In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest a...In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.展开更多
The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication e...The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R<sup>2</sup> of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.展开更多
Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose tissues.OA presents diverse clinical phenotypes and distinct molecular endotypes,...Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose tissues.OA presents diverse clinical phenotypes and distinct molecular endotypes,including inflammatory,metabolic,mechanical,genetic,and synovial variants.Consequently,innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches.Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints,causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues.This issue has led to standardization difficulties and hindered the success of clinical trials.Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues,encompassing DNA,RNA,metabolites,and proteins,as well as their chemical properties,elemental composition,and mechanical attributes,can contribute to a more comprehensive understanding of the disease subtypes.Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment,providing a more holistic view of cellular function.Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various-omics lenses,such as genomics,transcriptomics,proteomics,and metabolomics,with spatial data.This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates.Furthermore,advanced imaging techniques,including high-resolution microscopy,hyperspectral imaging,and mass spectrometry imaging,enable the visualization and analysis of the spatial distribution of biomolecules,cells,and tissues.Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes.This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis.It explores their applications,challenges,and potential opportunities in the field of OA.Additionally,this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.展开更多
On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage ...On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.展开更多
Check dams are widely used on the Loess Plateau in China to control soil and water losses,develop agricultural land,and improve watershed ecology.Detailed information on the number and spatial distribution of check da...Check dams are widely used on the Loess Plateau in China to control soil and water losses,develop agricultural land,and improve watershed ecology.Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams.Thus,this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis.First,we made a sample dataset of check dams using GaoFen-2(GF-2)and Google Earth images.Next,we evaluated five popular deep-learning-based object detectors,including Faster R-CNN,You Only Look Once(version 3)(YOLOv3),Cascade R-CNN,YOLOX,and VarifocalNet(VFNet),to identify the best one for check dam detection.Finally,we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results.Precision,recall,average precision at intersection over union(IoU)threshold of 0.50(AP_(50)),IoU threshold of 0.75(AP_(75)),and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step(AP_(50-95)),and inference time were used to evaluate model performance.All the five deep learning networks could identify check dams quickly and accurately,with AP_(50-95),AP_(50),and AP_(75)values higher than 60.0%,90.0%,and 70.0%,respectively,except for YOLOv3.The VFNet had the best performance,followed by YOLOX.The proposed framework was tested in the Yanhe River Basin and yielded promising results,with a recall rate of 87.0%for 521 check dams.Furthermore,the geographic analysis deleted about 50%of the false detection boxes,increasing the identification accuracy of check dams from 78.6%to 87.6%.Simultaneously,this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets.The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.展开更多
Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only sp...Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only species distribution models are commonly used in these evaluations.The maximum entropy algorithm(MaxEnt)has gained popularity for modelling species distribution.Here,MaxEnt was used to model the spatial distribution of the Mexican pine bark beetle(Dendroctonus mexicanus)in a daily fashion by using forecast data from the Weather Research and Forecasting model.This study aimed to exploit freely available geographic and environmental data and software and thus provide a pathway to overcome the lack of costly data and technical guidance that are a challenge to implementing national monitoring and management strategies in developing countries.Our results showed overall agreement values between 60 and 87%.The results of this research can be used for D.mexicanus monitoring and management and may aid as a model to monitor similar species.展开更多
Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely b...Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely beennon-spatial, reducing the ability to find spatial relationships between countries and SDGs to help cooperationand proffer country-specific interventions. This study adopted techniques of exploratory and inferential spatialstatistics to assess the successes of African countries from 2016 to 2020 in achieving the goals of sustainable de-velopment. Also, the study sought to understand how the spatial synergies and trade-offs between SDGs vary percountry and time. The results revealed that spatial hotspots of countries with high SDGs scores were mostly con-fined to northern African countries with significant coldspots within central and eastern Africa and few patchesin western and southern Africa for 2016. In 2020, the number of countries forming hotspots reduced, with Cen-tral African countries as significant cold spots. Five main spatial relationships: positive linear, negative linear,concave, convex and undefined complex, were found among countries and the SDGs. However, these spatialrelationships were fluid as they changed over time and with different levels of influence from 2016 to 2020.The study concludes that generic solutions and policies by development agencies, governments, developmentfinance instiutions and other impact investors will not be enough in achieving the SDGs because of the spatialheterogeneity of the continent. Tailored and country-specific policies based on results of spatial statistics matter.展开更多
