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Könyv Improving GIS-based Wildlife-Habitat Analysis Jeffrey K. Keller

Improving GIS-based Wildlife-Habitat Analysis

Szerző: Jeffrey K. Keller, Charles R. Smith
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer International Publishing AG
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
19 771 Ft
Geographic Information Systems (GIS) provide a powerful tool for the investigation of species-habita...

Információk a könyvről

Szerző
Jeffrey K. Keller, Charles R. Smith
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2014
oldal
132
EAN
9783319096070
ISBN
3319096079
Enbook ID
05038032
Kiadó
Springer International Publishing AG
Súly
236
Méretek
154 x 236 x 9

Teljes leírás

Geographic Information Systems (GIS) provide a powerful tool for the investigation of species-habitat relationships and the development of wildlife management and conservation programs. However, the relative ease of data manipulation and analysis using GIS, associated landscape metrics packages, and sophisticated statistical tests may sometimes cause investigators to overlook important species-habitat functional relationships. Additionally, underlying assumptions of the study design or technology may have unrecognized consequences. This volume examines how initial researcher choices of image resolution, scale(s) of analysis, response and explanatory variables, and location and area of samples can influence analysis results, interpretation, predictive capability, and study-derived management prescriptions. Overall, most studies in this realm employ relatively low resolution imagery that allows neither identification nor accurate classification of habitat components. Additionally, the landscape metrics typically employed do not adequately quantify component spatial arrangement associated with species occupation. To address this latter issue, the authors introduce two novel landscape metrics that measure the functional size and location in the landscape of taxon-specific solid and edge habitat types. Keller and Smith conclude that investigators conducting GIS-based analyses of species-habitat relationships should more carefully 1) match the resolution of remotely sensed imagery to the scale of habitat functional relationships of the focal taxon, 2) identify attributes (explanatory variables) of habitat architecture, size, configuration, quality, and context that reflect the way the focal taxon uses the subset of the landscape it occupies, and 3) match the location and scale of habitat samples, whether GIS- or ground-based, to corresponding species detection locations and scales of habitat use.

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