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...

There are high demands for water content estimation in vegetation, e.g. water-stress control for sweet crops, forest disease monitoring and drought monitoring. In this paper, normalized difference-based and ratio-based water stress indices by means of hyperspectral information from NIR to SWIR, spectral ranges of InGaAs sensor, are introduced to facilitate realizing simple measurement system at...

Assessment of vegetation water content is critical for monitoring vegetation condition, detecting plant water stress, assessing the risk of forest fires and evaluating water status for irrigation. The main objective of this study was to investigate the performance of various monoand multi-variate statistical methods for estimating vegetation water content (VWC) from hyper-spectral data. Hyper-s...

Multiple endmember spectral mixture analysis (MESMA) has been widely applied for estimating fractional land covers from remote sensing imagery. MESMA has proven effective in addressing inter-class and intra-class endmember variability by allowing pixel-specific endmember combinations. This method, however, assumes that each land cover type has an equal probability of being included in the model...

Accurate estimation of green aboveground biomass in arid and semiarid grassland is essential for a variety of studies, such as sustainable grassland management, fire risk assessment, climate change, and environmental degradation. A great need exists for the establishment of robust method for estimating green aboveground biomass in arid and semiarid grassland due to the influences of soil backgr...

Seeds of 200 accessions of alfalfa (Medicago sativa L.) were provided from Iraniannatural resource gene bank and were sown as drilled plot using alpha designs/unreplicatedwith 2 repeated entries within all of 10 blocks under dry land farming system in agriculturalresearch center of Hamadan, Iran during 2009 to 2010. The data were collected and analyzedfor plant height, stem number, leaf stem ra...

Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to deri...

The monitoring of herbaceous fuel moisture content is a crucial activity in order to assess savanna fire risks. Faced with the difficulty of managing wide areas of vegetated surfaces, remote sensing appears an attractive alternative for terrestrial measurements because of its advantages related to temporal resolution and spatial coverage. Earth observation (EO)-based vegetation indices (VIs) an...

In this paper, we propose a method for using mobile laser-scanning data to estimate the green space ratio (GSR), a landscape index that represents the proportion of green area to the whole-view area. The proposed method first classifies and segments vegetation using voxel-based and shape-based approaches. Vertical planar-surface objects are excluded, and randomly distributed objects are extract...