Sorghum is one of the most widely cultivated cereal crops in Ethiopia which is grown for food and feed uses. It’s far an indigenous crop that’s grown in incredibly diverse environments of getting diverse water strai...Sorghum is one of the most widely cultivated cereal crops in Ethiopia which is grown for food and feed uses. It’s far an indigenous crop that’s grown in incredibly diverse environments of getting diverse water strain, soil fertility, and temperature situations. Trait of sorghum varieties tolerant to drought and producing desirable grain yield at the same time as addressing the biomass requirement is one of the techniques within the sorghum breeding program to the dry lowland surroundings so one can feed the growing population in Ethiopia. A total of 126 superior early maturing sorghum elite lines had been evaluated through along with recently released popular trendy check Melkam and Argiti to estimate the grain yield and stability of overall performance throughout the testing environments. Based on the overall performance of grain yield, flowering time, </span><span style="font-family:""><span style="font-family:Verdana;">plant height, and the stability of grain yield genotype ETSC14501-2-2 and</span><span style="font-family:Verdana;"> 14MWLSDT7196 become top ranked followed by genotype 14MWLSDT7176, 14MWLSDT7241 and 13MWF6#6037 which could be a capability candidate for production to the target environments. The varieties had better grain yield </span><span style="font-family:Verdana;">performance and stability across the environment, which may be used as capacity parental lines for genetic improvement in the sorghum improvement program. Finally based on the presented result on early maturing variety ETSC14501-2-2 with the pedigree of Redswazi/Meko-1 identified and registered for variety verification across locations on stations and on farms to confirm the stability and preference by farmers with their own farming practices.展开更多
Sorghum is a staple food crop in Ethiopia and its production is mainly constrained by drought, other environmental factors, and the use of low-yielding, local sorghum varieties. To improve sorghum productivity, it is ...Sorghum is a staple food crop in Ethiopia and its production is mainly constrained by drought, other environmental factors, and the use of low-yielding, local sorghum varieties. To improve sorghum productivity, it is crucial to provide farmers with high yielding, stable sorghum cultivars that are tolerant to drought and other constraints. The stable performance of sorghum varieties in a growing region is critical to obtain a high and stable yield. In the 2012-2014 crop year, 24 genotypes, including standard controls, were evaluated at the national variety trial stage over six main dry lowland sorghum growing sites and two years made 7 environments to evaluate their performance, stability and to quantify Genotype by Environment Interaction (GEI) across moisture stress sorghum growing areas of Ethiopia. Spatial modeling has been used to estimate predicted mean (BLUPs) results and Performance and estimation of environmental correlation, heritability, GEI, and other parameters using the ASReml3-R analysis package. The predicted mean yield of the test genotypes across the environment ranged from 3.45 to 1.56 t<span style="font-family:Verdana;">·</span><span style="font-family:;" "=""><span style="font-family:Verdana;">ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;">. Based on the result genotype G13, it could be further promoted because of its yield advantage and other important attributes over the standard checks, but it is the least stable. Based on the analyzed result, two mega environments were formed and Environment 1 (E1) is identified as an ideal environment among the testing environments.</span></span>展开更多
In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatia...In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.展开更多
Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this wo...Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this work is to assess the risks and vulnerability to these hazards in order to strengthen the resilience of the Malagasy population. Our approach is based on multi-criteria spatial analysis using the Analytical Hierarchy Process (AHP). The results form decision spatial information that can be used at the strategic level of natural risk and disaster management. This work focuses on the degree of vulnerability and it was found in this study that the Androy and Atsimo-Atsinanana regions are the most vulnerable to major hazards in Madagascar not only because of their exposure to risk but also because of their very low socio-economic status.展开更多
Malaria is still the major parasitic disease in the world, with approximately 438,000 deaths in 2015. Environmental risk factors (ERF) have been widely studied, however, there are discrepancies in the results abo...Malaria is still the major parasitic disease in the world, with approximately 438,000 deaths in 2015. Environmental risk factors (ERF) have been widely studied, however, there are discrepancies in the results about their influence on malaria transmission. Recently, papers have been published about geospatial analysis of ERF of malaria to explain why malaria varies from place to place. Our primary objective was to identify the environmental variables most used in the geospatial analysis of malaria transmission. The secondary objective was to identify the geo-analytic methods and techniques, as well as geo-analytic statistics commonly related to ERF and malaria. We conducted a systematized review of articles published from January 2004 to March 2015, within Web of Science, Pubmed and LILACS databases. Initially 676 articles were found, after inclusion and exclusion criteria, 29 