This paper discusses the use of multitemporal remote sensing data for mapping and monitoring land cover in Acre State located in the western Brazilian Amazônia. According to IBGE vegetation maps, the study area is primarily covered by moist tropical forests (“Floresta Ombrofila Aberta”) that has been partially deforested during the last decades. The climate in Acre is classified as Am in the Ko...

The use of Pseudoinvariant Areas (PIA) makes it possible to carry out a reasonably robust and automatic radiometric correction for long time series of remote sensing imagery, as shown in previous studies for large data sets of Landsat MSS, TM, and ETM+ imagery. In addition, they can be employed to obtain more coherence among remote sensing data from different sensors. The present work validates...

Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the Landsat satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, trom planting until harvest. With an atmospheric path radiance model and Landsat 2 calibration data, the reflectan...

Classifying remote sensing imageries to obtain reliable and accurate land use and land cover (LULC) information still remains a challenge that depends on many factors such as complexity of landscape, the remote sensing data selected, image processing and classification methods, etc. The aim of this paper is to extract reliable LULC information from Landsat imageries of the Lower Hunter region o...

Classification-based applications of remotely sensed data have increased significantly over the years. Very often, these data are gathered from different sources and in different formats causing the classification process to be scenespecific. Alternatively, spectral band indices have been developed to emphasize some elements based on spectral characteristics and therefore improving the final cl...

This paper presents an approach in extracting multi-temporal land-cover information (years 1976-2001) from cloud-contaminated remotely-sensed images acquired by the Landsat Multi-Spectral Scanner (MSS) and Enhanced Thematic Mapper plus (ETM+) sensors in order to detect and analyze deforestation and other types of land-cover change (LCC) in two forest resource-rich provinces of Agusan del Norte ...

SKYLAB and LANDSAT MSS data were analyzed using computer-aided analysis techniques (CAAT) developed at LARS. Results indicated that the middle infrared wavelength bands of the SKYLAB S-192 scanner would allow effective discrimination between snowcover and water-droplet clouds, whereas the limited spectral response of the LANDSAT-1 or 2 scanners do not allow such spectral discrimination. In the ...

The tropical rain forests in Indonesia are affected by socio-economic and ecological factors and processes that result in an increasing destabilisation of the rainforest margins. Optical satellite data have been explored to document changes in land cover throughout the past 30 years and to monitor the current status and dynamics of land cover and land cover conversion for an investigation area ...