SciELO - Scientific Electronic Library Online

 
vol.18 número2¿Medir el pH del suelo en la mezcla suelo: agua en reposo o agitando?Incidencia de la intensidad de lluvia en el tiempo de concentración de microcuencas del Uruguay índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Links relacionados

Compartilhar


Agrociencia (Uruguay)

versão impressa ISSN 1510-0839versão On-line ISSN 2301-1548

Resumo

BAEZA, Santiago et al. Land Use/Land Cover Classification in Uruguay Using Time Series of MODIS Images. Agrociencia Uruguay [online]. 2014, vol.18, n.2, pp.95-105. ISSN 1510-0839.

The spatial distribution of land use/land cover is the main control of energy, carbon and water dynamics; is also extremely important in environmental monitoring and decision-making in the agricultural sector. The objective of this work was to develop rapid and low cost land use/land cover classifications in Uruguay. We performed decision tree classifications using phenological information derived of NDVI-MODIS (Normal Difference Vegetation Index) time series (period: May 2011-March 2012), field data, and high spatial resolution images (Landsat) to identify «pure» agricultural lots (belonging to a single land use /land cover class). 1.7x107 hectares were classified, discriminating four major categories: Perennial Forage Resources, Afforestation and Forest, Summer Crops, and Winter-Summer Crops; they occupied respectively 63.6, 13.1, 14.3 and 7.4 % of the mapped area. Overall map accuracy was high (89.6 %) and the less accurate class was summer crops (85.8 %). This classification is one of the first descriptions of land use/land cover for the entire Uruguayan territory with high levels of accuracy. The results show a very significant decrease in forage resources occurred in recent years mainly due to the advance of the agricultural frontier. The method used is a fast, repeatable, measurable and inexpensive alternative to describe land use/land cover over large areas and monitor its change over time.

Palavras-chave : </="font-weight: normal"VEGETATION PHENOLOGY; REMOTE SENSING; NDVI.

        · resumo em Espanhol     · texto em Espanhol     · Espanhol ( pdf )

 

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons