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Urban landscapes are heterogeneous mosaics that develop via significant land-use and land cover (LULC) change. Current LULC models project future landscape patterns, but generally avoid urban landscapes due to heterogeneity. To project LULC change for an urban landscape, we parameterize an established LULC model (Dyna-CLUE) under baseline conditions (continued current trends) for a sub-tropical urban watershed in Tampa, FL. Change was modeled for 2012-2016 with observed data from 1995-2011. An ecosystem services-centric classification was used to define 9 LULC classes. Dyna-CLUE projects change using two modules: non-spatial quantity and spatial reallocation. The data-intensive spatial module requires a binomial logistic regression of socioecological driving factors, maps of restricted areas, and conversion settings, which control the sensitivity of class-to-class conversions. Observed quantity trends showed a decrease in area for agriculture, rangeland and upland forests by 49%, 56% and 27% respectively with a 22% increase in residential and 8% increase in built areas, primarily during 1995-2004. The spatial module projected future change to occur mostly in the relatively rural northeastern section of the watershed. Receiver-operating characteristic curves to evaluate driving factors averaged an area of 0.73 across classes. The manipulation of these baseline trends as constrained scenarios will not only enable urban planners to project future patterns under many ecological, economic and sociological conditions, but also examine changes in urban ecosystem services.

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A GIS can be used in land management to document existing conditions, plan future operations, and archive completed work. Farming applications include soil productivity for different crops, crop yield prediction, and determining fertilizer and pesticide application rates. Forestry applications include estimating forest stand acreage, determining forest stand characteristics, and determining where to harvest. This 4-page fact sheet was written by John Lagrosa, Chris Demers, and Michael Andreu, and published by the UF Department of School of Forest Resources and Conservation, March 2012.

Land-use and land-cover (LULC) change is a primary driver of terrestrial carbon release, often through the conversion of forest into agriculture or expansion of urban areas. Classification schemes are a key component of landscape analyses. This study creates a novel LULC classification scheme by incorporating ecological data to redefine classes of an existing LULC classification based on variation in above-ground tree carbon. A tree inventory was conducted for 531 plots within a subbasin of the Tampa Bay Watershed, Florida, USA. Above-ground tree carbon was estimated using the i-Tree model. Plots were classified using the Florida Land Use Cover Classification System. Mean quantities of above-ground tree carbon, by class, were tested for statistical differences. A reclassification was conducted based on these differences. Sub-classes within a given “land cover” class were similar for six of the seven classes. Significant differences were found within the “Wetlands” class based on vegetation cover, forming two distinct groups: “Forested Wetlands” and “Non-forested and Mangrove Wetlands”. The urban “land use” class showed differences between “Residential” and “Non-residential” sub-classes, forming two new classes. LULC classifications can sometimes aggregate areas perceived as similar that are in fact distinct regarding ecological variables. These aggregations can obscure the true variation in a parameter at the landscape scale. Therefore, a study’s classification system should be designed to reflect landscape variation in the parameter(s) of interest.