Land, Volume 13, Issue 5 (May 2024) – 56 articles

Ancient Andean agricultural landscapes have been the subject of a large number of archaeological and agro-ecological studies, which generally refer to regions with favourable environmental conditions or, in the case of arid and semi-arid environments, those with irrigation facilities. The aim of this article is to present and analyse the pre-Hispanic rain-fed farming systems widely represented in two adjacent regions of Bolivia’s arid and cold southern Altiplano. The search for archaeological agricultural areas combined aerial analysis and field surveys. Agro-ecological characterisation was based on historical and ethnographic studies of the region’s present-day populations. Despite their geographical proximity, similar environmental conditions, and same agropastoral way of life, the typology of cultivated areas developed in the southern altiplano differs significantly. Within this same framework of adaptation and resilience, the sectorisation of agricultural systems observed in these two regions reveals a regional productive specialisation that favoured internal exchanges and exchanges with other regions. These differences are related to two models of non-centralised, low-inequality societies—one strongly based on cohesion and the other characterised by greater fragmentation and social conflict—underlining the limits of strict environmental determinism in shaping agricultural landscapes. These results provide new food for thought in the debate on the use and value of rain-fed agricultural practices and more broadly on the diversity of adaptations by human societies in extreme and unstable environmental contexts. Full article

Land-use change is an important factor affecting terrestrial carbon balance, and it is crucial to explore the response of terrestrial carbon stocks to land-use change, especially in the Songnen Plain, which faces a fierce conflict between the rapid growth of production activities and ecosystem degradation. In this study, we measured soil organic carbon and vegetation biocarbon stocks in the Songnen Plain based on IPCC-recommended methodologies, and explored the characteristics of carbon stock changes in land-use trajectories, land-use drivers, and specific land-use change scenarios (cropland cultivation, returning cropland to forests, the expansion of land for construction, deforestation, greening, and land degradation). The results showed that soil organic carbon stock in the Songnen Plain decreased by 1.63 × 10⁵ t, and vegetation biocarbon stock increased by 2.10 × 10⁷ t from 2005 to 2020. Human factors and natural factors jointly contributed to the land-use change, but the extent of the role of human factors was greater than that of natural factors. The increase in land-use trajectory led to the decrease in soil organic carbon stock and the increase in vegetation biocarbon stock. There was no difference in the effects of human-induced and natural-induced land-use changes on vegetation biocarbon stocks, but the effects on soil organic carbon stocks were diametrically opposite, increasing by 43.27 t/km² and decreasing by 182.02 t/km², respectively. The reclamation of arable land, returning cropland to forests, and greening led to a net increase in terrestrial carbon stocks (+813,291.84 t), whereas land degradation, deforestation, and land-use expansion led to a decrease in terrestrial carbon stocks (−460,710.2 t). The results of this study can provide a reference for the adjustment of land-use structure and the increase in terrestrial carbon stock in the Songnen Plain. Full article

Land cover (LC) plays a crucial role in the monitoring and planning of the environment among various domains, such as climate change, the management of natural resources, and sustainable development. However, inconsistent LC legends hamper their usability, particularly as technologies, like remote sensing, rapidly improve data quality and quantity for extracting valuable information. Ontologies play a pivotal role in improving the standardization and harmonization of different LC taxonomies, enabling both a reduction in inconsistencies and a way to harness ever-increasing computing power to help scientists provide faster and better answers. However, using ontologies without suitable tools, especially when expressive power is matched with complexity, can prove a daunting task. This paper introduces the land characterization system (LCHS), an innovative tool built to support the ontology discussed in the ISO 19144-2 standard, known as Land Cover Meta Language (LCML). The LCHS can help streamline and speed up the creation and editing of LC legends using a data-driven design approach. Full article

Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability. Full article

As climate change intensifies, drought has become a major global engineering and environmental challenge. In critical areas such as agricultural production, accurate drought monitoring is vital for the sustainable development of regional agriculture. Currently, despite extensive use of traditional meteorological stations and remote sensing methods, these approaches have proven to be inadequate in capturing the full extent of drought information and adequately reflecting spatial characteristics. Therefore, to improve the accuracy of drought forecasts and achieve predictions across extensive areas, this paper employs deep learning models, specifically introducing an attention-weighted long short-term memory network model (AW-LSTM), constructs a composite drought monitoring index (CDMI) and validates the model. Results show that: (1) The AW-LSTM model significantly outperforms traditional long short-term memory (LSTM), support vector machine (SVM) and artificial neural network (ANN) models in drought monitoring, offering not only better applicability in meteorological and agricultural drought monitoring but also the ability to accurately predict drought events one month in advance compared to machine learning models, providing a new method for precise and comprehensive regional drought assessment. (2) The Huang-Huai-Hai Plain has shown significant regional variations in drought conditions across different years and months, with the drought situation gradually worsening in the northern part of Hebei Province, Beijing, Tianjin, the southern part of Huai North and the central part of Henan Province from 2001 to 2022, while drought conditions in the northern part of Huai North, southern Shandong Province, western Henan Province and southwestern Hebei Province have been alleviated. (3) During the sowing (June) and harvesting (September) periods for summer maize, the likelihood of drought occurrences is higher, necessitating flexible adjustments to agricultural production strategies to adapt to varying drought conditions. Full article

Thanks to the development of geodetic methods and equipment, there has been a transition from conventional methods to modern technologies, which can efficiently and accurately acquire a large amount of data in a short time without the need for direct contact with the measured object. Combined technologies such as Structure from Motion (SfM), Multi-View Stereo (MVS) photogrammetry using Unmanned Aerial Systems (UAS), and terrestrial laser scanning (TLS) are often used for monitoring geohazards and documenting objects in quarries to obtain detailed and accurate information about their condition and changes. This article deals with the analysis of point clouds obtained with different settings in terms of average absolute point distance, average point density, and time range for surveying and office work. The numerical and graphical results of the research lead to conclusions for scientific and practical applications for activities in the mining industry. Full article

In the granite regions of southern China, benggang poses a substantial threat to the ecological environment due to significant soil erosion. This phenomenon also imposes constraints on economic development, necessitating substantial investments in restoration efforts in recent decades. Despite these efforts, there remains a notable gap in comprehensive risk assessment that integrates both the erosion risk and disaster risk associated with benggang. This study focuses on a representative benggang area in Wuhua County, Guangdong province, employing transformer methods and high-resolution imagery to map the spatial pattern of the benggang. The integrated risk of benggang was assessed by combining soil-erosion risk and disaster risk, and cultivated land, residential land, and water bodies were identified as key disaster-affected entities. The machine-learning Segformer model demonstrated high precision, achieving an Intersection over Union (IoU) of 93.17% and an accuracy (Acc) of 96.73%. While the number of large benggang is relatively small, it constitutes the largest area proportion (65.10%); the number of small benggang is more significant (62.40%) despite a smaller area proportion. Prioritization for benggang management is categorized into high, medium, and low priority, accounting for 17.98%, 48.34%, and 33.69%, respectively. These priorities cover areas of 30.27%, 42.40%, and 27.33%, respectively. The findings of this study, which offer benggang management priorities, align with the nature-based solutions approach. Emphasizing the importance of considering costs and benefits comprehensively when formulating treatment plans, this approach contributes to sustainable solutions for addressing the challenges posed by benggang. Full article

