Land Use Allocation Research Articles

Land-Use Impact and Nitrate Analysis to Validate DRASTIC Vulnerability Maps Using a GIS Platform of Pablillo River Basin, Linares, N.L., Mexico

Preventive management of groundwater resources and their protection against pollution is one of the major challenges of our society. Groundwater systems are related with the surficial processes like territorial administration that is one of the most important tasks into the human development, because it involves serious problems to define the spatial medium, the industrial site-selection and the land-use allocation. Land-use and anthropogenic distribution could be the origin of the emission of pollutants that constitutes a serious health risk in urban areas. Nitrate was used as a pollution indicator in the Pablillo River Basin (PRB), to know the evolution of groundwater quality between 1981 and 2009 using GIS platform linked to vulnerability maps of DRASTIC (Depth to the water table; net groundwater Recharge; Aquifer type; Soil type; Topography; Impact of the vadose zone and hydraulic Conductivity of the saturated zone). The study area is centered on the Linares city; changes in aquifer vulnerability were assessed over time on two stages (2007 and 2001). In both cases, depth from surface to groundwater plays an important role by being the most dynamic variable over time. This study shows that the depth of water table is the key factor in the evaluation of groundwater vulnerability. The significance of land-use impact in contamination process called Index of Pollution Risk (IPR) and nitrate distribution process in the aquifer system was used as anthropogenic indicator together with the IPR in order to associate the land-use, the aquifer-vulnerability and human-activities. The final map of IPR allows determining possible polluted zones verified by high nitrate contents over the aquifer system. Land-use proved to be an important parameter necessary to correct the vulnerability maps using the DRASTIC method. This assessment is valid for situations where a specific time is defined because six of seven parameters change their properties in a very long term. The IPR-map could be an important key tool to prevent complex scenarios of groundwater contamination and to improve the aquifer management for decision makers, governments and private companies.

Impacts of Planners' Different Viewpoints on Optimum Land-Use Allocation

Development of different viewpoints/perspectives in the planning process and discussion of their empirical results will allow creation of “better land-use plans”. In this sense, one of the deficiencies met by the land-use planners is lack of decision support system that can analyse the empirical results of different viewpoints analytically. The aim of this study is to analyse impacts between planners' different viewpoints and the optimum land-uses allocation empirically and analytically. The study uses a generalized land assignment model formulated by Hanink and Cromley (1998) [Land-use allocation in the absence of complete market values, Journal of Regional Science, 38(3), pp. 465–480] that integrates the geographical information systems with multi-criteria decision-making techniques in Cesme/Izmir in Turkey. The study results indicated that the model is very useful to analyse impacts between planners' viewpoint and optimum land-use allocation.

Use of Inverse Spatial Conservation Prioritization to Avoid Biological Diversity Loss Outside Protected Areas

Globally expanding human land use sets constantly increasing pressure for maintenance of biological diversity and functioning ecosystems. To fight the decline of biological diversity, conservation science has broken ground with methods such as the operational model of systematic conservation planning (SCP), which focuses on design and on-the-ground implementation of conservation areas. The most commonly used method in SCP is reserve selection that focuses on the spatial design of reserve networks and their expansion. We expanded these methods by introducing another form of spatial allocation of conservation effort relevant for land-use zoning at the landscape scale that avoids negative ecological effects of human land use outside protected areas. We call our method inverse spatial conservation prioritization. It can be used to identify areas suitable for economic development while simultaneously limiting total ecological and environmental effects of that development at the landscape level by identifying areas with highest economic but lowest ecological value. Our method is not based on a priori targets, and as such it is applicable to cases where the effects of land use on, for example, individual species or ecosystem types are relatively small and would not lead to violation of regional or national conservation targets. We applied our method to land-use allocation to peat mining. Our method identified a combination of profitable production areas that provides the needed area for peat production while retaining most of the landscape-level ecological value of the ecosystem. The results of this inverse spatial conservation prioritization are being used in land-use zoning in the province of Central Finland.

