A Web Platform Development to Perform Thematic Accuracy Assessment of Sugarcane Mapping in South-Central Brazil

Remote Sensing

Marcos Adami¹  Marcio Pupin Mello²  Daniel Alves Aguiar²  Bernardo Friedrich Theodor Rudorff² 

[1] Remote Sensing Division (DSR), National Institute for Space Research (INPE), Av. dos Astronautas, 1758, São Josédos Campos-SP, 12227-010, Brazil;

关键词: Canasat Project;    stratified random sampling;    classification;    remote sensing;   

DOI  :  10.3390/rs4103201

来源: mdpi

【 摘 要 】

The ability to monitor sugarcane expansion in Brazil, the world’s largest producer and exporter of sugar and second largest producer of ethanol, is important due to its agricultural, economic, strategic and environmental relevance. With the advent of flex fuel cars in 2003 the sugarcane area almost doubled over the last decade in the South-Central region of Brazil. Using remote sensing images, the sugarcane cultivation area was annually monitored and mapped between 2003 and 2012, a period of major sugarcane expansion. The objective of this work was to assess the thematic mapping accuracy of sugarcane, in the crop year 2010/2011, with the novel approach of developing a web platform that integrates different spatial and temporal image resolutions to assist interpreters in classifying a large number of points selected by stratified random sampling. A field campaign confirmed the suitability of the web platform to generate the reference data set. An overall accuracy of 98% with an area estimation error of −0.5% was achieved for the sugarcane map of 2010/11. The accuracy assessment indicated that the map is of excellent quality, offering very accurate sugarcane area estimation for the purpose of agricultural statistics. Moreover, the web platform showed to be very effective in the construction of the reference dataset.

【 授权许可】

CC BY   
© 2012 by the authors, licensee MDPI, Basel, Switzerland.