What is it about?
While forest statistics are currently released at NUTS-1 (macro-regions) or NUTS-2 (administrative regions) levels, advancements in remote sensing technology may improve their accuracy at smaller spatial units. To explore the potential contribution of remote sensing in downscaling forest cover rates to finer administrative levels, we run a quantitative analysis of the statistical relationship between selected indicators of forest cover derived from 16 independent (wall-to-wall) map-sources and 4 probabilistic sampling surveys (land cover/forest inventories) with the aim at verifying the consistency of their statistical distribution at the regional scale in Italy
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Why is it important?
The empirical results indicate that, given current technological capabilities and the standard land cover classifications used in each survey, only a limited number of map-based (local-scale) sources align with official sampling sources provided at large (regional) scale.
Perspectives
Forest cover rates derived from map sources can serve as valuable ancillary variables in spatial downscaling procedures of official (sample-based) forest estimates provided at a large scale, thus representing a reliable source of information for the routine production of official statistics at the level of small-area administrative units.
Piermaria Corona
University of Tuscia, Viterbo (Italy)
Read the Original
This page is a summary of: Deriving forest cover rates from map sources: A contribution to official statistics and environmental reporting, Environmental Impact Assessment Review, July 2025, Elsevier,
DOI: 10.1016/j.eiar.2025.107920.
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