DocumentCode :
3071567
Title :
Spatial statistic to assess remote sensing acreage estimates: An analysis of sugarcane in São Paulo State, Brazil
Author :
Pupin Mello, Marcio ; Alves Aguiar, Daniel ; Rudorff, Bernardo Friedrich Theodor ; Pebesma, Edzer ; Jones, John ; Pontes Santos, Naiara Carolina
Author_Institution :
Nat. Inst. for Space Res. - INPE, São José dos Campos, Brazil
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
4233
Lastpage :
4236
Abstract :
After the launching of the Landsat-5/TM in the 1980´s, remote sensing based methods appeared as an alternative to obtain agricultural statistics. Using the case study of sugarcane acreage in São Paulo State, this paper compares, at a municipal scale, the differences between the remote sensing based (Canasat Project) and the official (Brazilian Institute of Geography and Statistics - IBGE) estimates of relative sugarcane acreage in 2010. This evaluation was carried out through graphical and spatial statistical analyses. Despite individual divergences, results indicated that on average Canasat and IBGE are in agreement. Moreover, large differences were rarely observed for municipalities with high sugarcane production. The remote sensing based method seems to be of great potential for agricultural statistics as it tends to maintain the consistence of current official agricultural statistics with the benefit of further improving estimates. The spatial statistical analyses showed to be effective to assess remote sensing based acreage estimates.
Keywords :
agriculture; crops; statistical analysis; vegetation mapping; AD 2010; Brazilian Institute of Geography and Statistics; Canasat Project; IBGE; Landsat-5 TM; Sao Paulo State; agricultural statistics; graphical statistical analysis; remote sensing acreage estimate assessment; remote sensing based method; spatial statistical analysis; sugarcane acreage; sugarcane analysis; sugarcane production; Accuracy; Correlation; Monitoring; Production; Remote sensing; Satellites; Statistical analysis; Canasat Project; IBGE; accuracy; agricultural statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
ISSN :
2153-6996
Print_ISBN :
978-1-4799-1114-1
Type :
conf
DOI :
10.1109/IGARSS.2013.6723768
Filename :
6723768
Link To Document :
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