0.1-0.15 percent are considered as soils containing normal amounts of nitrogen. the values...

anomaly detection (ad) has recently become an important application of target detection in hyperspectral images. the reed-xialoi (rx) is the most widely used ad algorithm that suffers from “small sample size” problem. the best solution for this problem is to use dimensionality reduction (dr) techniques as a pre-processing step for rx detector. using this method not only improves the detection p...

expensive to provide these maps  with field measurements  therefore  it is better to use new methods. this study provides a lithological and alteration mapping units with dominant minerals based on hyperspectral images of eo1-hyperion satellite. to do so, two different zones  were  investigated:  the  cuprite-nevada  and  mozahem  volcano  in  iran  which  have suitable conditions for our study...

hyperspectral sensors provide a large number of spectral bands. this massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. we propose to use overlap-based feature weigh...

Over the past two decades, hyperspectral remote sensing from airborne and satellite systems has been used as a data source for numerous applications. Hyperspectral imaging is quickly moving into the mainstream of remote sensing and is being applied to remote sensing research studies. Hyperspectral remote sensing has great potential for analysing complex urban scenes. However, operational applic...

Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...

Hyperspectral remote sensing has become one of the research frontiers in ground object identification and classification. On the basis of reviewing the application of hyperspectral remote sensing in identification and classification of ground objects at home and abroad. The research results of identification and classification of forest tree species, grassland and urban land features were summa...

In this paper different types of image classification will be studied. Decision level fusion, using a specific criterion or algorithm to integrate the classified results from different classifiers, has shown great benefits to improve classification accuracy of multi-source remote sensing images. Based on a survey to hyperspectral remote sensing classification techniques and decision level fusio...

The paper presents an experimental research of proposed method of atmospheric correction of hyperspectral remote sensing data. The method is based on approximate solution of MODTRAN transmittance equation using simultaneous analysis of remote sensing hyperspectral image and an ideal hyperspectral image of the same territory. Results of experimental research imitating conditions of practical met...