Case Study Area Research Articles

Counting Crofters: Digitised Census Enumerators Books as a New Source for the Later Nineteenth Century

This paper explores some of the ways in which access to the census enumerators books for later nineteenth century censuses, now digitised by the ‘Integrated Census Microdata’ project, can throw new light on a range of socio-demographic developments in the ‘Crofting Counties’ between the early 1850s and the early 1880s. Collating and mapping occupational titles by parish reveals major changes in the titles recorded for those farming small land parcels and in the spatial distributions and age profiles or those heading such households. The numbers of household heads reported as ‘Crofter’ markedly increased between 1851 and 1881 (including outside the ‘Crofting Counties’), as use of terms like ‘Tenant’ and ‘Lotter’ declined. ‘Cottar’, even in 1851 used in very small numbers in most places, was reported in 1881 in very limited areas, even where the estates still used it extensively. The number of households headed by ‘Fishermen’ increased greatly in some areas, notably in Lewis. At the same time, the numbers of men becoming heads of small agriculturalist households at younger ages fell markedly, while rising numbers headed households as ‘Fishermen’. Comparative analysis of four case study areas suggests that, when fishing and other incomes fell markedly in the early 1880s, inter-generational differences in access to headship of a croft may have been a significant stimulus to localised outbreaks of disturbance pressing for land reform.

Climate Change, Air Pollution, and Human Health in the Kruger to Canyons Biosphere Region, South Africa, and Amazonas, Brazil: A Narrative Review

Climate Change, Air Pollution, and Human Health in the Kruger to Canyons Biosphere Region, South Africa, and Amazonas, Brazil: A Narrative Review

Living with technological drought: Experience of smallholding farmers of Bangladesh

Technological drought is caused by a lack of irrigation technology and a poor water management system. Here we present and analyse the results of a large survey of farmers in Bangladesh, designed to reveal their experience of and attitudes to, as well as factors and challenges of technological drought management. Also, we analysed the impact of water sources and the role of irrigation development to mitigate the technological drought taking North Bengal of Bangladesh as a case study. To explore the nature and characteristics of technological drought, we have used both qualitative and quantitative data from the study area. We used Principal Component Analysis (PCA) to find out the underlying dimensions and factor loadings of the technological drought using the field data. Moreover, we compared the relations and associations between socio-demographic, water source characteristics and technological drought perceptions. PCA results indicated seven underlying dimensions (challenges) out of thirty-one factors of technological drought related to river water management, irrigation technology, socio-economic conditions, land use, and electricity and fuel supply. The high population, lack of modern irrigation technology, upstream management problems, inefficiencies in the system, electricity connections, load shedding, and poor socio-economic conditions prevent people from getting the water they desperately need in the case study area. We also found a significant relationship between farmers’ socio-demographic and water source characteristics with technological drought perceptions. Although there has been increasing use of irrigation technology and improved water resource management in recent years, it is essential to highlight that there will likely be more challenges in the future if this trend continues.

Spatial constraints in cellular automata-based urban growth models: A systematic comparison of classifiers and input urban maps

Spatial constraints are fundamental to integrating the spatial suitability to urbanization into Cellular Automata-based (CA) urban growth models, but there is a lack of consensus on the optimal methods for this purpose. This study compared the performance of three probabilistic classifiers to generate suitability surfaces for CA-based urban growth models: Logistic Regression using Generalized Linear Model (LR-GLM), Logistic Regression using Generalized Additive Model (LR-GAM), and Random Forest (RF). The study also evaluated the sensitivity of these classifiers to the input urban map adopted as a dependent variable. For this analysis, seven maps were tested: the historical urban map containing the entire extent of the urban footprint, and six additional maps containing only the recently urbanized areas over timeframes ranging from one year up to two decades. The comparison evaluated the goodness of fit of the suitability surfaces and the spatial accuracy of the urban growth simulations, using five large Brazilian cities as case study areas. The results revealed that the RF classifier significantly outperformed the LR-based classifiers. However, this overperformance was more prominent when incorporating the new urban cells over the last one to two decades of growth as input urban maps. In addition, the sensitivity analysis of the input urban maps emphasized the benefits of calibrating the classifier using the recently urbanized cells rather than the historical urban extent. We consistently observed these results concerning classifiers and input urban maps across all five case study areas. Thus, the RF classifier combined with a training dataset containing the newly urbanized areas over at least the last 10 years systematically resulted in the suitability surfaces with the highest predictability among all tested scenarios.

Revealing hidden diversity and community dynamics of land snails through DNA barcoding: implications for conservation and ecological studies

IntroductionLand snails play a crucial role in maintaining ecosystem sustainability within their habitats. Therefore, understanding the characteristics of their communities is vital for ecological studies and the development of effective conservation strategies. In this study, land snail communities inhabiting the Hyrcanian forest were identified and the variations in their community composition along elevational gradients were investigated.MethodsSnail samples were collected from three distinct elevations in three different forest locations within the Hyrcanian area of Iran. This study utilized DNA barcoding to identify land snail species. By employing statistical analyses such as ANOVA and PERMANOVA, significant differences in the features of snail communities across different elevations were examined. Concurrently, soil samples were collected from each site to assess soil physicochemical parameters about snail presence.ResultThrough this comprehensive analysis, a total of 10 OTUs, were further classified into seven families, and nine genera were identified. Five of these genera had never been reported in the study region before. We observed a decline in OTU richness with increasing elevation; however, the maximum abundance of snails was found at higher elevations. CCA demonstrated that Ca, Mg, and moisture saturation predominantly shape snail community composition.DiscussionThe unique climatic conditions and spatial distribution of precipitation from lowlands to highlands, as well as from west to east, make the Hyrcanian forests an ideal case study area for understanding the dynamics of land snail communities. In summary, this study provides new insights into the land snail communities thriving in the Hyrcanian forests. The findings from our research can contribute to the development of effective conservation management strategies for forest ecosystems. By understanding the factors influencing the distribution and composition of land snail communities, we can make informed decisions to protect and preserve land snails and the balance they maintain within their habitats.

Are forest management practices to improve carbon balance compatible with maintaining bird diversity under climate change? A case study in Eastern North America

The combination of climate change and anthropogenic disturbance significantly impacts forest bird assemblages. Assessing the cumulative effects of forest management and climate change on biodiversity and ecosystem services, including carbon sequestration and storage and provisioning of wood products is key to informing forest management and conservation decision making. Specifically, we projected changes in forest composition and structure according to various forest management strategies under a changing climate using LANDIS-II for two case study areas of Quebec (Canada): a hemiboreal (Hereford Forest) and a boreal (Montmorency Forest) area. Then, we assessed projected bird assemblage changes, as well as sensitive and at-risk species. As part of an integrated assessment, we evaluated the best possible management measures aimed at preserving avian diversity and compared them with optimal options for mitigation of carbon emissions to the atmosphere. Forest management and climate change were projected to lead to significant changes in bird assemblages in both types of forest through changes in forest composition. We projected an increase in deciduous vegetation which favored species associated with mixed and deciduous stands to the detriment of species associated with older, coniferous forests. Changes were more pronounced in Hereford Forest than Montmorency Forest. In addition, Hereford’s bird assemblages were mainly affected by climate change, while those in Montmorency Forest were more impacted by forest management. We estimated that 25% of Hereford and 6% of Montmorency species will be sensitive to climate change, with projected abundance changes (positive or negative) exceeding 25%. According to the simulations, a decrease in the level of forest harvesting could benefit bird conservation and contribute to reduction of carbon emissions in the boreal forest area. Conversely, the hemiboreal forest area require trade-offs, as mitigation of carbon emissions is favored by more intensive forest management that stimulates the growth and carbon sequestration of otherwise stagnant stands.

