Because of all-weather working ability, sensitivity to biomass and moisture, and high spatial resolution, Synthetic aperture radar (SAR) satellite images can perfectly complement optical images for pasture monitoring. This paper aims to examine the potential of the integration of COnstellation of small Satellites for the Mediterranean basin Observasion (COSMO-SkyMed), Environmental Satellite Ad...

Detecting land cover change over semi-arid rangeland is important for monitoring vegetation responses to drought, population expansion, and changing agricultural practices. Such change can be detected using vegetation indices, but these do not represent non-green vegetation and are dominated by seasonal changes. An alternative is to observe spatial changes in thermal emissivities, a measure tha...

Remotely sensed imageries were used to analyze the response of desert vegetation to physiographic factors and accumulated precipitation in drier and wetter years within a region of >16,500 km(2) sampled with 5,000 random pixels of 30 m. Vegetation development was indexed by the annual maximum values for greenness (SAVI) and canopy water content (NDII). Precipitation was interpolated from the 0....

This study presents a method for quantitatively estimating leaf area index (LAI) in winter wheat by exploring bi-directional reflectance distribution function (BRDF) data. In BRDF data, near-infrared reflectance (NIR) which is sensitive to crown component, canopy cover and crown shape, is affected by illuminated crown component, while red reflectance is sensitive to canopy gaps and controlled b...

Estimating forest variables, such as photosynthetic light use efficiency, from satellite reflectance data requires understanding the contribution of photosynthetic vegetation (PV) and nonphotosynthetic vegetation (NPV). The fractions of PV and NPV present in vegetation reflectance data are typically controlled by the canopy structure and the respective viewing angle. The persistent but highly v...

A coupled vegetation growth and SVAT (Soil-Vegetation-Atmosphere Transfer) model is used in conjunction with data collected in the course of the SALSA program during the 1997, 1998 and 1999 growing seasons in Mexico. The objective is to provide insights on the interactions between grassland dynamics and water and energy budgets. These three years exhibit drastically different precipitation regi...

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation produc...

Pan-sharpening is the process of fusing higher spatial resolution panchromatic (PAN) with lower spatial resolution multispectral (MS) imagery to create higher spatial resolution MS images. Here, our overall objective was to pan-sharpen Landsat-8 images and calculate vegetation greenness (i.e., normalized difference vegetation index (NDVI)), canopy structure (i.e., enhanced vegetation index (EVI...

Cloud contamination is one of the severest problems for the time-series analysis of optical remote sensing data such as vegetation phenology detection. Sub-pixel clouds are especially difficult to identify and remove. It is important for accuracy improvement in various terrestrial remote sensing applications to clarify the influence of these residual clouds on spectral vegetation indices. This ...