This paper is based on the combination of a Geographic Information System (GIS) and tools or multi-criteria decision making (MCDM) methods in order to obtain the evaluation of the optimal placement ...of photovoltaic solar power plants in the area of Cartagena (Region of Murcia), in southeast Spain.
The combination GIS–MCDM generates an excellent analysis tool that allows for the creation of an extensive cartographic and alphanumeric database that will later be used by multi-criteria methodologies to simplify problems to solve and promote the use of multiple criteria.
In GIS two types of criteria will be reflected: constraints or restrictive criteria, and weighting criteria or factors. Constraints or restrictive criteria will make it possible to reduce the area of study by discarding those areas that prevent the implementation of renewable energy plants. These criteria will be obtained from the legislation (planning regulations, protected areas, road networks, railways, waterways, mountains, etc). Weighting criteria or factors will be those which, according to the objective to be reached, influence the ability to solve a concrete alternative. The choice of such criteria is marked by the influence presented to the overall goal; in this case they will be location, geomorphological, environmental and climatic criteria.
Through the use of MCDM the criteria or factors mentioned will be weighted in order to evaluate potential sites to locate a solar plant. Analysis and calculation of the weights of these factors will be conducted using Analytic Hierarchy Process (AHP). The assessment of the alternatives according to their degree of adequacy is carried out through the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution).
The purpose of this document is to provide guidance to new and inexperienced gazetteer builders, especially those constructing a digital gazetteer of historical places using historical maps, and in ...particular those building a gazetteer as a means to an end of answering specific research questions vs. those building a gazetteer as an end in itself to be used by the general research community. In support of this target audience, the following is an accumulation of lessons learned while using historical maps to create digital gazetteers of historical places. The lessons cover gazetteer planning, design, and construction issues. As an overview of how to use historical maps to create a digital gazetteer of historical places, this document can provide new and inexperienced gazetteer builders with starting points for in-depth study of these and associated issues. An example gazetteer is provided to illustrate the lessons covered here.
A quantitative understanding of the hydro-environmental factors that influence the occurrence of agricultural drought events would enable more strategic climate change adaptation and drought ...management plans. Practical drought hazard mapping remains challenging due to possible exclusion of the most pertinent drought drivers, and to the use of inadequate predictive models that cannot describe drought adequately. This research aims to develop new approaches to map agricultural drought hazard with state-of-the-art machine learning models, including classification and regression trees (CART), boosted regression trees (BRT), random forests (RF), multivariate adaptive regression splines (MARS), flexible discriminant analysis (FDA) and support vector machines (SVM). Hydro-environmental datasets were used to calculate the relative departure of soil moisture (RDSM) for eight severe droughts for drought-prone southeast Queensland, Australia, over the period 1994–2013. RDSM was then used to generate an agricultural drought inventory map. Eight hydro-environmental factors were used as potential predictors of drought. The goodness-of-fit and predictive performance of all models were evaluated using different threshold-dependent and threshold-independent methods, including the true skill statistic (TSS), Efficiency (E), F-score, and the area under the receiver operating characteristic curve (AUC-ROC). The RF model (AUC-ROC = 97.7%, TSS = 0.873, E = 0.929, F-score = 0.898) yielded the highest accuracy, while the FDA model (with AUC-ROC = 73.9%, TSS = 0.424, E = 0.719, F-score = 0.512) showed the worst performance. The plant available water holding capacity (PAWC), mean annual precipitation, and clay content were the most important variables to be used for predicting the agricultural drought. About 21.2% of the area is in high or very high drought risk classes, and therefore, warrant drought and environmental protection policies. Importantly, the models do not require data on the precipitation anomaly for any given drought year; the spatial patterns in AGH were consistent for all drought events, despite very different spatial patterns in precipitation anomaly among events. Such machine-learning approaches are able to construct an overall risk map, thus assisting in the adoption of a robust drought contingency planning measure not only for this area, but also, in other regions where drought presents a pressing challenge, including its influence on key practical dimensions of social, environmental and economic sustainability.
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•Spatial and temporal machine learning approaches proposed for drought risk mapping.•Performance of six machine learning models is compared.•MARS and RF are suitable machine learning models for spatial risk mapping•Approximately 26% of the study area is at high or very high drought risk.•New approach considers hydro-geo-environmental factors for drought risk policy.