Housing-industry transformation development and rural revitalization path based on complex adaptive system in Three Gorges Reservoir Area of China

The core of dual circulation in the Three Gorges Reservoir Area (TGRA) and the greening Yangtze River is sustainable development. Reservoir housing-industry coordinate sustainable is extremely important to ensuring a more sustainable TGRA. Here, we investigate the overall characteristics of housing-industry transformation development and rural revitalization path in the TGRA at microscopic perspective. Taking Wutu village (WTV), a historical and cultural rural in the TGRA, as case study area, we also analyze the evolution, stage characteristics, and trends of housing-industry system (HIS) using theoretical analysis and empirical research from the perspective of spatio-temporal-development and complex adaptability system model. The findings reveal that: (1) In the traditional housing-industry separation stage(1978–1998), the development of villagers' self-organization and the positive and correct leadership of the village party branch are the dominant forces for the evolution of HIS in WTV. The adaptive behavior of the main body and the strength of the housing-industry effect are limited, and the evolution of the HIS is in the accumulation stage of quantitative change. (2) In the stage of cooperative transformation of housing-industry (1999–2018), the positive and correct leadership of the village party branch is the dominant force of the evolution of HIS in WTV, and the government's policy support is the main force of the evolution of HIS in WTV. (3) In the stage of modern housing-industry integration (2019 to present), the interaction of multiple subjects is the dominant force in the evolution of HIS in WTV. Multiple entities further adapt to various changes in the external environment, and the system structure and level have taken a qualitative leap. Overall, the evolution of HIS in WTV is a dynamic and continuous process. Based on the evolution stage and driving mechanism of HIS, it is necessary to improve the self-organization and adaptive response and ability of the complex adaptive system in WTV, adapt to the general law of system evolution, and effectively regulate the transformation and upgrading of HIS in WTV. Our research outcomes offer valuable insights for fostering rural transformation, enhancing the housing-industry environment, and ultimately propelling the TGRA towards a more sustainable and prosperous future.

Linkages between urban growth and land surface temperature variations in the Seoul metropolitan area: A spatial first-order difference approach

This study investigates the effects of urban development and expansion on Land Surface Temperature (LST) changes from 2000 to 2018, using the Seoul Metropolitan area (SMA) as a case study area. Along with descriptive analysis, this study uses a spatial first-order difference model to statistically analyze the longitudinal relationship between land use features and LST, including impervious surface (IS), enhanced vegetation index (EVI), anthropogenic factors, and urban spatial and topographical factors as well as urban development types as influential factors on LST variations. Our findings support prior research indicating the cooling effects of vegetation and warming effects of imperviousness. We also found a positive association between detached housing units, manufacturing activities and LST changes and a negative relationship between apartment units, urban parks, service activities and LST changes. More importantly, substantial LST reduction was found in the large-scale high-rise apartment complexes redeveloped from the low-rise, detached housing sites in inner-city infill areas, contrasting with significant LST rise in the suburban new town development. We suggest redevelopment of inner-city low-rise compact areas into high-rise but greener blocks as a LST mitigation strategy, equipped with cooling strategies such as green infrastructure and climate-sensitive design considering local microclimate and natural ventilation.

Scaling up of sustainable soil management practices: some lessons from the hills of Nepal

A study was conducted to assess the scaling up processes of soil management practices under maize based farming systems in Panchkhal and Sanga areas of Kavre district. The key objectives of the study are to analyze the scaling up processes and pathways of soil management practices in the case study areas and identify factors related to scaling up at different levels. Three principalquestions guiding the analysis were: a) what are the positive aspects of scaling up processes and how can these be built on? b) What are the problems being experienced and how can these be overcome? c) What is the influence of people's livelihood strategies and assets on the processes? Kavre is one of the 10 districts where Sustainable soil Management Programme (SSMP) ofHelvetas has helped local people in the adoption of innovative soil management practices integrated with various cash and subsistence crops. With SMP support and advice, services to farmers in these areas create awareness and build their institutions (CIs) provide extension services to farmers in these areas create awareness and build their institutional capacity onadopting innovative soil management practices. The goal of the project is to improve livelihoods of resource poor farmers.Data for the study were gathered from 29 households through interviews, two workshops with key informants at the community level and a workshop with CIs at district levels, and review of SSMP and partners' documented information on the subject. The research team also made transect visits through the area, and interviewed several staff of the collaborating institutions. Qualitativeanalysis (in terms of perceptions of respondents) as well as quantitative analysis of data was done at household, community and institutional levels.