An improved artificial immune system for seeking the Pareto front of land-use allocation problem in large areas

The Pareto front can provide valuable information on land-use planning decision by revealing the possible trade-offs among multiple, conflicting objectives. However, seeking the Pareto front of land-use allocation is much more difficult than finding a unique optimal solution, especially when dealing with large-area regions. This article proposes an improved artificial immune system for multi-objective land-use allocation (AIS-MOLA) to tackle this challenging task. The proposed AIS is equipped with three modified operators, namely (1) a heuristic hypermutation based on compromise programming, (2) a non-dominated neighbour-based proportional cloning and (3) a novel crossover operator that preserves connected patches. To validate the proposed algorithm, it was applied in a hypothetical land-use allocation problem. Compared with the Pareto Simulated Annealing (PSA) method, AIS-MOLA can generate solutions more approximate to the Pareto front, with computation time amounting to only 5.1% of PSA. In addition, AIS-MOLA was also applied in the case study of Panyu, Guangdong, PR China, a large area with cells. Experimental results indicate that this algorithm, even dealing with large-area land-use allocation problems, is capable of generating optimal alternative solutions approximate to the true Pareto front. Moreover, the distribution of these solutions can quantitatively demonstrate the complex trade-offs between the spatial suitability and the compactness in the study area. Software and supplementary materials are available at http://www.geosimulation.cn/AIS-MOLA/.

CASIMOD’N: An agro-hydrological distributed model of catchment-scale nitrogen dynamics integrating farming system decisions

This work presents the new integrative model CASIMOD’N (Catchment and Agricultural Systems Integrated MODel for Nitrogen), which assesses effects of farming systems on nitrogen (N) dynamics at the catchment level. Its main innovation is the consideration of the level of the farming system through production strategies, farmer decisions and the expression of decisions as management practices, along with the link between these farming systems, their practices and water pollution. CASIMOD’N integrates farming systems at the farm level and N transfers and transformations at the field, farm and catchment levels. It was built by adapting and combining three models: the catchment-scale biophysical model TNT2 and two farm-scale models, TOURNESOL and FUMIGENE, for the allocation of land use and manure, respectively. The intrinsic logic behind farming system design and function was represented by ensuring agreement between livestock-feeding and manure-management strategies under specific farm constraints (land fragmentation, distance between fields and farmyards) and agronomic rules. The model is able to simulate management practices (crop, manure and mineral fertiliser allocation).An assessment of the farming system modelling was performed by comparing the management practices simulated with CASIMOD’N with (i) observed data from a livestock-oriented catchment and (ii) a reference dataset of management practices reconstructed with a Markov chain and Knapsack-based algorithm. Then, the spatial distributions of the main N fluxes at the sub-catchment scale simulated with CASIMOD’N and based on the reconstructed management practices are discussed.Simulations of the two options had few differences in spatial distribution of the main N compartments, organic and mineral fertilisation and N flux at the outlets both at catchment and sub-catchment levels. However, CASIMOD’N was more accurate for simulating farming systems than the reconstructed reference dataset of management practices. This suggests that CASIMOD’N can be used to conceive, implement and assess prospective scenarios involving farming system redesign.

Combining system dynamics and hybrid particle swarm optimization for land use allocation

Urban land use spatial allocation is crucial to lots of countries that are usually under severe environmental and demographic pressures, because it can be used to alleviate some land use problems. A number of models have been proposed for the optimal allocation of land use. However, most of these models only address the suitability of individual land use types and spatial competition between different land uses at micro-scales, but ignore macro-level socio-economic variables and driving forces. This article proposes a novel model (SDHPSO-LA) that integrates system dynamics (SD) and hybrid particle swarm optimization (HPSO) for solving land use allocation problems in a large area. The SD module is used to project land use demands influenced by economy, technology, population, policy, and their interactions at macro-scales. Furthermore, particle swarm optimization (PSO) is modified by incorporating genetic operators to allocate land use in discrete geographic space. The SDHPSO-LA model was then applied to a case study in Panyu, Guangdong, China. The experiments demonstrated the proposed model had the ability to reflect the complex behavior of land use system at different scales, and can be used to generate alternative land use patterns based on various scenarios.

MATERIAL CULTURE OF POST-COLONIAL WILDLIFE TOURISM

Many independent nations with strong tourism economies have colonial pasts. In parts of Africa and Asia, former colonial powers have left post-colonial legacies of language, buildings, trade and diplomatic links, and government bureaucratic structures (Ashcroft et al., 2007, Sharp, 2009, Zein-Alabdin, 2009). There are also strong postcolonial influences on tourism (Carrigan, 2011, Hall and Tucker, 2004, Tucker and Abama, 2009). These range from large-scale factors such as key markets and land-use allocation (Akama et al., 2011, Nelson, 2010), to localised concerns such as the authenticity of performances (Martin, 2010). In nations such as India, the newly wealthy middle class may use tourism to sample former colonial lifestyles (Bandyopadhyay, 2012).

