Accuracy assessment methodology for the Mexican national forest inventory: A pilot study in the Cuitzeo lake watershed
Por:
Couturier S., Mas J.-F., López E., Cuevas G., Vega A., Tapia V.
Publicada:
1 ene 2006
Resumen:
A methodology for assessing the accuracy of the Mexican National Forest Inventory (NFI) map is presented. This methodology emerges as the most adequate strategy found after various trials along the successive steps of the assessment design. A main challenge was to integrate the high diversity of classes encompassed in the classification scheme within a cost-controlled statistically sound assessment. A pilot study focused on the Cuitzeo Lake watershed region covering 400, 000 ha of the 2000 Landsat-derived NFI. The availability of detailed quasisynchronous reference data and the high variability of mapped classes allowed a careful thematic analysis on the selected region, relevant for national extrapolation. The assessment strategy incorporated an original two stage sampling design. The selection of Primary Sampling Units (PSU) was done under separate schemes for commonly and scarcely distributed classes. A compromise was statistically found for maximizing PSU spatial distribution while including all classes. The verification protocol included stereoscopic photointerpretation and a digital restitution towards the geometry of the Landsat data. A scale adjustment operator, based on the epsilon probabilistic band approach, was applied to the PSU verification maplets in order to reduce the inclusion of errors due to scale. A total of 2023 punctual secondary sampling units were then compared with their NFI map label, according to conventional Boolean and linguistic fuzzy criteria. Issues regarding the assessment strategy and trends of class confusions are devised. Conclusions are drawn in terms of separability of classes on remote-sensing supports, classification system, geographic stratification and scale. This methodology is to be applied to a larger territory including a wider set of classes in the classification system.
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