title: Stratifying land use/land cover for spatial analysis of disease ecology and risk: an example using object-based classification techniques.
abstract: Landscape epidemiology has made significant strides recently, driven in part by increasing availability of land cover data derived from remotely-sensed imagery. Using an example from a study of land cover effects on hantavirus dynamics at an Atlantic Forest site in eastern Paraguay, we demonstrate how automated classification methods can be used to stratify remotely-sensed land cover for studies of infectious disease dynamics. For this application, it was necessary to develop a scheme that could yield both land cover and land use data from the same classification. Hypothesizing that automated discrimination between classes would be more accurate using an object-based method compared to a per-pixel method, we used a single Landsat Enhanced Thematic Mapper+ (ETM+) image to classify land cover into eight classes using both per-pixel and object-based classification algorithms. Our results show that the object-based method achieves 84% overall accuracy, compared to only 43% using the per-pixel method. Producer's and user's accuracies for the object-based map were higher for every class compared to the per-pixel classification. The Kappa statistic was also significantly higher for the object-based classification. These results show the importance of using image information from domains beyond the spectral domain, and also illustrate the importance of object-based techniques for remote sensing applications in epidemiological studies.
authors.affiliation: Department of Geography, Kansas State University, Manhattan, KS 66506-2904, USA.
authors.forename: David E
authors.initials: DE
authors.lastname: Koch
authors.forename: Rhett L
authors.initials: RL
authors.lastname: Mohler
authors.forename: Douglas G
authors.initials: DG
authors.lastname: Goodin
mesh_terms: D000383:Agriculture / Q000145:classification*; D000818:Animals; D003141:Communicable Diseases; D004463:Ecology; D017753:Ecosystem; D006476:Orthohantavirus; D018778:Hantavirus Infections / Q000453:epidemiology / Q000469:parasitology*; D010239:Paraguay / Q000453:epidemiology; D010781:Photography; D018570:Risk Assessment; D018531:Spacecraft