Geospatial Analysis of Urban Heat Island Effects and Tree Equity

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.

Spatial Analysis of the Aging Population and Socio-economic Factors of China:Global and Local Perspectives

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

The SIA method for spatial analysis of precipitation in the upper-middle reaches of the Yangtze River

Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitation and topographical variables are established to extract the effect of topography on the annual and seasonal precipitation in the upper-middle reaches of the Yangtze River. Then, this paper uses a successive interpolation approach (SIA), which combines GIS techniques with the multiple regressions, to improve the accuracy of the spatial interpolation of annual and seasonal rainfall. The results are very satisfactory in the case of seasonal rainfall, with the relative error of 6.86%, the absolute error of 13.07 mm, the average coefficient of variation of 0.070, and the correlation coefficient of 0.9675; in the case of annual precipitation, with the relative error of 7.34%, the absolute error of 72.1 mm, the average coefficient of variation of 0.092, and the correlation coefficient of 0.9605. The analyses of annual mean precipitation show that the SIA calculation of 3-5 steps considerably improves the interpolation accuracy, decreasing the absolute error from 211.0 mm to 62.4 mm, the relative error from 20.74% to 5.97%, the coefficient of variation from 0.2312 to 0.0761, and increasing the correlation coefficient from 0.5467 to 0.9619. The SIA iterative results after 50 steps identically converge to the observed precipitation.

Spatial analysis increases efficiency of progeny testing of Chinese fir

We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in a tree breeding program for Chinese fir （Cunninghamia lanceolata （Lamb.） Hook） on a hilly site with an environmental gradient from hill top to bottom. Diameter at breast height （DBH） and tree height data had significant spatial auto-correlations among rows and columns. Adding a firstorder separable autoregressive term more effectively modelled the spatial variation than did the incomplete block （IB） model used for the experimental design. The spatial model also accounted for effects of experimental design factors and greatly reduced residual variances. The spatial analysis rel- ative to the IB analysis improved estimation of genetic parameters with the residual variance reduced 13 and 19% for DBH and tree height, respectively; heritability increased 35 and 51% for DBH and tree height, respectively; and genetic gain improved 3-5%. Fitting global trend and postblocking did not improve the analyses under IB model. The use of a spatial model or combined with a design model is recommended for forest genetic trials, particularly with global trend and local spatial variation of hilly sites.

Gold Resources Potential Assessment in Eastern Kunlun Mountains of China Combining Weights-of-evidence Model with GIS Spatial Analysis Technique

Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern Kunlun Mountains,Qinghai Province,China was assessed by combining weights-of-evidence model with GIS spatial analysis technique.All the data sets used in this paper were derived from an established multi-source geological spatial database,which contains geological,geophysical,geochemical and remote sensing data.Three multi-class variables,i.e.,structural intersection,Indosinian k-feldspar granite and regional fault,were used in proximity analysis to examine their spatial association with known gold deposits.A prospectivity map was produced by weights-of-evidence model based on seven binary evidential maps,all of which had passed a conditional independence test.The study area was divided into three target zones of high potential,moderate potential and low potential areas,among which high potential areas and moderate potential areas accounted for 20% of the total area and contained 32 of the 43 gold deposits.The results show that the gold resources potential assessment in the eastern Kunlun Mountains has a higher precision.

SOIL SPATIAL ANALYSIS AND AGRICULTURAL LAND USE OPTIMIZATION BY USING GIS

This paper discusses the methods and process of Geographic Information System (GIS) applied in soil spatial analysis, involving the collection of soil spatial data that GIS required, spatial analysis method of soil nutrient, land use, slope and exposure of geography, crop yield and other factors, and also including acquiring soil spatial information and creating thematic map, and so on. Taking Hengjing Town in Wuxian County of Jiangsu Province as a case study and the maximum income as a principle, and applying the GIS methods and their interrelated models, we have calculated the most optimized agricultural land and the possible maximum income of Hengjing Town. According to the method, we can rationally regulate local agricultural production, and put forward some scenarios for optimizing agricultural structure of Hengjing Town. The paper puts forward an evaluation method of land adaptability based on soil spatial analysis, and offers some research clews to optimize agricultural land use constitution, so the paper will be have important reference value for soil study.

Modelling potential distribution of a pine bark beetle in Mexican temperate forests using forecast data and spatial analysis tools

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.

Spatial analysis of synergies and trade-offs between the Sustainable Development Goals (SDGs) in Africa

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.

The MET Analysis of Yield Performance of Advanced Sorghum [<i>Sorghum Bicolor</i>(L.) Moench] Lines under Moisture Stress Areas Using Spatial Analysis

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, plant height, and the stability of grain yield genotype ETSC14501-2-2 and 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 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.

Distinguishing of Stable Genotypes and Mega Environment for Grain Yield Performance of Sorghum [<i>Sorghum bicolor</i>(L.) Moench] Genotypes Using Spatial Analysis

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·ha-1. 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.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

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.

Spatial Analysis of Risks and Vulnerabilities to Major Hazards in Madagascar Using the Multi-Criteria Method Based on the Analytical Hierarchy Process (AHP)

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.

Systematized Literature Review on Spatial Analysis of Environmental Risk Factors of Malaria Transmission

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.

Spatial Analysis and Modelling of Wind Farm Site Suitability in Nasarawa State, North-Central Nigeria

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.

Spatial Analysis of Traffic Accidents in the City of Medina Using GIS

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.

Change in Adaptability of Residential Architecture:Spatial Analysis on Traditional and Contemporary Houses of Bangladesh

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.

Investigations of Carbon Sequestration and Storage Using Advanced Geospatial Analysis

This research demonstrated quantitative methods of geospatial analysis applicable to carbon sequestration and storage in the conterminous United Sates. We identified national-scale NEP （net ecosystem production） changes for conversions to and from crop, and land in frequent conversion among forest, wetland, pasture and rangeland. The trend showed an increase in the margins of the Corn Belt states and coincided with land conversion from previous non-cropland to cropland in the United States. This research will not only improve the engineering understanding of carbon dioxide removal options involving the terrestrial biosphere, but will also inform decision-making in the carbon emission impacts. Therefore, it will provide a spatio-temporal reference for analyzing the national-level carbon exchange systems in the United States.

Urban Settlement Spatial Analysis in Permanent Preservation Area of M’boicy Watershed River, Foz do Iguaçu City in Brazil

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.

Methodological Guidelines for the Use of Geoprocessing Tools:Spatial Analysis Operations—Kernel,Buffer and the Remote Sensing Image Classification

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.

Optimizing Spatial Pattern Analysis in Serial Remote Sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.