GIS-based DRASTIC, Pesticide DRASTIC and the Susceptibility Index (SI): comparative study for evaluation of pollution potential in the Nabeul-Hammamet shallow aquifer, Tunisia

Three vulnerability index models were applied to assess the pollution potential of Nabeul-Hammamet shallow aquifer, Tunisia: DRASTIC, Pesticide DRASTIC and the Susceptibility Index (SI). An output map layer of each one was obtained using a geographic information system (GIS). The SI layer was overlain with DRASTIC and Pesticide DRASTIC and the percentage areas of agreement and divergence in vulnerability categories were extracted. DRASTIC results suggest the aquifer has mostly low vulnerability. Pesticide DRASTIC and SI identify three vulnerability categories (low, moderate, high) in the aquifer. Published data on current chemical groundwater composition indicate that parts of the aquifer are highly contaminated, revealing that DRASTIC underestimates the risk of pollution; Pesticide DRASTIC and SI reflect this risk better. Agreement in vulnerability categories between the two last models is found for 64 % of the aquifer area. To help manage land-use allocation and prevent Nabeul-Hammamet-aquifer contamination, DRASTIC is not recommended. Pesticide DRASTIC and SI are recommended but for slightly different applications. SI helps in the monitoring of current vulnerable areas and, thus, in contamination prevention. Pesticide DRASTIC could better intervene as a criterion in a multi-criteria analysis to select the best sites for specific on-the-ground practice or future land use.

Spatial model steering, an exploratory approach to uncertainty awareness in land use allocation

One evidenced based approach for exploring future agricultural land use change scenarios is Land Use Allocation (LUA). This approach can be used to support medium to long term strategic planning. S...

What to Expect in 2030

The cost of travel, which depends largely on fuel prices, can have a significant effect on the allocation of land use, the amount of travel, selected modes, and route choice. With the volatility of energy prices during the past several decades, the growing instability of energy supply—both domestic and foreign—and ever-growing demand, it is difficult to predict fuel prices and thus the cost of travel. To begin to grapple with such uncertainty, planners must understand the potential effects of energy prices. With a knowledge of these effects, better planning can be achieved to accommodate the likely outcomes. This paper investigates the effects of increased fuel prices on the performance of future transportation systems by using an integrated land use and transportation model. Several scenarios build on national macroeconomic forecasts of changes in household and employment allocations with future transportation network improvements, modeled for 2030 in the capital megaregion area. The scenarios are designed so that the effect on land use and travel behavior from changes in fuel prices and economy is captured. The model results show that increased fuel prices lead to a denser land use pattern and a reduction in automobile mode share and vehicle miles traveled, even though fuel economy increases. The reduction is less pronounced if fuel economy increases significantly. When technological advances lead to very high fuel economy in the future, it may be necessary for policy intervention to increase travel cost to meet planning goals that aim to prevent sprawl.

Effectiveness of collaborative map-based decision support tools

This article reports on the results of an empirical analysis of the effectiveness of a set of collaborative spatial decision support tools developed to support a land use allocation problem in a pe...

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology.

The implications of the 2003 Common Agricultural Policy reforms for land-use and landscape quality in England

The assessment of the potential landscape impacts of the latest Common Agricultural Policy reforms constitutes a challenge for policy makers and it requires the development of models that can reliably project the likely spatial distribution of land uses. The aim of this study is to investigate the impact of 2003 CAP reforms to land uses and rural landscapes across England. For this purpose we modified an existing economic model of agriculture, the Land-Use Allocation Model (LUAM) to provide outputs at a scale appropriate for informing a semi-quantitative landscape assessment at the level of ‘Joint Character Areas’ (JCAs). Overall a decline in the cereal and oilseed production area is projected but intensive arable production will persist in specific locations (East of England, East Midlands and South East), having ongoing negative effects on the character of many JCAs. The impacts of de-coupling will be far more profound on the livestock sector; extensification of production will occur in traditional mixed farming regions (e.g. the South West), a partial displacement of cattle by sheep in the upland regions and an increase in the sheep numbers is expected in the lowlands (South East, Eastern and East Midlands). This extensification process will affect positively those JCAs of mixed farming conditions, but it will have negative impacts on the JCAs of historically low intensity farming (e.g. the uplands of north-west) because they will suffer from under-management and land idling. Our analysis shows that the territorialisation between intensively and extensively agricultural landscapes will continue.

Spatial model steering, an exploratory approach to uncertainty awareness in land use allocation

One evidenced based approach for exploring future agricultural land use change scenarios is Land Use Allocation (LUA). This approach can be used to support medium to long term strategic planning. Specifically, land managers can consider a number of diverse environmental social, economic and physical factors, and explore land use allocation scenarios before choosing to produce one or more commodities in a given region. One of the most successful ways to implement a LUA approach is through the integration of geoprocessing with Multi-Criteria Decision Making methods (MCDM). Leveraging this spatial MCDM modeling approach with the Service Oriented Architecture (SOA) paradigm, we have developed a Spatial Model Steering (SMS) framework that enables users to explore the decision space and thus increase their awareness of the influence of key variables. In this framework a user can visually steer the LUA model key factors, explore and compare “what if” future land use scenarios by changing these factors and visualizing a range of potential LUA outcomes. In doing so, we believe that users can develop increased confidence in their understanding of the key factors governing the underlying models and ultimately obtain greater awareness of the uncertainty in the outcomes.

