Predicting of cattle density and location at the frontier of Brazil and Paraguay using remote sensing

Amaral Thais Basso, Gond Valéry, Tran Annelise. 2014. Predicting of cattle density and location at the frontier of Brazil and Paraguay using remote sensing. In : Proceedings of the XV Brazilian Symposium on Geoinformatics (GeoInfo 2014), November 30 to December 3, 2014, Campos do Jordao, Brazil. Clocoveu A. Davis Jr., Karine Reis Ferreira (eds.). Sao José dos Campos : MC TI/INPE, 61-73. Brazilian Symposium on GeoInformatics. 15, Campos do Jordão, Brésil, 30 Novembre 2014/3 Décembre 2014.

Url - autre : https://ainfo.cnptia.embrapa.br/digital/bitstream/item/118832/1/Paper11-F-p12.pdf

Résumé : In this paper, we explore the potential of remote sensing to map pastures areas and by this way establish models for predicting cattle density and location. First, an object based classification (OB) was made in Landsat 5 images for three different municipalities to provide a land-cover map. Second, on the basis of Brazilian official livestock database, a statistical model to predict number of cattle in function of declared pasture area by the farmers was produced. Finally, this model was applied to the pasture areas detected by remote sensing to predict cattle density. Coefficient of determination of the model was 0.63. The results indicate that the methodology used for estimating cattle density has a potential to be applied in regions where no information about farm location and cattle density exists.

Classification Agris : L01 - Élevage - Considérations générales
U30 - Méthodes de recherche

Auteurs et affiliations

• Amaral Thais Basso, EMBRAPA (BRA)
• Gond Valéry, CIRAD-ES-UPR BSef (FRA) ORCID: 0000-0002-0080-3140
• Tran Annelise, CIRAD-ES-UPR AGIRs (FRA) ORCID: 0000-0001-5463-332X

Source : Cirad - Agritrop (https://agritrop.cirad.fr/574472/)

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