Cutting-edge remote sensing technology has a significant role for managing the natural resources as well as the any other applications about the earth observation. Crop monitoring is the one of these applications since remote sensing provides us accurate, up-to-date and cost-effective information about the crop types at the different temporal and spatial resolution. In this study, the potential...

Spectral vegetation indices are frequently used to estimate vegetation biophysical/biochemical characteristics. In general they have been proposed to reduce spectral effects caused by external factors such as the atmosphere and the soil background. This study evaluated narrow band vegetation indices for estimation of vegetation leaf area index. The study takes advantage of using a dataset colle...

[1] The evaluation of the relationship between satellitederived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive...

Current methods for large-scale vegetation monitoring rely on multispectral remote sensing, which has serious limitation for the detection of vegetation stress. To contribute to the establishment of a generalized spectral approach for vegetation stress detection, this study compares the ability of high-spectral-resolution reflectance (R) and fluorescence (F) foliar measurements to detect vegeta...

This paper describes the implementation of a physical and mathematical approach to designing advanced vegetation indices optimized for future sensors operating in the solar domain such as the medium resolution imaging spectrometer (MERIS), the global imager (GLI), and the VEGETATION instrument, and proposes an initial evaluation of such indices. These optimized indices address sensor-specific i...

Many algorithms have been developed for the remote estimation of vegetation fraction in terms of combinations of spectral bands, derivatives of reflectance spectra, neural networks, inversion of radiative transfer models, and several multi-spectral statistical approaches. The most widespread type of algorithm used is the mathematical combination of visible and near-infrared reflectance, in the ...

Remotely sensed vegetation indices have been extensively used to quantify plant and soil characteristics. The objectives of this study were to: (i) compare vegetation indices developed at different scales for measuring canopy N content (g∙N∙m −2 ) and concentration (%); and (ii) evaluate the effects of soil background reflectance, cultivar, illumination and atmospheric conditions on the ability...

Vegetation indices (VI), such as greenness (GVI), perpendicular (PVI), transformed soil adjusted (TSAVI), and normalized difference (NDVI), measure the photosynthetic size of plant canopies and portend yields. A set of equations, called spectral components analysis (SCA), that interrelates VI or cumulative seasonal VI (Y'.VI), leaf area index (L), fractional photosynthetically active radiation ...

Spectral vegetation indices have been used extensively INTRODUCTION to predict ecological variables, such as percent vegetation On 18 May 1980, Mount St. Helens in the State of cover, above-ground biomass, and leaf-area index. We exWashington erupted with catastrophic, landscape-scale amined the use of various vegetation indices and multiple effects (Lipman and Mullineaux, 1981). In a mere 10 l...