Context: Green infrastructure may improve water quality and mitigate flooding in forest-urban watersheds, but reliably quantifying all benefits is challenging because most land cover maps depend on moderate- to low-resolution data. Complex and spatially heterogeneous landscapes that typify forest-urban watersheds are not fully represented with these types of data. Hence important questions concerning how green infrastructure influences water quality and quantity at different spatial scales remain unanswered. Objectives: Demonstrate the feasibility of creating novel high-resolution land cover maps across entire watersheds and highlight deficiencies of standard land cover products. Methods: We used object-based image analysis (OBIA) to create high-resolution (0.5 m) land cover maps and detect tree canopy overlapping impervious surfaces for a representative forest-urban watershed in Duluth, MN, USA. Unbiased estimates of accuracy and area were calculated and compared with similar metrics for the 30-m National Land Cover Database (NLCD). Results: Mapping accuracies for the high-resolution land cover and canopy overlap maps were ~90 %. Error-adjusted estimates of area indicated that impervious surfaces comprised ~21 % of the watershed, tree canopy overlapped ~10 % of impervious surfaces, and that three high-resolution land cover classes differed significantly from similar NLCD classes. Conclusions: OBIA can efficiently generate high-resolution land cover products of entire watersheds that are appropriate for research and inclusion in the decision-making process of managers. Metrics derived from these products will likely differ from standard land cover maps and may produce new insights, especially when considering the unprecedented opportunity to evaluate fine-scale spatial heterogeneity across watersheds.
Bibliographical noteFunding Information:
We are especially grateful for funding and support from the cooperative agreement between the US Environmental Protection Agency’s Mid-Continent Ecology Division and the Department of Biology at the University of Minnesota Duluth. Although the research described in the article has been funded partly by the US Environmental Protection Agency, it has not been subjected to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. Richard Bunten and the City of Duluth provided access to high-resolution aerial photography that was used in our analysis. Paul Meysembourg and Richard Axler from the Natural Resources Research Institute at the University of Minnesota Duluth also delivered technical support and advice throughout various stages of the Project. This is contribution number 580 from the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.
© 2014, Springer Science+Business Media Dordrecht.
- Aerial photography
- Green infrastructure
- Impervious surfaces
- Object-based image analysis