Key points are not available for this paper at this time.
Abstract This paper reviews and illustrates the advantages of the use of NOAA‐AVHRR data for vegetation mapping and monitoring in the Amazon Basin. The data are considered under two main categories: data of low spatial but high temporal resolution and long time period availability, and data of a higher spatial resolution but more limited temporal availability. A review of the use of the former type of data reveals that this has been relatively successful in generalised classifications of broad land cover categories in the Amazon Basin. However these generalised classifications have in the past attempted to replicate as closely as possible, broad classes represented on continental or global scale maps. By doing so they have overlooked the important inter‐ and intra‐annual information on vegetation vigour and seasonality within Amazon forest areas that may be discerned with careful analysis of the data. The widespread use of the full spatial resolution NOAA‐AVHRR imagery for large scale deforestation mapping and monitoring is also reviewed. This shows that while most deforestation was successfully detected on the imagery, the resolution of the sensor hindered the accurate measurement of deforestation areas and rates, especially where the pattern of deforestation was complex. Finally, the potential operational use of NOAA‐AVHRR data in an automated deforestation mapping system is presented. It is suggested that full spatial resolution NOAA‐AVHRR data can provide a suitable base for an automated deforestation mapping system, especially when combined with information derived from higher spatial resolution imagery to adjust for forest/non‐forest interface patterns and with data of low spatial but high temporal resolution to adjust for forest seasonality variations.
D’Souza et al. (1994) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: