High Potential Areas Research Articles

GIS-based ranking and categorization of potential impact on drought as disaster mitigation effort in Bandung Barat Regency (KBB) using Simple Additive Weighting (SAW)

Drought is a disaster that has a significant impact on agriculture, economics, health and the environment, and many other aspects of life all including Kabupaten Bandung Barat (KBB), Indonesia. The Regional Disaster Management Agency (BPBD) of KBB shows that in 2018, over 92,780 houses in 47 villages were affected by drought. This study aims to predict which area in KBB will be impacted by drought using Geographical Information System (GIS). Previous studies have shown much evidence that GIS will work, but none were done in Indonesia. We use the Simple Additive Weighting (SAW) method to create the ranking, categorization, and information on potential droughts. The method analyses historical drought impact, rainfall densities, water resources, rivers, and lakes availability, and settlement area. At the end of this study, we successfully categorize 162 villages into 4 categories. Accuracy on the result is also tested using real data from 2018, which resulted in 70.21% accuracy out compared to all 47 villages that were affected in 2018. An increase in accuracy of 72.50% also highlighted when comparing the result of very high potential and high potential area affected by drought with the 2018 data. Furthermore, a convincing 100% accuracy was obtained when comparing the top-10 data of very high potential in droughts and 2018 data. As our future recommendation, We suggest more parameters to be included in the calculations and also to use a 3-dimensional GIS approach as a tool to visualize the information.

The Archaeology of Inundated Cultural Landscapes in Freshwater Lake Systems: Preliminary Insights from a Multi-Methods Study in the Kawartha Lakes Region, Ontario

In this paper, we review the goals, methods, and results of our modelling of the shoreline history and archaeological survey of the inundated portions of a freshwater lake system within the Lake Ontario watershed of south-central Ontario, Canada. We first review the character of the regional archaeological record and highlight the likelihood that the relatively few documented sites in this region before 6000 cal BP is due to landscape inundation from shoreline transgression. The first part of our analytical work focuses on the derivation of paleoshoreline models to identified now flooded, but formerly inhabitable landscapes. The second phase of our work reports on the shallow water survey of high potential areas. We documented over 1000 artifacts in a set of targeted surveys, including the presence of material diagnostic of the early Holocene, which is underrepresented in the terrestrial record. The results of our work emphasize the importance of evaluating the potential for cultural landscape inundation in freshwater lake systems and, when so identified, how underwater surveys contribute to regional studies of hunter-gatherer settlement and land use patterns.

Evaluation of groundwater potential using Dempster-Shafer model and sensitivity analysis of effective factors: A case study of north Khuzestan province

In order to optimize the management of groundwater resources, accurate measurement of groundwater potential is necessary. Application of learning models and remote sensing is very encouraging in reducing the costs of groundwater potential measurement. In this research, Dempster-Shafer learning model and remote sensing data are used to evaluate the groundwater potential in the north of Khuzestan. The study area has a semi-arid climate and is mostly covered by quaternary sediments except for the north, which is mountainous and different geological formations are seen there. For this purpose, 9 parameter layers including: lithology, soil type, slope percent, land use, altitude, TWI index, lineament density, river density and distance from the river as the most effective parameters in groundwater potential are prepared. Additionally, 474 wells in high potential areas have been selected as suitable real data for training and testing of the model. In the training phase, the weights of the layers were calculated using Dempster-Shafer model based on real data of 70% of wells then the groundwater potential map was obtained by combining the weighted layers. To confirm the efficiency of the model and the accuracy of the groundwater potential map, the ROC curve is plotted on the basis of 30% of wells that were not used during the training phase. The results show that the final groundwater potential map is 86% accurate. After verifying the efficiency of the model, sensitivity analysis of effective parameters in predicting groundwater potential is performed using map removal sensitivity analysis method. The results show that all of the considered parameters have a positive effect on groundwater potential prediction accuracy. However, lithology, soil type, and slope percent are the most effective on the accuracy of the model.

