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| Hott,Marcos Cicarini; Carvalho,Luis Marcelo Tavares de; Antunes,Mauro Antonio Homem; Santos,Polyanne Aguiar dos; Arantes,Tássia Borges; Resende,João Cesar de; Rocha,Wadson Sebastião Duarte da. |
| Abstract: The objective of this work was to analyze the development of grasslands in Zona da Mata, in the state of Minas Gerais, Brazil, between 2000 and 2013, using a parameter based on the growth index of the normalized difference vegetation index (NDVI) from the moderate resolution imaging spectroradiometer (Modis) data series. Based on temporal NDVI profiles, which were used as indicators of edaphoclimatic conditions, the growth index (GI) was estimated for 16-day periods throughout the spring season of 2012 to early 2013, being compared with the average GI from 2000 to 2011, used as the reference period. Currently, the grassland areas in Zona da Mata occupy approximately 1.2 million hectares. According to the used methods, 177,322 ha (14.61%) of these... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Growth index; Pastures; Remote sensing; Time series; Zona da Mata.. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2016000700858 |
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| Souza,Carolina Gusmão; Arantes,Tássia Borges; Carvalho,Luis Marcelo Tavares de; Aguiar,Polyanne. |
| Abstract: The objective of this work was to propose a new methodology for mapping coffee cropping areas that includes multitemporal data as input parameters in the classification process, by using the Landsat TM NDVI time series, together with an object-oriented classification approach. The algorithm BFAST was used to analyze coffee, pasture, and native vegetation temporal profiles, allied to a geographic object-based image analysis (GEOBIA) for mapping. The following multitemporal variables derived from the R package greenbrown were used for classification: mean, trend, and seasonality. The results showed that coffee, pasture, and native vegetation have different temporal behaviors, which corroborates the use of these data as input variables for mapping.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: BFAST; Classification; MODIS; NDVI; Remote sensing; R package greenbrown. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103701 |
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