Land-use conflicts (LUCs) are pivotal in assessing human–land interaction, reflecting the intricate interplay between natural and anthropogenic drivers. However, existing studies often overlook nuanced non-linear responses and critical threshold recognition, focusing solely on linear correlations between isolated factors and LUCs. This study, situated in Xinjiang, China’s arid and semiarid region, introduces a novel analytical framework and threshold application model for LUCs. Integrating land-use and socioeconomic data, we quantified LUCs using Fragstats, correlation analysis, and restricted cubic spline (RCS) regression. Exploring non-linear dynamics between LUCs and 14 potential drivers, including natural and anthropogenic factors, we identified critical thresholds. LUC zones were delineated using a four-quadrant method, allowing tailored mitigation strategies. Our findings reveal Xinjiang’s distinct LUC spatial pattern, with intense conflicts surrounding mountainous areas and milder conflicts in basin regions, showing marked diminishment from 2000 to 2020. RCS effectively identifies LUC thresholds, indicating persisting severity pre- or post-specific thresholds. Xinjiang’s LUCs are categorized into key control areas, urgent regulation zones, elastic development territories, and moderate optimization regions, each with significant regional disparities. Tailored optimization suggestions mitigate linear analysis limitations, providing a fresh perspective on land zoning optimization. This research supports comprehensive land management and planning in Xinjiang, China. Full article

This study aimed to develop a remote sensing method for estimating the aboveground fresh weight (AGFW) of sugarcane using multispectral images and light detection and ranging (LiDAR). Remotely sensed data were acquired from an unmanned aerial vehicle (drone). Sample plots were harvested and the AGFW of each plot was measured. Sugarcane crown heights and volumes were obtained by isolating individual tree crowns using a LiDAR-derived digital surface model of the area. Multiple linear regression (MLR) and partial least-squares regression (PLSR) models were tested for the field-sampled AGFWs (dependent variable) and individual canopy heights and volumes, and spectral indices were used as independent variables or predictors. The PLSR model showed more promising results than the MLR model when predicting the AGFW over the study area. Although PLSR is well-suited to a large number of collinear predictor variables and a limited number of field samples, this study showed moderate results (R² = 0.5). The visual appearance of the spatial distribution of the AGFW map is satisfactory. The limited no. of field samples overfitted the MLR prediction results. Overall, this research highlights the potential of integrating remote sensing technologies in the sugarcane industry, thereby improving yield estimation and effective crop management. Full article

Chile’s central-south region has experienced significant land use changes in the past fifty years, affecting native forests, agriculture, and urbanization. This article examines these changes and assesses their impact on native forest cover and agricultural land. Agricultural data for Chile (1980–2020) were obtained from public Chilean institutions (INE and ODEPA). Data on land use changes in central and south Chile (1975–2018), analysed from satellite images, were obtained from indexed papers. Urban area expansion in Chile between 1993 and 2020 was examined using publicly available data from MINVIU, Chile. Additionally, photovoltaic park data was sourced from SEA, Chile. Field crop coverage, primarily in central and southern Chile, decreased from 1,080,000 ha in 1980 to 667,000 ha in 2020, with notable decreases observed in cereal and legume crops. Conversely, the coverage of export-oriented orchards and vineyards increased from 194,947 ha to 492,587 ha. Forest plantations expanded significantly, ranging from 18% per decade in northern central Chile to 246% in the Maule and Biobío regions. This was accompanied by a 12.7–27.0% reduction per 10 years in native forest. Urban areas have experienced significant growth of 91% in the last 27 years, concentrated in the Mediterranean climate region. Solar photovoltaic parks have begun to increasingly replace thorn scrub (Espinal) and agricultural land, mirroring transformations seen in other Mediterranean nations like Spain and Portugal. Full article

Assessing urban service locations is a key issue within city planning, integral to promoting the well-being of citizens, and ensuring effective urban development. However, many current approaches emphasize spatial analysis focused solely on physical attributes, neglecting the equally vital social dimensions essential for enhancing inhabitants’ comfort and quality of life. When social factors are considered, they tend to operate at smaller scales. This paper addresses this gap by prioritizing integrating social factors alongside spatial analysis at the community level. By employing space syntax theory, this study investigates urban service suitability in Hajjah, a Palestinian urban community, presenting a novel approach in the literature. The research identifies good spots for essential governmental facilities like health clinics and fire stations using axial map analysis. It also suggests reallocation for some schools. Additionally, it shows ways to improve the placement of community amenities, finding ideal park locations but suboptimal mosque placements. Commercial services also exhibit areas for enhancement including gas stations and shops. The insights from this research can offer policymakers and planners insights to create more efficient, equitable, and accessible cities. The research approach incorporates social behavior dynamics into spatial analysis, promoting inclusive urban planning. Full article

