The Value of Economic and Community Development Anchors

Purpose: The broad objective of the study was to assess the effect of Land Use Changes on Human Wildlife Conflict in Kajiado County, Kenya. The specific land use changes that was focused on comprised of settlement pattern changes and agricultural expansion. Methodology: The Land Tenure Theory and Habitat Suitability Theory anchored the study. The study used descriptive design targeting the local community representatives, farmers and pastoralists, wildlife rangers and officers, community leaders, Government and County Officials and Wildlife Conservation Organizations. In total, the target population comprised of 2419 respondents. A stratification of the population was done to enhance sampling while random sampling was applied to identify the specific respondents from ach stratum. A sample size of 343 respondents was determined using Cochran's formula. A combination of structured questionnaires and semi structured interview guides were employed to gather both quantitative and qualitative data. Quantitative data was analyzed using mean and standard deviation and Pearson Correlation Coefficient for inferential analysis. Qualitative data was analyzed using thematic analysis. The results of the analysis were displayed in form of tables and figures. Findings: The study established that land use changes comprising of settlement pattern changes and agricultural expansion positively and significantly affect human wildlife conflict in Kajiado County. This was depicted by beta values of 0.538 and 0.411. The study concluded that increase in the land use changes increases animal wildlife conflicts in Kajiado County. Unique Contribution to Theory, Practice and Policy: The study recommends regulating settlement patterns, and implementing wildlife friendly farming to minimize human wildlife conflicts in Kajiado County.

Using GIS and Multi-criteria Decision Analysis for Conflict Resolution in Land Use Planning

The dynamics of remote sensing (RS), a geographic information system (GIS) technique, and the applications of global positioning system (GPS) were used to respond to a wide geospatial need in Owerri Land use, in Nigeria. Promotion (further use) of supervised classification is an exclusive use of scientific analysis to decompose a supervised classification error. This method promoted community and economic development. The term promote, means further analysis for more applications of the error matrix, to gain knowledge of specific land use activities within different land use categories. The project finds that the regimes of the series of satellite imagery hold more data of information than the supervised classification alone. One of such knowledge or information was phase withdrawal of some land use categories, which was shared for agricultural and economic development, transportation planning, and Homeland Security management. The regimes of the land use and land cover change (LUCC) revealed some impact distribution on regional resources. It provided sufficient data and metadata for land use management. The results were geo-database development for land ownership and the Urban Pedestrian Resource Network (UPRN). This network created opportunities for minorities like women, who want to stay closer to home while actively engaged in business. This was due to market applications of a geo-database. The system is recommended for smaller cities, or rural communities with inherent land use management and development problems.

A study involving a computerized data base for land use planning at the county level required early decisions (1) in the selection of physical characteristics that best describe the land relative to planning and (2) the size of the data cell for encoding and storing this information. These aspects of the complete study, which are necessary features for all computer-based land use plans, are explored in this paper. Information related to areal distribution and engineering characteristics of earth materials, topography, surface and ground water aspects, provides the needed input data for the base. Such data when supplemented with economic, cultural, and demographic information provide the basis on which planning agencies can formulate realistic land use plans. This information is digitized for computer storage and subsequent computation to be used for decision making. The first step in determining the suitability of a piece of land involved selection of the variables, which are the physical characteristics of the land. In addition, the relative importance of each variable, in relation to a given land use, is evaluated. Next, all the subcategories of each of the variables are assigned levels of importance, called ranking. These procedures are then followed by computer processing whereby the product of level-ranking and variable weighting is computed for each data point for a specific land use. The computer then sums up these products for all the variables and assigns a numerical ranking for each data point. Maps are subsequently printed out depicting the numerical value for each point from which locations with the greatest potential for the specific land use, corresponding to the highest number, can be determined. Selection of cell size for encoding data is a primary task in data base studies for land use planning. A cell provides the dimension of the land surface on which the researcher must determine the nature of the material and supply the input for the data base. The time needed to encode data increases rapidly with decreasing cell size for the same total area and is accompanied by an attendant increase in cost. Based on statistical analysis a cell measuring 154.2 m (500 ft) on the side was found to be most suitable for land use planning at county level.

