Projecting Land-Use and Land Cover Change in a Subtropical Urban Watershed

Abstract

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.

Measuring and Predicting Long-Term Land Cover Changes in the Functional Urban Area of Budapest

“…The rapid expansion of artificial surfaces in metropolitan regions has caused versatile conflicts between nature and society and has created challenges for sustainability [1][2][3][4][5][6][7]. Urban fringe areas are especially under the pressure of "urban sprawl", as substantial areas of agricultural land along city boundaries have been converted into urbanized surfaces [8][9][10][11][12][13][14][15]. Land cover changes in suburban locations are driven by very complex socioeconomic factors and often result in environmental damage, landscape degradation, land fragmentation, and the shrinkage of wildlife habitat and undermine peri-urban agricultural capacity for examining long-term land use changes in the Budapest FUA from the late 1950s to 2040; however, they did not pay attention to the loss of farmland and the restructuring of the agricultural sector.…”

Urban Science: Putting the “Smart” in Smart Cities

“…In contrast, Lagrosa et al [10] utilize an existing model for predicting land-use and land-cover change, demonstrating that carefully informed parameterization is crucial for the model's accuracy. The authors reinforce the notion that parameterizing models with existing data should be informed by relevant theory.…”

Future land use conflicts: Comparing spatial scenarios for urban-regional planning

“…Cramer's V test generates an index from 0 to 1 and weights the power of the exploratory variable (driving forces), where values of over 0.15 are considered good, and values over 0.4 are considered very good (Eastman, 2012). The exploratory variables are then analyzed using the logistic regression model (Lagrosa IV et al, 2018). The Geographical Information System Idrisi Selva (Eastman, 2012) was used to estimate the two statistical procedures (Cramer's V test and logistic regression), importing files in ASCII format containing georeferenced data applied to a 30x30 m resolution.…”