Geoscience Reference
In-Depth Information
3.1.3
Lessons Learned from IGPB DISCover
The IGBP DISCover LC dataset, produced from 1.1-km spatial resolution AVHRR data by
Loveland et al. (2000), remains a milestone in global LC classification using satellite data. The
validation process used incorporated a global random sample stratified by cover type. Selected
pixels were examined at high spatial resolution using Landsat and SPOT data in a design that
featured multiple photographic interpreters classifying each pixel. Although not without difficul-
ties, the validation process was very successful, yielding the first global validation of a global
thematic map.
Recent research by Estes et al. (1999) summarized the lessons learned in the IGBP DISCover
validation effort that apply to current and future global LC validation efforts. A primary conclusion
was that the information of coarse-resolution satellite datasets is limited by such factors as multidate
registration, atmospheric correction, and directional viewing effects. These limits in turn impose
limits on the accuracies achievable in any global classification scenario. It should be noted that
coarse-resolution satellite imaging instruments continue to produce data of improved quality. For
example, data from MODIS that are used to develop LC products include nadir-looking surface
reflectances that are obtained at multiple spatial resolutions (250, 500, and 1000 m).
Second, LC products developed using the spectral and temporal information available from
coarse-resolution satellite imagers will always be an imperfect process, given the high intrinsic
variance found in the global range (variability) of cover types. While the natural variation within
many cover types is large, new instruments may yield new data streams that increase the certainty
of identifying them uniquely. Among these are measures of vegetation structure derived from multi-
angular observations, measures of spatial variance obtained from finer-resolution channels, and
ancillary datasets such as land surface temperature.
A third lesson concerns the quality and availability of fine-resolution imagery for use in
validation. Not only were Landsat and SPOT images costly, they were also very scarce for some
large and ecologically important regions, such as Siberian conifer forest. However, the present
Landsat 7 acquisition policy, which includes acquiring at least four relatively cloud-free scenes per
year for every path and row, coupled with major price decreases, has eased this problem significantly
for future validation efforts. However, the recent degradation of Enhanced Thematic Mapper Plus
(ETM
) capabilities may significantly reduce future data acquisition capabilities.
A fourth lesson documented that interpreter skill and the quality of ancillary data are major
factors that significantly affect assessment results. Best results were obtained using local interpreters
who were familiar with the region of interest. The most important observation was that proper
validation was an essential component of the mapping process and required a significant amount
of the total effort. Roughly one third of the mapping resources were expended equally to each of
the following: (1) data assembly, (2) data classification, and (3) quality and accuracy assessment
of the result. Supporting agencies need to understand that a map classification is not completed
until it is properly validated.
+
3.2 VALIDATION OF THE EUROPEAN COMMISSION'S GLOBAL
LAND-COVER 2000
The general objective of the European Commission's Global Land Cover (GLC) 2000 was to
provide a harmonized global LC database. The year 2000 was considered a reference year for envi-
ronmental assessment in relation to various activities, and in particular the United Nation's Ecosystem-
related International Conventions. To achieve this objective GLC 2000 made use of the
VEGA 2000
dataset: a dataset of 14 months of preprocessed daily global data acquired by the VEGETATION
instrument aboard SPOT 4. These data were made available through a sponsorship from members of
the VEGETATION program (http://www.gvm.sai.jrc.it/glc2000/defaultGLC2000.htm).
