Spatial Econometrics Revisited: A Case Study of Land Values in Roanoke County

Omitting spatial characteristics such as proximity to amenities from hedonic land value models may lead to spatial autocorrelation and biased and inefficient estimators. A spatial autoregressive error model can be used to model the spatial structure of errors arising from omitted spatial effects. This paper demonstrates an alternative approach to modeling land values based on individual and joint misspecification tests using data from Roanoke County in Virginia. Spatial autocorrelation is found in land value models of Roanoke County. Defining neighborhoods based on geographic and socioeconomics characteristics produces better estimates of neighborhood effects on land values than simple distance measures. Implementing a comprehensive set of individual and joint misspecification tests results in better correction for misspecification errors compared to existing practices.Land Economics/Use,

Local Geography of Row-Crop Quality Land and Cropland Cash Rental Rates

While farmland rental markets are likely to be spatially differentiated, the fine spatial structure of row-crop quality land should have a significant effect on cash rent determination. This study provides a rigorous empirical understanding of the effect of land spatial heterogeneity on cash rental rates. The lacunarity index is employed to measure spatial heterogeneity of land quality, which is built directly upon a soil quality measure, the land parcel’s corn suitability rating index (CSR). A panel data random effect model is applied on annual survey data of farmland cash rental rates of Iowa for 1987-2009. As expected, land spatial heterogeneity has a statistically significant and negative effect on local cash rent rates. The effect’s origin warrants further research.land spatial heterogeneity, rental market, Agricultural Finance, C5, G1, Q1,

An Agent-Based Model of Mediterranean Agricultural Land-Use/Cover Change for Examining Wildfire Risk

Humans have a long history of activity in Mediterranean Basin landscapes. Spatial heterogeneity in these landscapes hinders our understanding about the impacts of changes in human activity on ecological processes, such as wildfire. The use of spatially-explicit models that simulate processes at fine scales should aid the investigation of spatial patterns at the broader, landscape scale. Here, we present an agent-based model of agricultural land-use decision-making to examine the importance of land tenure and land use on future land cover. The model considers two 'types' of land-use decision-making agent with differing perspectives; 'commercial' agents that are perfectly economically rational, and 'traditional' agents that represent part-time or 'traditional' farmers that manage their land because of its cultural, rather than economic, value. The structure of the model is described and results are presented for various scenarios of initial landscape configuration. Land-use/cover maps produced by the model are used to examine how wildfire risk changes for each scenario. Results indicate that land tenure configuration influences trajectories of land use change. However, simulations for various initial land-use configurations and compositions converge to similar states when land-tenure structure is held constant. For the scenarios considered, mean wildfire risk increases relative to the observed landscape. Increases in wildfire risk are not spatially uniform however, varying according to the composition and configuration of land use types. These unexpected spatial variations in wildfire risk highlight the advantages of using a spatially-explicit agent-based model of land use/cover change.Land Use/Cover Change, Land Tenure, Wildfire, Mediterranean-Type Ecosystem, Agriculture, Spatial Heterogeneity

SOCIOECONOMIC INFLUENCES ON LAND USE CHOICE AT WATERSHED LEVEL: A MULTINOMIAL LOGIT ANALYSIS OF LAND USE DISTRIBUTION IN WEST GEORGIA

Allocation of fixed proportion of land to developed, forest, agricultural and other land uses in a watershed was modeled as an optimization problem faced by a single user. A multinomial logit model was used to estimate the effects of urbanization, demographic structure, personal income and spatial distribution of watersheds.Land Economics/Use,

The Capitalization of Public Services and Amenities into Land Prices – Empirical Evidence from German Communities

Applying the hedonic approach to land prices, this paper investigates the capitalization of public services and pure amenities in a cross section of German communities. Possible spill-over effects from neighboring municipalities are explicitly included in the analysis and prove to be of considerable importance. Estimates of the impacts of local attributes on land prices are obtained taking into account the spatial structure among unobserved variables. The results confirm that differences in land prices can largely be attributed to local conditions and policies. This implies a significant degree of mobility as well as a sizeable valuation of local attributes by German households.Land Prices, Hedonic Regression, Spatial Dependence

Buying Ecological Services: Fragmented Reserves, Core and Periphery National Park Structure, and the Agricultural Extensification Debate

�Growing demand for cropland products has placed intense pressure on the abilityof land resources to support nature, straining public budgets to purchase environmental goods.Fixing overall agricultural output, two environmental policy options are whether to a) promotemore agricultural extensification and nature friendly farming practices or b) produce intensivelyon some land and leave the rest wild. Microeconomic models of the topic have not accounted forwidely recognized spatial externalities regarding fragmented reserves. This article does so, usingWirtinger’s inequality to also identify a third policy possibility. This is that ecological servicescan follow a smoothly varying spatial path chararacterized by harmonic functions. We use theresults to rationalize the core and periphery National Park structure put in place around theworld, i.e., versions of our third policy possibility have been implemented.Environmental policy; Land use; National Park management; Spatial externalities; Wirtinger’s inequality