This book focuses on the use of GIScience in conjunction with historical visual sources to resolve past scenarios. The themes, knowledge gained and methodologies conducted might be of interest to a ...variety of scholars from the social science and humanities disciplines.
Preparation of natural hazards maps are vital and essential for urban development. The main scope of this study is to synthesize natural hazard maps in a single multi-hazard map and thus to identify ...suitable areas for the urban development. The study area is the drainage basin of Xerias stream (Northeastern Peloponnesus, Greece) that has frequently suffered damages from landslides, floods and earthquakes.
Landslide, flood and seismic hazard assessment maps were separately generated and further combined by applying the Analytical Hierarchy Process (AHP) and utilizing a Geographical Information System (GIS) to produce a multi-hazard map. This map represents the potential suitability map for urban development in the study area and was evaluated by means of uncertainty analysis.
The outcome revealed that the most suitable areas are distributed in the southern part of the study area, where the landslide, flood and seismic hazards are at low and very low level. The uncertainty analysis shows small differences on the spatial distribution of the suitability zones. The produced suitability map for urban development proves a satisfactory agreement between the suitability zones and the landslide and flood phenomena that have affected the study area. Finally, 40% of the existing urban pattern boundaries and 60% of the current road network are located within the limits of low and very low suitability zones.
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•Individual landslide, flood and seismic hazard assessment maps are produced.•Natural hazard maps are created and correlated via multi-criteria analysis.•Suitable sites for urban development are selected using multi-hazard map.•Suitable area for urban development is located in the southern part of the study area.•Almost 40% of the urban area is located in the low to very low susceptibility zones.
Kota Malang dianugerahkan sebagai kota layak huni berdasarkan IAP dalam kajian Most Livable City Index di tahun 2017. Namun, perlu adanya kajian lebih lanjut dalam mengidentifikasi area mana saja ...yang masuk dalam kategori kelayakhunian tinggi, sedang, dan rendah di Kota Malang berdasarkan indikator fisik yang mengandung nilai spasial. Fokus dari penelitian ini adalah untuk mengidentifikasi dan menilai zona layak huni di Kota Malang. Metode yang digunakan pada penelitian ini adalah analisis skoring dan analisis spasial menggunakan bantuan GIS. Data-data yang digunakan adalah data sekunder dari instansi terkait serta hasil observasi kondisi eksisting Kota Malang.
•We used disparate data in a decision tree to refine the mapping of Irish peat soils.•Peat Associated Landcover Class concept was applied to locate converted peatlands.•Shallow peat soils ≥ 10 cm ...were included in the new Irish Peat Soils Map (IPSM).•The IPSM shows a larger peat area than previous peat maps and accuracies ≥ 74 %.•The Adaptative Mapping Framework implemented can be applied in other regions.
Accurate mapping for effective management of peat soils is necessary to help reduce GHG emissions and improve environmental quality. However, mapping remains a major challenge as definitions of peat soils vary substantially between jurisdictions and organizations, while field data are sparse and difficult to produce, and remote sensing of limited use for converted peatlands. Using an Adaptive Mapping Framework, this paper compiles disparate data sources to update the Derived Irish Peat Map to better facilitate its application for environmental issues. This includes incorporation of areas considered to be underlain by shallow peat soils (≥ 10 cm and ≥ 8.6 % Organic Matter content), and augmentation of the overall test dataset with an additional ∼ 20,000 points.
The workflow for map generation employed 20 Decision Tree Output Maps (DTOMs), aggregated into 33 Map Combinations (MCs). These facilitated the addition of new areas and removal of areas where the presence of peat could not be confidently identified. The MC selected for the update had the highest accuracy metrics (≥ 74 %), consisting of DTOMs with a user accuracy ≥ 66 % and assessed over a minimum number of test points ≥ 50. The resulting map reveals peat to underlie 1.66 M ha of Ireland (∼ 23.3 % of the country), identified with values of 83 % for overall accuracy and F1 score for peat areas. This extent is 13.2 % larger than that delineated in previous versions and at least 23.2 % larger than areas presented in other previous maps. The methodology also allows transparency from which data sources can be distinguished to define different key peat thickness ranges (≥ 10 cm, ≥ 30–40 cm), better facilitating assessment of environmental impacts arising from land use change.
