Obtaining detailed and reliable data about local economic livelihoods in developing countries is expensive, and data are consequently scarce. Previous work has shown that it is possible to measure local-level economic livelihoods using high-resolution satellite imagery. However, such imagery is relatively expensive to acquire, often not updated frequently, and is mainly available for recent yea...

We tested the accuracy of an atmospheric correction method that depends on clear water bodies to infer solar and atmospheric parameters for radiative transfer equations by measuring the reflectance signature of four prominent south Texas rangeland plants with the Earth Resource Technology (LANDSAT) satellite multispectral scanner (MSS) and a ground-based Exotech Model 20 spectroradiometer. The ...

The next generation of remote sensing observing systems will routinely provide multispectral data from a very large number of sensors. For example, the Landsat-type instrument of the planned Earth observing system (Eos) satellite will be the HIghResolution Imaging Spectrometer (HIRIS). The HIRIS will have 192 channels, compared to seven on the current Landsat Thematic Mapper (TM). Similarly, th...

Image fusion of multispectral and panchromatic satellite image is used to combine spatial detail of the panchromatic image of high spatial resolution and spectral information of multispectral image of low resolution, in order to create a synthetic multispectral high-resolution image. This process is called pansharpening and the resulting image, has among others, improved visual quality and visu...

This note is a review of works on retrieval of snow grain size from satellite images. A theoretical background is given and a number of models and algorithms are described. Most of the works are based on Landsat images with 30 m resolution and 7 optical channels, but the hyperspectral airborne AVIRIS sensor with 20 m resolution, and SAR has also been used. An algorithm derived from Landsat imag...

Satellite-based multispectral imaging systems have been in operation since 1972 and the latest in the Landsat series of sensors was launched in July 1982. One system parameter of interest is resolution and this paper discusses experiments to determine the actual overall resolution after launch. Atmospheric effects and postprocessing effects add to the prelaunch optical resolution. Scene structu...

Measuring the aerial extent of tropical deforestation for other than localized areas requires the use of satellite data.We present evidence to show that an accurate determination of tropical deforestation is very di cult to achieve by a ‘random sampling’ analysis of Landsat or similar high spatial resolution data unless a very high percentage of the area to be studied is sampled. In order to a...

This present work evaluates the use of knowledge-based techniques for the analysis of medium-resolution satellite images of the Amazon, and estimates the impact they may bring to the task of mapping the deforestation in this region by. Landsat images of Rondônia State were submitted to a supervised classification; the editing of these classifications, an usually manual process that depends tota...

Knowledge of the spatial distribution of biofuel crops is an important criterion to determine the sustainability of biofuel energy production. Remotely sensed image analysis is a proven and effective tool for describing the spatial distribution of crops using vegetation characteristics. Increases in the number of options and availability of satellite sensors have expanded the horizon of choices...

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODI...