Spatial and temporal analysis of MODIS and AVHRR images have been carried out to discriminate burned areas from other land covers. Spatial and temporal analysis were performed based on statistical separability and temporal changes. The objective of these analysis was to find out the most sensitive bands for burned land mapping in order to design spectral indices better adapted to the discrimina...

Automatic registration is one of the key technologies for remote sensing image processing.Considering the influence of cloud points, the phenomenon of uneven distributed control points and other problems in the process of registration for the widely used AVHRR remote sensing images, an automatic registration method for AVHRR remote sensing images is proposed. In this method, the cloud points ar...

This research explores the possibility of using linear mixture model to generate fraction images from 1km time series NOAA AVHRR monthly composite NDVI data. The percentages of forest, grassland and farmland in the pixels are determined by applying the Constrained Least Squares (CLS) method over the study area in the northeast region of China. The validation of the model for AVHRR monthly compo...

A technique has been developed to detect and map fire growth by using a multitemporal multispectral analysis of AVHRR images. The application of this technique allows fire growth nwnitoring. The technique is mainly based on comparison of brightness temperature differences and AVHRR Channels 3 and 4 for successive images. It provides a rapid evaluation of the area affected by the fire but suppre...

This paper presents a comparison of tropical deforestation estimates in AVHRR/NOAA and TM/Landsat images for a region in Central Brazil where large clearings in the forest prevail. A TM scene of 02/Sept/89 in the scale of 1:250,000 was visually interpreted to produce a map with four classes: natural forests, deforested areas, natural savannahs, and rivers. The AVHRR image of 17/Sept/89 with ful...

Comparing satellite data derived map products are affected by differences in data characteristics, image acquisition dates, processing techniques, and classification schemes used for assigning pixels to a thematic class. By comparing two forest maps generated from Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Very High Resolution Radiometer (AVHRR) images acquired on the same day, a...

In this study, satellite-based remote sensing techniques were developed for identifying smoke from forest fires. Both artificial neural networks (NN) and multithreshold techniques were explored for application with imagery from the Advanced Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. The NN was designed such that it does not only classify a scene into smoke, cloud, or clear ...

SomeAVHRR® re detection studies have excluded pixels that exceeded an arbitrary scan angle. This exclusion seems to be based on the distortion of pixels at high scan angles and the well-documented e€ ects of scan angle on the Normalized Di€ erence Vegetation Index. However, excluding high scan angle pixels reduces the temporal resolution of an AVHRR ® re detection system, especially at high lat...

Recent progress in canopy bidirectional reflectance distribution function (BRDF) model inversions has allowed accurate estimates of vegetation biophysical characteristics from remotely sensed multi-angle optical data. Since most current BRDF inversion methods utilize one-dimensional (1-D) models, surface homogeneity within an image pixel is implied. The Advanced Very High Resolution Radiometer ...