Intensive economic and human activities present challenges to the carbon storage capacity of terrestrial ecosystems, particularly in arid regions that are sensitive to climate change and ecologically fragile. Therefore, accurately estimating and simulating future changes in carbon stocks on the northern slope economic belt of Tianshan Mountains (NSEBTM) holds great significance for maintaining ecosystem stability, achieving high-quality development of the economic belt, and realizing the goal of “carbon neutrality” by 2050. This study examines the spatiotemporal evolution characteristics of the NSEBTM carbon stocks in arid regions from 1990 to 2050, utilizing a combination of multi-source data and integrating the Patch-generating Land use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models. Additionally, an attribution analysis of carbon stock changes is conducted by leveraging land use data. The findings demonstrate that (1) the NSEBTM predominantly consists of underutilized land, accounting for more than 60% of the total land area in the NSEBTM. Unused land, grassland, and water bodies exhibit a declining trend over time, while other forms of land use demonstrate an increasing trend. (2) Grassland serves as the primary reservoir for carbon storage in the NSEBTM, with grassland degradation being the leading cause of carbon loss amounting to 102.35 t over the past three decades. (3) Under the ecological conservation scenario for 2050 compared to the natural development scenario, there was a net increase in carbon storage by 12.34 t; however, under the economic development scenario compared to the natural development scenario, there was a decrease in carbon storage by 25.88 t. By quantitatively evaluating the land use change in the NSEBTM and its impact on carbon storage in the past and projected for the next 30 years, this paper provides scientific references and precise data support for the territorial and spatial decision making of the NSEBTM, thereby facilitating the achievement of “carbon neutrality” goals. Full article

Considering the essential expansion of agricultural production, current research primarily focuses on static factors, such as the distribution of fine-grained arable land, omitting an in-depth analysis of its developmental dynamics and key drivers. Addressing this knowledge gap is crucial for enhancing the scalability of agricultural production. This research utilizes landscape ecology techniques, correlation analysis, random forest algorithms, and structural equation modeling to explore spatial pattern trends of arable land in the Beijing–Tianjin–Hebei region. Its objective is to clarify how the expansion of agricultural production scale affects food production through changes in arable land patterns and to determine the impact of socio-economic factors on these configurations. The results show that: (1) the landscape pattern of arable land is transitioning to a more fragmented arrangement with complex contours, (2) grain yield per unit area correlates positively with the landscape pattern index in Beijing, negatively in Hebei, and exhibits no significant correlation in Tianjin, and (3) land ownership plays a crucial role in land fragmentation, alterations in land morphology, and influences other socio-economic variables. Analyzing the spatial pattern of arable land in conjunction with socio-economic factors is essential for developing holistic land management approaches, improving resource efficiency, minimizing external inputs, and mitigating food security challenges. Full article

The relocation of Indonesia’s capital to the IKN (Ibu Kota Negara) Nusantara in East Kalimantan is leading to significant changes in land use, shifting from natural vegetation and agriculture to urban infrastructure. This transition brings about economic diversification and urban expansion, but it also raises concerns about its impact on society, the economy, and the environment. The rapid development affects biodiversity conservation, food security, and the livelihoods of rural and Indigenous communities, leading to conflicts across social and economic dimensions. This research uses qualitative and quantitative data to examine the socio-economic and environmental changes in the IKN Nusantara area from 2003 to 2023. The findings show a notable increase in built-up areas, indicating urbanization and a decrease in agricultural land. The study discusses the implications for local populations and ecosystems, emphasizing the need for inclusive governance, community participation, and conflict resolution. It also proposes a comprehensive policy framework that promotes sustainable land management, recognizes Indigenous and local rights, and fosters inclusive economic growth to respect Indonesia’s rich environmental and cultural heritage. Full article

