Abstract
Predictive ecosite mapping involves developing computer models that consistently identify and map ecosystems. This method of predicting ecosystem occurrence on the landscape uses basic inventory information and expert knowledge, and is an effective integrated planning tool for providing a record of the location and spatial distribution of ecosystems within a management area. Fuzzy logic technology can be used to computerize essential elements of ecosystem identification, and the outputs can be linked to a Geographic Information System for map production. A pilot study was undertaken on the application of this technology to the Alberta Ecological Land Classification database and the resulting ecosite map for a township located in central Alberta (Tp42R9W5). The range of attributes used in the program was constrained by the attributes recorded on mapped polygons. Three maps with suitable attributes were available for the township studied: a Digitized Elevation Model map, an Alberta Vegetation Inventory map, and a reconnaissance soil survey map. Attributes of all polygons from all three maps were compiled and seven attributes (humus form, Ah thickness, surface texture, aspect, organic thickness, slope angle, and Alberta Vegetation Inventory moisture regime) were chosen to produce a computerized program for ecosite identification. Four sets of data were used to calibrate the program, as well as a small-plot data set collected from the township studied. The computer program was used to analyze the polygon data corresponding to two sets of data collected in the field and resulted in 72% and 70% similarity between the choices of experts and of the computer program. The quality of the original polygon attributes contributed to errors in identification. In addition, the reconnaissance soil survey map gave only an estimate of four attributes (Ah horizon thickness, organic thickness, humus form, and surface texture). Key words: ecosystem classification, site classification, fuzzy logic, fuzzy sets, predictive ecosystem mapping, predictive site mapping
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.