manuscripts were selected. Temperature, land use and land cover, surface moisture and vector breeding site were the most frequent included variables. As for geo-analytic methods, geostatistical models with Bayesian framework were the most applied. Kriging interpolations, Geographical Weighted Regression as well as Kulldorff’s spatial scan were the techniques more widely used. The main objective of many of these studies was to use these methods and techniques to create malaria risk maps. Spatial analysis performed with satellite images and georeferenced data are increasing in relevance due to the use of remote sensing and Geographic Information System. The combination of these new technologies identifies ERF more accurately, and the use of Bayesian geostatistical models allows a wide diffusion of malaria risk maps. It is known that temperature, humidity vegetation and vector breeding site play a critical role in malaria transmission;however, other environmental risk factors have also been identified. Risk maps have a tremendous potential to enhance the effectiveness of malaria-control programs.展开更多
There has been an increasing global and local interest in developing renewable, clean, and cheap energy towards achieving Goal number 7 of the Sustainable Development Goals (SDG). However, decisions involving suitable...There has been an increasing global and local interest in developing renewable, clean, and cheap energy towards achieving Goal number 7 of the Sustainable Development Goals (SDG). However, decisions involving suitable and sustainable locations for renewable energy projects remain an important task. This study employed Geographic Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) to spatially analyze and model wind farm site suitability in Nasarawa State. The aim is to integrate the environmental, social, and economic aspects of decision-making for identifying sustainable wind farm sites. The study distinguished between two sets of decision criteria: decision constraints and decision factors. The former defined the exclusion zones while the latter were standardized based on fuzzy logic to depict varying degrees of suitability across the State. The MCDA applied the weighted linear combination method, with relative weights generated through pairwise comparisons of the analytic hierarchy process to analyze three policy scenarios: equal weights, environmental/social priority, and economic priority scenario. A combination of resulting composite maps from the constraints and the factors gave the final suitability maps. The resulting suitability index (SI) for the respective policy scenario describes the degrees of suitability: Ideal locations were denoted by one (1) and the not suitable locations by zero (0), with values in-between depicting varying degrees of wind farm site suitability. Based on the SI, priority locations indicating areas with good prospects, in addition to the most suitable parcels of land, were identified and delineated. The composite decision constraint revealed that wind farm projects would not be viable in more than half (57.58%) of the State. Wind speed was the major constraint and accounted for the exclusion of 46.25%, with a mean fuzzy membership value of 0.2008 indicating low suitability across the State. Also, the average acceptable wind farm location for the three-policy scenario was 33.33% of the entire study area. Lafia, Obi, Keana, Awe, Nasarawa-Eggon, Wamba and Kokona LGAs were the identified priority Local Government Areas (LGAs). However, only Lafia, Obi, and Nasarawa-Eggon were consistent with changes in the policy objectives. All the priority LGAs have one or more of the most suitable parcels within their administrative boundaries except for Wamba. Despite the severe limitations of wind speed, substantial parts of Nasarawa State still provide great development potentials for wind energy. The “most suitable” locations in Lafia, Nasarawa-Eggon, and Obi LGAs should have first consideration for the development of wind energy in the State.展开更多
The general objective of this research is to determine how to use the spatial analysis of traffic accidents in Medina Menorah City through geographic information systems. This research aimed to identify, locate and de...The general objective of this research is to determine how to use the spatial analysis of traffic accidents in Medina Menorah City through geographic information systems. This research aimed to identify, locate and define the sites where traffic accidents are concentrated and determine the need to apply specific safety standards to reduce accidents and identify their causes thereof. This current research applied the analytical descriptive approach for its relevance with this specific research. This research collected traffic accidents data from the Ministry of the Interior, Department of General Traffic. That data captured the hotspots accidents in Medina Menorah City. Some of the most important results of the study are as follows: many roads were selected as High Accident Location HAL, such as Central Ring Roads, King Faisal bin Abdul-Aziz Road, Prince Abdul Majid bin Abdul-Aziz Road, and King Abdulla bin Abdel-Aziz Road. The high-speed roads are heavily linked to the massive increase of traffic accident rates, and the increase in the street section length led to the soaring number of total accidents. The study recommended performing more studies and different highway safety studies to identify and locate accident patterns on road networks. Due to the fact that the accidents concentration is intensely focused on Medina City center and Prophet’s Mosque, it is a must to increase the number of public transportations to and from Prophet’s Mosque, particularly during the Hajj period, because of the fact that the visitors of Prophet’s Mosque is on the increase during the said period. This study can be applied in other cities because knowing the locations of traffic crash hotspots can provide us with valuable insights into the causes of accidents and this knowledge helps decision-makers to better assess the risk associated with accidents.展开更多
