Land, Volume 10, Issue 5 (May 2021) – 107 articles

Climate and socioeconomic and policy factors are found to stimulate land use changes along with changes in greenhouse gas emissions and adaption behaviors. Most of the studies investigating land use changes in the U.S. have not considered potential spatial effects explicitly. We used a two-step linearized multinomial logit to examine the impacts of various factors on conterminous U.S. land use changes including spatial lag coefficients. The estimation results show that the spatial dependences have existed for cropland, pastureland, and grasslands with a negative dependence on forests but weakened in most of the land uses except for croplands. Temperature and precipitation were found to have nonlinear impacts on the land use shares in the succeeding years by exerting opposite effects on crop versus pasture/grass shares. We also predicted land use changes under different climate change scenarios. The simulation results imply that the southern regions of the U.S. would lose cropland shares with further severity under the business-as-usual climate scenarios, while the land use shares for pasture/grass and forest would increase in those regions. As land use plays an important role in the climate system and vice versa, the results from this study may help policymakers tackle climate-driven land use changes and farmers adapt to climate change. Full article

Urban regeneration governance (URG) has become a popular issue in academia, politics and civil society because it has a significant influence on the success of urban regeneration activities. However, a comprehensive review on URG has yet to be produced, which hinders providing references to developing appropriate governance arrangements. Therefore, this study selected 88 relevant literatures from 1990 to 2019 to conduct a critical review. The goal of this review is to conceptualize URG, refine the signature elements of URG, compare the main modes of URG, and analyze the influential factors of URG. As a decision-making mode or a partnership, URG consists of three elements—partner, power and procedure—and influenced by three factors, the plan, place and person. There are three main modes of URG and each has pros and cons. Based on a comprehensive review, this paper concludes some findings and draws an 8p model that can provide an analysis framework for decision makers. Finally, four avenues for future research are proposed. Full article

Despite the increased usage of global soil property maps, a proper review of the maps rarely takes place. This study aims to explore the options for such a review with an application for the S-World global soil property database. Global soil organic carbon (SOC) and clay content maps from S-World were studied at two spatial resolutions in three steps. First, a comparative analysis with an ensemble of seven datasets derived from five other global soil databases was done. Second, a validation of S-World was done with independent soil observations from the WoSIS soil profile database. Third, a methodological evaluation of S-world took place by looking at the variation of soil properties per soil type and short distance variability. In the comparative analysis, S-World and the ensemble of other maps show similar spatial patterns. However, the ensemble locally shows large discrepancies (e.g., in boreal regions where typically SOC contents are high and the sampling density is low). Overall, the results show that S-World is not deviating strongly from the model ensemble (91% of the area falls within a 1.5% SOC range in the topsoil). The validation with the WoSIS database showed that S-World was able to capture a large part of the variation (with, e.g., a root mean square difference of 1.7% for SOC in the topsoil and a mean difference of 1.2%). Finally, the methodological evaluation revealed that estimates of the ranges of soil properties for the different soil types can be improved by using the larger WoSIS database. It is concluded that the review through the comparison, validation, and evaluation provides a good overview of the strengths and the weaknesses of S-World. The three approaches to review the database each provide specific insights regarding the quality of the database. Specific evaluation criteria for an application will determine whether S-World is a suitable soil database for use in global environmental studies. Full article

Land-use intensity (LUI) is one of the most direct manifestations of regional land use efficiency. The study of cross-administrative LUI in urban agglomerations is of great importance for the sustainable development of land, new urbanization, and territorial spatial planning. In this study, the urban agglomeration in the middle reaches of the Yangtze River in China was used as the case study area to explore the spatial spillover effect through the administrative division, underlying driving mechanism, and spatial interactions or constraints of LUI. First, LUI was measured using the index of the proportion of construction land to the total area of the administrative region. Second, the adjacency relationship of the county-level administrative units was identified on the basis of the queen-type adjacency criterion under the county-level administrative division system. Thereafter, spatial weight matrix for spatial modeling was constructed. Last, a spatial model using the “Spatial adjacency matrix” was devised to examine the influencing factors and the potential spatial interactions or constraints of administrative units. Results revealed that the level of LUI of different county-level administrative units were quite different, and the gap of LUI among county-level administrative units widened from 2010 to 2017. The fixed asset investment per land (FAIL), gross domestic product per capital (PGDP), and proportion of tertiary sector (PTS) are the driving factors of LUI. County-level administrative units not only had a significant and increasing spatial interaction effect based on the relationship of cooperation, but also had an influence of restraint mutually which was caused by the competition. The direct spatial spillover effect was remarkable. In the future, the effect of interaction among administrative units under the administrative division should be considered to promote the reasonable use and optimal layout of regional urban land to realize the optimal allocation of land resources. Full article