Abstract* Real estate valuation is carried out correctly if it takes into account all the conditions occurring on a given market at the time of its performance. One of the important determinants of correct valuation is the proper determination of the land use class of the property being valued. It is equally important to find similar properties with the same land use classes as the property subjected to valuation. This does not pose a problem when a property is located within an area with one specific land use zone. If, however, its land use zoning is not homogeneous, finding similar properties may be difficult. If those contained in the database of comparable properties differ from the real estate being valued with regard to land uses of individual areas or proportions of areas with a specific use, it is suggested to divide transaction prices obtained for the whole property into components of those prices that correspond to the fragments of this property with specific land uses. In this paper, the conditional model has been used for this purpose.

Soil type and land use intensity determine the composition of arbuscular mycorrhizal fungal communities

INTRODUCTION: Air pollution has been studied extensively in large and developed nations. However, spatiotemporal trends of pollution in smaller Eastern Caribbean countries have typically been underexplored despite increased emissions driven by development. This study sought to estimate and describe air pollution per specific land use features in the islands of St. Kitts and Nevis where air quality has not been characterized. METHODS: Transport (T), recreation (R) and construction (C) sites were identified using Geographic Information Systems (GIS) and local land use records. In total, 33 monitoring sites were chosen (nT=15, nR=10, nC=8) via stratified random and purposeful sampling. Nitrogen Dioxide (NO2), Ozone (O3) and Particulate Matter (PM) levels were measured actively (1 hour) and passively (2 weeks) in 2015 and 2016. Bivariate analysis, linear mixed effects modeling and land use regression were carried out via SAS 9.4 to evaluate spatiotemporal trends. RESULTS: For active 1-hour sampling, average NO2, O3 and PM10 levels were 29.4 ppb (range: 0-182 ppb), 8.6 ppb (range: 0-106 ppb) and 15.5 µg/m3 (range: 0-302 µg/m3) respectively. Construction NO2 levels were higher than recreation (p<0.01). O3 levels were lower in recreation than construction (p<0.01). Construction PM10 levels exceeded transport (p=0.03). NO2 moderately correlated with O3 (r = 0.54; p<0.01). NO2 was higher in dry season (p<0.05) and near construction (p<0.01); lower in proximity to coast (p=0.01). O3 was inverse to road proximity (p<0.01); higher near construction (p<0.05). PM10 varied by site (p<0.001) and marginally by wind direction (p=0.07). Passive O3 was higher in transport than recreation (p<0.01). DISCUSSION: This study provides evidence of air pollution in small developing nations. Maxima indicate potential for exceedance of World Health Organization guidelines. Land use types, specific land use features, time and meteorology proved significant. Further research is warranted.

Aquatic contamination by potentially toxic metals is a problem that has been aggravated, especially due to the quantity and the diversity of sources. Locating these sources is not always an easy task, especially because of the wide variety of possibilities. In this context, the application of geostatistical methods may represent an excellent tool to find out sources of metal contaminants in aquatic systems. Thus, the objective of this work was to elaborate an approach to identify sources of potentially toxic metals (Zn, Ba, Pb, Cr, Mn and Fe), by relating their spatial-temporal variations with the local land use patterns, along a longitudinal profile of the Pirapora River, located in the State of Sao Paulo, Brazil. For this purpose, water samples were collected at different points, taking into consideration each specific land use pattern and quantifying the metals contents by microwave plasma atomic emission spectrometry. In this work, thirteen land use patterns have been identified: mining, forestry, abandoned pasture, water, urban area, human occupation, floodplain, bare soil, temporary crop, roads, forest, streets and pasture. The results revealed temporal variations for the metals Ba, Cr, Fe, and Pb and spatial for Zn and Mn, making possible to correlate the presence of these two latter metals with mining and forestry, the most proeminent activities in the region. Overall, this work proposes a model which brings together geoprocessing and analytical methods, in order to correlate spatial-temporal variations of potentially toxic metals with specific land use patterns of a determined region, aiming the environmental monitoring.

