Valuing Natural Space and Landscape Fragmentation in Richmond, VA

Hedonic pricing methods and GIS (Geographic Information Systems) were used to evaluate relationships between sale price of single family homes and landscape fragmentation and natural land cover. Spatial regression analyses found that sale prices increase as landscapes become less fragmented and the amount of natural land cover around a home increases. The projected growth in population and employment in the Richmond, Virginia region and subsequent increases in land development and landscape fragmentation presents a challenge to sustaining intact healthy ecosystems in the Richmond region. Spatial regression analyses helped illuminate how land cover patterns influence sale prices and landscape patterns that are economically and ecologically advantageous

Moving Beyond Static Species Distribution Models in Support of Conservation Biogeography

Aim: To demonstrate that multi-modeling methods have effectively been used to combine static species distribution models (SDM), predicting the geographical pattern of suitable habitat, with dynamics landscape and population models in order to forecast the impacts of environmental change on species, an important goal of conservation biogeography. Methods: Three approaches were considered: a) incorporating models of species migration in order to understand the ability of a species to occupy suitable habitat in new locations; b) linking models of landscape disturbance and succession to models of habitat suitability; and, c) fully linking models of habitat suitability, habitat dynamics and spatially-explicit population dynamics. Results: Linking species-environment relationships, landscape dynamics and population dynamics in a multi-modeling framework allows the combined impacts of climate change (affecting species distribution and vital rates) and land cover dynamics (land use change, altered disturbance regimes) on species be predicted. This approach is only feasible if the life history parameters and habitat requirements of the species are well understood. Main Conclusions: Forecasts of the impacts of global change on species have been improved by considering multiple causes. A range of methods are available to address the interactions of changing habitat suitability, habitat dynamics and population response that vary in their complexity, realism and data requirements.

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesIn this paper urban land use change analysis and modeling of the Concelhos of Setúbal and Sesimbra, Portugal is accomplished using multitemporal and multispectral satellite images acquired in the years 2000 and 2006 and other vector datasets. The LULC maps are first obtained using an object-oriented image classification approach with the Nearest Neighbour algorithm in Definiens. Classification is assessed using the overall accuracy and Kappa measure of agreement. These measures of accuracies are above minimum standard accepted levels. The land use dynamics, both for pattern and quantities are also studied using a post classification change detection technique together with the following selected spatial/landscape metrics: class area, number of patches, edge density, largest patch index, Euclidian mean nearest neighbor distance, area weighted mean patch fractal dimension and contagion. Urban sprawl has also been measured using Shannon Entropy approach to describe the dispersion of land development or sprawl. Results indicated that the study area has undergone a tremendous change in urban growth and pattern during the study period. A Cellular Automata Markov (CA_Markov) modeling approach has also been applied to predict urban land use change between 1990 and 2010 with two scenarios: MMU 1ha and MMU 25ha. The suitability maps (change drivers) are calibrated with the LULC maps of 1990 and 2000 using MCE and a contiguity filter. The maps of 1990 and 2000 are also used for the transition probability matrix. Then, the land use maps of 2006 are simulated to compare the result of the “prediction” with the actual land use map in that year so that further prediction can be carried out for the year 2010. This is evaluated based on the Kappa measure of agreement (Kno, Klocation and Kquanity) and produced a satisfactory level of accuracy. After calibrating the model and assessing its validity, a “real” prediction for the year 2010 is carried out. Analysis of the prediction revealed that the rate of urban growth tends to continue and would threaten large areas that are currently reserved for forest cover, farming lands and natural parks. Finally, the modeling output provides a building block for successive urban planning, for exploring how an

Geospatial modeling of forest landscape assessment: A case study from Ikere forest reserve

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment. Keyword: Landscape, Spatial metrics, sustainable forest and Environment

Characterization and Visualization of Spatial Patterns of Urbanisation and Sprawl through Metrics and Modeling