Previous studies mainly focused on quantifying the contribution rate of different factors on annual runoff variation in the source region of the Yellow River (SRYR), while there are few studies on the seasonal runoff variation. In this study, the monthly water storage and monthly actual evaporation of SRYR were calculated by the monthly ABCD model, and then a seasonal Budyko frame was constructed. Finally, the contribution rate of climatic and anthropic factors on the seasonal runoff variation in Tangnaihai hydrological station were quantitatively calculated. It turned out that: (1) The changing point of runoff data at Tangnaihai hydrological station is 1989. (2) The ABCD monthly hydrological model could well simulate the monthly runoff variation of Tangnaihai hydrological station. (3) Anthropic factors play a major role in runoff change in spring, summer, and winter, while climatic factors play a major role in runoff change in autumn. Full article

World War II’s military activities and the post-war devastation period destroyed many European cities and towns. One of the areas that was struck the most was former East Prussia, currently located in Poland and the Kaliningrad Region (the Russian Federation). In addition to the destruction of cities, which are strategically and economically important, small towns have also suffered. An example of such a town is Węgorzewo, where the scale of destruction of the pre-war urban tissue exceeded 80%, and the old town’s built-up area practically ceased to exist. This town magnifies most of the processes and spatial problems characteristic of Central and Eastern Europe’s towns of the “metamorphic” type. Post-war zoning during the Polish People’s Republic period, in the spirit of constructing a socialist town and bypassing the original spatial arrangement, brought about irreversible changes in the urban tissue. This was reflected in the break with the town’s original layout and the creation of modernist buildings. The changes were solidified or even deepened during the economic and political transition of the 1990s in Poland. Today, decades after the end of World War II, despite taking corrective measures, the town is still facing the problem of spatial chaos. Its morphological and physiognomic manifestations in the lack of a central public space, the loss of its historic character, the disharmonization of the urban landscape, and the dispersed development are the main subjects of this article’s analysis. This study uses a diverse methodological apparatus consisting of an analysis of the town’s morphological transformations, an analysis of the physiognomy of the urban landscape and architecture, in situ studies, and an analysis of municipal documents and expert interviews. In the discussion, the study results are embedded in the context of the cases of other European cities and towns. The conclusions indicate the risks to the formation of spatial order in Węgorzewo and possible paths of action. Full article

The pollination ecology in agroecosystems tackles a landscape in which plants and pollinators need to adjust, or be adjusted, to human intervention. A valid, widely applied approach is to regard pollination as a link between specific plants and their pollinators. However, recent evidence has added landscape features for a wider ecological perspective. Are we going in the right direction? Are existing methods providing pollinator monitoring tools suitable for understanding agroecosystems? In Italy, we needed to address these questions to respond to government pressure to implement pollinator monitoring in agroecosystems. We therefore surveyed the literature, grouped methods and findings, and evaluated approaches. We selected studies that may contain directions and tools directly linked to pollinators and agroecosystems. Our analysis revealed four main paths that must come together at some point: (i) the research question perspective, (ii) the advances of landscape analysis, (iii) the role of vegetation, and (iv) the gaps in our knowledge of pollinators taxonomy and behavior. An important conclusion is that the pollinator scale is alarmingly disregarded. Debate continues about what features to include in pollinator monitoring and the appropriate level of detail: we suggest that the pollinator scale should be the main driver. Full article

Ordination methods are used in ecological multivariate statistics in order to reduce the number of dimensions and arrange individual variables along environmental variables. Geoheritage designation is a new challenge for conservation planning. Quantification of geoheritage to date is used explicitly for site selection, however, it also carries significant potential to be one of the indicators of sustainable development that is delivered through geosystem services. In order to achieve such a dominant position, geoheritage needs to be included in the business as usual model of conservation planning. Questions about the quantification process that have typically been addressed in geoheritage studies can be answered more directly by their relationships to world development indicators. We aim to relate the major informative geoheritage practices to underlying trends of successful geoheritage implementation through statistical analysis of countries with the highest trackable geoheritage interest. Correspondence analysis (CA) was used to obtain information on how certain indicators bundle together. Multiple correspondence analysis (MCA) was used to detect sets of factors to determine positive geoheritage conservation outcomes. The analysis resulted in ordination diagrams that visualize correlations among determinant variables translated to links between socio-economic background and geoheritage conservation outcomes. Indicators derived from geoheritage-related academic activity and world development metrics show a shift from significant Earth science output toward disciplines of strong international agreement such as tourism, sustainability and biodiversity. Identifying contributing factors to conservation-related decisions helps experts to tailor their proposals for required evidence-based quantification reports and reinforce the scientific significance of geoheritage. Full article

Access to land for many people in Africa is insecure and continues to pose risks to poverty, hunger, forced evictions, and social conflicts. The delivery of land tenure in many cases has not been adequately addressed. Fit-for-purpose spatial frameworks need to be adapted to the context of a country based on simple, affordable, and incremental solutions toward addressing these challenges. This paper looked at three case studies on the use of the Social Tenure Domain Model (STDM) tool in promoting the development of a fit-for-purpose land administration spatial framework. Data gathering from primary and secondary sources was used to investigate the case studies. The empirical findings indicated that the use and application of the STDM in support of the fit-for-purpose land administration framework is quite effective and can facilitate the improvement in land tenure security. The findings also revealed that the tool, together with participatory and inclusive processes, has the potential to contribute to other frameworks of Fit-For-Purpose Land Administration (FFP LA) toward influencing changes in policy and institutional practices. Evidently, there was a remarkable improvement in the institutional arrangements and collaboration among different institutions, as well as a notable reduction in land conflicts or disputes in all three case studies. Full article

The purpose of this study is to reveal the spatial-temporal change and driving factors of green space in coastal cities of southeast China over the past 20 years. A supervised classification method combining support vector machines (SVMs) and visual interpretation was used to extract the green space from Landsat TM/OLI imageries from 2000–2020. The landscape pattern index was used to calculate geospatial information of green space and analyze their spatial-temporal changes. The hierarchical partitioning analysis was then used to determine the influences of anthropogenic and geographic environmental factors on the spatial-temporal changes in green space. The results indicated that the total area of green space remained constant over the past 20 years in coastal cities of southeast China (1% reduction). The spatial change of green space mainly occurred in the area near the ocean and the southern region. 41.37% of forest land was transferred from cultivated land, while 44.56%, 41.83%, 43.20%, 46.31%, 41.98% and 40.20% of shrub land, sparse woodland, other woodland, high-coverage grassland, moderate-coverage grassland and low-coverage grassland were transferred from forest land. The number of patches, patch density, edge density, landscape shape index and Shannon’s diversity index increased from 2000–2015, and then decreased to the minimum in 2020, while largest patch index continued to decline from 2000–2020. The contribution of anthropogenic factors (0.53–0.61) on the spatial-temporal changes of green space continually increased over the past 20 years, which was also higher than geographical environment factors (0.39–0.41). Our study provides a new perspective to distinguish the impact of anthropogenic activities and geographical environmental factors on the change of green space area, thereby providing a theoretical support for the construction and ecological management of green space. Full article

Land system change has been identified as one of four major Earth system processes where change has passed a destabilizing threshold. A historical record of landscape change is required to understand the impacts change has had on human and natural systems, while scenarios of future landscape change are required to facilitate planning and mitigation efforts. A methodology for modeling long-term historical and future landscape change was applied in the Delaware River Basin of the United States. A parcel-based modeling framework was used to reconstruct historical landscapes back to 1680, parameterized with a variety of spatial and nonspatial historical datasets. Similarly, scenarios of future landscape change were modeled for multiple scenarios out to 2100. Results demonstrate the ability to represent historical land cover proportions and general patterns at broad spatial scales and model multiple potential future landscape trajectories. The resulting land cover collection provides consistent data from 1680 through 2100, at a 30-m spatial resolution, 10-year intervals, and high thematic resolution. The data are consistent with the spatial and thematic characteristics of widely used national-scale land cover datasets, facilitating use within existing land management and research workflows. The methodology demonstrated in the Delaware River Basin is extensible and scalable, with potential applications at national scales for the United States. Full article

The world can learn two key lessons from spontaneous settlements: (i) design so as to adapt to human biology; and (ii) design to save energy. Timeless processes of urban growth and sustainability have forced societies to conserve energy. Yet, nowadays, a profession focused on design ideology and short-term profit discredits many economical and effective long-term design methods. Decision-makers, politicians, and urbanists talk of energy conservation while continuing to use failed notions of industrial urbanity in place of documented solutions that work. Most damaging is the myopic academic elite’s fixation on an unsustainable industrial-modernist visual vocabulary of minimalist forms. By promoting typologies based on images dating from the 1920s, instead of using scientific analysis, the industry serves extractive global imperialism rather than satisfying the world’s population needs. We should instead learn from how self-builders adapt form, geometry, materials, surfaces, and ornament to maximize the user’s emotional experience in an otherwise extremely challenging environment. Full article