This study explores how cultural landscapes serve as dynamic interfaces between human societies and their environments, reflecting intricate interactions shaped by historical and societal changes. Cultural landscapes, embodying both tangible heritage (e.g., architecture, gardens, and urban spaces) and intangible heritage (e.g., traditions and practices), act as living archives that document the evolution of cultural identities and environmental care. Through the lens of historical analysis and case studies, including that of the legacy of the Roman Empire, this research examines the transformative impacts of political, economic, social, and cultural shifts on these landscapes. Methods include a comparative analysis of historical data and contemporary landscape assessments, used to understand how these spaces adapt to and reflect societal changes. The findings highlight the importance of preserving cultural landscapes for their educational and aesthetic value, ecological sustainability, and their role in maintaining historical continuity. The study underscores the need for integrating historical insights into contemporary landscape preservation and urban design to keep these spaces relevant for future generations. This research contributes to our understanding of the deep-seated connection between past civilizations and modern cultural identities through the stewardship of cultural landscapes. Full article

This study utilizes provincial panel data from China spanning the period from 2011 to 2020 to assess the coupled and coordinated development of spatial functions related to production, life, and ecology (PLE) in rural areas. The assessment is based on quantifying the spatial function indices for PLE in China’s rural regions. Additionally, it examines the characteristics of their spatial and temporal evolution, spatial correlation, and driving factors. The findings indicate a modest upward trend in the spatial coupling and coordination levels of these functions across rural China, although a significant proportion of provinces still exhibit a near-disordered decline. Exploratory spatial data analysis reveals a geographical disparity, with higher levels of coupled and coordinated development observed in the eastern regions, lower levels in the west, and noticeable spatial clustering. By employing the spatial Durbin model to investigate the determinants of coupling degrees, we discovered that factors such as regional economic development, urbanization, the urban–rural income gap, financial support for agriculture, science and technology investment level, and agricultural structural adjustments significantly influence the spatial coupling of rural PLE functions. Furthermore, using the geographic detector model, the analysis identifies science and technology investment level, economic development, and financial support for agriculture as key drivers influencing the spatial coupling and coordination of these functions. These findings provide valuable reference points for policies and strategies related to rural management. Full article

With the advancement of artificial intelligence, deep learning has become instrumental in land cover classification. While there has been a notable emphasis on refining model structures to improve classification accuracy, it is imperative to also emphasize the pivotal role of data-driven optimization techniques. This paper presents an in-depth investigation into optimizing multi-class land cover classification using high-resolution multispectral images from Worldview3. We explore various optimization strategies, including refined sampling strategies, data band combinations, loss functions, and model enhancements. Our optimizations led to a substantial increase in the Mean Intersection over Union (mIoU) classification accuracy, improving from a baseline of 0.520 to a final accuracy of 0.709, which represents a 35.2% enhancement. Specifically, by optimizing the classic semantic segmentation network in four key aspects, we improved the mIoU by 15.5%. Further improvements through changes in data combinations, sampling methods, and loss functions led to an overall 17.2% increase in mIoU. The proposed model optimization methods enabled the OUNet to outperform the baseline model by providing more precise edge detection and feature representation, while reducing the model parameters scale. Experimental evidence shows that in the application of multi-class land surface classification, increasing the quantity and diversity of samples, avoiding data imbalance issues, is equally valuable for improving overall classification accuracy as it is for enhancing model performance. Full article

