Final project and presentation Basic Mapping: Applications and Analysis Lehman College - Spring 2014 Elia Machado, Ph.D. Mapping invasive species with remote sensing and GIS Oliver C. Smith 13 May 2014 1 Ash leaves. From: The Guardian 2012. Photo: www.alamy.com
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Final project and presentationBasic Mapping: Applications and Analysis
Lehman College - Spring 2014Elia Machado, Ph.D.
Mapping invasive species with remote sensing and GIS
Oliver C. Smith13 May 2014
1
Ash leaves. From: The Guardian 2012. Photo: www.alamy.com
4.3 ResultsScanned region A:High ash density and prolonged EAB infestation.
Scanned region B:High ash density and no known EAB infestation.
Scanned region C:High ash density, some decline but no EAB reports.
Maybe this region is EAB infested!
3.9
8
2.1
Oliver C. Smith for GEP 204/504 2014
4.9Declineaverage
Declineaverage
Declineaverage
Fig. 5. Decline averages. (Pontius et. al, 2008)
4.4 Conclusions“The combination of traditional plot-level forest health assessment techniques with commercially available hyperspectral remote sensing imagery can produce accurate, detailed, large-scale maps of forest health.”
Oliver C. Smith for GEP 204/504 20149
(Pontius et al., 2008)
5.0 Case study #2
Oliver C. Smith for GEP 204/504 201410
TitleModeling local and long-distance dispersal of invasive emerald ash borer in North America (Muirhead, Leung, Overdijk, Kelly, Nandakumar, Marchant, & MacIsaac, 2006)
ObjectiveValidate models for predicting EAB dispersal.
MethodsTwo models are tested:
A. Short-range dispersal by flight.1
B. Long-range dispersal via human activity.
1Predicted areas of short-range dispersal mapped with ARCGIS and Albers-Equal Areas Conic projection to maintain shape/distance between infested areas.
5.1 Short-range dispersal by flight
Oliver C. Smith for GEP 204/504 201411
Epicenter
2002
2003
2004
2005
2004infestedDispersal
prediction
Fig. 6. Short-range dispersal 2002-2005. (Muirhead et al., 2006)
2005infested
2002infested
2003infested
Oliver C. Smith for GEP 204/504 201412
Epicenter
Infestedarea
Proximity to human population centers and epicenter as factors influencing probability of infestation
5.2 Long-range dispersal via human activityHigh
Low
Fig. 7. Probability of infestation. (Muirhead, 2006)
Infestedarea
Results:
Probability of infestation:•Decreases with distance from epicenter.•Increases near human population centers.•Model is accurate to 97.5%.
Table 1. Validating proximity to human population and distance from epicenter as factors influencing probability of infestation. (Muirhead, 2006)
populationcenters???
5.3 Conclusions
Oliver C. Smith for GEP 204/504 201413
•EAB has spread in North America through short-range flights and by long-range dispersal linked to human activity.
•Probability of infestation decreases with distance from epicenters, but increases in proximity to human population centers. (Muirhead et al., 2006)
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