A Fit-for-Purpose (FFP) land administration system strives for a more flexible, inclusive, participatory, affordable, reliable, realistic, and scalable approach to land administration and management in developing countries. The FFP finds itself thus at the interface with the coordination and governance challenges of the mainstream promotion of democratic decentralization of the past decades in general, and collaborative systems for decentralized and participatory land governance in Africa, in particular. One recent example of such collaborative systems for decentralized land governance is the introduction in South Africa between 2015 and 2019 of District Land Reform Committees (DLRCs). We analyze this official experiment in collaborative land governance from a ‘system of innovation’ (SI) perspective. An adapted SI framework is developed and applied in three DLRCs. This study points out that for the innovation of collaboration to be effective, DLRCs require a firm operational and institutional backup. This is an important lead for the general discussion on inclusion, participation, and collaboration in FFP. We not only need these innovations to be well-supported and -resourced; they also require the explicit adoption of a systemic perspective in which various technical and social dimensions are interlinked. Full article

The characteristics of housing and location conditions are the main drivers of spatial differences in housing prices, which is a topic attracting high interest in both real estate and geography research. One of the most popular models, the hedonic price model (HPM), has limitations in identifying nonlinear relationships and distinguishing the importance of influential factors. Therefore, extreme gradient boosting (XGBoost), a popular machine learning technology, and the HPM were combined to analyse the comprehensive effects of influential factors on housing prices. XGBoost was employed to identify the importance order of factors and HPM was adopted to reveal the value of the original non-market priced influential factors. The results showed that combining the two models can lead to good performance and increase understanding of the spatial variations in housing prices. Our work found that (1) the five most important variables for Shenzhen housing prices were distance to city centre, green view index, population density, property management fee and economic level; (2) space quality at the human scale had important effects on housing prices; and (3) some traditional factors, especially variables related to education, should be modified according to the development of the real estate market. The results showed that the demonstrated multisource geo-tagged data fusion framework, which integrated XGBoost and HPM, is practical and supports a comprehensive understanding of the relationships between housing prices and influential factors. The findings in this article provide essential implications for informing equitable housing policies and designing liveable neighbourhoods. Full article

Farmers’ livelihood and land have been the focus of academic and political attention for a long time. In the process of rapid urbanization in China, as farmers change their livelihood strategies and livelihood capital allocation driven by economic interests, farmland abandonment increases, which is not conducive to the guarantee of food security. This study aims to explore the characteristics of livelihood capital and land transfer of farmers under different livelihood strategies and the effect of livelihood capital on land transfer. Based on the data obtained from Sichuan Province in 2012, 2016 and 2019 by the China Rural Development Survey Group, this paper divides farmers into pure farmers, part-time farmers and non-farmers according to the proportion of non-agricultural income in total income, and constructed the panel binary Logit model and panel Tobit model. The analysis points to the following results: (1) pure farmers tend to shift other capitals toward natural capital, so their livelihood capital total index value decreased. The part-time farmers have different shift characteristics but their livelihood capital total index value both increased first and then decreased. Non-farmers tend to shift natural capital towards other livelihood capitals, so their livelihood capital total index value increased. (2) The higher the natural capital and human capital, the higher the probability of land transfers in. The higher the natural capital, the larger the area of land transfers in. The higher the financial capital, the higher the probability of land transfers out. The higher the financial capital and social capital, the larger the area of land transfers out. It is expected to provide suggestions for the policy of farmers’ land transfer under different livelihood capital endowments. Full article

