Physical Geographical Factors Research Articles

Spatial–temporal trends in leprosy burden and its associations with socioeconomic and physical geographic factors: results from the Global Burden of Disease Study 2019

ObjectivesThe purpose of our study was to assess the multiscalar changes in leprosy burden and its associated risk factors over the last three decades. Study designWe conducted an in-depth examination of leprosy's spatial–temporal trends at multiple geographical scale (global, regional, and national), utilizing information from Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2019). MethodsIncidence and the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) of leprosy were determined, with countries categorized based on leprosy incidence changes. We examined socioeconomic and physical geography influences on leprosy incidence via Spearman correlation analysis, using ternary phase diagrams to reveal the synergetic effects on leprosy occurrence. ResultsGlobally, incident cases of leprosy decreased by 27.86% from 1990 to 2019, with a reduction in ASIR (EAPC = −2.53), yet trends were not homogeneous across regions. ASIR and EAPC correlated positively with sociodemographic index (SDI), and an ASIR growth appeared in high SDI region (EAPC = 3.07). Leprosy burden was chiefly distributed in Tropical Latin America, Oceania, Central Sub-Saharan Africa, and South Asia. Negative correlations were detected between the incidence of leprosy and factors of SDI, GDP per capita, urban population to total population, and precipitation, whereas the number of refugee population, temperature, and elevation showed opposite positive results. ConclusionsDespite a global decline in leprosy over the past three decades, the disparities of disease occurrence at regional and national scales still persisted. Socioeconomic and physical geographic factors posed an obvious influence on the transmission risk of leprosy. The persistence and regional fluctuations of leprosy incidence necessitate the ongoing dynamic and multilayered control strategies worldwide in combating this ancient disease.

Abandoned cropland mapping and its influencing factors analysis: A case study in the Beijing-Tianjin-Hebei region

Abandoned cropland (AC) is one of the important types of land cover and land use change that poses a threat to food security, nature conservation, and ecosystem protection. Despite its significance, detailed spatial distribution patterns of AC across expansive geographic regions remain under-explored. Therefore, this study 1) proposes a novel framework designed to precisely determine the timing and extent of AC, and evaluates its effectiveness in the Beijing-Tianjin-Hebei region from 2000 to 2020; 2) analyses the spatial and temporal evolution of AC; 3) investigates the relationship between AC and both physical geographic and socio-economic factors. The proposed AC recognition framework integrates the method of change detection. Initially, regions changing are pinpointed, followed by categorizing pre- and post-change images to ascertain the magnitude and timing of these shifts, enabling the pinpointing of AC locations and their temporal onset. The results showed that the accuracy of land cover classification mapping ranged from 80.83% to 99.08%. Specifically, the user's accuracy of the proposed method varied between 79.29% and 89.38%. We discerned that AC was mainly distributed in the northwest water conservation belt, adopting an inverted “L” pattern. Additionally, physical geographic factors predominantly influenced AC. The use of remote sensing plays a crucial role in assessing AC, which is of great significance for understanding the evolution of abandoned landscapes and analyzing the relationship between abandonment and geology, environment, and socio-economy.

Spatial Association between Socioeconomic Factors, Physical Geographic Factors, and Suicide in Thailand

Background: Suicide is a significant cause of death in many countries worldwide. In Thailand, it ranks second in unnatural deaths, following accidents, with an increasing trend. This study aims to 1) describe the spatial distribution of suicide rates and 2) identify the spatial relationships among socioeconomic status, physical geography and suicide rates during the years 2012–2021. Methods: This study sought to explain the spatial distribution of suicide rates across provinces in Thailand from 2012 to 2021. The spatial relationships were analyzed using LISA and spatial regression. Results: The result obtained from univariate LISA indicated a concentration of suicide rates in the northern region of Thailand for the period from 2012 to 2021. Spatial regression analysis using OLS, SLM and SEM demonstrated the relationships between suicide rates and various variables, such as divorce rates, poverty rates, elderly proportions and NDWI. These factors exhibited a positive correlation with suicide rates and were statistically significant. Conversely, the NTL density and average rainfall displayed a negative correlation with suicide rates. Conclusion: Our study observed that the distribution of divorce rates, poverty population proportion, elderly population proportion and the normalized difference water index were likely to be associated with enhancing the suicide rate. However, the intensity of average Night-Time-Light (NTL) was observed to reduce the suicidal rate. Therefore, these present findings can be utilised in the development of policy as well as strategies concerning surveillance, control and prevention of suicide in Thailand.

