Claire Jantz

Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model

This paper presents a fine-scale (30 meter resolution) regional land cover modeling system, based on the SLEUTH cellular automata model, that was developed for a 257000 km 2 area comprising the Chesapeake Bay drainage basin in the eastern United States. As part of this effort, we developed a new version of the SLEUTH model (SLEUTH-3r), which introduces new functionality and fit metrics that substantially increase the performance and applicability of the model. In addition, we developed methods that expand the capability of SLEUTH to incorporate economic, cultural and policy information, opening up new avenues for the integration of SLEUTH with other land-change models. SLEUTH-3r is also more computationally efficient (by a factor of 5) and uses less memory (reduced 65%) than the original software. With the new version of SLEUTH, we were able to achieve high accuracies at both the aggregate level of 15 subregional modeling units and at finer scales. We present forecasts to 2030 of urban development under a current trends scenario across the entire Chesapeake Bay drainage basin, and three alternative scenarios for a sub-region within the Chesapeake Bay watershed to illustrate the new ability of SLEUTH-3r to generate forecasts across a broad range of conditions.

Analysis of scale dependencies in an urban land‐use‐change model

Different processes shaping land‐use patterns are observed at different scales. In land‐use modelling, scale can influence the measurement and quantitative description of land‐use patterns and can therefore significantly impact the behaviour of model parameters that describe land‐use change processes. We present results of a rigorous sensitivity analysis of a cellular urban land‐use‐change model, SLEUTH, testing its performance in response to varying cell resolutions. Specifically, we examine the behaviour of each type of urban growth rule across different cell sizes, and explore the models ability to capture growth rates and patterns across scales. Our findings suggest that SLEUTHs sensitivity to scale extend beyond issues of calibration. While the model was able to capture the rate of growth reliably across all cell sizes, differences in its ability to simulate growth patterns across scales were substantial. We also observed significant differences in the sensitivity of the growth rules across cell sizes, indicating that SLEUTH may perform better at certain cell sizes than at others. These findings emphasize the importance of scale considerations in land‐use‐change modelling research, particularly in terms of determining the relevant and appropriate scales of enquiry for the processes being simulated.

Evaluation of Impervious Surface Estimates in a Rapidly Urbanizing Watershed

Accurate measurement of impervious surface (IS) cover is an essential indicator of downstream water quality and a critical input variable for many water quality and quantity models. This study compares IS estimates from a recently developed satellite imagery/land cover approach with a more traditional aerial photography/land use approach. Both approaches are evaluated against a high-quality validation set consisting of planimetric data merged with manually-delineated areas of soil disturbance. The study area is the rapidly urbanizing 127 km 2 Cub Run watershed in northern Virginia, located on the fringe of the Washington, D.C. metropolitan region. Results show that photo-interpreted IS estimates of land class are higher than satellite-derived IS estimates by 100 percent or more, even in land uses conservatively assigned high IS values. Satellite-derived IS estimates by land class correlate well with planimetric reference data (r � 0.95) and with published ranges for similar sites in the region. Basin-wide mean IS values, difference grids, and regression and density plots validate the use of satellite-derived/land cover-based IS estimates over photo-interpreted/land use-based estimates. Results of this site-specific study support the use of automated, satellite-derived IS estimates for planning and management within rapidly urbanizing watersheds where a GIS system is in place, but where time-sensitive, high quality planimetric data is unavailable.

Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges, and Strategies

William J. McConnell, James D. A. Millington, Nicholas J. Reo, Marina Alberti, Heidi Asbjornsen, Lawrence A. Baker, Nicholas Brozov, Laurie E. Drinkwater, Scott A. Drzyzga, Jose, Fragoso, Daniel S. Holland, Claire A. Jantz, Timothy Kohler, Herbert D. G. Maschner, Michael Monticino, Guillermo Podesta, Robert Gilmore Pontius, Jr., Charles L. Redman, David Sailor, Gerald Urquhart, and Jianguo Liu. (2011). Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges, and Strategies. Bulletin of the Ecological Society of America April: 218-228.