Combining fuzzy analytic hierarchy process with concentration–area fractal for mineral prospectivity mapping: A case study involving Qinling orogenic belt in central China

We combined cluster analysis, the fuzzy analytic hierarchy process (fuzzy AHP), and the concentration–area (C-A) fractal for mineral prospectivity mapping. First, cluster analysis was used to determine the indicator elements for orogenic Au deposits (omitting redundant geochemical elements). Subsequently, according to pairwise comparisons of mineralization alternatives performed by three exploration experts, a series of fuzzy evaluation matrices were constructed, and the corresponding normalized weights were calculated. Furthermore, on the basis of the multifractal theory, two thresholds for each alternative were obtained (each alternative was divided into a background region, a general anomaly region, and a high anomaly region), and the fuzzy membership function was used to obtain the normalized score of each alternative. Finally, the weight of each alternative was multiplied by the normalized score, and fuzzy superposition was employed to generate a mineralization prediction map, which consisted of high, medium, low, and weak metallogenic potential areas, accounting for 7.05%, 19.67%, 40.99%, and 32.29% of the study area, which contained 4, 1, 1, and 0 of the six known mine occurrences, respectively. The prediction area (P-A) plot indicated that the result predicted 83.3% of Au deposits with an area of 16.7%, indicating that the combination of cluster analysis, the fuzzy AHP, and the concentration–area method is an efficient and economical forecasting method that has guiding significance for mineral prospectivity mapping (MPM).

The first radon potential map of the Campania region (southern Italy)

This is the first paper to report a potential map of radon (222Rn) distribution in the Campania region of southern Italy, using the geostatistical kriging interpolation method using QGIS® software. The response variable is the 222Rn indoor measurements, whereas proxy variables used as predictors are: geology, faults, soils permeability, meteorological/climatic parameters, 238U distribution, 222Rn emanation coefficients and exhalation rates, 226Ra in building materials and gamma dose rate in dwellings. The map shows high radon potential areas in correspondence to the main volcanic centres and the faults network of the region. The map is a useful instrument to identify radon-prone areas and evaluate radon risk level for the population.

Prospectivity modelling of Canadian magmatic Ni (±Cu ± Co ± PGE) sulphide mineral systems

New mineral deposit discoveries are required to meet the forecasted demand for some critical raw materials. Governments are responding to that challenge by investing in mineral systems research and by by making government geoscience datasets freely available to the public and explorers. However, translating conceptual mineral system models to mappable geological, geochemical, and geophysical proxies is difficult with incomplete data of variable quality from modern and legacy surveys. Herein we address those knowledge gaps and propose a new open source workflow in R for prospectivity modelling using public geoscience datasets. We focus on the largest footprints of magmatic Ni (±Cu) sulphide mineral systems and their critical raw materials (±Co ± PGE). Multiple prospectivity models are presented, including data-driven methods (e.g., weights of evidence, gradient boosting machines) that use the features of known mineral occurrences as a training set and a hybrid method that also incorporates conceptual mineral system criteria. All models are validated using data from northern Canada (i.e., north of 60° latitude) as a test set. Statistical analysis of the prospectivity results suggests that rock types and geological ages are two of the most important predictive datasets, which correspond to the sources and drivers within the mineral system framework, respectively. Variable importance plots further suggest that geological boundaries (e.g., horizontal gradient magnitude of the gravity data and multi–scale edges) and the close spatial association between areas of high mineral potential and the edges of thick continental crust represent prospective ore-forming pathways. Model performance and the best combination of predictors and hyperparameters for each model are based on the receiver operating characteristics (ROC) plots, which yield a range of area under the curve (AUC) from 0.846 to 0.923 for the spatially independent test set. Most Canadian geological provinces, possibly with the exception of the Grenville orogen for the hybrid and weights of evidence methods (AUC = 0.716–0.726), yield comparable model performance, suggesting that the heterogeneous spatial distribution of different mineral system sub-types (e.g., komatiite-associated, rift-related, Alaskan-type, and hydrothermal awaruite) have a relatively minor impact on the prospectivity results. Monte Carlo-type simulations further suggest that the expert weightings used in the hybrid method (AUC = 0.843) are only slightly better than an average model constructed from random combinations of weightings (AUC = 0.809). The general agreement between different methods and multiple iterations of the same model demonstrate that public geoscience datasets can effectively reduce the search space to support mineral exploration targeting (i.e., less than 8% of map pixels contain more than 80% of the known Ni mineralization). However, vast segments of the Canadian landmass have not undergone systematic geological surveying or data acquisition. Prospectivity modelling can thus also be used by governments and academia to prioritize areas for future targeted geoscience research.