Analysis of Spatial Pattern and Geographical Divergence Characteristics of Traditional Villages Oriented to Digital Landscape Technology

Abstract In order to study the spatial pattern and geographical differentiation characteristics of traditional villages, this paper combines digital landscape technology to analyze the influencing factors of the distribution of traditional villages. Based on multi-source data, this paper reveals the spatial pattern and geographical differentiation characteristics of traditional villages with the help of GIS, RS and mathematical and statistical methods and systematically explores the inner mechanism and laws. It also combines digital landscape technology, which is in line with the trend of the times, and designs an image visual optimization model based on digital landscape technology so as to make the experimental analysis of the distribution of traditional villages more convenient. It is obtained that the 3D modeling errors using digital landscape technology are all lower than 1.12%, the 3D modeling errors of the overhead GIS 3D modeling method are between 3.21% and 4.58%, and the 3D modeling errors of the digital photography 3D modeling method are all higher than 4.82%. The distance from the urban center, population density, ethnic distribution, and average annual temperature was the main influencing factors, all of which exceeded the explanatory power of 0.4. Average annual rainfall, administrative center, and GDP per capita were the secondary influencing factors, with explanatory power over 0.15. Based on this study, the spatial distribution density of traditional socio-economic villages was more influenced by socio-economic factors, followed by physical geographic factors.

Evaluating Hydrological Drought Risk in Lithuania

Hydrological drought poses a major global challenge, exacerbated by climate change and increasing water demand, leading to water scarcity, environmental degradation, and socioeconomic impacts. Thereby, there is a need for comprehensive methods to assess and predict hydrological droughts. The methodology part was based on the calculation of hydrological drought risk components—hazard and vulnerability—according to the equal weight scale of each variable. The spatial distribution of point values was performed by the inverse distance weighting interpolation method. To calculate indices, the spatial layer overlapping of variables was performed using the Raster Calculator tool. Statistical tools were used to estimate drought risk in river catchments. As a result, three main maps were prepared: The hydrological drought hazard index, the hydrological drought vulnerability index, and the hydrological drought risk. These maps highlight regional variations in drought hazards, vulnerability, and risk. Hazard and risk index values are higher in the northern part of Lithuania and lower in the south. The central region exhibits the highest percentage of areas at high and very high risk; the western region shows less risk due to a maritime climate; and the Southeastern region demonstrates the lowest susceptibility to hydrological drought due to physical-geographical factors.

Evolution Pattern of Blue–Green Space in New Urban Districts and Its Driving Factors: A Case Study of Zhengdong New District in China

Understanding the spatial–temporal evolution of the blue–green space (BGS) is crucial for urban planning and ecological security protection. However, the evolutionary patterns and driving factors of the BGS in new urban districts remain unclear. Based on the classical qualitative models, “patch–corridor–matrix” and “sustainability prism”, this study adopted the land use transition matrix and landscape index to quantify evolution patterns, and Pearson correlation and geographical detector analysis methods to reveal the driving factors. Taking Zhengdong New District as a case study, the results indicated the following: (1) The BGS rate was reduced by 35% from 2003 to 2021, with the most significant decrease in cultivated lands. (2) The evolution pattern of BGS alternated sequentially among ecological, disorderly, and balanced states. Among them, urban green spaces tended towards a more stable and aggregated state. Other BGSs became more fragmented and discontinuous. (3) The “sustainability prism” model consists of four driving factors, including social economy, rainwater safety, ecological liveability, and physical geography. (4) Socioeconomic factors significantly decreased the BGS, as indicated by the correlation coefficients of −0.988 and −0.978 between built-up areas and population and gross domestic products, respectively. Physical geographic factors played weak roles in the evolution of the BGS. Meanwhile, rainwater safety and ecological liveability positively affected the BGS.

