title: Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification.
abstract: The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential.
authors.affiliation: University of Bayreuth, Faculty of Biology, Chemistry and Earth Sciences, Professorship of Ecological Services, Universitätsstraße 30, 95440 Bayreuth, Germany.
authors.forename: Yohannes
authors.initials: Y
authors.lastname: Ayanu
authors.affiliation: University of Wuerzburg, Department of Geography, Remote Sensing Unit, Am Hubland, 97074 Wuerzburg, Germany.
authors.forename: Christopher
authors.initials: C
authors.lastname: Conrad
authors.affiliation: University of Bayreuth, Faculty of Biology, Chemistry and Earth Sciences, Professorship of Disturbance Ecology, Universitätsstraße 30, 95440 Bayreuth, Germany.
authors.forename: Anke
authors.initials: A
authors.lastname: Jentsch
authors.affiliation: University of Bayreuth, Faculty of Biology, Chemistry and Earth Sciences, Professorship of Ecological Services, Universitätsstraße 30, 95440 Bayreuth, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Koellner
mesh_terms: D000383:Agriculture; D003247:Conservation of Natural Resources / Q000379:methods; D018556:Crops, Agricultural / Q000254:growth & development*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D005002:Ethiopia; D005502:Food; D005523:Food Supply; D065928:Forests; D040362:Geographic Information Systems; D058998:Remote Sensing Technology / Q000379:methods*; D063809:Satellite Imagery / Q000379:methods*