SPOT VEGETATION Data Research Articles

Mapping ecological conditions in the Okavango delta, Botswana using fine and coarse resolution systems including simulated SPOT vegetation imagery

Aspects of wetland monitoring in southern Africa are significant in the light of the Ramsar Convention, which has recently been signed by Botswana. The present work initially indicated that most ecological units in the Okavango delta can be identified and mapped using fine resolution satellite imagery and aerial photography. A second step involved assessing which of these units could also be identified using coarse resolution imagery. Contrasting results were obtained from a relatively high quality solid state sensor system (simulated SPOT 4-VEGETATION) and a relatively low quality system (NOAA-AVHRR). The extent of the water surface in the flooded areas could not be accurately mapped using NOAA-AVHRR data because of pixel saturation effects. However the presence of water was generally located using AVHRR data. The ecologically significant riparian woodlands were found to saturate pixel response on Thematic Mapper (TM) imagery. As a result of detailed comparisons, it was found that simulated SPOT VEGETATION data could be used for mapping and monitoring major changes in grassed floodplains and wooded peripheral drylands which are not spectrally separable using NOAA-AVHRR data. Most ecological change in the Okavango delta which involves such small-scale transformations as thicket development (shrub growth) and minor land-use changes related to tourism, requires the use of finer resolution systems for instance high resolution false colour aerial photography in conjunction with fieldwork. In terms of overall needs for mapping and monitoring wetland conditions in semi-arid areas it appears that major changes in flood extent and related floodplain drying vegetation changes are best detected accurately using fine resolution (TM) satellite data. Large-scale ecological changes can be semi-quantified using high quality imagery data at coarse resolutions similar to SPOT VEGETATION data.

Thematic mapper (TM) based accuracy assessment of a land cover product for Canada derived from SPOT VEGETATION (VGT) data

This paper addresses the accuracy assessment of land cover products derived from coarse-resolution data. The specific product being evaluated covers the landmass of Canada and was derived from the Satellite pour l'observation de la terre 4 SPOT-4 VEGETATION (VGT) data for 1998. A set of representative Landsat frames was identified using a selection algorithm. Recent growing season thematic mapper (TM) (or enhanced thematic mapper plus, ETM+) scenes were digitally classified and precisely registered to the VGT map, and confusion matrixes were produced. The paper addresses methodological issues concerned with geometric and thematic correspondence between the two data sets, the VGT class accuracies, and factors affecting these. It was found that depending on the number of thematic classes (35 to 9) and VGT pixel homogeneity, the agreement between VGT and TM classifications ranged from 20 to 70%. These results are consistent with earlier assessments of similar products using high-resolution land cover maps. Using a TM data set representing ~8% of the total area, the VGT and TM classifications overestimated the extent of forests by 7.2% (35 classes) and 5.9% (12 classes), respectively. It is shown that the main obstacle to achieving high accuracies of land cover products derived from coarse-resolution satellite data is the heterogeneous land cover at subpixel resolution. The effects of within-pixel land cover heterogeneity, labelling errors, and geographic variations are discussed.

A new SPOT4-VEGETATION derived land cover map of Northern Eurasia

The European Commission's Joint Research Centre and the Russian Academy of Science's Centre for Forest Ecology and Productivity have produced a new 1 km spatial resolution land cover map of Eurasia from 1999 SPOT4-VEGETATION data. The legend is designed to serve users from science programmes, policy makers, environmental convention secretariats, non-governmental organizations, development-aid projects and the national forest service. The 1999 map is also being updated as part of an international exercise to map Global Land Cover for the year 2000. This Letter describes the map legend, the image classification method, the map accuracy assessment process and presents the land cover map.

Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications

The Global Vegetation Moisture Index (GVMI) was developed to retrieve vegetation water content from local to global scale rapidly and reliably using SPOT-VEGETATION data. This paper validates the GVMI with field measurements of vegetation water content measured over four different ecosystems in Senegal. Two of the sites show exact concordance between GVMI-derived and field-measured water content. The remaining two sites show differences in value but provide identical evolution over time. Comparison between ecosystems illustrates that GVMI-derived water content is consistent with field measurements of water content expressed as a quantity of water per unit area. Additional study shows that GVMI is not related to the vegetation moisture content expressed as a percentage of water per quantity of biomass. Comparison between the GVMI and NDVI methods also illustrates that the NDVI provides different information (vegetation greenness), which is not directly related to the quantity of water in the vegetation. Potential applications of the new GVMI are also discussed.

Fraction images derived from SPOT-4 VEGETATION data to assess land-cover change over the State of Mato Grosso, Brazil

(2002). Fraction images derived from SPOT-4 VEGETATION data to assess land-cover change over the State of Mato Grosso, Brazil. International Journal of Remote Sensing: Vol. 23, No. 23, pp. 4979-4983.

Monitoring land-cover changes in West Africa with SPOT Vegetation: impact of natural disasters in 1998-1999

A multi-temporal change-vector algorithm has been applied to SPOT Vegetation data of West Africa over two growing seasons. Change maps displaying the impact on surface attributes of natural disasters such as floods and droughts were produced, based on different vegetation indices and compositing periods. The accuracy assessed on the basis of independent data on natural disasters, was high (76% correct for the NDVI-based map). This land-cover change product provides important information to evaluate the spatial and temporal distribution of rapid changes in land surface attributes.

Monitoring land-cover changes in West Africa with SPOT Vegetation: Impact of natural disasters in 1998-1999

A multi-temporal change-vector algorithm has been applied to SPOT Vegetation data of West Africa over two growing seasons. Change maps displaying the impact on surface attributes of natural disasters such as floods and droughts were produced, based on different vegetation indices and compositing periods. The accuracy assessed on the basis of independent data on natural disasters, was high (76% correct for the NDVI-based map). This land-cover change product provides important information to evaluate the spatial and temporal distribution of rapid changes in land surface attributes.

A near-real time forest-cover map of Madagascar derived from SPOT-4 VEGETATION data

Using SPOT-4 VEGETATION data for near-real time mapping is new. In this Letter, a robust technique for cloud decontamination of the ten-day composites is presented. A forest-cover map of Madagascar is derived from monthly images from October 1998 to September 1999 with a user's accuracy of 87.8%.

The potential of SPOT-Vegetation data for fire scar detection in boreal forests

Boreal forests cover 10% of the land surface and experience wide ranges of temperature and precipitation. In many parts of the boreal zone, fire drives vegetation succession, landscape dynamics and carbon cycling. Global climate change may affect the frequency and size of wildfires and alter the rate of carbon release into the atmosphere. Monitoring changes in fire frequency are therefore vital for forest management and predicting climate change impacts. The continuity of remotely sensed data, combined with the extent and remoteness of the boreal ecosystem make Earth observation an important tool for fire monitoring. This Letter examines the applicability of data from SPOT-Vegetation for regional fire monitoring in the context of other available Earth observation instruments. We show that use of the middle-infrared waveband gives a more reliable indication of fire scars than vegetation index approaches currently employed.