Spatiotemporal distribution and driving factors of regional green spaces during rapid urbanization in Nanjing metropolitan area, China

In China, regional green spaces (RGSs) are green spaces outside urban built-up areas and have a wide distribution, large scale, and outstanding ecological function. RGSs have become increasingly important as urban clusters expand and increase in number. However, studies on RGSs are rare and it remains unclear what drives their distribution in the context of rapid urbanization. This study used integrated approaches to explore the distribution and driving factors of RGSs in the Nanjing metropolitan area (NMA) between 2000 and 2020, using Landsat image data. Spatiotemporal variations in the distribution of RGSs were obtained using the net change rate index and standard deviational ellipse. The driving factors were identified using Pearson correlation, ordinary least squares (OLS), and geographically weighted regression (GWR). We found that: (1) More RGSs are in the south of the NMA, and less in the north region. A “V” pattern of RGSs area change was observed, with substantial losses shifting from Yangtze River coastline to hilly and mountainous regions from 2000 to 2020. (2) The distribution of RGSs was affected by a combination of physical geographic, socioeconomic, and policy management factors. The functions of these influencing factors have pronounced spatiotemporal heterogeneity in direction or magnitude. Physical geographic factors including slope and annual precipitation exhibited the strongest correlation with RGSs distribution, and the regression coefficients showed relatively stable spatial performance. Among the socioeconomic factors, the distance from built-up areas and GDP played an important role. Policy management has played a guiding role, and the positive influence generated by dedicated financial expenditure and statutory green space area tends to increase and maintain a balance. The results of this study can help further understand the spatial distribution of RGSs and provide theoretical support for green space construction and ecological management of metropolitan areas during rapid urbanization.

Rural Landscape Change: The Driving Forces of Land Use Transformation from 1980 to 2020 in Southern Henan, China

Rapid urbanization has had an important impact on the pattern and function of rural land use. To better understand the key drivers of the landscape pattern evolution in southern Henan in China from 1980 to 2020, we used techniques of GIS(Geographic Information System) technology and the geodetector model in the research area of landscape pattern evolution characteristics. The research results show that the land use transformation in the rural areas of southern Henan has been characterized by the conversion of production land to living land and ecological land, with the highest conversion rate and continuous growth of construction land, a decreasing trend of cropland, and continuous and stable growth of land for forest and water body in the past 40 years. Land use conversion in the rural areas of southern Henan is mainly concentrated in the northern, central, and southern areas, and the spatial conversion has shifted from mountainous areas to the plains. The center of gravity of forest, cropland, and water body has most obviously shifted, and human interference and ecological environment destruction are the main influencing factors. The overall landscape pattern in the rural areas of southern Henan has increased in fragmentation and landscape heterogeneity, evenness has decreased, irregular patches have increased, and landscape connectivity has decreased. The combined effect of the six dimensions of elevation, slope, night lighting, average annual precipitation, average annual temperature, and population density in the rural areas of southern Henan has led to the transformation of land use and changes in landscape pattern. Physical geographic factors are the main drivers of rural landscape pattern changes in southern Henan, while population density changes and urbanization are secondary drivers. The results of the study have important guiding significance for the further optimization of rural landscape patterns and the sustainable development of rural areas.