Model Optimisasi Multiobjektif untuk Masalah Alokasi Penggunaan Lahan dengan Menggunakan Analisis Data Spasial

A good land-use allocation is an important effort to create a safe urban space, comfortable, productive, and sustainable. This is as stipulated in UU RI No. 26 of 2007 regarding spatial planning in Indonesia. Therefore the optimization on allocation land use is important to do. In this paper we present a different approach to solve the land-use allocation problem, i.e,, by using multiobjective optimization, branch and bound methods and generating spatial data analysis via uniformly weighted matrix. In this problem, the objective function is to maximize the total density index and total comprehensive index of the land-use types. An illustrative data that refer to Region Regulation for Bandung No. 09 of 2009 is presented.

Combined land-use and water allocation planning

A general framework for a combined land use and water management is described. An optimization problem is formulated that combines combinatorial and spatial characteristics. The aim of the planning is to maximize economic benefit, while minimizing water extraction and transportation cost under ecological constraints. A genetic algorithm is employed endowed with a new neighborhood operator. This operator acts on a local level, but it produces global results. Although the computational scheme does not include compactness as a separate objective, compact patterns are produced as emergent results. The algorithm is tested on a fictive area represented as a grid with 15×15 land blocks and, also, on a real-world case study.

Optimal land use allocation of urban fringe in Guangzhou

In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.

Rural land use spatial allocation in the semiarid loess hilly area in China: Using a Particle Swarm Optimization model equipped with multi-objective optimization techniques

Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion, cultivated land conservation, soil erosion and water shortage, and require land use allocation to reconcile these environmental conflicts. We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization (PSO) model in conjunction with multi-objective optimization techniques. Our study focuses on Yuzhong County of Gangsu Province in China, a typical catchment on the Loess Plateau, and proposes a land use spatial optimization model. The model maximizes land use suitability and spatial compactness based on a variety of constraints, e.g. optimal land use structure and restrictive areas, and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation (DWA) method to obtain the optimized land use spatial pattern. The results suggest that (1) approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area; (2) the major reshuffling is slope farmland and newly added construction and cultivated land, whereas the unchanged areas are largely forests and basic farmland; and (3) the PSO is capable of optimizing rural land use allocation, and the determinant initialization method and DWA can improve the performance of the PSO.

The Optimal Allocation of Global Land Use in the Food-Energy-Environment Trilemma

This study analyzes the optimal allocation of the world's land resources over the course of the next century in the dynamic forward-looking framework, which brings together distinct strands of economic, agronomic, and biophysical literature and incorporates key drivers affecting global landuse. We show that, while some deforestation is optimal in the near term, the desirability of further deforestation is elimated by mid-century under the baseline scenario. While the adverse productivity shocks from climate change have a modest effect on global land use, when combined with high growth in energy prices they lead to significant deforestation and higher GHG emissions than in the baseline. Imposition of GHG emissions constraint further heightens the competition for land, as fertilizer use declines and land-based mitigation strategies expand. However, the effectiveness of such a pre-announced constraint is completely diluted by intertemporal substitution of deforestation which accelerates prior to imposition of the target.

Transient groundwater modelling with spatio-temporally variable fluxes in a complex aquifer system: new approach in defining boundary conditions for a transient flow model

Long-term water resource planning requires both spatial and temporal information on groundwater recharge in order to properly manage not only water use and exploitation but also land-use allocation and development. In this context, a three-dimensional transient numerical model is developed to support management of groundwater resources and decision analysis for the coastal plain of Corinthos in Greece. Transient simulations usually are used to analyse time-dependent problems such as climate change and groundwater-level change. Among transient models, the most reliable but also the least explored, probably due to the demanding input data requirements, are the models with temporally variable recharge, also termed as fully transient models. In these models, the temporal variability of heads is dependent not only on the temporal variability of aquifer storage but also on the temporal variability of fluxes. In order to arrive at a credible set of flux data as boundary conditions for the numerical model, a sinusoidal equation is developed to simulate the missing water-level data and to forecast the future sequential records of the expected recharge. The results of the developed model reveal that at least two periodicities can be identified in the observed subsurface head-level data.