There is a rivalry between policies on intensification of forest management to meet the demands of a growing bioeconomy, and policies on green infrastructure functionality. Evaluation of the net effects of different policy instruments on real-world outcomes is crucial. First, we present data on final felling rates in wood production landscapes and stand age distribution dynamic in two case study regions, and changes in dead wood amounts in Sweden. Second, the growth of formally protected areas was compiled and changes in functional connectivity analysed in these regions, and the development of dead wood and green tree retention in Sweden was described. The case studies were the counties Dalarna and Jämtland (77,000 km²) representing an expanding frontier of boreal forest transformation. In the wood production landscape, official final felling rates averaged 0.84%/year, extending the regional timber frontier. The amount of forest <60 years old increased from 27–34% in 1955 to 60–65% in 2017. The amounts of dead wood, a key forest naturalness indicator, declined from 1994 to 2016 in north Sweden, and increased in the south, albeit both at levels far below evidence-based biodiversity targets. Formal forest protection grew rapidly in the two counties from 1968 to 2020 but reached only 4% of productive forests. From 2000 to 2019, habitat network functionality for old Scots pine declined by 15–41%, and Norway spruce by 15–88%. There were mixed trends for dead wood and tree retention at the stand scale. The net result of the continued transformation of near-natural forest remnants and conservation efforts was negative at the regional and landscape levels, but partly positive at the stand scale. However, at all three scales, habitat amounts were far below critical thresholds for the maintenance of viable populations of species, let alone ecological integrity. Collaboration among stakeholder categories should reject opinionated narratives, and instead rely on evidence-based knowledge about green infrastructure pressures, responses, and states. Full article

We adopted a weight of evidence approach to establish a causal analysis of an impaired land ecosystem on a regional scale; namely, Daye, a traditional mining city in China. Working processes, including problem statements, a list of candidate causes, and a conceptual model were developed to represent a causal hypothesis for describing land degradation. Causal criteria were applied to integrate multiple lines of evidence. Then, various pieces of evidence were scored to either strengthen or weaken our causal assumptions. Results showed that habitat alteration, heavy metal accumulation, organic pollutants, water eutrophication, and nutrient runoff were the probable causes of land ecosystem impairment in Daye. Meanwhile, noxious gas, toxicants, altered underground runoff, atmospheric deposition, and acid rain were identified as possible causes. The most unlikely causes were altered hydrology, altered earth surface runoff, and soil erosion. Soil salinization, soluble inorganic salts, biological species invasion, and pathogens were deferred as delayed causes due to lack of adequate information. The causal analysis approach was applied to identify the primary causes of land degradation and implement accurate protective measures in an impaired land ecosystem. Full article

This article seeks to initiate research into traditional rural hedging techniques, hedge types, and hedgerow networks for the purpose of their potential adaptation as urban green systems (UGS). The research involves three scales: (1) the plant scale and related manipulation techniques; (2) hedgerows and their context-specific types, ecosystem function, and ecosystem services; and (3) hedgerow networks as continuous green systems that characterize and support specific landscapes. This research required an interdisciplinary approach. The analysis was conducted by applying different modes of research including: (a) an extensive literature review, (b) analysis and systematization of hedge types and manipulation methods, (c) field experiments, (d) design experiments, and (e) examination of real-life projects that use hedges or hedging techniques as distinct design features. The initial research indicates that traditional hedges can be adapted to vitally contribute to UGS by providing a broad range of urban ecosystem services. Furthermore, the research includes initial proposals on future applications of adapted rural hedge types and techniques. On the larger scale, anticipated difficulties regarding implementation, such as land allocation in cities and resource-intensive planting, management, and maintenance, are discussed and further research questions are outlined. Full article

In the last few decades, land use/land cover (LULC) has changed significantly under the influence of local planning and policy implementation, and this has had a profound impact on the regional ecological environment. By taking the Hengduan Mountain region as the study area, this study considered the demands of various commodities and services and applied the CLUMondo model to predict the trajectory of change in the land system for the years 2010–2030. The results indicate that the forest system expands significantly in this time, while the grassland and cropland systems are projected to develop intensively under the three scenarios. The high demand for livestock products is the main cause of the intensification of the grassland system under the TREND scenario, the demand for forests leads to the expansion of the forest land system under the FOREST scenario, and the significant intensification of the cropland system under the CONSERVATION scenario is closely related to an increase in the area of ecological land. The results of this study can provide a scientific reference for the optimal management of land systems in other mountainous areas. Full article

Climate change has proved to be a threat to food security the world over. Using temperature and precipitation data, this paper examines the differential effects climate change has on different land uses in the Luvuvhu river catchment in South Africa. The paper uses the Normalised Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI), which were calculated from Landsat images, and the Standardised Precipitation Index (SPI) for a sample of years between 1980 and 2016 to assess how drought and flood frequency have affected the agricultural environment. The results indicate that the lowest SPI values were recorded in 1996/1997, 2001/2002 and 2014/2015, suggesting the occurrence of drought during these years, while the highest SPI values were recorded in 1997/1998, 2002/2003 and 2004/2005. The relationship between three-month SPI (SPI_3) and VCI was strongest in grassland, and subsistence farming areas with the correlation coefficients of 0.8166 (p = 0.0022) and −0.6172 (p = 0.0431), respectively, indicating that rainfall variability had a high negative impact on vegetation health in those land uses with shallow-rooted plants. The findings of this study are relevant to disaster management planning in South Africa, as well as development of farming response strategies for coping with climate hazards in the country. Full article