SPATIAL ANALYSIS AND TENDENCIES OF THE INCIDENCE OF HEART DISEASES OF THE POPULATION OF UKRAINE

Since September 29, 2000 the International day of heart has been celebrated on the initiative of the World Federation of heart. Its main task is to attract the attention of the people of the planet to the problems of circulatory system diseases as the ones which have the highest incidence rates and mortality. The aim of the paper was to make a spatial analysis and to find out the morbidity tendencies of heart diseases among the population of Ukraine. The incidence structure of Ukraine’s population was identified. The dynamics of circulatory system morbidity in the years of 2009–2017 in Ukraine was analyzed. It has been established that heart disease incidence has tended to decrease. The administration regions of Ukraine were grouped according to the incidence rate of heart diseases among the population. The attention is paid to hypertension and myocardial infarction as they are the most common among the diseases of circulatory system. The decrease in the incidence rate by 1.6 and 1.1 times was recorded, respectively. In Ukraine the mortality dynamics from the diseases of circulatory system was analyzed for the years of 2009–2020. Cardiovascular diseases are the leaders in mortality of the population. The analysis of the mortality dynamics from the diseases of circulatory system proved the tendency towards its increase. The analysis of the statistical and cartographical data made it possible to single out two groups of the factors which predetermine the morbidity of circulatory system diseases among the population of Ukraine: physical-geographical and social-economic. The physical-geographical factors of the diseases of circulatory system (abnormallly high air temperatures in summer, a great number of days with heat stress, abrupt changes of atmospheric pressure) determine the highest incidence rates in southern (Odesa, Mykolayiv, Dnipropetrovsk, Kharkiv regions) and western (Zakarpattia, Ternopil, Ivano-Frankivsk, Khmelnytsk regions) areas of Ukraine. It has been stated that physical-geographical conditions of the territory, namely the location of the regions with high incidence rates near large mineral deposits, determine the next group of the factors of circulatory system diseases. The group includes a large number of industrial enterprises, situated in the vicinity of the mining area, sedentary work and the age of the population. A correlation analysis pointed out to the availability of a multi-leveled connection between people’s morbidity and its age structure. An average level of the correlation between cardiovascular diseases and the population over 65 (years old) was established. A cluster analysis was made by means of which the typification of the regions based on medical indicators was carried out.

Exploring the Determinants of the Urban–Rural Construction Land Transition in the Yellow River Basin of China Based on Machine Learning

Understanding the determinants of urban–rural construction land transition is necessary for improving regional human–land relationships. This study analysed the spatiotemporal pattern of urban–rural construction land transition at the grid scale in the Yellow River Basin (YRB) of China during 2000–2020 by bivariate spatial autocorrelation analysis and further explored its determinants based on a machine learning method, the gradient boosted decision tree (GBDT) model. The results showed that both urban construction land (UCL) and rural residential land (RRL) increased, with an annual growth amount of UCL three times that of RRL, and the proportion of UCL (LUUR) remained stable after 2015. The determinants of UCL, RRL, and LUUR varied. The UCL mainly depended on socioeconomic factors, with their contribution exceeding 50%, while the RRL transition was mainly determined by physical geographic factors, with their contribution decreasing from 67.6% in 2000 to 59.7% in 2020. The LUUR was influenced by both socioeconomic and physical geographic factors, with the relative importance of socioeconomic factors increasing over the years. Meanwhile, the impacts of different determinants were nonlinear with a threshold effect. In the future, optimizing the distribution of urban–rural construction land and rationally adjusting its structure will be necessary for promoting urban–rural sustainability in the YRB.

Spatial Evolution and Multi-Scenario Simulation of Rural “Production–Ecological–Living” Space: A Case Study for Beijing, China

With the vigorous development of industrialization and urbanization, rural space faces many difficulties in achieving sustainable development, such as the spatial structure being unbalanced. To explore the sustainable development of rural space, this study evaluates the spatial evolution and multi-scenario simulation of rural space with reference to the three dominant functions of land use, namely “production–ecological–living” (PEL), based on the interpretation of land use remote sensing data in 2000, 2010, and 2020. The change characteristics and the formation mechanism of the territorial spatial pattern were quantitatively analyzed by gravity center transfer, territorial spatial transfer matrix, standard deviational ellipse, geo-detector, and artificial neural network CA simulation. The results showed that (1) from 2000 to 2020, the rural production space in Beijing continued to decrease, the rural living space continued to increase and then gradually contracted, and the rural ecological space as a whole also showed a downward trend. (2) During the study period, the formation and evolution of the ecological spatial pattern of rural production and living in Beijing were affected by both regional physical geographical factors and human, social, and economic factors, with significant differences; the interaction between two driving factors is stronger than that within a single factor, and the main mode of action is double factor enhancement and nonlinear enhancement. (3) Compared with the other three scenarios, the performance of Beijing’s rural space in 2030 under the harmonious development scenario is more compact and stable, the rural production space is basically guaranteed, the intensity of rural living space is enhanced, and the overall situation of rural ecological space is stable. Our results show that in the future decision-making of rural land and space development around a metropolis, we should fully consider the evolution law of rural spatial pattern, as well as the driving force of natural geographical factors and economic activity factors and discuss the optimization and overall management of rural production and living ecological space through multi-scenario spatial simulation.