Determinants of Spatial Distribution of Organic Farming in Germany

The share of organically managed land is spread unevenly throughout Germany and shows pronounced regional concentrations. The spatial distribution of organic farming is assumed to be influenced by several factors. Location factors of farms are regionally different and thus may influence the spatial distribution of organic farming. Agglomeration effects and therefore spatial dependence are also considered important in determining spatial distribution. These factors with a potential influence on the spatial distribution of organic farming can be divided into four categories: natural factors, farm-structure factors, socio-economic factors and political factors. Their possible influence on the spatial distribution of organic farming is analysed by several statistical methods: ordinary least square regression model, spatial autoregressive models, analysis of variance and Spearman correlation. Of the analysed factors, spatial contiguity has the strongest influence on the spatial distribution of organic farming (indicating relevant agglomeration effects)

Prediction of spatial distribution for some land use allometric characteristics in land use planning models with geostatistic and Geographical Information System (GIS) (Case study: Boein and Miandasht, Isfahan Province, Iran)

Although traditional census can present unbiased information about different land uses, it is spatial independent and do not present particular  information about spatial distribution of studied characteristic. In this study, we used geostatistic and Geographical Information System (GIS) to estimate some different land uses allometric characteristics in Isfahan Province (Iran). Thus, samples information was surveyed considering their geographic position in the studied area. After optimizing variogram parameters,  empirical variogram was prepared to investigate spatial structure of different land uses allometric characteristics. Our results confirme that spatial  structure for the quantitative characteristics of different land uses has a moderate degree of spatial correlation, except for type variable that has no spatial structure. Nugget effect for variogram obtained from the quantitative characteristics of different land uses was equal to 35 to 64%. We used ordinary Kriging for preparing Kriging map and Kriging standard deviation of different land uses. Also, we used geostatistic and GIS to compare geostatistical and algebraic interpolation methods and nine different interpolation methods (Kriging, local polynomial methods, inverse distance weighted, radial basis functions, global polynomial, moving average  weighted, natural neighbor, nearest neighbor and triangulation with Linear Interpolation) were investigated. Spatial distribution of different land uses quantitative characteristics were validated with ordinary Kriging and algebraic methods. Our results confirm that ordinary Kriging has more accuracy than other methods for spatial prediction of different land uses quantitative characteristics.Key words: Geostatistic, interpolation method, land use allometric  characteristics, Kriging

Integrated planning of water and land-use

The role of water in spatial planning has received increasing attention in recent years. It was, for example, one of the leading motives in the preparation of the latest National Spatial Planning Note for The Netherlands. For the preparation of such spatial plans, and to support the associated policy analysis, there is a need to fully identify and characterize the interactions between the water sector and spatial planning and establish the process for making consistent joint projections for the water sector and land-use. This should account for spatial claims from the water sector, balance those claims with claims from other sectors, and feed back spatial constraints and opportunities. Land-use markets and government policies (translated e.g. in spatial reservations) form an important input in this balance. Modeling is indispensable to keep track of spatial characteristics and trace changes. Most of the available modeling considers a layered structure with a layer for national/regional projections and a GIS based layer to keep track of land use changes. Basically such model makes a distribution (rule based) of the national projections into the GIS based spatial raster, followed by an impact assessment based on the changes in the raster. Those models are generally weak in representing the processes driving land use changes such as the housing and labor market and – the water sector. The challenge remains to set up a suitable module covering these spatial - and water sector development processes. Based on the experience of the authors with many water studies and the recent development of a space-transport modeling tool (integration of transport and land-use), a sketch will be made of the requirements for such module. The scope for such planning tool will be illustrated (with data for The Netherlands), addressing key aspects such as competition for space, costs, risk, and environmental impact.

A model to evaluate the environmental and energetic efficiency of the territorial functionality (transport and activity location)

The main objective of the study is the development of a model for the evaluation of the environmental and energy efficiency of the interaction (mobility) and land use structure (called as 'territorial functionality'), applied to the metropolitan area of Barcelona . In particular there are four points that underpin the model: a) a basic land use-transportation model (LUTM), b) a model for the energy consumption and environmental emissions produced by the territorial functionality, c) a model for the consumption of land produced by the territorial functionality (developed land), and d) assessment of social equity in access to urban activities, and exposure to environmental effects. The goodness of the proposed model is that is composed of empirical models (econometric), robust in their specific topic, but spatially disaggregated (municipality). With this structure is possible to evaluate the effects of functional changes (transport projects or urban planning) in the spatial structure of energy consumption, environmental emissions, and consumption of land, and also identifying the participation (responsibility) of different territories in these effects. It is a systemic and spatial view of the role that each territory plays in the functionality, and their responsibility in the environmental effects. The model is currently under construction, joining the calibrated models of consumption and environmental emissions to an existing transport model in the metropolitan area of Barcelona. This paper presents the mathematical model, and the indicators defined for characterizing the state of the territorial system, and a simple simulation of the possible analysis and results.