|
|||||
|
|
The use of local indicators of spatial association to improve LiDAR-derived predictions of potential amphibian breeding ponds |
|
| Authors: | James T. Julian John A. Young John W. Jones Craig D. Snyder C. Wayne Wright |
| Affiliation: | (1) Penn State Cooperative Wetlands Center, 302 Walker Building, Department of Geography, The Pennsylvania State University, University Park, PA 16802, USA;(2) Leetown Science Center, US Geological Survey, 11649 Leetown Road, Kearneysville, WV 25430, USA;(3) Eastern Region Geography, US Geological Survey, 12201 Sunrise Valley Drive, Reston, VA 20192, USA;(4) Florida Integrated Science Center, US Geological Survey, 600 4th Street South, St. Petersburg, FL 33701, USA |
| Abstract: | We examined whether spatially explicit information improved models that use LiDAR return signal intensity to discriminate in-pond habitat from terrestrial habitat at 24 amphibian breeding ponds. The addition of Local Indicators of Spatial Association (LISA) to LiDAR return intensity data significantly improved predictive models at all ponds, reduced residual error by as much as 74%, and appeared to improve models by reducing classification errors associated with types of in-pond vegetation. We conclude that LISA statistics can help maximize the information content that can be extracted from time resolved LiDAR return data in models that predict the occurrence of small, seasonal ponds. |
| Keywords: | LiDAR Local indicator of spatial association Seasonal wetland Remote sensing |
| 本文献已被 SpringerLink 等数据库收录！ | |