Variations in Ecosystem Service Value and Its Driving Factors in the Nanjing Metropolitan Area of China

More than 60% of the world’s ecosystem services have deteriorated over the past few decades. Studying the spatio-temporal fluctuations in ecosystem service value and its influencing factors is important for identifying regional ecosystem service value issues, upholding regional ecological harmony, and encouraging regionally healthy and coordinated sustainable development. Ecosystem service value has so far been studied primarily in relation to the effect of socioeconomic and physical–geographical variables. However, the trade-offs and synergies among ecosystem service values also drive the spatio-temporal variations in ecosystem service value. Few studies have been conducted to date to investigate the trade-offs and synergies between ecosystem service values and their impact on ecosystem service value. Therefore, this paper used sensitivity analysis, correlation analysis, trade-offs and synergies analysis, and a Geodetector to examine changes in ecosystem service value and their influencing factors within the Nanjing metropolitan region. The ecosystem service value decreased somewhat overall between 2000 and 2020, with a decline rate of 2.19 million CNY/year. In comparison to the north of the Nanjing metropolitan region, the ecosystem service value was relatively higher in the south. The water bodies had the highest total ecosystem service value, followed by forest land, cultivated land, and grassland, with construction land and unused land having the lowest ecosystem service values overall. The main socioeconomic factor influencing the spatial variations in ecosystem service value was population density, while the main physical–geographical factors were the digital elevation model, the normalized difference vegetation index, and precipitation. As a result, the Nanjing metropolitan area should tighten its grip on excessive population growth. In contrast to the expository strength of a single factor on the ecosystem service value, the influence of all individual elements on the ecosystem service value under interaction was significantly increased, and the interaction among the normalized difference vegetation index and gross economic product had the most obvious effect on the ecosystem service value. The spatial variation in the ecosystem service value was also influenced by trade-offs and synergies between the value of supply services, regulation services, support services, and cultural services. Therefore, trade-offs and synergies among ecosystem services also need to be considered in land-use decisions.

Dynamic Changes in Habitat Quality and the Driving Mechanism in the Luoxiao Mountains Area from 1995 to 2020

The strengthening of regional habitat quality is crucial to protect biodiversity and fully utilize ecosystem services such as those provided by forestry and aquatic ecosystems. However, the long-term patterns of change in the habitat quality of the Luoxiao Mountains area, which is both an important ecological barrier area and a concentrated poverty-stricken area, and the driving mechanism remain unclear. In this study, the InVEST model was used to assess the habitat quality of the Luoxiao Mountains area in 1995 to 2020, and the spatial autocorrelation model was used to explore the spatial and temporal variation and distribution characteristics of habitat quality. Further, ordinary least squares (OLS) model, geographically weighted regression (GWR) model, and random forest (RF) algorithm were combined with multidimensional datasets to explore the underlying mechanisms driving changes in habitat quality. According to the results, the habitat quality indices of the Luoxiao Mountains area in 1995, 2005, 2015, and 2020 were 0.822, 0.818, 0.817, and 0.813, respectively, with an overall decreasing trend. The RF model was the best fit for habitat quality, better than the GWR and OLS models. Physical geographic factors such as slope and precipitation, as well as socioeconomic factors such as gross domestic product, were key drivers of habitat quality in the Luoxiao Mountains. Precise implementation of ecological protection and restoration measures, improvements in the efficiency of spatial utilization, and exploration of the value of ecological products are key factors in maintaining a balance between habitat quality and economic growth into the future.

Analysis of the Spatial–Temporal Distribution Characteristics of NO2 and Their Influencing Factors in the Yangtze River Delta Based on Sentinel-5P Satellite Data

The recent rapid economic development in the Yangtze River Delta (YRD) has led to atmospheric destruction; therefore, it is imperative to solve the issue of atmospheric environmental pollution to ensure stable long-term development. Based on the NO2 column concentration observed by the TROPOMI (a tropospheric monitoring instrument) on the Sentinel-5P, the spatial–temporal distribution characteristics of the NO2 column concentration in the YRD from 2019 to 2020 were analyzed using the Google Earth Engine (GEE) platform, and the Geographical Detector (Geodetector) model was used to determine the driving factors of the NO2 column concentration. The results show that the correlation between the NO2 column concentration and the ground-monitored NO2 concentrations reached 70%. The annual variation trend of the NO2 column concentration exhibited a ‘U’-shaped curve, with the characteristics of ‘high in winter and low in summer, with a transition between spring and autumn’. It exhibited obvious agglomeration characteristics in terms of the spatial distribution, with a high-value agglomeration in the central region of the YRD, followed by the northern region, and a low-value agglomeration in the southern region, with higher altitudes. The change in the NO2 column concentration in the YRD was affected by both physical geographical factors and socio-economic factors; it is clear that the influence of socio-economic factors has increased.

