Add to ORKGRemote sensing data is very useful for many important applications. Mono spectral consistsof single band, multispectral of few up to 10 numbersof bands and Hyper spectralbands consist of hundreds of bands.Indices are used to recognize crops or any other material
ABSTRACT. Remote sensing technologies are recognized as an efficient tool for getting information ab...
ABSTRACT: Spectral indices are combinations of surface reflectance at two or more bands which indica...
Hyperspectral image processing is a promising tool for the analysis of vegetation in remote sensing ...
Remote sensing data is very useful for many important applications. Mono spectral consistsof single ...
The interpretation of spectral information is at the very core of remote sensing data analysis. Howe...
Vegetation indices computed from remote sensing data became key components of agricultural monitorin...
NumerollS formulae. vegetation indices. have been developed to reduce multispectral scanner (MSS) da...
Monitoring of the state of agricultural crops and forecasting the crops development begin with aeria...
Over the past decades, the discipline of remote sensing has become an essential tool in earth scienc...
Hyperspectral analysis of vegetation involves obtaining spectral reflectance measurements in hundred...
The calculation of Normalized Difference Vegetation Indices (NDVI) can be very useful in the generat...
Hyperspectral remote sensing imagery was collected over a soybean field in central Illinois in mid-J...
This paper describes a rational approach to the design of an optimal index to estimate vegetation pr...
Non-Peer ReviewedRemote Sensing, with its unique characteristics of multi-spatial, multi-temporal, a...
Numerous spectral indices have been developed to assess plant diversity. However, since they are dev...
ABSTRACT. Remote sensing technologies are recognized as an efficient tool for getting information ab...
ABSTRACT: Spectral indices are combinations of surface reflectance at two or more bands which indica...
Hyperspectral image processing is a promising tool for the analysis of vegetation in remote sensing ...
Remote sensing data is very useful for many important applications. Mono spectral consistsof single ...
The interpretation of spectral information is at the very core of remote sensing data analysis. Howe...
Vegetation indices computed from remote sensing data became key components of agricultural monitorin...
NumerollS formulae. vegetation indices. have been developed to reduce multispectral scanner (MSS) da...
Monitoring of the state of agricultural crops and forecasting the crops development begin with aeria...
Over the past decades, the discipline of remote sensing has become an essential tool in earth scienc...
Hyperspectral analysis of vegetation involves obtaining spectral reflectance measurements in hundred...
The calculation of Normalized Difference Vegetation Indices (NDVI) can be very useful in the generat...
Hyperspectral remote sensing imagery was collected over a soybean field in central Illinois in mid-J...
This paper describes a rational approach to the design of an optimal index to estimate vegetation pr...
Non-Peer ReviewedRemote Sensing, with its unique characteristics of multi-spatial, multi-temporal, a...
Numerous spectral indices have been developed to assess plant diversity. However, since they are dev...
ABSTRACT. Remote sensing technologies are recognized as an efficient tool for getting information ab...
ABSTRACT: Spectral indices are combinations of surface reflectance at two or more bands which indica...
Hyperspectral image processing is a promising tool for the analysis of vegetation in remote sensing ...