How do owners of California's working landscapes manage their land?

Plieninger, T., S. Ferranto, L. Huntsinger, M. Kelly, and C. Getz. 2012. Appreciation, use, and management of biodiversity and ecosystem services in California’s working landscapes. Environmental Management. 50(3):427-440 DOI 10.1007/s00267-012-9900-z. 

‘‘Working landscapes’’ is the concept of fostering effective ecosystem stewardship and conservation through active human presence and management and integrating livestock, crop, and timber production with the provision of a broad range of ecosystem services at the landscape scale. Based on a statewide survey of private landowners of ‘‘working’’ forests and rangelands in California, we investigated whether owners who are engaged in commercial livestock or timber production appreciate and manage biodiversity and ecosystem services on their land in different ways than purely residential owners.

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How do we characterize food stores for public health research?

Kersten, E., B. Laraia, M. Kelly, N. Adler, and I. Yen. 2012. Small food stores and availability of nutritious foods: A comparison of database and in-store measures, Northern California, 2009. Preventing Chronic Disease 9:120023. DOI: http://dx.doi.org/10.5888/pcd9.120023

Small food stores are prevalent in urban neighborhoods, but the availability of nutritious food at such stores is not well known. The objective of this study was to determine whether data from 3 commercially available sources would yield a single, homogenous, healthful food store category that can be used to accurately characterize community nutrition environments for public health research. We conducted in-store surveys in 2009 on store type and the availability of nutritious food in a sample of nonchain food stores (n = 102) in 6 predominantly urban counties in Northern California (Alameda, Contra Costa, Marin, Sacramento, San Francisco, and Santa Clara). We compared survey results with commercial database information and neighborhood sociodemographic data by using independent sample t tests and classification and regression trees. We found that commercial databases alone may not adequately categorize small food stores and the availability of nutritious foods. Alternative measures are needed to more accurately inform research and policies that seek to address disparities in diet-related health conditions. 

Journal Link. Pdf download.

Mapping fisher denning trees with lidar

Zhao, F., R.A. Sweitzer, Q. Guo, and M. Kelly. 2012. Characterizing habitats associated with fisher den structures in the Southern Sierra Nevada, California using discrete return lidar. Forest Ecology and Management 280: 112–119

This study explored the ability of lidar-derived metrics to capture topography and forest structure surrounding denning trees used by the Pacific fisher (Martes pennanti) as a case study to illustrate the utility of lidar remote sensing in studying mammal-habitat associations. We used Classification and Regression Trees (CART) to statistically compare the slope and lidar-derived forest height and structure metrics in the circular area (with radius of 10–50 m) surrounding denning trees and randomly selected non-denning trees. We accessed our model accuracy using resubstitution and cross-validation methods. Our results show that there is a strong association between fisher denning activity and its surrounding forested environment across scales, with high classification accuracy (overall accuracies above 80% and cross-validation accuracies above 70%) at 20, 30 and 50 m ranges. The best classification accuracies were found at 20 m (optimal resubstitution accuracy 86.2% and cross-validation accuracy 78%). Tree height and slope were important variables in classifying the area immediately surrounding denning trees; at scales larger than 20 m, forest structure and complexity became more important. Pdf download. Journal link.

Using the web as a participatory tool in adaptive management

Kelly, M., S. Ferranto, S. Lei, K. Ueda, L. Huntsinger. 2012. Expanding the table: The web as a tool for participatory adaptive management in California forests. Journal of Environmental Management 109: 1-11

Participatory adaptive management is widely promoted as the new paradigm in public lands management. It is grounded in two underlying principles - that management experiments and diverse sources of information should be used to continually refine management in complex ecological systems, and that the public must be included throughout the adaptive management process. Access to scientific results and exchange of information is at the core of both of these principles. The recent proliferation of Internet communities and web-based participation tools raises the question of how the Internet might help facilitate information exchange in participatory adaptive management. Using a case study approach, the role of web technologies in facilitating the flow of transparent and useful information was examined in a participatory adaptive management project focused on Forest Service vegetation management treatments in California’s Sierra Nevada.