Physical Geographical Factors Leading to the Disparity of Regional Development: The Case Study of Java Island

The complexity of regional disparity has encouraged viewing this issue from various perspectives, one of which is the role of physical geography in disparity. On Java Island, an observation on the role of geographical aspect is needed due to the spatial sturdiness of disparity. This study aims to provide quantitative proof that differences in the physical geography of Java’s regions account for the persistent regional disparity. We applied two approaches namely correlation and typology, employing data of physical geographical attributes and development level. The methods used were correlation analysis, factor analysis, cluster analysis, and one-way ANOVA. Based on the correlation approach, we found the association of regional development level with terrain ruggedness, soil parent materials, sea depth, elevation, and precipitation. Then, based on endowment-based typology approach, Java’s regions could be grouped into lowland, volcanic, old volcanic, and calcareous dry regions. The two latter performed poorly in all socio-economic indicators examined.

Physical geographical factors affecting honey bee breeding in Baghdad governorate

تؤثر العوامل الجغرافية الطبيعية بشكل مباشر في تربية نحل العسل وتوزيعها الجغرافي، تتمثل هذه العوامل (بالسطح، المناخ، التربة، الموارد المائية، النبات الطبيعي)، يكون تأثيرها بصورة كبيرة من حيث النمو والتكاثر الطبيعي وانتاج العسل. يهدف البحث الى بيان دور العوامل الجغرافية الطبيعية في التوزيع المكاني لتربية نحل العسل حسب الوحدات الإدارية لسنة 2018، عن طريق الدراسة الحقلية واستمارة الاستبيان وبيانات الدوائر المختصة، وبيان صورة التوزيع الجغرافي وعن طريق تصنيف البيانات على أساس الفئات باستخدام تقنية (التصنيف اللوغاريتمي) وتمثيلها على الخرائط. توصل البحث الى عدة نتائج اهمها ملائمة العوامل الجغرافية الطبيعية لتربية نحل العسل في منطقة الدراسة. واحتلت محافظة بغداد المركز الاول بأعداد الخلايا والمناحل وكمية الانتاج من العسل على مستوى محافظات العراق، اما على مستوى الوحدات الادارية داخل بغداد فاحتلت قضاء المدائن المركز الاول على مستوى الوحدات الادارية بأعداد الخلايا والمناحل وكمية انتاج العسل (6400 خلية و206 منحل و48135 كغم)، وأدنى مستوى احتلته ناحية التاجي بأقل عدد من الخلايا بلغ 406 خلية، وقضائي الرصافة والنهروان بأقل عدد من المناحل بلغ3 منحل، وناحية اللطيفية بأقل انتاج بلغ 305 كغم من العسل.

Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China.

Land surface temperature (LST) is a joint product of physical geography and socio-economics. It is important to clarify the spatial heterogeneity and binding factors of the LST for mitigating the surface heat island effect (SUHI). In this study, the spatial pattern of UHI in Fuzhou central area, China, was elucidated by Moran’s I and hot-spot analysis. In addition, the study divided the drivers into two categories, including physical geographic factors (soil wetness, soil brightness, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), water density, and vegetation density) and socio-economic factors (normalized difference built-up index (NDBI), population density, road density, nighttime light, park density). The influence analysis of single factor on LST and the factor interaction analysis were conducted via Geodetector software. The results indicated that the LST presented a gradient layer structure with high temperature in the southeast and low temperature in the northwest, which had a significant spatial association with industry zones. Especially, LST was spatially repulsive to urban green space and water body. Furthermore, the four factors with the greatest influence (q-Value) on LST were soil moisture (influence = 0.792) > NDBI (influence = 0.732) > MNDWI (influence = 0.618) > NDVI (influence = 0.604). The superposition explanation degree (influence (Xi ∩ Xj)) is stronger than the independent explanation degree (influence (Xi)). The highest and the lowest interaction existed in ”soil wetness ∩ MNDWI” (influence = 0.864) and “nighttime light ∩ population density” (influence = 0.273), respectively. The spatial distribution of SUHI and its driving mechanism were also demonstrated, providing theoretical guidance for urban planners to build thermal environment friendly cities.

