The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

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Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

Modeling the interplay between land use, bioenergy production and climate change

Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.

Assessment of land use and land cover changes during the last 50 years in oases and surrounding rangelands of Xinjiang, NW China

An analysis of historical Corona images, Landsat images, recent radar and Google Earth® images was conducted to determine land use and land cover changes of oases settlements and surrounding rangelands at the fringe of the Altay Mountains from 1964 to 2008. For the Landsat datasets supervised classification methods were used to test the suitability of the Maximum Likelihood Classifier with subsequent smoothing and the Sequential Maximum A Posteriori Classifier (SMAPC). The results show a trend typical for the steppe and desert regions of northern China. From 1964 to 2008 farmland strongly increased (+ 61%), while the area of grassland and forest in the floodplains decreased (- 43%). The urban areas increased threefold and 400 ha of former agricultural land were abandoned. Farmland apparently affected by soil salinity decreased in size from 1990 (1180 ha) to 2008 (630 ha). The vegetated areas of the surrounding rangelands decreased, mainly as a result of overgrazing and drought events.The SMAPC with subsequent post processing revealed the highest classification accuracy. However, the specific landscape characteristics of mountain oasis systems required labour intensive post processing. Further research is needed to test the use of ancillary information for an automated classification of the examined landscape features.

Simulating SOC changes in 11 land use change chronosequences from the Brazilian Amazon with RothC and Century models

Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

Land administration in a micro-state: the role of land use planning

Land policy in micro-states and the land administration that underpins it is often devised within a legacy framework inherited from a colonial past. Independence has allowed self-determination of the future political direction yet the range, legal framework, institutional structure and administration systems tend to mirror those of ex-colonial powers. Do land policies, administration systems and processes developed to serve large heavily populated countries scale down to serve the requirements of micro-states? The evidence suggests not: many land administration systems in the Caribbean face difficulties due to poor records, unclear title, exploitation of state lands, incomplete or ongoing land reform programmes, irregular or illegal settlement and non-enforced planning regulations. Land matters are typically the responsibility of several government departments and agencies responsible for land titling and registration, cadastral surveying of property interests, physical planning, taxation and financial regulation. Although planning is regarded as a land administration function, organisational responsibility usually rests with local rather than central government in large countries, but in microstates local government may be politically weak, under-resourced or even non-existent. Using a case study approach this paper explores how planning functions are organised in the Caribbean state of St Vincent & the Grenadines in relation to land administration as a whole and compares the arrangement with other independent micro-states in the region.

Land use, water quality and ecological responses in Lake Colac – trends from Australia

Purpose - Recently, Colac Otway Shire in Australia released its management plan for Lake Colac, claiming over-enrichment of the lake with nutrients and degraded water quality. This paper aims to investigate these claims by establishing a correlation between key water and ecological indicators and land uses.

Design/methodology/approach - Examines the correlation between impairment and stressors in Lake Colac. This was achieved by identifying the likely sources of pollutants into Lake Colac; identifying any existing monitoring program; and characterizing the water and sediment inputs. The likely impacts of increased nutrients and sediment levels on indigenous flora and fauna were also examined. The use of meiofauna (very small benthic metazoan animals) was investigated as an indicator of degraded sites. Plankton diversity as a measure of water health was also assessed.

Findings - Water quality in Lake Colac was found to vary both temporally and spatially, and exhibited low attainment against acceptable trigger values/objectives. At current levels the lake can be classified as poorly degraded. Likely sources of pollution were identified to be related to land uses in the catchments. The biota of the lake, investigated at four study sites, yielded a sparse, benthic macrofaunal assemblage that was dominated by oligochaetes. In contrast, an abundant and taxonomically diverse meiofaunal assemblage was noted. Future meiofaunal analyses are likely to resolve suitable biotic indicator species of free-living nematodes in response to land use and waterway threats specified in the study. Originality value - This work will provide a better understanding of integrated environmental systems to enable development of best management practices, thus transforming the way the land and water are used in the future. Following the present work, other key water and ecological indicators (increased dispersion and dominance of biological species) at five additional sites were studied. Alternative management options for the effluent generated at Colac Sewage Treatment Plant and possible ecological effects of each option were also evaluated. More recently, a sediment characterization study was also carried out at sensitive sites representative of locations where build up of sediments and algae outbreaks are reported. This will enable classification of sediment and evaluation of dredging options.

Evaluating public risk preferences in forest land-use choices using multi-attribute utility theory

Forest policy decisions inherently involve multiple attributes and risk and uncertainty as they largely deal with complex biological, ecological, and socio-political systems. Identifying risk preferences and quantifying their inter-relationships and tradeoffs are useful in formulating better forest policy. Often, technocrats and experts deal with risky decisions, but ideally, stakeholder risk characteristics should be explicitly considered in making policy decisions. This paper analysed societal risk preferences on public forest land-use attributes using multi-attribute utility theory (MAUT). The results indicate significant risk-averse behaviour towards old-growth forest conservation and forest-based recreation but less risk-averse behaviour towards native timber extraction. Overall, the respondents preferred a more conservative forest land-use option, which is consistent with their risk attitudes. The method provides insights into risk preferences of forest stakeholders, which could lead to better understanding of forest management conflicts. Moreover, the method explicitly distinguishes the technical and value components of the decision and is useful in unravelling public risk preferences in multiple-use forest planning situations.

