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Automatizing photo interpretation of satellite imagery in the context of the Common Agriculture Policy subsidy control
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Autores
Orientador(es)
Resumo(s)
Computer Assisted Photo-Interpretation (CAPI) uses remotely sensed imagery to control
farmers’ subsidy applications in the context of the EU’s Common Agriculture Policy. A simple
and reproducible method to automatize CAPI in an operational context with the overreaching
goal to reduce control costs and completion time was developed in this study. Validated control
data provided by the Portuguese Control and Paying Agency for Agriculture (IFAP) and a
multispectral atmospherically corrected Landsat ETM+ time series were used to calibrate and
test the method. Taking advantage of the nature of subsidy declarations, object-based land
cover classification for the 12 most controlled classes was carried out in the region of Ribatejo.
The main feature of the presented method is that it allows choosing a confidence level on the
automatic classification of farmers’ parcels. While higher confidence levels reduce the risk of
misclassifications, lower levels increase the number of automatic control decisions. A confidence
level of 80% is a good compromise. This confidence level leads to over 55% of automatically
taken control decisions with an overall accuracy of 84%. Furthermore, over 85% of all parcels
classified as maize, rice, wheat or vineyard can be controlled by the method with the optimal
confidence level.
Descrição
Mestrado em Engenharia do Ambiente - Instituto Superior de Agronomia
Palavras-chave
Common Agricultural Policy subsidy control Landsat multitemporal analysis operational crop discrimination parcel-based classification remote sensing
Contexto Educativo
Citação
Schmedtmann. J. - Automatizing photo interpretation of satellite imagery in the context of the Common Agriculture Policy subsidy control. Lisboa: ISA, 2014, 64 p.