Land use optimization (LUO) first considers which types of land use should exist in a certain area, and secondly, how to allocate these land use types to specific land grid units. As an intelligent global optimization search algorithm, the Genetic Algorithm (GA) has been widely used in this field. However, there are no comprehensive reviews concerning the development process for the application of the Genetic Algorithm in land use optimization (GA-LUO). This article used a bibliometric analysis method to explore current state and development trends for GA-LUO from 1154 relevant documents published over the past 25 years from Web of Science. We also displayed a visualization network from the aspects of core authors, research institutions, and highly cited literature. The results show the following: (1) The countries that published the most articles are the United States and China, and the Chinese Academy of Sciences is the research institution that publishes the most articles. (2) The top 10 cited articles focused on describing how to build GA models for multi-objective LUO. (3) According to the number of keywords that appear for the first time in each time period, we divided the process of GA-LUO into four stages: the presentation and improvement of methods stage (1995–2004), the optimization stage (2005–2008), the hybrid application of multiple models stage (2009–2016), and the introduction of the latest method stage (after 2017). Furthermore, future research trends are mainly manifested in integrating together algorithms with GA and deepening existing research results. This review could help researchers know this research domain well and provide effective solutions for land use problems to ensure the sustainable use of land resources. Full article

Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are known to have caused changes to the hydrological cycle. Therefore, quantifying the net influence of anthropogenic contribution to the runoff changes is a challenge. This study applied the original and modified Mann–Kendall trend test, including the Sen’s slope test, Pettitt’s test, double cumulative curve, and elasticity methods. These methods were applied to determine the historical trends, magnitude changes and change points of the temperature, precipitation, potential evapotranspiration, and runoff from 1950 to 2016. In addition, the contributions of climate change and anthropogenic activities to runoff changes in the KRB were evaluated. The trend analysis showed a significant increasing trend in annual temperature and potential evapotranspiration, while the annual precipitation trend showed an insignificant decreasing trend during the 1950–2016 time period. The change point in runoff occurred in 1986 in the upstream region and 1991 in the downstream region. Further, the time series (1950–2016) is separated into the prior impacted period (1950–1986 and 1950–1991) and post impacted period (1987–2016 and 1992–2016) for the upstream and downstream regions, respectively. During the post impacted period, climate change and anthropogenic activities contributed to 87.96% and 12.04% in the upstream region and 7.53% and 92.47% in the downstream region of the KRB. The results showed that in runoff changes, the anthropogenic activities played a dominant role in the downstream (97.78%) and the climate change impacts played a dominant factor in the upstream region (87.96%). In the land-use type changes, the dominant role was played by construction land, which showed that the area from 248.63 km² in 1990 increased to 685.45 km² (175.69%) in 2015. These findings suggest that it is essential to adopt effective steps for the sustainable development of the ecological, hydrological, and social order in the KRB in Central Asia. Full article

Our paper deals with a micro-study of one residential building in the city center of Brno (Czech Republic) where we strived to identify and better understand the main factors behind the successful implementation of environmentally friendly solutions during the regeneration process. We followed the unique, complicated, and often conflictual story of the regeneration (conducted during the years 2010–2020) of the residential building, which was originally built in the 1930s. In total, 18 solutions were discussed—all four solutions on the state level of centralization were realized, only two of six solutions on the building level of centralization were materialized, and six of eight decentralized solutions were realized during the regeneration process. In the field of energy savings requiring high investments, a significant dominance of centralized solutions (on the state level) was identified. Centralized solutions on the building level such as heat pumps or solar panels were not realized. In the area of waste management and care for community greenery (that did not require large investments), we see as the most beneficial the promotion of decentralized solutions in the form of community-funded communal composting or the planting of new greenery. The formation of various regeneration options, which is discussed in detail, appeared as an integral instrument for dealing with conflicts among residents during the planning phase. Full article