Unhealthy landscapes: policy recommendations on land use change and infectious disease emergence

Anthropogenic land use changes drive a range of infectious disease outbreaks and emergence events and modify the transmission of endemic infections. These drivers include agricultural encroachment, deforestation, road construction, dam building, irrigation, wetland modification, mining, the concentration or expansion of urban environments, coastal zone degradation, and other activities. These changes in turn cause a cascade of factors that exacerbate infectious disease emergence, such as forest fragmentation, disease introduction, pollution, poverty, and human migration. The Working Group on Land Use Change and Disease Emergence grew out of a special colloquium that convened international experts in infectious diseases, ecology, and environmental health to assess the current state of knowledge and to develop recommendations for addressing these environmental health challenges. The group established a systems model approach and priority lists of infectious diseases affected by ecologic degradation. Policy-relevant levels of the model include specific health risk factors, landscape or habitat change, and institutional (economic and behavioral) levels. The group recommended creating Centers of Excellence in Ecology and Health Research and Training, based at regional universities and/or research institutes with close links to the surrounding communities. The centers' objectives would be 3-fold: a) to provide information to local communities about the links between environmental change and public health ; b) to facilitate fully interdisciplinary research from a variety of natural, social, and health sciences and train professionals who can conduct interdisciplinary research ; and c) to engage in science-based communication and assessment for policy making toward sustainable health and ecosystems.

Land use change and impacts on nutrient loads using GIS

Land use change and its impacts on nutrient loads were investigated for the Glenelg-Hopkins Catchment in south-west Victoria, Australia. The study involved a cross-disciplinary approach comprising of remote sensing, Geographical Information Systems, spatial and statistical modelling to identify relationships between land use and stream water quality over a large regional catchment of 27,000 square kilometers.

Integrative catchment modelling of land use, turbidity, flow and geology

The thesis outlines and demonstrates the various aspects that contribute towards water quality management systems and the important use of storage/water quality models. The application of models is demonstrated through the functions that modelling components have on sustainable regional development, and through linkage with water quality systems.

Relationships of land use mix with walking for transport : do land uses and geographical scale matter?

Physical activity and public health recommendations now emphasize the creation of activity-friendly neighborhoods. Mixed land use in a neighborhood is important in this regard, as it reflects the availability of destinations to which residents can walk or ride bicycles, and thus is likely to contribute to residents’ active lifestyles that in turn will influence their overall health. Relationships between land use mix (LUM) and physical activity have not been apparent in some studies, which may be because geographical scale and the specificity of hypothesized environment–behavior associations are not taken into account. We compared the strength of association of four Geographic Information Systems-derived LUM measures with walking for transport and perceived proximity to destinations. We assessed physical activity behaviors of 2,506 adults in 154 Census Collection Districts (CCDs) in Adelaide, Australia, for which ‘‘original’’ LUM measures were calculated, and then refined by either: accounting for the geographic scale of measurement; including only the most-relevant land uses; or, both. The refined (but not the ‘‘original’’) LUM measures had significant associations with the frequency of walking for transport (p < 0.05) and area-corrected measures had significant associations with the duration of walking for transport. All LUM measures had significant associations with perceived proximity to destinations, but stronger associations were seen when using the refined measures compared with the original LUM. Identifying the LUM attributes most strongly associated with walking for transport is a priority and can inform environmental and policy initiatives that are needed to promote health-enhancing physical activity.

Preserving the environment and traditional communities : a land use change modeling approach

Human populations can cause serious damage to the natural environment. This, however, depends on the type of society and its size. Many traditional communities have a balanced relation with the environment, using practices for managing the soil, water and natural resources in order to satisfy their needs that are compatible to the general goals of environmental preservation.

The most usual approach to environmental conservation in the world sees human beings as intruders, potentially destroyers of the nature and, as a consequence, generally requires local population to be expelled from the protected regions. This situation has generated social conflicts because many protected areas, particularly in developing countries, are inhabited by indigenous or other traditional communities.

The disagreement about expelling or maintaining traditional communities in environmental conservation areas is strengthened by the lack of diagnostics on which changes are produced or suffered by communities in the region where they live. This paper presents a methodology developed to analyse land use dynamics in region with environmental conservation and traditional communities. We seek a better understanding of the way traditional communities use their space, the spatial pattern of land uses, which factors drive land use change, which impacts can be seen in those regions and identify the effects of conservation policies on land use dynamics.

The application of the method to the National Park of Superagui, Brazil, has successfully performed characterisation, analysis and simulation of land use dynamics in a region of environmental importance. Testing different scenarios has suggested that the adoption of a less restrictive policy for environmental conservation would have resulted in less social conflict with the same environmental efficiency than the established current policy.