This approach has potential relevance for peat mapping globally, notably in areas containing disparate datasets (e.g., land cover, soil map, etc.), or employing different production methods. The accuracy metrics generated also suggest that the approach can be used as a basis for implementing or updating national and international regulations concerning carbon-rich soils in comparable settings to those encountered in Ireland.
Air pollution is gradually becoming a major health concern globally and Nigeria is especially susceptible to air pollution Available data indicates that vehicular traffics, industries, wildfire and ...biomass burning are significant sources of air pollutants such as Particulate Matter PM, Carbon Monoxide CO, Nitrogen Dioxide NO2, Sulphur Dioxide SO2 and Volatile Organic Compounds VOCs in the air in Lagos State. The aim of this study is to perform geospatial modelling of air pollution around Olusosun and Solous dumpsites in Lagos State. The study analyses, assesses, and predicts air pollution emission in these dumpsites and examines their possible health impact on residents. Using both ground and satellite-based data, different GIS techniques were used to model this pollution concentration. These methods include Kriging, Regression, and Landfill Gas Emissions Model (LANDGEM) which helps to analyse, model and predict the air pollutant levels around these dumpsite. The average pollution level of Particulate Matter with a diameter that is 2.5 micrometers (PM2.5) in Olusosun was 94.29 μg/m3 while those in Solous was 94.12 μg/m3 over a 24 h period. This is way above the Air Quality Guideline recommended by the WHO which is 15 μg/m3 over a 24 h period. This is similar to the high pollution level of NO2 which was 237.64 μg/m3 in Olusosun and 255.84 μg/m3 in Solous as against the WHO Air Quality Guideline of 25 μg/m3 over a 24 h period. SO2 level is also varyingly high in Olusosun and Solous. The reading of 109.27 μg/m3 in Olusosun is considerably high as compared to the reading of 43.82 μg/m3 in Solous. However, both readings are relatively higher than the Air Quality Guideline recommended by the WHO which was 40 μg/m3. The CO air quality level of 0.55 mg/m3 in Olusosun and 0.52 mg/m3 in Solous is within the accepted level of the Air Quality Guideline recommended by the WHO. This shows that CO is not a pollution threat in the major dumpsites in Lagos. This is similar to the readings of PM5 and PM10 which are within the WHO Air Quality Guidelines over a 24 h period. The Moderate Resolution Imaging Spectroradiometer (MODIS) data shows a trend of increasing concentration of PM2.5 over the 5 study months due to an increase in the quantity of waste disposal, which shows that high waste disposal is directly proportional to high level of PM2.5. It is recommended that living farther (more than 15 km) away from the dumpsites can reduce the high risk of air pollution and its related diseases for residents. Also, there is need for proper incineration and maintenance of waste to reduce the level of air and other pollutants in and around the dumpsites.
•More than one-third of the world's land area is prone to flooding which consequently affects about 82% of the world's population.•Flooding in Ghana has resulted in a high impact and concerns within ...various communities.•A GIS-based approach is used to delineate flood-prone areas via identification and grading from Digital Elevation Models (DEMs).•Accurate assessment and prediction of flood prone zones is achieved for the Tarkwa mining area of Ghana.
Flood is one of the most imperious natural hazards that can cause economic damages to infrastructures and natural ecosystems. In view of the extensive mining activities in the Tarkwa area, there has been an increase in human intervention of natural water bodies via degradation of vegetation in the watershed area, inappropriate land-use change, soil erosion and expansion of paved surface area for settlement and industrialisation. This has increased the degree of flood susceptibility within the area, with major flood incidents recorded on a timely basis. In this study, a GIS-based approach was utilised to delineate flood-prone zone within the Tarkwa mining area using Digital Elevation Models (DEMs). A DEM-derived morphologic features including local slope and streamflow network were developed using ArcGIS. The flood susceptible map was generated by merging the slope map and the stream network maps. The results indicate that about 42.59% of the study area were highly prone to flooding. The areas susceptible to flooding were mainly made up of agricultural lands with high usage of chemical fertilizers for farming, which may leach into nearby rivers, streams, lakes and groundwater during flood occurrence. It is understood from this study that the mining areas within the Tarkwa Nsuaem municipality were less susceptible to flooding. The outcome of this study provides a simplified method of mapping and assessment of flood susceptible areas which can be used as a reference for flood risk management, prevention, and reduction of natural disasters in the study area.
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