Determination of Fishing Grounds Distribution of the Indian Mackerel in Malaysia’s Exclusive Economic Zone Off South China Sea Using Boosted Regression Trees Model

With the ongoing climate change affecting the ocean, there is a need to understand and predict the future distributions of marine species in order to assess the sustainability of marine ecosystem. In this study, remotely-sensed satellite oceanographic data together with Indian mackerel (Rastrelliger kanagurta) fishery dataset were used to predict potential fishing grounds in the Exclusive Economic Zone (EEZ) of Peninsular Malaysia using boosted regression trees (BRT) model. The model was developed using three years (2008–2010) fish catch data and environmental variables of chlorophyll-a (chl-a), sea surface temperature (SST) and sea surface height (SSH). Result indicated that potential fishing grounds were closely associated with SSH, followed by SST and chl-a. The performance of the BRT model indicated acceptable fishing grounds prediction accuracy (AUC value of 0.749). Seasonal variability in fishing grounds was related to favorable environmental conditions of SSH (1.1–1.3 m), SST (29–32 °C) and chl-a (0.3–0.6 mg/m3). The projection of increases in SST due to climate change according to IPCC-AR5-RCPs was observed to influence the spatial and temporal distributions R. kanagurta. Increased temperature at 1.80 °C resulted in high potential catch areas for R. kanagurta in the EEZ. Meanwhile, elevated temperature at 2.60 °C and 3.30 °C showed decreased in potential catch areas for R. kanagurta in the EEZ. Most of the future fishing grounds area were projected to decline, and it was observed to shift outside the EEZ off South China Sea. Hence, by understanding these relationships, this analysis identifies where strategies can be adapted to face the ecological impacts under changing environmental conditions.

Regulations applicable to ecotourism in an emerging destination: the case of Sabana Occidente Cundinamarca geographical region

A review of current regulations of ecotourism is done, finding that ecotourism legislation in Colombia is included in tourism legislation and national environmental legislation. Normative context of ecotourism applicable in Sabana Occidente Province of Cundinamarca is identified. Sabana Occidente has small natural areas of high ecotourism potential that require protection and development. Ecotourism activities, subject to regulations established for ecological tourism, are conditioned by the current status of natural areas and local tourism development plans.

Mapping smouldering fire potential in boreal peatlands and assessing interactions with the wildland–human interface in Alberta, Canada

Treed peatlands exhibit both crown and smouldering fire potential; however, neither are included in Canadian wildfire management models and, as such, they are not formally represented in management decision-making. The lack of smouldering fire risk assessment is a critical research gap as these fires can represent heavy resource draws and are predominant sources of smoke, air pollutants and atmospheric carbon. Here, for the first time, we combine existing knowledge of the controls on smouldering peat fire with expert opinion-based weightings through a multi-criteria decision analysis, to map the smouldering fire potential (i.e. hazard) of treed peatlands in the Boreal Plains, Alberta, Canada. We find that smouldering potential varies considerably between treed peatlands and that areas of sparser peatland coverage may contain high smouldering-potential peatlands. Further, we find that treed peatlands are a common feature in the wildland–human interface and that proportionally, the area of high smouldering potential is greater closer to roads compared with farther away. Our approach enables a quantitative measure of smouldering fire potential and evidences the need to incorporate peatland–wildfire interactions into wildfire management operations. We suggest that similar frameworks could be used in other peatland dominated regions as part of smouldering fire risk assessments.

The firewall between Cerrado and Amazonia: Interaction of temperature and fire govern seed recruitment in a Neotropical savanna

AbstractQuestionsModels predicting the distribution of savannas worldwide have identified rainfall and fire as their primary determinants. However, most of them have relied upon adult traits, while juvenile traits, at the bottleneck of the plant's life cycle, have been largely overlooked. We developed a novel mechanistic model based on the effects of temperature and fire on germination traits to predict the distribution of Cerrado, i.e., the largest neotropical savanna.LocationCerrado and neighboring biomes.MethodsWe compiled data on the germination of seeds subjected to temperature and heat shock treatments and used generalized additive mixed models to predict germination potential as a function of temperature, species, physiognomy (forest/savanna), habits (herbs/shrubs/trees), and fire frequency.ResultsThe best model showed that seasonal temperatures set the germination limits for seeds of both savanna and forest physiognomies. Forest seeds presented a higher germinability in the optimum temperature range, but savanna seeds had higher survival rates after heat shocks. The model revealed that the southern limit of Cerrado is determined by low winter temperatures, while the western and eastern boundaries are set by high summer temperatures. The model also predicted an area of high germination potential that coincides with high biodiversity and climate stability in the Cerrado.ConclusionsGermination traits are highly valuable to predict vegetation responses to climate. Seasonal temperatures are primary determinants of the Cerrado’s extent, while fire favors the recruitment of savanna species over the Cerrado–Amazonia ecotone. Global warming may significantly impact the germination potential of native species.

