There is a critical need to locate innovative forest management institutions that significantly impact forest cover change. This research presents an initial “proof of concept” methodology which combines deforestation theory with satellite image change analysis to identify forested areas that, theoretically, should probably not be there. Ten such “forest anomalies” are identified using temporal analysis of Landsat TM imagery of the Chitwan district in Nepal, linked with a GIS database on roads and a visual estimation of topography. A rapid field reconnaissance is undertaken to determine which of these anomalies exhibit interesting forest management innovations. Based on this information, one case is selected for detailed field study: this turns out to be a major case of community forestry and a premier ecotourism initiative that we were not aware of until we undertook this analysis. The utility and limitations of the method are described for monitoring trends in forest cover change.
You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither BioOne nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the BioOne website.