This study focused on spatial analysis to identify the changes in adaptability over the last five decades.The features influencing adaptability were selected from the reference study.An appropriate method was used to ...This study focused on spatial analysis to identify the changes in adaptability over the last five decades.The features influencing adaptability were selected from the reference study.An appropriate method was used to analyse these features through spatial analysis.Six distinctive typologies of rural houses were selected from six regions.Unlike the traditional houses,the contemporary houses in the same area reflected a different character.Urban houses built since the early and mid-20th century were compared with contemporary houses.After analysing the openness,generality,flexibility,depth,typicality,construction technique,involvement of end-users,and the feedback from the inhabitants,the study identified a significant decrease in contemporary houses'adaptability.Spatial analysis was used to quantify the different features and comparison between traditional and contemporary houses.Though the adaptability had been reduced over time,the latest houses started to achieve better flexibility in some features due to government policy and implementation of statutory building regulations.Further recommendations were provided to enhance the residential architecture's adaptability in future.The study samples were selected from different regions of Bangladesh.Still,the result and policy recommendations can be helpful for other countries,especially with high population density and a developing economy.展开更多
Irregular urban settlement increases environmental impacts, especially when these occupations occur in fragile location, as the environmental preservation areas. In these areas, also defined as Permanent Preservation ...Irregular urban settlement increases environmental impacts, especially when these occupations occur in fragile location, as the environmental preservation areas. In these areas, also defined as Permanent Preservation Area (PPA), the presence of watersheds is common, which is the factor that increases the need of protecting them from anthropic actions. Those actions deteriorate the environment and mainly the watercourses. This research objective is to identify and estimate the environmental risks of M’Boyci watershed River PPA occupied areas by urban population. The risk analysis approach, at this PPA in Foz do Iguacu City in Brazil, is able to support public interventions in order to reestablish the PPA natural conditions. To reach this goal, it was necessary to use cartographical representation images, generated from digital orthophotos analyzed through free geographical information systems. The overlap and the contrast of geographical data related to preservation in urban areas show that urban occupation reaches almost 40% of the permanent preservation area. Complementarily, it is evidenced that the development of a risk map identifies PPA areas characterized by a greater concentration of irregular settlement, contributing to the planning process of residents, relocation actions and recovery of degraded areas.展开更多
The so-called geotechnology has been used in recent years in the planning, supervision and monitoring of various human activities, both locally and regionally, nationally and internationally, either it in the rural en...The so-called geotechnology has been used in recent years in the planning, supervision and monitoring of various human activities, both locally and regionally, nationally and internationally, either it in the rural environment, as in urban áreas. This study, based on references and activities in the Geographic Information Analysis Laboratory of the Federal University of Pará (LAIG/UFPA), selects and presents the application of three tools for spatial analysis available in the Terraview [1] and Arcgis softwares, with the main objective being to demonstrate how they can be applied in geographical studies, starting with the spatial information gathered by remote or Field sensors, assisting the activities of researchers who stick to working with the planning and management of natural and human resources. Geotechnologies are important tools in the analysis of geographic space and its use tends to be increased with the advancement of new software and hardware collection, manipulation and generation of new specialized information. So we will do in this manuscript a brief discussion of three spatial analysis tools that can be used in rural areas with agricultural potential.展开更多
Flooding is becoming a yearly reoccurring event in many communities and cities in Nigeria, leading to the destruction of properties and deaths;hence, we must take measures to either prepare for the impact or curb the ...Flooding is becoming a yearly reoccurring event in many communities and cities in Nigeria, leading to the destruction of properties and deaths;hence, we must take measures to either prepare for the impact or curb the occurrence. The study identified flood vulnerability levels of communities in Isoko North LGA based on physical environmental domains such as land use, elevation, and proximity to river channel (drainage) using geospatial techniques. Also, attributes that could contribute to the resilience capacity building of the communities were assessed. From the study, 73.93% of the entire area is moderately and highly vulnerable to flood, while among the communities, seventeen (17) are categorized as moderately vulnerable, and four (4) are lowly vulnerable. The overall resilience capacity of the communities indicated can build a substantial capacity towards community resilience (3.02, 0.06). However, there is a need to encourage collaboration with stakeholders to improve mitigation action and enhance various shortcomings toward resilience capacity building.展开更多
Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification r...Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.展开更多
The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) dis...The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.展开更多
文摘In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.