Characterisation of spatial patterns of urban dynamics of Coimbatore, India is done using temporal remote sensing data of 1989 to 2013 with spatial metrics. Urban morphology at local levels is assessed through density gradients and zonal approach show of higher spatial heterogeneity during late1980’s and early 90’s. Urban expansion picked up at city outskirts and buffer region dominated with large number of urban fragments indicating the sprawl. Urban space has increased from 1.87% (1989) to 21.26 % (2013) with the decline of other land uses particularly vegetation. Higher heterogeneous land use classes during 90’s, give way for a homogeneous landscape (with simple shapes and less edges) indicating the domination of urban category in 2013. Complex landscape with high number of patches and edges in the buffer region indicate of fragmentation due to urban sprawl in the region. Visualisation of urban growth through Fuzzy-AHP-CA model shows that built up area would increase to 32.64% by 2025. The trend points to lack of appropriate regional planning leading to intensification of spatial discontinuity with the unsustainable urban growth

Impact of rapid urban expansion on green space structure

Rapid urban expansion has had a significant impact on green space structure. A wide variety of modelling approaches have been tested to simulate urban expansion; however, the effectiveness of simulations of the spatial structure of urban expansion remains unexplored. This study aims to model and predict urban expansion in three cities (Kuala Lumpur, Metro Manila and Jakarta), all experiencing rapid urban expansion, and to identify which are the main drivers, including spatial planning, in the resulting spatial patterns. Land Change Modeller (LCM)-Markov Chain models were used, parameterised on changes observed between 1988/1989 and 1999 and verified with the urban form observed for 2014. These models were then used to simulate urban expansion for the year 2030. The spatial structure of the simulated 2030 land use was then compared with the 2030 master plan for each city using spatial metrics. LCM-Markov Chain models proved to be a suitable method for simulating the development of future land use. There were also important differences in the projected spatial structure for 2030 when compared to the planned development in each city; substantive differences in the size, density, distance, shape and spatial pattern. Evidence suggests that these spatial patterns are influenced by the forms of rapid urban expansion experienced in these cities and respective master planning policies of the municipalities of the cities. The use of integrated simulation modelling and landscape ecology analytics supplies significant insights into the evolution of the spatial structure of urban expansion and identifies constraints and informs intervention for spatial planning and policies in cities

Spatial Dynamic Modeling and Urban Land Use Transformation:

Assessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community.

Spatio-temporal land use/land cover changes analysis and monitoring in the Valencia Municipality, Spain

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesIssues of land use/land cover changes and the direct or indirect relationships of these changes have drawn much attention in recent years. In the Mediterranean Spain, observed environmental changes influenced with dramatic urban growth and their likely changes can have extensive unforeseen ramification. Thus, the objectives of this research were to map and determine the nature, extent and rate of changes and to analyze the spatio-temporal land use/land cover change patterns and fragmentation that has occurred in Valencia Municipality. Multi-temporal Landsat MSS1976, TM1992 and ETM2001 images were acquired. Digital orthophotos, IKONOS images and existing Corine land cover maps were used as reference. More than 130 training samples were selected for classification of the Landsat images using supervised method parallelepiped-maximum likelihood algorithm in ERDAS Imagine 9.1, and land cover maps were generated and change detection analysis was performed.(...

Land Change Science and the STEPLand Framework : An Assessment of Its Progress

This contribution assesses a new term that is proposed to be established within Land Change Science: Spatio-TEmporal Patterns of Land ('STEPLand'). It refers to a specific workflow for analyzing land-use/land cover (LUC) patterns, identifying and modeling driving forces of LUC changes, assessing socio-environmental consequences, and contributing to defining future scenarios of land transformations. In this article, we define this framework based on a comprehensive meta-analysis of 250 selected articles published in international scientific journals from 2000 to 2019. The empirical results demonstrate that STEPLand is a consolidated protocol applied globally, and the large diversity of journals, disciplines, and countries involved shows that it is becoming ubiquitous. In this paper, the main characteristics of STEPLand are provided and discussed, demonstrating that the operational procedure can facilitate the interaction among researchers from different fields, and communication between researchers and policy makers