Identifying the land-use type and spatial distribution of urban construction land is the basis of studying the degree of exposure and the economic value of disaster-affected bodies, which are of great significance for disaster risk predictions, emergency disaster reductions, and asset allocations. Based on point of interest (POI) data, this study adopts POI spatialization and the density-based spatial clustering of applications with noise (DBSCAN) algorithm to accomplish the spatial classification of construction land. Zhejiang province is selected as a study area, and its construction land is divided into 11 land types using an accurate spatial classification method based on measuring the area of ground items. In the research, the POI dataset, which includes information, such as spatial locations and usage types, was constructed by big data cleaning and visual interpretation and approximately 620,000 pieces in total. The overall accuracy of the confusion matrix is 76.86%, which is greatly improved compared with that constructed with EULUC data (61.2%). In addition, compared with the official statistical data of 11 cities in Zhejiang Province, the differences between the calculated spatial proportions and statistics are not substantial. Meanwhile, the spatial characteristics of the studied land-use types are consistent with the urban planning data but with higher accuracy. The research shows that the construction land in Zhejiang Province has a high degree of land intensity, concentrated assets, and high economic exposure. The approach proposed in this study can provide a reference for city management including urbanization process, risk assessment, emergency management and asset allocation. Full article

Revealing the spatio-temporal change of the supply, demand and balance of ecosystem services (ESs) associated with human activities and land-use changes is of great significance for watershed ecosystem management. Taking the Lancang river valley as a case, we explicitly studied the ES spatial characteristics, using the land use/land cover (LULC) matrix model, Optimized Hot Spot Analysis and landscape pattern analysis. Furthermore, we screened out the dominant explanatory variables that had significant influence on the ES supply, demand and balance by means of the Geographical Weighted Regression (GWR) method at pixel scale. The results showed that the ES demand intensity varied little throughout the watershed, while the downstream ES supply capacity and balance values were greater than upstream ones. Meanwhile, the hotspots of ES supply and demand were mainly distributed in the south part with coldspots in the north part. Human activity factors integrating landscape pattern variables were verified to have a negative impact on the ES balance in general. Among them, the Largest Patch Index (LPI) had a negative influence on the majority of pixels, while the Gross Domestic Product (GDP), cultivated land ratio and Area Weighted Average Patch Fractal Dimension (AWAPFD) had positive effects on a few pixels. This study will provide scientific support for regional ecosystem service trade-off and regulation at multiple scales. Full article

Human activities are increasingly recognized as having a critical influence on hydrological processes under the warming of the climate, particularly for dam-regulated rivers. To ensure the sustainable management of water resources, it is important to evaluate how dam construction may affect surface runoff. In this study, using Mann–Kendall tests, the double mass curve method, and the Budyko-based elasticity method, the effects of climate change and human activities on annual and seasonal runoff were quantified for the Yellow River basin from 1961–2018; additionally, effects on runoff were assessed after the construction of the Xiaolangdi Dam (XLD, started operation in 2001) on the Yellow River. Both annual and seasonal runoff decreased over time (p < 0.01), due to the combined effects of climate change and human activities. Abrupt changes in annual, flood season, and non-flood season runoff occurred in 1986, 1989, and 1986, respectively. However, no abrupt changes were seen after the construction of the XLD. Human activities accounted for much of the reduction in runoff, approximately 75–72% annually, 81–86% for the flood season, and 86–90% for the non-flood season. Climate change approximately accounted for the remainder: 18–25% (annually), 14–19% (flood season), and 10–14% (non-flood season). The XLD construction mitigated runoff increases induced by heightened precipitation and reduced potential evapotranspiration during the post-dam period; the XLD accounted for approximately 52% of the runoff reduction both annually and in the non-flood season, and accounted for approximately −32% of the runoff increase in the flood season. In conclusion, this study provides a basic understanding of how dam construction contributes to runoff changes in the context of climate change; this information will be beneficial for the sustainable management of water resources in regulated rivers. Full article

Recent years have seen the global proliferation and integration of transportation systems in urban agglomeration (UA), suggesting that transportation networks have become more prominent in the sustainable development of UA. Core cities play a radiating and driving role in affecting their adjacent cities to formulate transportation networks. Such a phenomenon is called the radiation effect of transportation networks and can be imaged using a field strength model as proposed in the study. The field strength model was verified using the Chengdu–Chongqing urban agglomeration (CCUA) as a case. Case data concerning transportation routes and traffic volume were collected for the past 20 years. The data analyses results indicate a relatively stable pattern of transportation networks in the UA. UA cities’ radiation effects follow the same compactness trend. The core cities’ radiation spheres go beyond their territories, and they can envelop the surrounding cities, highlighting the core cities’ dominance in the entire transportation network. Moreover, two development stages of UA transportation—focus and spillover—are also identified. This study contributes to the literature by providing an innovative quantitative method to detect the interaction between a city’s transportation system and peripheral cities or regions. The radiation effect of cities’ transportation systems should be considered in the UA transportation development plan, so as to meet the needs of spatial structure planning and coordinated development of the UA. Full article