文摘The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R<sup>2</sup> of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.
基金IP would like to acknowledge the NHMRC Investigator grant fellowship(APP1176298)the EMCR grant from the Centre for Biomedical Technologies(QUT).X.F.acknowledges the QUT Postgraduate Research Award(QUTPRA),QUT HDR TOP-UP scholarship and QUT HDR Tuition Fee Sponsorship+1 种基金I.O.A.acknowledges funding support from the Academy of Finland(315820)the Jane and Aatos Erkko Foundation(190001).
文摘Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose tissues.OA presents diverse clinical phenotypes and distinct molecular endotypes,including inflammatory,metabolic,mechanical,genetic,and synovial variants.Consequently,innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches.Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints,causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues.This issue has led to standardization difficulties and hindered the success of clinical trials.Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues,encompassing DNA,RNA,metabolites,and proteins,as well as their chemical properties,elemental composition,and mechanical attributes,can contribute to a more comprehensive understanding of the disease subtypes.Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment,providing a more holistic view of cellular function.Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various-omics lenses,such as genomics,transcriptomics,proteomics,and metabolomics,with spatial data.This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates.Furthermore,advanced imaging techniques,including high-resolution microscopy,hyperspectral imaging,and mass spectrometry imaging,enable the visualization and analysis of the spatial distribution of biomolecules,cells,and tissues.Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes.This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis.It explores their applications,challenges,and potential opportunities in the field of OA.Additionally,this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
基金supported by the National Natural Science Foundation of China project (No. 42372339)the China Geological Survey Project (Nos. DD20221816, DD20190319)。
文摘On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.
基金This research was supported by the National Natural Science Foundation of China(41977064)the National Key R&D Program of China(2021YFD1900700).
文摘Check dams are widely used on the Loess Plateau in China to control soil and water losses,develop agricultural land,and improve watershed ecology.Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams.Thus,this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis.First,we made a sample dataset of check dams using GaoFen-2(GF-2)and Google Earth images.Next,we evaluated five popular deep-learning-based object detectors,including Faster R-CNN,You Only Look Once(version 3)(YOLOv3),Cascade R-CNN,YOLOX,and VarifocalNet(VFNet),to identify the best one for check dam detection.Finally,we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results.Precision,recall,average precision at intersection over union(IoU)threshold of 0.50(AP_(50)),IoU threshold of 0.75(AP_(75)),and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step(AP_(50-95)),and inference time were used to evaluate model performance.All the five deep learning networks could identify check dams quickly and accurately,with AP_(50-95),AP_(50),and AP_(75)values higher than 60.0%,90.0%,and 70.0%,respectively,except for YOLOv3.The VFNet had the best performance,followed by YOLOX.The proposed framework was tested in the Yanhe River Basin and yielded promising results,with a recall rate of 87.0%for 521 check dams.Furthermore,the geographic analysis deleted about 50%of the false detection boxes,increasing the identification accuracy of check dams from 78.6%to 87.6%.Simultaneously,this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets.The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.
文摘Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment.Presence-only species distribution models are commonly used in these evaluations.The maximum entropy algorithm(MaxEnt)has gained popularity for modelling species distribution.Here,MaxEnt was used to model the spatial distribution of the Mexican pine bark beetle(Dendroctonus mexicanus)in a daily fashion by using forecast data from the Weather Research and Forecasting model.This study aimed to exploit freely available geographic and environmental data and software and thus provide a pathway to overcome the lack of costly data and technical guidance that are a challenge to implementing national monitoring and management strategies in developing countries.Our results showed overall agreement values between 60 and 87%.The results of this research can be used for D.mexicanus monitoring and management and may aid as a model to monitor similar species.
