Paper Info
Title
Object Based Image Analysis (OBIA) and Data Mining (DM) in Landsat time series for mapping soybean in intensive agricultural regions.
Abstract
Soya is a widely grown crop in many countries worldwide, being United States, Brazil, Argentina and China the major producers. In Brazil, in the last three decades an explosive growth in production has occurred, nearly thirty times, causing a chain of unprecedent changes of land uses and land cover (LULC) in the territory. Therefore, it becomes highly necessary to develop means to monitor such LULC changes, and remote sensing is one of the more potential tools for this monitoring. Thus, the aim of this research was to develop a methodology for contributing in the mapping and monitoring soybeans planted areas, with time-series of remotely sensed Landsat imagery. Two main techniques were combined: Object Based Image Analysis (OBIA) and Data Mining (DM). OBIA was used to represent the knowledge needed to map soybeans areas, and DM was applied to generate the knowledge model. The study area comprises three municipalities in the northwest of Sao Paulo State, being this area well representative of the agricultural conditions of the Southern and Southeastern regions of Brazil. Classification accuracy was calculated over a set of 500 points not previously used during the training stage. The statistics indicated an overall accuracy of 95% and a kappa coefficient of 0.88. These results indicate that the combination of OBIA + DM + multitemporal imagery is very efficient and promising for the soybeans mapping process.
Year
DOI
Venue
2012
10.1109/IGARSS.2012.6351047
IGARSS
Keywords
Field
DocType
crops,data mining,geophysical image processing,image classification,vegetation mapping,Argentina,China,LULC change monitoring,Landsat time series,Southeastern Brazil,Southern Brazil,United States,classification accuracy,crop,data mining,intensive agricultural regions,knowledge model,land cover,land uses,multitemporal imagery,northwest Sao Paulo state,object based image analysis,soya,soybean mapping,Data Mining (DM),Object Based Image Analysis (OBIA),Soybean,agriculture,remote sensing
Data mining,Computer science,Remote sensing,Cohen's kappa,Agriculture,Contextual image classification,Land cover,Land use
Conference
ISSN
Citations 
PageRank 
2153-6996
5
0.58
References 
Authors
1
3
Name
Order
Citations
PageRank
Antônio Roberto Formaggio1243.72
Matheus A. Vieira260.95
Camilo Daleles Rennó3175.08