Using Google Street View to examine changes in food environments around secondary schools in regional and metropolitan areas of New South Wales, Australia

Food environments surrounding secondary schools are a known influence on the purchasing and consumption habits of adolescents(1). Understanding their obesogenic potential is important for informing strategies to create more healthful food environments for adolescents, particularly for those living in regional areas, and is a key component of Australia’s National Obesity Strategy(2). This repeated cross-sectional study examined the food environment surrounding secondary schools in regional and metropolitan New South Wales from 2007-2023. Google Street View was used to collect data regarding food outlets within a walkable distance (1.6 km) of all secondary schools in Wagga Wagga and Blacktown, our regional and metropolitan case study areas respectively, over 17 years. A Food Environment Score(3) tool was used to characterise the healthfulness of food environments by categorising food outlets into Food Outlet Type categories (e.g. Cafés, Fast-Food Franchises, Restaurants etc.) and Healthfulness categories (“Healthful”, “Less Healthful”, “Unhealthful”). Descriptive statistics were used to characterise changes in the food environments by Food Outlet Type and Healthfulness categories from 2007-2023. Chi-Squared tests were used to determine any significant differences in the proportion of healthful, less healthful and unhealthful food outlets between the regional and metropolitan study areas and between 2007 and 2023 in both areas. In both Wagga Wagga and Blacktown, the most common food outlet types surrounding secondary schools from 2007-2023 were classified as less healthful or unhealthful. As of 2023, less healthful food outlets [restaurants (19.4%), cafes (16.8%)] and unhealthful food outlets [fast-food franchises (15.1%), independent takeaway (14.1%)] were the most common food outlet types in Wagga Wagga, making up 52% and 36% of all identified food outlets respectively. These outlet types have remained the most prevalent over the 17-year period, though restaurants and cafes have since surpassed fast-food franchises and independent takeaway stores, by proportion, which were the most common in 2007. Similarly in Blacktown, 2023, less healthful [restaurants (21.1%), cafés (11.1%)] and unhealthful [fast-food franchises (17.4%)] were the most common food outlets, making up 41% and 37% of all identified food outlets. Restaurants, cafés and fast-food franchise outlets were consistently observed to be the most prevalent in Blacktown food environments over the 17-year study period. No significant difference was found when comparing the healthfulness profiles of regional and metropolitan food environments nor were significant changes observed between 2007 and 2023 in Wagga Wagga and Blacktown (p > 0.05 for all). The prevailing high proportion of less healthful and unhealthful food outlets near secondary schools in regional and metropolitan areas upholds the need for public health policies and planning strategies to address the obesogenic potential of school food environments.

Intensively Cultivated Roman Villae Estates: Case Study of Medulin Bay (Istria, Croatia)