文摘Challenges faced by African countries in achieving the goals of sustainable development are similar and trans-boundary. Previous analysis of Africa’s progress on the Sustainable Development Goals (SDGs) has largely beennon-spatial, reducing the ability to find spatial relationships between countries and SDGs to help cooperationand proffer country-specific interventions. This study adopted techniques of exploratory and inferential spatialstatistics to assess the successes of African countries from 2016 to 2020 in achieving the goals of sustainable de-velopment. Also, the study sought to understand how the spatial synergies and trade-offs between SDGs vary percountry and time. The results revealed that spatial hotspots of countries with high SDGs scores were mostly con-fined to northern African countries with significant coldspots within central and eastern Africa and few patchesin western and southern Africa for 2016. In 2020, the number of countries forming hotspots reduced, with Cen-tral African countries as significant cold spots. Five main spatial relationships: positive linear, negative linear,concave, convex and undefined complex, were found among countries and the SDGs. However, these spatialrelationships were fluid as they changed over time and with different levels of influence from 2016 to 2020.The study concludes that generic solutions and policies by development agencies, governments, developmentfinance instiutions and other impact investors will not be enough in achieving the SDGs because of the spatialheterogeneity of the continent. Tailored and country-specific policies based on results of spatial statistics matter.
文摘Sorghum is one of the most widely cultivated cereal crops in Ethiopia which is grown for food and feed uses. It’s far an indigenous crop that’s grown in incredibly diverse environments of getting diverse water strain, soil fertility, and temperature situations. Trait of sorghum varieties tolerant to drought and producing desirable grain yield at the same time as addressing the biomass requirement is one of the techniques within the sorghum breeding program to the dry lowland surroundings so one can feed the growing population in Ethiopia. A total of 126 superior early maturing sorghum elite lines had been evaluated through along with recently released popular trendy check Melkam and Argiti to estimate the grain yield and stability of overall performance throughout the testing environments. Based on the overall performance of grain yield, flowering time, </span><span style="font-family:""><span style="font-family:Verdana;">plant height, and the stability of grain yield genotype ETSC14501-2-2 and</span><span style="font-family:Verdana;"> 14MWLSDT7196 become top ranked followed by genotype 14MWLSDT7176, 14MWLSDT7241 and 13MWF6#6037 which could be a capability candidate for production to the target environments. The varieties had better grain yield </span><span style="font-family:Verdana;">performance and stability across the environment, which may be used as capacity parental lines for genetic improvement in the sorghum improvement program. Finally based on the presented result on early maturing variety ETSC14501-2-2 with the pedigree of Redswazi/Meko-1 identified and registered for variety verification across locations on stations and on farms to confirm the stability and preference by farmers with their own farming practices.
文摘Sorghum is a staple food crop in Ethiopia and its production is mainly constrained by drought, other environmental factors, and the use of low-yielding, local sorghum varieties. To improve sorghum productivity, it is crucial to provide farmers with high yielding, stable sorghum cultivars that are tolerant to drought and other constraints. The stable performance of sorghum varieties in a growing region is critical to obtain a high and stable yield. In the 2012-2014 crop year, 24 genotypes, including standard controls, were evaluated at the national variety trial stage over six main dry lowland sorghum growing sites and two years made 7 environments to evaluate their performance, stability and to quantify Genotype by Environment Interaction (GEI) across moisture stress sorghum growing areas of Ethiopia. Spatial modeling has been used to estimate predicted mean (BLUPs) results and Performance and estimation of environmental correlation, heritability, GEI, and other parameters using the ASReml3-R analysis package. The predicted mean yield of the test genotypes across the environment ranged from 3.45 to 1.56 t<span style="font-family:Verdana;">·</span><span style="font-family:;" "=""><span style="font-family:Verdana;">ha</span><sup><span style="font-family:Verdana;">-1</span></sup><span style="font-family:Verdana;">. Based on the result genotype G13, it could be further promoted because of its yield advantage and other important attributes over the standard checks, but it is the least stable. Based on the analyzed result, two mega environments were formed and Environment 1 (E1) is identified as an ideal environment among the testing environments.</span></span>
文摘In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.
文摘Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this work is to assess the risks and vulnerability to these hazards in order to strengthen the resilience of the Malagasy population. Our approach is based on multi-criteria spatial analysis using the Analytical Hierarchy Process (AHP). The results form decision spatial information that can be used at the strategic level of natural risk and disaster management. This work focuses on the degree of vulnerability and it was found in this study that the Androy and Atsimo-Atsinanana regions are the most vulnerable to major hazards in Madagascar not only because of their exposure to risk but also because of their very low socio-economic status.