DESIGN FOR THE DEPOPULATING LANDSCAPE: A RETROFIT APPROACH TO URBAN REGENERATION IN JOHNSTOWN, PENNSYLVANIA, USA

Over the last 50 years, 370 large cities worldwide have severely depopulated, or shrunk, by at least 10%. Johnstown, Pennsylvania, is the third fastest U.S. shrinking city. Primarily a victim of deindustrialization, Johnstown faces severe decline issues related to depopulation, including social disorder and lowered quality of life. This project develops a framework for urban design for shrinking cities, integrating permanent functions into high development potential areas but temporary functions into declining areas. This approach allows for future development to occur through time as the city recovers. Using a GIS-based weighted overlay model to assess the threat level of decline, 4 sites were identified and strategies for each were developed. Master plans to retrofit new functions integrating residents' desire and demands into vacant / abandoned properties were then generated for each site. Rather than chasing hefty attempted quick-hitting developmental incentives, this approach will bring new long-term economic engines and lifestyles to the city due to a diversity in the economic base; it also pays attention to the social dimension of urban regeneration by providing a structured way to promoting social justice and equity in shrinking cities.

Detection of high potential areas of persian oak forests decline in Zagros, Iran, using topsis method

ABSTRACT Background: During the past decade, the phenomenon of Oak decline has affected valuable Zagros Oak Forests in western Iran. Quercus brantii as the most important tree species of these forests has been damaged more than any other species. Many factors are involved in this phenomenon. The purpose of this study was to identify areas with high potential for decline and determine the most important factors affecting it. In this study, using multi-criteria evaluation methods based on the Geographic Information System (GIS) Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and fuzzy logic, the map of decline potential of two selected stands (Dalab and Cheghasabz) in Ilam Province was prepared to reveal the high-risk areas of decline. The analytical hierarchical process was used to determine the weight of the factors. Results: The results showed that both selected stands had decline potential. However, the Dalab stand at 25% and the Cheghasabz, at approximately 60% of the stand has an extreme potential for decline. Rainfall factors, pests, and diseases also have the greatest effect on Oak forest decline. Conclusion: Due to socio-economic problems such as land use change, fire, tourism, grazing, and pruning, the Cheghasabz is more prone to decline than the Dalab, which was a forest reserve. The multi-criteria evaluation model used in the study can be a guide in identifying high-risk areas in other parts of the Zagros forests. The large area of critical areas in these two regions reveals the need for planning to implement support operations to reconstruct damaged ecosystems.

Designing conduit sabo dam series as a debris flow protection structure

A high potential area for landslides was identified upstream of the Air Beras River on Bukit Beriti Besar which was feared to generate debris flow through the Air Beras River. One of the preventive efforts that can be conducted for debris flow is the sabo dam. This study aims to design a series of conduit sabo dams and evaluate the structure stability according to SNI 2851:2015 and Technical Standards and Guidelines for Planning and Design of Sabo Structures (JICA, 2010). By using the design discharge of debris flow of 120 m3/s, the velocity of 5.06 m/s, and the inclination of the riverbed of around 6.16°, the spillway height of the Sabo Dam 1 was determined to be 3 m, while the spillway height of Sabo Dam 1 was 2 m. The Sabo Dam 1 has a height of 10 m and a width of 30 m with a total manageable volume of 49,600 m3 while the Sabo Dam 2 has a height of 10 m and a width of 45 m with a total manageable volume of 91,500 m3. The safety factors of the sabo dam in the debris flow condition were 2.14 for overturning, 1.50 for sliding, and 5.74 for bearing capacity. Based on the result, the conduit sabo dam series effectively controls the destructive power of debris flow.

Mineralogical geochemical characteristics and resource potential of copper ore in the Lang Chanh area, Thanh Hoa Province