ABSTRACTOur image of the Roman landscape of Istria is characterised by large‐scale centuriation and architectural remains of Roman villae. Detection and mapping of other, less dramatic landscape features require systematic large‐scale prospection, but this faces significant difficulties in the Mediterranean environment. However, the developments in the field of airborne laser scanning offer the possibility to create archaeologically usable digital terrain models under water and under very dense and low maquis vegetation. This paper reports on the use of terrain models created using a green laser and a sophisticated archaeologically driven ground point filtering strategy. Combined with archaeological aerial photo interpretation, this provides the means for landscape mapping and interpretation that has revealed a wealth of archaeological structures hinting at Roman agricultural practices and landscape. Our case study is based on a laser scan of about 24 km2 of land and underwater terrain in Medulin Bay. Processed, visualised and interpreted for archaeological purposes, the data reveal not only features ranging from prehistoric hilltop settlements to modern military installations but also features a complex picture of the Roman land use. Of particular interest is the large number of planting pits, which extend over a total length of 4 km. They were laid on a regular grid of approximately 35 × 35 m, sometimes combined in contiguous parcels. They can be interpreted as remains of orchards or tree nurseries of Roman date, and the paper examines also the question of whether they can be linked to the associated Roman estates. The case study area presented here shows that the potential of remote sensing methods goes far beyond the mere finding of traditional sites but can open up new landscape‐scale perspectives on regions that have been archaeologically little explored.

Performance investigation of solar ejector cooling system: Case study area-Addis Ababa, Ethiopia

This study investigates the performance of a solar ejector cooling system under both on-design and off-design operating conditions, focusing on the case study area of Addis Ababa, Ethiopia. Data crucial to the analysis were gathered from the Ethiopian National Meteorology Agency (ENMA) over six consecutive years (2013-2018). The system's performance was evaluated through hourly and monthly analyses under on-design conditions, yielding promising results. Under on-design conditions, the system demonstrated favorable performance metrics. Specifically, at noontime in March, when the design points were set at Tg = 90°C, Tc = 30°C, and Te= 12°C, the system achieved a total hourly maximum coefficient of performance (COP) of 0.2049 and a cooling capacity of 186.9 W/m². Furthermore, the study determined that a collector area of 22.3 m² per ton of cooling capacity is required during noontime for all cooling seasons in Addis Ababa, Ethiopia. Additionally, an off-design operating condition map was developed for the system. The findings indicate that the solar ejector cooling system can effectively provide cooling during office hours (8:00-15:00) in Addis Ababa, Ethiopia.

City-scale analysis of PV potential and visibility in heritage environment using GIS and LiDAR

Increasing the share of renewables, especially utilizing solar power in our energy mix is a highly prioritized aim of the EU. Budapest, the largest city and the capital of Hungary, contains almost 1 million flats in more than 190 thousand buildings, organized in various characteristic urban fabric types. Although on-site renewable energy production is severely limited in dense urban environments, the roofs offer a considerable potential to generate energy on-site.The present paper introduces a method to estimate the PV potential of rooftops on a large scale applying a GIS approach. Using LiDAR data, a Digital Surface Model (DSM) was created. The DSM was utilized to evaluate roof slope, orientation, and global irradiation. Solar potentials, available roof area, photovoltaic (PV) system capacities and estimated annual electricity production were derived from the GIS model. The method was used to develop an open access website called the Budapest Solar Map, which provides decision-makers with solar PV data. However, the nominal PV potential is limited by layers of heritage protection regulations that safeguard the sight of our case study area, Budapest, which is a World Heritage Site. Visibility is also surveyed with GIS and geometrical modeling from designated high points and from the street level, respectively.

Exploring the motivation and challenges for land-users engaged in sustainable grazing in Europe

Grazing of both domestic and wild large herbivores can contribute to multiple ecosystem services. However, grazing systems strongly differ in the intensity of management and outcomes, and we define sustainable grazing as grazing which benefits multiple environmental ecosystem services. Previous studies have found that, in general, grazing systems with relatively low densities of animals, and with minimal and only targeted applications of deworming and other medicinal treatments, are most sustainable. However, for people engaged in such grazing management, a key question is what are their challenges and motivation.We conducted interviews with 74 land-users, who are engaged in sustainable grazing management, in eight case-study areas in Europe. Employing the capability, opportunity and motivation-behaviour model (COM-B), we identified key motivation factors driving sustainable grazing management and the challenges which these land-users face. We found that capability and opportunity linked to land abandonment and rural exodus impact upon land-users’ management, especially in parts of South and Eastern Europe. Furthermore, challenges linked to the environment were particularly important in remote areas. In addition, we found economic aspects to be important in driving land-users’ behaviour, especially fiscal measures of the Common Agricultural Policy. Moreover, our results indicate that engagement in sustainable grazing management is often intrinsically motivated by the interest in nature conservation, intergenerational continuity and cohesion in the rural community.Based on these results, using the Behaviour Change Wheel, we identify key interventions that could facilitate and encourage the capabilities and opportunities to conduct sustainable grazing management. These include incentivising extensification using subsidies, developing direct market possibilities and removing administrative hurdles for practises related to very extensive and semi-wild grazing.