文摘Malaria is still the major parasitic disease in the world, with approximately 438,000 deaths in 2015. Environmental risk factors (ERF) have been widely studied, however, there are discrepancies in the results about their influence on malaria transmission. Recently, papers have been published about geospatial analysis of ERF of malaria to explain why malaria varies from place to place. Our primary objective was to identify the environmental variables most used in the geospatial analysis of malaria transmission. The secondary objective was to identify the geo-analytic methods and techniques, as well as geo-analytic statistics commonly related to ERF and malaria. We conducted a systematized review of articles published from January 2004 to March 2015, within Web of Science, Pubmed and LILACS databases. Initially 676 articles were found, after inclusion and exclusion criteria, 29 manuscripts were selected. Temperature, land use and land cover, surface moisture and vector breeding site were the most frequent included variables. As for geo-analytic methods, geostatistical models with Bayesian framework were the most applied. Kriging interpolations, Geographical Weighted Regression as well as Kulldorff’s spatial scan were the techniques more widely used. The main objective of many of these studies was to use these methods and techniques to create malaria risk maps. Spatial analysis performed with satellite images and georeferenced data are increasing in relevance due to the use of remote sensing and Geographic Information System. The combination of these new technologies identifies ERF more accurately, and the use of Bayesian geostatistical models allows a wide diffusion of malaria risk maps. It is known that temperature, humidity vegetation and vector breeding site play a critical role in malaria transmission;however, other environmental risk factors have also been identified. Risk maps have a tremendous potential to enhance the effectiveness of malaria-control programs.
文摘There has been an increasing global and local interest in developing renewable, clean, and cheap energy towards achieving Goal number 7 of the Sustainable Development Goals (SDG). However, decisions involving suitable and sustainable locations for renewable energy projects remain an important task. This study employed Geographic Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) to spatially analyze and model wind farm site suitability in Nasarawa State. The aim is to integrate the environmental, social, and economic aspects of decision-making for identifying sustainable wind farm sites. The study distinguished between two sets of decision criteria: decision constraints and decision factors. The former defined the exclusion zones while the latter were standardized based on fuzzy logic to depict varying degrees of suitability across the State. The MCDA applied the weighted linear combination method, with relative weights generated through pairwise comparisons of the analytic hierarchy process to analyze three policy scenarios: equal weights, environmental/social priority, and economic priority scenario. A combination of resulting composite maps from the constraints and the factors gave the final suitability maps. The resulting suitability index (SI) for the respective policy scenario describes the degrees of suitability: Ideal locations were denoted by one (1) and the not suitable locations by zero (0), with values in-between depicting varying degrees of wind farm site suitability. Based on the SI, priority locations indicating areas with good prospects, in addition to the most suitable parcels of land, were identified and delineated. The composite decision constraint revealed that wind farm projects would not be viable in more than half (57.58%) of the State. Wind speed was the major constraint and accounted for the exclusion of 46.25%, with a mean fuzzy membership value of 0.2008 indicating low suitability across the State. Also, the average acceptable wind farm location for the three-policy scenario was 33.33% of the entire study area. Lafia, Obi, Keana, Awe, Nasarawa-Eggon, Wamba and Kokona LGAs were the identified priority Local Government Areas (LGAs). However, only Lafia, Obi, and Nasarawa-Eggon were consistent with changes in the policy objectives. All the priority LGAs have one or more of the most suitable parcels within their administrative boundaries except for Wamba. Despite the severe limitations of wind speed, substantial parts of Nasarawa State still provide great development potentials for wind energy. The “most suitable” locations in Lafia, Nasarawa-Eggon, and Obi LGAs should have first consideration for the development of wind energy in the State.
文摘The general objective of this research is to determine how to use the spatial analysis of traffic accidents in Medina Menorah City through geographic information systems. This research aimed to identify, locate and define the sites where traffic accidents are concentrated and determine the need to apply specific safety standards to reduce accidents and identify their causes thereof. This current research applied the analytical descriptive approach for its relevance with this specific research. This research collected traffic accidents data from the Ministry of the Interior, Department of General Traffic. That data captured the hotspots accidents in Medina Menorah City. Some of the most important results of the study are as follows: many roads were selected as High Accident Location HAL, such as Central Ring Roads, King Faisal bin Abdul-Aziz Road, Prince Abdul Majid bin Abdul-Aziz Road, and King Abdulla bin Abdel-Aziz Road. The high-speed roads are heavily linked to the massive increase of traffic accident rates, and the increase in the street section length led to the soaring number of total accidents. The study recommended performing more studies and different highway safety studies to identify and locate accident patterns on road networks. Due to the fact that the accidents concentration is intensely focused on Medina City center and Prophet’s Mosque, it is a must to increase the number of public transportations to and from Prophet’s Mosque, particularly during the Hajj period, because of the fact that the visitors of Prophet’s Mosque is on the increase during the said period. This study can be applied in other cities because knowing the locations of traffic crash hotspots can provide us with valuable insights into the causes of accidents and this knowledge helps decision-makers to better assess the risk associated with accidents.