Lang Chanh area, Thanh Hoa province, is considered a high potential area of copper deposits such as the Lang Van, Lang Trang, and Lang Hac copper occurrences. Based on published data and our supplement analyses of 5 thin sections, 4 thick sections, and 2 scanning electron microscope samples, we found that the copper mineralization had formed from hydrothermal activities at moderate-high temperature, belonging to quartz-copper-sulfur-polymetallic, magnetite-sulfur-copper (Lang Van, Lang Trang), and quartz-sulfur-copper (Lang Hac) mineral deposit types. The mineral composition was quite simple: pyrite, chalcopyrite, pyrrhotite, covelline, galenite, sphalerite, melnicovite, gothite, and magnetite. Non-ore minerals were quartz, rarely chlorite, siderite, sphene, garnet, and calcite. The copper contents in orebodies varied from low to high values, with average contents ranging from 0.20 to 7.45 (%). In the Lang Chanh area, 17 copper ore bodies were discovered and distributed in 9 mineralized zones, belonging to three areas of Lang Van, Lang Hac, Lang Trang, and some gabbro boulders the Nui Chua complex with disseminated chalcopyrite. Using linear calculation method for metallization parameters and Huvo methods to estimate gold resources in the study area, resulted in 1.44 million tons of Cu-metal. These results provided an overview of the prospect of copper resources, serving as a basis for determining the Cu prospective areas in Lang Chanh, Thanh Hoa province.

Perakende Market Lokasyonları için CBS Tabanlı Çok Kriterli AHP Yöntemi ile Optimal Yer Seçimi Analizi: İstanbul Örneği

Optimal selection of possible chain market locations is still an ongoing interest. A significant number of newly founded markets are suffering from low profitability and cannibalism. Contrary to the traditional methods which are based on personal experience or instincts, quantitative methods which employ Geographic Information Systems (GIS) and large data sets have proved to be more efficient to determine the most profitable and market locations. On the other hand, the larger the scale of the data set, the more prone it is to possible inconsistencies. In this study, we employ the largest available GIS data set for selection of chain market locations in İstanbul and carry out an extensive consistency test for the whole data set. A wide range of 23 attributes were incorporated into the analysis and Analytical Hierarchy Process (AHP) was used to determine the optimal locations. The results were also confirmed by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The results show that 218 out of 7196 markets are already located high potential areas determined in the analysis and there is still a potential to establish new markets in 75 high potential areas according to our analysis.

TIPOLOGI KERUSAKAN BANGUNAN AKIBAT CUACA EKSTREM STUDI KASUS CUACA EKSTREM KABUPATEN BANTUL 2019

The threat of disaster is unavoidable in Indonesia. In 2018, for example, 2,564 disasters occurred in which no city / district in Indonesia was free from threats. Statistical data shows that more than 90% of disasters in Indonesia are included in the hydrometereological disaster category, which has continued to increase over the past 15 years. Even in the early half of 2020, there were 256 disasters with 99% of them being hydrometereological disasters such as floods, landslides and tornadoes. The existence of extreme weather events in Bantul Regency in 2019 shows that the dangers of hydrometereology can cause considerable harm to the community. There needs to be a study to find out how to mitigate hydrometereological disasters which are the most common hazards in Indonesia. Analysis of building damage and disaster data needs to be carried out to determine the characteristics of the impact of extreme weather on buildings, to identify building elements that are vulnerable to damage, to provide anticipatory measures and alertness to extreme weather in Indonesia. Building damage data is grouped and processed in graphical form to read information patterns as material for analysis. The results of the study show that there are things that must be done in the face of extreme weather including: choosing the quality of materials and the strength of the construction of the building, attention to building elements, especially the back of the building (kitchen & bathroom), walls, and foundations, high vigilance in the area steep contours and highlands, need to be vigilant with all elements of society in areas of high potential for extreme weather, and the need to pay attention to vulnerable groups of the elderly and children.

Optimization of statistical and machine learning hybrid models for groundwater potential mapping

Determining areas of high groundwater potential is important for exploitation, management, and protection of water resources. This study assesses the spatial distribution of groundwater potential in the Zarrinehroud watershed of Kurdistan Province, Iran using combinations of five statistical and machine learning algorithms – frequency ratio (FR), radial basis function (RBF), index of entropy (IOE), evidential belief function (EBF) and fuzzy art map (FAM). To accomplish this, 1448 well locations in the study area were randomly divided into two data sets for training (70%= 1013 locations) and validation (30%= 435 locations) based on the holdout method. Fourteen factors that can affect the presence or absence of groundwater were identified, measured, and mapped using ArcGIS and SAGA-GIS software. The models were used to predict the locations of groundwater based on suitable combinations of the conditioning factors to produce groundwater potential maps. The probability of groundwater at any location was classified as low, moderate, high, or very high based on natural breaks in the data spectrum. The model predictions were tested for validity and their success was determined using receiver operating characteristic (ROC) curves, standard errors (SE), positive predictive value (PPV), negative predictive value (NPV), sensitivity (SST), specificity (SPF) and accuracy (ACC), and the Friedman test. The performance assessments of groundwater potential predictions using the area under the curve (AUC) and accuracy (ACC) showed that the FR-RBF model had very good performance (AUC= 0.889, ACC= 87.51). FR-FAM (AUC= 0.869, ACC= 84.67), EBF-FAM (AUC= 0.864, ACC= 84.42), EBF-RBF (AUC= 0.854, ACC= 83.94), FR-IOE (AUC= 0.836, ACC= 83.62), and EBF-IOE (AUC= 0.833, ACC= 80.42) also had acceptable performance. The results of the Friedman test also show that there are significant differences between the models and the highest mean rank was generated by the FR-FAM model (3.642). Therefore, the hybrid models can be used to increase the accuracy of groundwater-prediction models in the study region and perhaps in similar settings. Highlights The groundwater potential was studied in the area of Zarrinehroud watershed A combination of methods including FR, RBF, IOE, EBF and FAM Very high and high groundwater potential areas were located in the northern half The development of hybrid models can increase the accuracy of the results

Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing

Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of urban flooding or waterlogging in urban areas. The high rate of urbanization has caused waterlogging and urban flooding in many parts of Dhaka city. Therefore, the study is undertaken to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. The five-decadal LULC has been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, and water bodies for the years 1978, 1988, 1998, 2007, and 2018. Significant changes in LULC for the study area from 1978–2018 are observed as 13.1%, 4.8%, and 7.8% reduction in agricultural land, green spaces, and water bodies, respectively, and a 22.1% increase in the built-up area is estimated. Within Dhaka city, 14.6%, 16.0%, and 12.3% reduction in agricultural land, green spaces, and water bodies, respectively, and a radical increase of 41.9% in built-up area are reckoned. The decadal runoff assessment has been carried out using the NRCS-CN method, considering an extreme rainfall event of 341 mm/day (13 September 2004). The catchment area under very high runoff category is observed as 159.5 km2 (1978) and 318.3 km2 (2018), whereas, for Dhaka city, the setting is dynamic as the area under the very high runoff category has increased from 74.24 km2 (24.44%) to 174.23 km2 (57.36%) in years 1978 and 2018, respectively, and, mostly, the very high runoff potential areas correspond to the dense built-up surfaces.

Dynamic analysis and sizing optimization of a pumped hydroelectric storage-integrated hybrid PV/Wind system: A case study

The intermittent nature of variable renewable energy resources in conjunction with the fluctuating energy demand of load require using an efficient long-term energy storage means. Pumped Hydroelectric Storage (PHS) has proved its commercial viability as electricity storage technology and eligibility to be coupled with the Renewable Energy Systems (RESs). This paper proposes a simple and efficient procedure for optimal sizing of PHS-integrated hybrid PV/Wind power system for providing sustainable supply of electricity to an urban community in Brack city (27°32'N,14°17'E), Libya. The sizing procedure is considered as a constrained optimization problem. The constraints are developed to consider the operating conditions and the output uncertainty of RESs. The sizing algorithm and optimization procedure are explicitly described. Different operating scenarios were considered to identify the optimal size of the hybrid PV/Wind energy system and PHS. Using the measured date of climate conditions and load consumption, the energy production for different sizes of solar PV arrays and wind turbine farms were estimated by System Advisory Model (SAM) software. Based on the Levelized Cost Of Energy (LCOE), the optimum power capacity ratio of PV array to wind turbines farm was 1:5. For the system of optimal size, PHS contribute with a share of 15 % in covering the annual load energy. The obtained results revealed that coupling the hybrid RESs with PHS is cost competitive and reliable alternative for providing sustainable energy supply to urban areas of suitable topographical conditions and high potential of renewable energy resources.

Development of the Ontario Forest Resources Inventory: a historical review

The Forest Resources Inventory provides the base layer to support decision-making for a variety of stakeholders in Ontario, Canada. The inventory is used to identify areas of high economic potential, endangered species habitat, and recreational opportunities. As technology evolves, the inventory creation process has changed. From fully manual efforts conducted in the era before planes or roads to hand-drawn sketches made aboard early aircraft, the early inventory program was designed to provide a rough context of timber availability. As society changed, more was asked of the inventory, and ecological and biological features were added. With a land area larger than many European countries to inventory, the creation of an accurate forest inventory in Ontario is a technological and logistical challenge. Although the acquisition technology and strategy have changed over time, the goal of providing an improved understanding into the extent and distribution of natural resources in the province of Ontario has not changed. This review aims to provide a comprehensive look at the history of these inventory efforts in Ontario, as well as provide some context for why the inventory contains the attributes it does today.