The network characteristics of classic red tourist attractions in Shaanxi province, China.

Red tourism is a distinctive form of tourism in China. Its network attention serves as a typical indicator to measure the level of promotion and publicity for red tourism, as well as an important reflection of its influence. Understanding the network structure of red tourism is of significant importance for optimizing the spatial pattern of tourism and promoting the development of the tourism industry. Based on this, this study takes the classic red tourism attractions in Shaanxi province, China as an example and constructs a multi-source data network attention evaluation index. Additionally, it employs social network theory to explore the network attention and tourist flow characteristics of the case study area. Research shows that: (1) Overall, the network attention to case-based destinations is relatively low, and there are significant differences in network attention among different attractions. Spatially, the distribution of network attention is uneven. This is manifested by higher network attention to attractions in Yan'an city and lower network attention to attractions in other regions. (2) There are differences in the network attention of different types of attractions. High-level attractions have a higher level of online attention, while low-level attractions have a lower level of network attention. Additionally, archaeological sites tend to receive a higher level of online attention. (3) The network density of tourist flow is low, and the tourism connections between nodes are not closely linked. The linkage between core nodes and edge nodes in tourism is poor. Developed tourism routes only exist in core nodes. (4) Nodes such as Zaoyuan revolution site, Yangjialing revolution site, and Wangjiaping revolution site have a significant influence in the network structure. In addition, the integration and development between red nodes and non-red nodes have been achieved. (5) There is a correlation between network attention and tourist flow, as well as a 'misplacement' feature. Based on the characteristics of attractions, they can be divided into four types: bright-star attractions, cash-cow attractions, thin-dog attractions, and question attractions. Based on the above conclusions, this study proposes targeted development recommendations.

Study on the differences and influencing factors of spatial distribution of population aging at township scale: a case study of township research units in Anshun City, China.

An aging population is one of the main features of China's current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province's southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced multi-scale geographical weighted regression to explore its influencing factors. The results show that Anshun City's older people population proportion (OPP) is generally high with more than 7% of the older people there, making it part of an aging society. The OPP appeared high in the east and low in the west in spatial distribution; the older people population density (OPD) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.

Classification and Planning Strategies of Multidimensional Resilience Units for Urban Waterlogging: A Case Study of the Old City District in Shijiazhuang, China

The frequency of urban disasters such as waterlogging has markedly increased, highlighting the urgent need to strengthen urban disaster prevention capabilities and resilience. This research, anchored in the resilience characteristics of robustness, redundancy, resource deploy ability, and rapid response, devised a resilience clustering factor system specifically designed for older urban districts. The old city district of Shijiazhuang, China, was selected as the empirical case study area. This research employs the K-Means++ clustering method to analyze the region’s resilience units against waterlogging. Furthermore, it utilizes the method of pedigree classification to categorize the identified ten types of resilience. Secondly, these were subsequently divided into three primary categories based on a spectrum of strengths and weaknesses within each unit: dominant, mixed, and disadvantaged clustering. This categorization unveiled the unique resilience distribution patterns within the area. The findings of this study reveal a pronounced differentiation in resilience types among the units in Shijiazhuang’s old city district. This spatial analysis highlighted a significant heterogeneity, with a tendency towards cluster formation. The spatial distribution of different resilience unit types was found to be uneven, leading to the emergence of clustered, patch-like, and zonal agglomerations. Combined with the unit clustering classification and the mean clustering performance of each factor, the response unit of waterlogging control resilience planning is determined for the study area, and the strategy of resilience waterlogging control and linkage is proposed. By mapping the spectrum of rainwater resilience types across the studied area, this research broadens the scope of resilience evaluation from a traditional vertical-level assessment to a more comprehensive horizontal typological analysis, offering empirical, theoretical insights for future resilience-building endeavors in older urban districts.