Integrated Analysis of Ecosystem Interactions with Land Use Change: The Chesapeake Bay Watershed

The Chesapeake Bay is the largest estuary in the United States, encompassed by a watershed extending 168,000 km 2 over portions of six states and Washington, D.C. Restoration of the Bay has been the focus of a two-decade regional partnership of local, state and federal agencies, including a network of scientists, politicians and activists interacting through various committees, working groups, and advisory panels. The effectiveness of the restoration effort has been mixed, with both notable successes and failures. The overall health of the Bay has not declined since the restoration was initiated in 1983, but many of the advances have been offset by the pressure of increasing population and exurban sprawl across the watershed. The needs of the Chesapeake Bay Program are many, but the greatest is accurate information on land cover and land use change, primarily to assess the implications for water quality, examine various restoration scenarios, and calibrate spatial models of the urbanization process. We report here on a number of new land cover and land use data products, and associated applications to assist vulnerability assessment, integrated ecosystem analysis, and ultimately Bay restoration. We provide brief overviews of applications to model new residential development, assess losses and vulnerability of resource lands, and identify the factors that disrupt the health of streams in small watersheds. These data products and approaches are being applied by a number of agencies involved with the restoration effort, including the Chesapeake Bay Programs activities focused on living resources, water quality, and sound land use.

APPLICATION OF MULTITEMPORAL LANDSAT DATA TO MAP AND MONITOR LAND COVER AND LAND USE CHANGE IN THE CHESAPEAKE BAY WATERSHED

We have developed approaches to map and monitor land cover and land use change across the Chesapeake Bay watershed, in the mid-Atlantic region of the United States, using multi-temporal, multi-scale image data. Here we provide an overview of the methods and map products, which have relevance to a range of resource management and decision-support applications. 1 Introduction Multitemporal satellite data provide the capability for mapping and monitoring land cover and land use change, but require the development of accurate and repeatable techniques that can be extended to a broad range of environments and conditions. We have developed approaches to map and monitor land cover and land use change in the Chesapeake Bay watershed (CBW), a region comprised of diverse physiographic provinces and a complex mosaic of land cover types, farming practices and land use management strategies. Our results working in this region have practical implications for application to an even wider range of conditions. Decision-tree classification algorithms and associated decision rules have been developed using a combination of field data, digital Landsat, Ikonos and orthophoto (DOQ) imagery, and supporting geographic information system (GIS) coverages, including planimetric and land use maps contributed by numerous collaborators in the region. We report on the development of these maps and methods, including local-scale to region-wide products useful for a broad range of resource management and decision-support applications.

Monitoring and predicting urban land use change applications of multi-resolution multi-temporal satellite data

The ability to map and monitor the spatial extent of the built environment, and associated temporal changes, has important societal and economic relevance. Multitemporal satellite data now provide the potential for mapping and monitoring urban land use change, but require the development of accurate and repeatable techniques that can be extended to a broad range of conditions and environments. We have developed an approach using Landsat imagery, trained with the high resolution data sets, that identifies impervious surface areas (buildings, roads, etc) at subpixel resolution. We report on application of the approach over a range of scales, from the local to the entire Chesapeake Bay Watershed (168,000 km 2 ). We also developed maps of past changes in the built environment, used them to calibrate a spatial predictive model, and generated maps of expected future change under various policy scenarios out to year 2030. We believe these techniques have applicability to a wide range of applications.

Coupling of the Water Cycle with Patterns of Urban Growth in the Baltimore Metropolitan Region, United States†

Regional municipal water plans typically do not recognize complex coupling patterns or that increased withdrawals in one location can result in changes in water availability in others. We investigated the interaction between urban growth and water availability in the Baltimore metropolitan region where urban growth has occurred beyond the reaches of municipal water systems into areas that rely on wells in low-productivity Piedmont aquifers. We used the urban growth model SLEUTH and the hydrologic model ParFlow.CLM to evaluate this interaction with urban growth scenarios in 2007 and 2030. We found decreasing groundwater availability outside of the municipal water service area. Within the municipal service area we found zones of increasing storage resulting from increased urban growth, where reduced vegetation cover dominated the effect of urbanization on the hydrologic cycle. We also found areas of decreasing storage, where expanding impervious surfaces played a larger role. Although the magnitude of urban growth and change in water availability for the simulation period were generally small, there was considerable spatial heterogeneity of changes in subsurface storage. This suggests that there are locally concentrated areas of groundwater sensitivity to urban growth where water shortages could occur or where drying up of headwater streams would be more likely. The simulation approach presented here could be used to identify early warning indicators of future risk.