Options for including all lands in a future greenhouse gas accounting framework

Path dependency and contingent causation in policy adoption and land use plans: The case of Southeastern Peru

Integrating compound-specific δ13C isotopes and fallout radionuclides to retrace land use type-specific net erosion rates in a small tropical catchment exposed to intense land use change

BackgroundLand use for the conversion of energy from renewable sources into electrical energy is increasingly competing with cultural landscapes and natural areas. It is anticipated that by 2050, solar energy generation will have increased by a factor of 15, which will result in a considerable expansion of the land area required for photovoltaic (PV) power plants on a global scale. An increase in the efficiency of PV modules and an optimisation of the space usage for PV power plant construction will contribute to a reduction in the expected environmental impact on land use. This study represents an empirical investigation into the European development of specific energy and area-relevant key performance indicators of free-field PV power plants. It employs a comprehensive sample drawn from diverse European geographical locations from different installation years.MethodsThis study investigated the evolution of various location-independent and location-dependent system parameters over time, using a sample of 107 free-field PV power plants across diverse European regions from 2006 to 2022 related to the fenced area. The investigations concentrated on the land use per installed power, land use per module area, land use per generated electrical energy, generated electrical energy per PV module area, energy density, capacity factor, and power density. The determined data provide the first European average life cycle inventory data, disaggregated by year and location, for environmental life cycle assessment. To facilitate a comparison of the system parameters of PV power plants with those of other renewable energy technologies, a further database was employed, including 89 power plants from the biomass, wind power, geothermal energy, solar thermal energy, and photovoltaic sectors. The selected samples were compiled from this database to compare the area-specific energy yields of both data sources.ResultsThe European trends for free-field PV power plants demonstrate a 60% reduction in specific land use per installed power and land use per generated electrical energy over the study period. In 2022, the median values were 14 m2/kW and 0.011 m2.a/kWh, respectively. The analysis indicates that three significant technological advances have occurred at approximately 5-year intervals. At the mounting design level, the land use per module area for conventional fixed-tilt row systems decreased by 30%. Overall, the mean land usage of all the considered PV power plants is threefold greater than the module area over the entire study period. Likewise, the results show that the high land usage caused by tracking systems is entirely compensated for by a relatively high energy yield, which presents an opportunity to develop innovative designs for multiple-use systems. A comparison of PV power plants with other renewable energy power plants reveals that solar thermal heat is distinctly superior in terms of the energy yield received per unit area.ConclusionsTo minimise land use, it is recommended that minimum energy efficiency requirements should be defined for new free-field PV power plants in addition to an optimised mounting design within the fenced area. The high energy yield of tracking systems, which have comparatively large row/pole distances, provides the opportunity for multiple uses of the ground area. Furthermore, the discrepancy in energy yield between northern and southern Europe underscores the need for a more comprehensive European planning strategy with regard to the future location of free-field PV power plants. To realise energy transition in the future, it will also be essential to consider all energy potentials together rather than to focus on isolated and small-scale initiatives. The policy changes require Europe-wide coordination, coupled with tailored national and regional definitions. Integrated spatial and energy planning could be a potential avenue for achieving this challenging aim.

The aim of the study was to delineate soil landscape constraints to various land uses for urban and regional planning in the coastal areas of New South Wales (NSW), Australia. Soil landscape units mapped at 1:100,000 or coarser were sub-divided into component facets using advanced terrain modelling techniques in a geographic information system (GIS). The output facet grids were further overlain and linked with relevant GIS layers and soil databases to derive soil landscape constraint ratings for various land use purposes such as residential development, cropping and grazing. The constraint ratings for a specific land use were calculated based on objective and rule-based assessments of soil and landscape features such as engineering hazards, intrinsic fertility, drainage and other parameters. A series of soil landscape constraint maps which portray specific land use capability have been produced for the NSW coast. The methodology developed in this study has been demonstrated to be efficient in delineating soil landscape constraints and there is over 90% agreement between the model outputs and the assessment by soil surveyors with local knowledge. The output maps show levels of unprecedented detail of soil and landscape constraint for the coast of NSW and can be readily interpreted by land use planners and land managers for sustainable land use decision making practices.