İżnik Town and Its Rural Landscape: Decision Making, Socio-Demographic Profiling and Conservation Policy Development

ABSTRACT In light of recent advances in landscape conservation, this study introduces a profiling model that provides context-sensitive heritage conservation strategies. The model is adaptable and focuses on socio-demographic profiling of a rural landscape. It uses İznik (ancient Nicaea) town, a UNESCO World Heritage candidate, and the surrounding rural landscape as a case study area. The model captures the intricate interplay between the socio-demographic conditions of agriculture-based local communities and rural heritage, offering policy options to enhance community well-being and conserve rural heritage. Based on the complementary use of Cluster and Multiple Correspondence Analysis, the model employs multi-layered analysis of quantitative and qualitative data. The model identifies six distinct clusters, revealing the vulnerability and resilience of rural settlements around İznik town, and the priority sites where rural heritage and local populations face immediate threat. Fostering a symbiotic relationship between data-driven insights and locally informed policies, this model generates evidence-based, people-centred policy outputs for heritage conservation, which may be applicable in a variety of contexts.

Integrating the PROSAIL and SVR Models to Facilitate the Inversion of Grassland Aboveground Biomass: A Case Study of Zoigê Plateau, China

Grasslands play a vital role in the global ecosystem. Efficient and reproducible methods for estimating the grassland aboveground biomass (AGB) are crucial for understanding grassland growth, promoting sustainable development, and assessing the carbon cycle. Currently, the available methods are limited by their computational inefficiency, model transfer, and sampling scale. Therefore, in this study, the estimation of grassland AGB over a large area was achieved by coupling the PROSAIL model with the support vector machine regression (SVR) method. The ill-posed inverse problem of the PROSAIL model was mitigated through kernel-based regularization using the SVR model. The Zoigê Plateau was used as the case study area, and the results demonstrated that the estimated biomass accurately reproduced the reference AGB map generated by zooming in on on-site measurements (R2 = 0.64, RMSE = 43.52 g/m2, RRMSE = 15.13%). The estimated AGB map also maintained a high fitting accuracy with field sampling data (R2 = 0.69, RMSE = 44.07 g/m2, RRMSE = 14.21%). Further, the generated time-series profiles of grass AGB for 2022 were consistent with the trends in local grass growth dynamics. The proposed method combines the advantages of the PROSAIL model and the regression algorithm, reduces the dependence on field sampling data, improves the universality and repeatability of grassland AGB estimation, and provides an efficient approach for grassland ecosystem construction and planning.

Estimation of Demand for Urban Land Uses: A Case Study of Türkiye

Land use change can have adverse impact on society and environment and therefore this puts enormous pressure on governments. Accurate estimates of future urban expansion are essential for sustainable growth and the preservation of the environment. This article examines the land use changes for urban uses, and further applies different methods for the projection of residential and industrial/commercial land uses in the selected case study area i.e. NUTS3 (nomenclature of terrestrial units for statistics) regions of Turkey. Density measures, trend extrapolation and regression analysis are the subject statistical methods used for projecting the land use. The findings show that using the chosen methodologies to project past changes leads in significant uncertainty. The results are significantly influenced by the variation in selected variables, and spatial organization of the study region. Therefore, validation analysis as a future research focus will be essential to select the most appropriate model that can be used to project the land use changes in Turkey. The results from the current analysis can be adopted by the government and local authorities for the land management and sustainable growth of urban land use in the Turkish regional context.