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Characterizing owl nest trees with lidar

spotted owl, courtesy of the SNAMP owl team: http://snamp.cnr.berkeley.edu

García-Feced, C., D. Tempel, and M. Kelly. 2011. LiDAR as a tool to characterize wildlife habitat: California Spotted Owl nesting habitat as an example. Journal of Forestry 108(8): 436-443

We demonstrate the use of an emerging technology, airborne light detection and ranging (lidar), to assess forest wildlife habitat by showing how it can improve the characterization of California spotted owl (Strix occidentalis occidentalis) nesting habitat. We used lidar data, validated in the field, to measure the number, density and pattern of residual trees (≥ 90 cm dbh) and to estimate canopy cover within 200 m of four nest trees. Nest trees were surrounded by large numbers of residual trees and high canopy cover. We believe that lidar would greatly benefit forest managers and scientists in the assessment of wildlife-habitat relationships and conservation of important wildlife species.

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How do forest and rangeland owners in California get information about environmental sustainability?

Ferranto, S., L. Huntsinger, C. Getz, W. Stewart, G. Nakamura, and M. Kelly. 2012. Consider the source: The impact of media and authority in outreach to California’s forest and rangeland owners. Journal of Environmental Management 97(1): 131-140.

Over half of the United States is privately owned. Improving environmental sustainability requires that the scientific and management communities provide effective outreach to the many landowners making decisions about land use and management practices on these lands. We surveyed California forest and rangeland owners in ten counties throughout the state to assess the impact of existing outreach and identify gaps in information distribution and content. Although a number of organizations provide land management advice highly-ranked by landowners, no individual organization currently reaches more than 30% of forest and rangeland owners, and these groups together reach less than 60% of landowners.

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Finding trees in the lidar point cloud

individual trees extracted from the lidar point cloudLi, W., Q. Guo, M. Jakubowski and M. Kelly. 2012. A new method for segmenting individual trees from the lidar point cloud. Photogrammetric Engineering and Remote Sensing 78(1): 75-84

In this study we develop a new algorithm to segment individual trees from the small footprint discrete return airborne lidar point cloud. The new algorithm adopts a top-to-bottom region growing approach that segments trees individually and sequentially from the tallest to the shortest. We experimentally applied the new algorithm to segment trees in a mixed coniferous forest in the Sierra Nevada Mountains in California, USA. Our results indicate that the proposed algorithm has good potential in segmenting individual trees in mixed conifer stands of similar structure using small footprint, discrete return lidar data.

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Where will SF Bay wetlands be in 100 years?

Stralberg, D., M. Brennan, J. C. Callaway, J. K. Wood, L. M. Schile, D. Jongsomjit, M. Kelly, V. T. Parker, and S. Crooks. 2011. Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay. PLoS ONE 6(11): e27388.

Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions.

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Mapping downed logs with lidar + obia

downed logs in redBlanchard, S., M. Jakubowski, and M. Kelly. 2011. Object-based image analysis of downed logs in a disturbed forest landscape using lidar. Remote Sensing 3(11): 2420-2439.

Downed logs on the forest floor provide habitat for species, fuel for forest fires, and function as a key component of forest nutrient cycling and carbon storage. This study evaluates the utility of discrete, multiple return airborne lidar-derived data for image object segmentation and classification of downed logs in a disturbed forested landscape and the efficiency of rule-based object-based image analysis (OBIA) and classification algorithms.

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Use of obia in public health - a review, and call for more

Kelly M., S. Blanchard. E. Kersten and K. Koy. 2011. Object-based analysis of imagery in support of public health: new avenues of research. Remote Sensing 3:2321-2345

The benefits of terrestrial remote sensing in the environmental sciences are clear across a range of applications, and increasingly remote sensing analyses are being integrated into public health research. This integration has largely been in two areas: first, through the inclusion of continuous remote sensing products such as normalized difference vegetation index (NDVI) or moisture indices to answer large-area questions associated with the epidemiology of vector-borne diseases or other health exposures; and second, through image classification to map discrete landscape patches that provide habitat to disease-vectors or that promote poor health. In this second arena, new improvements in object-based image analysis (or “OBIA”) can provide advantages for public health research. This paper provides a brief review of what has been done in the public health literature with continuous and discrete mapping, and then highlights the key concepts in OBIA that could be more of use to public health researchers interested in integrating remote sensing into their work.

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