This study examined the relationship between stream temperature and environmental variables in a semiarid riparian corridor in northcentral Oregon, USA. The relationships between riparian vegetation cover, subsurface flow temperature, and stream temperature were characterized along an 800 m reach. Multiple stream temperature sensors were located along the reach, in open and closed canopy areas, with riparian vegetation cover ranging from 4% to 95%. A support vector regression (SVR) model was developed to assess the relationship between environmental characteristics and stream temperature at the larger valley scale. At the reach scale, results show that air temperature was highly correlated with stream temperature (Pearson’s r = 0.97), and no significant (p < 0.05) differences in stream temperature levels were found among sensor locations, irrespective of percent vegetation cover. Channel subsurface temperature levels from an intermittent flow tributary were generally cooler than those in the perennial stream in the summer and warmer during winter months, indicating that the tributary may have a localized moderating effect on stream temperature. At the valley scale, results from the SVR model showed that air temperature, followed by streamflow, was the strongest variable influencing stream temperature. Also, riparian area land cover showed little effect on stream temperature along the entire riparian corridor. This research indicates that air temperature, subsurface flow, and streamflow are important variables affecting the stream temperature variability observed in the study area. Full article

Real estate investment has been an important driving force in China’s economic growth in recent years, and the relationship between real estate investment and PM_2.5 concentrations has been attracting widespread attention. Based on spatial econometric modelling, this paper explores the relationships between real estate investment and PM_2.5 concentrations using multi-source panel data from 30 provinces in China between 1987 and 2017. The results demonstrate that compared with static spatial panel modelling, using a dynamic spatial Durbin lag model (DSDLM) more accurately reflects the influences of real estate investment on PM_2.5 concentrations in China, and that PM_2.5 concentrations show significant superposition effects and spillover effects. Moreover, there is an inverted U-shaped relationship between real estate investment and PM_2.5 concentrations in the Eastern and Central Regions of China. At the national level, the impacts of real estate investment on land urbanization and PM_2.5 concentrations first increased and then decreased over time. The key implications of this analysis are as follows. (1) it highlights the need for a unified PM_2.5 monitoring platform among Chinese regions; (2) the quality of population urbanization rather than land urbanization should be given more attention; and (3) the speed of construction of green cities and building of green transportation systems and green town systems should be increased. Full article

Soil organic carbon storage (SOCS) estimation is a crucial branch of the atmospheric–vegetation–soil carbon cycle study under the background of global climate change. SOCS research has increased worldwide. The objective of this study is to develop a two-stage approach with good extension capability to estimate SOCS. In the first stage, an artificial neural network (ANN) model is adopted to estimate SOCS based on 255 soil samples with five soil layers (20 cm increments to 100 cm) in Luoding, Guangdong Province, China. This method is compared with three common methods: The soil type method (STM), ordinary kriging (OK), and radial basis function (RBF) interpolation. In the second stage, a linear model is introduced to capture the regional differences and further improve the estimation accuracy of the Luoding-based ANN model when extending it to Xinxing, Guangdong Province. This is done after assessing the generalizability of the above four methods with 120 soil samples from Xinxing. The results for the first stage show that the ANN model has much better estimation accuracy than STM, OK, and RBF, with the average root mean square error (RMSE) of the five soil layers decreasing by 0.62–0.90 kg·m⁻², R² increasing from 0.54 to 0.65, and the mean absolute error decreasing from 0.32 to 0.42. Moreover, the spatial distribution maps produced by the ANN model are more accurate than those of other methods for describing the overall and local SOCS in detail. The results of the second stage indicate that STM, OK, and RBF have poor generalizability (R² < 0.1), and the R² value obtained with ANN method is also 43–56% lower for the five soil layers compared with the estimation accuracy achieved in Luoding. However, the R² of the linear models built with the 20% soil samples from Xinxing are 0.23–0.29 higher for the five soil layers. Thus, the ANN model is an effective method for accurately estimating SOCS on a regional scale with a small number of field samples. The linear model could easily extend the ANN model to outside areas where the ANN model was originally developed with a better level of accuracy. Full article