Measuring the Impact of Physical Geographical Factors on the Use of Coastal Zones Based on Bayesian Networks

Coastal regions of the Baltic Sea are among the most intensively used worldwide, resulting in a need for a holistic management approach. Therefore, there is a need for strategies that even out the seasonality, which would ensure a better utilization of natural resources and infrastructure and improve the social and economic conditions. To assess the effectiveness of coastal zone planning processes concerning sustainable tourism and to identify and substantiate significant physical geographical factors impacting the sustainability of South Baltic seaside resorts, several data sets from previous studies were compiled. Seeking to improve the coastal zone’s ecological sustainability, economic efficiency, and social equality, a qualitative study (content analysis of planning documents) and a quantitative survey of tourists’ needs expressed on a social media platform and in the form of a survey, as well as long-term hydrometeorological data, were used. Furthermore, a Bayesian Network framework was used to combine knowledge from these different sources. We present an approach to identifying the social, economic, and environmental factors influencing the sustainability of coastal resorts. The results of this study may be used to advise local governments on a broad spectrum of Integrated Coastal Management matters: planning the development of the beaches and addressing the seasonality of use, directing investments to improve the quality of the beaches and protect them from storm erosion, and maintaining the sand quality and beach infrastructure. The lessons learned can be applied to further coastal zone management research by utilizing stakeholders and expert opinion in quantified current beliefs.

BÖYÜK QAFQAZIN ŞIMAL-ŞƏRQ YAMACININ SUVARILMASI ÜÇÜN İSTİFADƏ OLUNAN ÇAY VƏ KANAL SULARININ EKOLOJİ ANALİZİ

The rivers flowing from the north-eastern slope of the Greater Caucasus are among the rivers that flow directly into the Caspian Sea. Sludge, sand, various suspended solids, organic compounds, mineral salts, etc. in river water. both naturally and through irrigation. As a result of multi-year irrigation, agro-irrigation horizons of different thicknesses are formed by the accumulation in the soil of water-derived organic and mineral compounds. Significant changes in the mechanical composition of the soil occur due to the accumulation of materials here. First of all, the amount of small fractional physical activity increases, geophysical and geochemical processes change. The density of the soil increases, the reclamation condition deteriorates, the drainage capacity weakens, and the air and water regime are negatively affected. During the research, the hydrological features of the area rivers, feeding regime, areas irrigated by the rivers, ecological analysis of the river and canal waters and the complex of physical-geographical factors causing it were studied. Key words:water supply, water consumption, irrigated areas, canal water, ecological analysis of river water, physical-geographical factors

Agricultural Land-Use Changes in the Judean Region from the End of the Ottoman Empire to the End of the British Mandate: A Spatial Analysis

Vines and olives are two important and widespread traditional agricultural crops that are also connected to the Judeo–Christian–Muslim tradition. The goal of the research was to demonstrate the importance of using cartographical sources to obtain a more accurate and complete view of the past. To this end, the aims were: (1) to reconstruct the former agricultural land-use in three periods, 1873–1874, 1917, and 1943–1945; (2) to analyze the different spatial physical factors that could explain the spatial distribution of traditional agricultural landscapes; (3) to identify the changes which took place between the three reconstructed timestamps. The research employed different cartographic sources and the implemented analyses were conducted using GIS tools and methods. The results show that, in the past, the distribution of vines and olive groves greatly depended on several physical geographic factors (climate, slopes, direction). Nonetheless, human factors such as political instability, cultural and religious beliefs contributed as well. Moreover, this research showed how GIS has advanced historical geography research. Lastly, the research demonstrated that obtaining the most complete view of the past can be achieved by a combination of sources together with the use of GIS tools and methods.