Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosyn...

Canopy chlorophyll content (Chl) closely relates to plant photosynthetic capacity, nitrogen status and productivity. The goal of this study is to develop remote sensing techniques for accurate estimation of canopy Chl during the entire growing season without re-parameterization of algorithms for two contrasting crop species, maize and soybean. These two crops represent different biochemical mec...

Green Leaf Area Index (GLAI) and Green Biomass (GBM) are two of the fundamental biophysical properties indicating vegetation physiological status. In the current research a new three channel normalized band ratio algorithm i.e. "Weighted Normalized Crop Index (WNCI)" is proposed for remote estimation of vegetation GLAI and GBM. WNCI takes into account three of the most common vegetation sensiti...

Vegetation indices have been used extensively to estimate the vegetation density from satellite and airborne images for many years. In this paper we first focus on one of the most popular vegetation indices, the normalized difference vegetation index (NDVI ) [1] and introduce a statistical framework to analyze it. We propose a solution to the saturation problem of this index based on our statis...

To enhance the vegetation signal in remotely sensed data and provide an approximate measure of live green vegetation, a number of spectral vegetation indices have been developed to estimate biophysical parameters of vegetation. The sensitivity of the normalized difference vegetation index (NDVI) to the soil background and atmospheric effects has generated an increasing interest in the developme...

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...

A new moisture adjusted vegetation index (MAVI) is proposed using the red, near infrared, and shortwave infrared (SWIR) reflectance in band-ratio form in this paper. The effectiveness of MAVI in retrieving leaf area index (LAI) is investigated using Landsat-5 data and field LAI measurements in two forest and two grassland areas. The ability of MAVI to retrieve forest LAI under different backgro...

We estimated the light use efficiency (LUE) via vegetation canopy chlorophyll content (CCCcanopy) based on in situ measurements of spectral reflectance, biophysical characteristics, ecosystem CO 2 fluxes and micrometeorological factors over a maize canopy in Northeast China. The results showed that among the common chlorophyll-related vegetation indices (VIs), CCCcanopy had the most obviously e...