Land use is an economic activity that generates large benefits for human society. One side effect, however, is that it has caused many environmental problems throughout history and still does today. Biodiversity, in particular, has been negatively influenced by intensive agriculture, forestry and the increase in urban areas and infrastructure. Integrated assessment such as Life Cycle Assessment (LCA), thus, incorporate impacts on biodiversity. The main objective of this paper is to develop generic characterization factors for land use types using empirical information on species diversity from Central Europe, which can be used in the assessment method developed in the first part of this series of paper. Based on an extensive meta-analysis, with information about species diversity on 5581 sample plots, we calculated characterization factors for 53 land use types and six intensity classes. The typology is based on the CORINE Plus classification. We took information on the standardized α-diversity of plants, moss and mollusks into account. In addition, threatened plants were considered. Linear and nonlinear models were used for the calculation of damage potentials (EDP S). In our approach, we use the current mean species number in the region as a reference, because this determines whether specific land use types hold more or less species diversity per area. The damage potential calculated here is endpoint oriented. The corresponding characterization factors EDP S can be used in the Life Cycle Impact Assessment as weighting factors for different types of land occupation and land use change as described in Part 1 of this paper series. The result from ranking the intensity classes based on the mean plant species number is as expected. High intensive forestry and agriculture exhibit the lowest species richness (5.7–5.8 plant species/m2), artificial surfaces, low intensity forestry and non-use have medium species richness (9.4–11.1 plant species/m2) and low-intensity agriculture has the highest species richness (16.6 plant species/m2). The mean and median are very close, indicating that the skewedness of the distribution is low. Standard error is low and is similar for all intensity classes. Linear transformations of the relative species numbers are linearly transformed into ecosystem damage potentials (EDP ). The integration of threatened plant species diversity into a more differentiated damage function $$EDP_{linear}^{S_{total} } $$ makes it possible to differentiate between land use types that have similar total species numbers, but intensities of land use that are clearly different (e.g., artificial meadow and broad-leafed forest). Negative impact values indicate that land use types hold more species per m2 than the reference does. In terms of species diversity, these land use types are superior (e.g. near-to-nature meadow, hedgerows, agricultural fallow). Land use has severe impacts on the environment. The ecosystem damage potential EDP S is based on assessment of impacts of land use on species diversity. We clearly base EDP S factors on α-diversity, which correlates with the local aspect of species diversity of land use types. Based on an extensive meta-analysis of biologists’ field research, we were able to include data on the diversity of plant species, threatened plant species, moss and mollusks in the EDP S. The integration of other animal species groups (e.g. insects, birds, mammals, amphibians) with their specific habitat preferences could change the characterization factors values specific for each land use type. Those mobile species groups support ecosystem functions, because they provide functional links between habitats in the landscape. The use of generic characterization factors in Life Cycle Impact Assessment of land use, which we have developed, can improve the basis for decision-making in industry and other organizations. It can best be applied for marginal land use decisions. However, if the goal and scope of an LCA requires it this generic assessment can be complemented with a site-dependent assessment. We recommend utilizing the developed characterization factors for land use in Central Europe and as a reference methodology for other regions. In order to assess the impacts of land use in other regions it would be necessary to sample empirical data on species diversity and to develop region specific characterization factors on a worldwide basis in LCA. This is because species diversity and the impact of land use on it can very much differ from region to region.

Land use optimization is a promising approach to achieve urban sustainability. Despite the increasing number of literature on land use optimization, a little investigation is made to systematically review urban land use optimization: its objectives, methodological approaches, and spatial data used etc. This creates room to review the methodological approaches to urban land use optimization. This study systematically reviews 55 articles following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to understand important aspects of urban land use optimization. We have found that the most common objectives which were used in urban land use optimization are maximization of spatial compactness (16.67 %, n=28) and maximization of land use compatibility (13.69%, n=23), followed by maximization of land use suitability (11.90%, n=20). The findings suggest that a) one and only one land use in each cell, b) minimum and maximum area of certain land use, and c) restriction on specific land use change are the important constraints. This study also identifies that urban sustainability has been merely touched upon in urban land use optimizations. While environmental (including ecology) and economic aspects of urban sustainability were included in 46.67% and 43.33% studies respectively, the social aspect (10%, n= 3) was mostly ignored. Our findings also indicate that there is no generalized method to measure economic, environmental, and social benefits from land use planning. This study also finds that the Genetic Algorithm (GA) (32.14%, n=18) accounts for a major contribution to solve the urban land use optimization problem. Based on the findings, this study proposes some recommendations for further research and practice. The most important of them include a) framing land use optimization objective functions considering urban sustainability, b) developing a standard method to calculate values of objective functions, and c) integrating a participatory approach with mathematical optimization to derive more feasible solutions. These recommendations could be the scope of future research.