文摘This study focused on spatial analysis to identify the changes in adaptability over the last five decades.The features influencing adaptability were selected from the reference study.An appropriate method was used to analyse these features through spatial analysis.Six distinctive typologies of rural houses were selected from six regions.Unlike the traditional houses,the contemporary houses in the same area reflected a different character.Urban houses built since the early and mid-20th century were compared with contemporary houses.After analysing the openness,generality,flexibility,depth,typicality,construction technique,involvement of end-users,and the feedback from the inhabitants,the study identified a significant decrease in contemporary houses'adaptability.Spatial analysis was used to quantify the different features and comparison between traditional and contemporary houses.Though the adaptability had been reduced over time,the latest houses started to achieve better flexibility in some features due to government policy and implementation of statutory building regulations.Further recommendations were provided to enhance the residential architecture's adaptability in future.The study samples were selected from different regions of Bangladesh.Still,the result and policy recommendations can be helpful for other countries,especially with high population density and a developing economy.
文摘Irregular urban settlement increases environmental impacts, especially when these occupations occur in fragile location, as the environmental preservation areas. In these areas, also defined as Permanent Preservation Area (PPA), the presence of watersheds is common, which is the factor that increases the need of protecting them from anthropic actions. Those actions deteriorate the environment and mainly the watercourses. This research objective is to identify and estimate the environmental risks of M’Boyci watershed River PPA occupied areas by urban population. The risk analysis approach, at this PPA in Foz do Iguacu City in Brazil, is able to support public interventions in order to reestablish the PPA natural conditions. To reach this goal, it was necessary to use cartographical representation images, generated from digital orthophotos analyzed through free geographical information systems. The overlap and the contrast of geographical data related to preservation in urban areas show that urban occupation reaches almost 40% of the permanent preservation area. Complementarily, it is evidenced that the development of a risk map identifies PPA areas characterized by a greater concentration of irregular settlement, contributing to the planning process of residents, relocation actions and recovery of degraded areas.
基金the discussions held during the implementation of the project“Participatory Mapping and survival strategies by traditional populations in Amazon/Para”,approved in Notice 14/2013(Universal Call-MCTI/CNPq)funded by the Qualified Publication Support Program(PAPQ),offered by the Dean of Research and Graduate Studies(PROPESP)the Foundation for the Support and Development of Research(FADESP),of the Federal University of Pará.
文摘The so-called geotechnology has been used in recent years in the planning, supervision and monitoring of various human activities, both locally and regionally, nationally and internationally, either it in the rural environment, as in urban áreas. This study, based on references and activities in the Geographic Information Analysis Laboratory of the Federal University of Pará (LAIG/UFPA), selects and presents the application of three tools for spatial analysis available in the Terraview [1] and Arcgis softwares, with the main objective being to demonstrate how they can be applied in geographical studies, starting with the spatial information gathered by remote or Field sensors, assisting the activities of researchers who stick to working with the planning and management of natural and human resources. Geotechnologies are important tools in the analysis of geographic space and its use tends to be increased with the advancement of new software and hardware collection, manipulation and generation of new specialized information. So we will do in this manuscript a brief discussion of three spatial analysis tools that can be used in rural areas with agricultural potential.
文摘Flooding is becoming a yearly reoccurring event in many communities and cities in Nigeria, leading to the destruction of properties and deaths;hence, we must take measures to either prepare for the impact or curb the occurrence. The study identified flood vulnerability levels of communities in Isoko North LGA based on physical environmental domains such as land use, elevation, and proximity to river channel (drainage) using geospatial techniques. Also, attributes that could contribute to the resilience capacity building of the communities were assessed. From the study, 73.93% of the entire area is moderately and highly vulnerable to flood, while among the communities, seventeen (17) are categorized as moderately vulnerable, and four (4) are lowly vulnerable. The overall resilience capacity of the communities indicated can build a substantial capacity towards community resilience (3.02, 0.06). However, there is a need to encourage collaboration with stakeholders to improve mitigation action and enhance various shortcomings toward resilience capacity building.
文摘Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.
基金supported by Science and Technology Major Project of the Hall of Science and Technology of Fujian (No. 2012NZ0001)the Project of National Natural Science Fund of China (No.30671664)
文摘The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.
