Most paddy rice in the world grows in warm, humid and rainy environment where it is hard to acquire optical remote sensing data. Synthetic Aperture Radar (SAR) can acquire remote sensing information due to its all weather imaging and frequent revisit capability in the areas. A semi-empirical backscattering model was used to estimate leaf area index (LAI) from ENVISAT ASAR (Advanced Synthetic Ap...

nowadays, remote sensing comes under the title of management method for precision farming. for provision of the land cover and therefore land use map use must be made of satellite images. for an assessment of the type of agricultural crops it is required to have satellite images of high resolution. from specifications of the satellite images one is to produce maps with varied scales. in this re...

In contrast to herbaceous canopies and forests, savannas are grassland ecosystems with sparsely distributed individual trees, so the canopy is spatially heterogeneous and open, whereas the woody cover in savannas, e.g., tree cover, adversely affects ecosystem structures and functions. Studies have shown that the dynamics of canopy structure are related to available water, climate, and human act...

Leaf area index (LAI) is one of the most important parameter of forest structure. The study site was an isolated forest in Kyoto City in Japan and it vegetation type was mixed forest. We took fisheye photos at 102 points in the study area, and calculated the LAI and Canopy-open. We classified the laser data into 4 classes, that is, First pulse, Last pulse, Only pulse and Ground pulse. We counte...

This study demonstrates the potentials of IRS P6 LISS-IV high-resolution multispectral sensor (IGFOV 6 m)-based estimation of biomass in the deciduous forests in the Western Ghats of Karnataka, India. Regression equations describing the relationship between IRS P6 LISS-IV data-based vegetation index (NDVI) and field measured leaf area index (ELAI) and estimated above-ground biomass (EAGB) were ...

Understanding variation in SW (seed weigh) is of major importance in understanding SY (seed yield) variation. The objective of this study was to determine factors such as SN (seed number) per unit area, SFD (seed filling duration) and SFR (seed filling rate) and temperature, LAI (leaf area index), LAD (leaf area duration), above-ground dry matter, CGR (crop growth rate), leaf dry matter re...

Vegetation plays an important role in the exchange of carbon dioxide, water, and energy between the land surface and the atmosphere. LAI, defined as one-half the total green leaf area per unit of ground surface area, drives the within and the below canopy microclimate, determines canopy water interception, radiation extinction, and water and carbon gas exchange. Therefore, accurate LAI is a key...

[1] This paper presents results of validating the Collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) product using LAI data collected in a 3 3 km agricultural (grasses and cereal crops) area near Avignon, France, and 30 m resolution Enhanced Thematic Mapper (ETM+) image. Estimates of the accuracy, precision, and uncertainty with which the ETM+ data convey i...

This study is aimed at demonstrating the feasibility of a large-scale leaf area index (LAI) inversion using high resolution airborne imagery without calibrating using ground based measurements. The study area is located in the Gatineau Park, Southern Quebec, Canada. The developed methods are evaluated in relatively high forest cover where remote sensing retrieval of biophysical parameters is co...

Increasing attention is being paid on leaf area index (LAI) retrieval in mountainous areas. Mountainous areas present extreme topographic variability, and are characterized by more spatial heterogeneity and inaccessibility compared with flat terrain. It is difficult to collect representative ground-truth measurements, and the validation of LAI in mountainous areas is still problematic. A cost-c...