By leveraging a multiscale geographically weighted regression (MGWR) model, this paper delves into the intricate factors that influence housing prices in the prototypical mountainous cityscape of Chongqing’s central urban area. The key findings are as follows: Firstly, the distribution of housing prices in the study region exhibits pronounced spatial heterogeneity, with the core area exhibiting a distinct “high-high” clustering pattern and manifesting characteristics of a multicenter group distribution. Secondly, the MGWR model effectively assigns an individual bandwidth to each feature quantity, allowing for a more nuanced portrayal of the varying influence scales exerted by diverse variables. Lastly, the study reveals that factors such as property cost, greening rate, building age, and proximity to rivers have a notable negative impact on housing prices, whereas, educational facilities exert a marked positive influence. Elevation, floor area ratio, and distance from the Central Business District (CBD) exhibit a more complex influence on housing prices. Full article

The increasing urbanization trend, projected to reach 70% of the global population residing in cities by 2050, underscores the pivotal role of cities in achieving the Sustainable Development Goals (SDGs) set by the 2030 Agenda for Sustainable Development (UN, 2015) and combating climate change. Nonetheless, the 2023 report by the United Nations Human Settlements Programme (UN Habitat) reveals an alarming gap in achieving SDG 11 “Sustainable cities and communities” by 2030. This gap highlights the urgent need for transformative shifts in urban policies and investments to prevent cities from becoming centers of global disparities, including socio-economic inequalities, digital divide, and spatial fragmentation, particularly in marginal areas. Marginal areas suffer indeed from conditions of sub-optimality in planning capacity, valuable decision-making, and project implementation. The inadequate planning, management, and governance of marginal areas, coupled with suboptimal investments, can severely compromise their socioeconomic condition. Planning efforts frequently fall short in achieving long-term sustainability goals due to localized and short-sighted decision-making processes, particularly evident in marginal areas. It is crucial, though, to support their public administrations in the achievement of the SDG 11 targets and in their responsive participation in the calls for the allocation of public funding. In this paper, we provide a theoretical and methodological approach to evaluate urban regeneration projects in marginal areas. In detail, we develop an A’WOT approach, which combines a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis to the Analytic Hierarchy Process (AHP), to rank alternative urban development projects. Full article

The rapid urbanization process means that even moderate-sized cities can quickly become part of larger urban agglomerations, creating new urban zones. Urban Green Infrastructure (UGI) plays a crucial role in these clusters, acting as precious green spaces essential for maintaining ecological safety. This study combines fluctuation analysis based on Morphological Spatial Pattern with traditional landscape pattern analysis, comprehensively addressing the evolution of UGI in terms of quantity, characteristics, and morphology. We selected the Taiyuan-Jinzhong agglomeration as our study area, which is currently in an agglomeration process. The results demonstrated the critical role of surrounding mountains as natural ecological barrier zones. During urban agglomeration, management strategies focused on large-scale afforestation to ensure the quantity of UGI. However, this approach also led to a more clustered landscape with reduced connectivity. Additionally, linear or small-scale UGI types such as branch and islet have seen reductions over the past decade. Changes in internal morphological and complex fluctuations within UGI can harm the formation of ecological networks and potentially negatively affect biodiversity and ecological safety. The research highlights how ecological protection and urban planning policies can influence UGI fluctuations. Therefore, urban managers should not just concentrate on maintaining the quantity of UGI, but also give consideration to changes in its internal features and morphology. Before cities further agglomerate into larger urban clusters, it is crucial to address deficiencies in UGI, continuously improving type configurations and functional structures at the landscape scale. Through strategic planning of UGI, cities can mitigate ecological risks and foster sustainable urban development. Full article

Vine growing is one of the most economically important sectors of Mediterranean agriculture, but its cultivation practices are highly detrimental to the environment and the associated biota. The application of both natural products inducing endogenous plant defense mechanisms and natural soil management systems represents a potential solution for the preservation and improvement of soil health and biodiversity. The Life Green Grapes project aimed at evaluating the effects of different natural and sustainable vine protection strategies and soil management on vineyard edaphic communities. Soil TOC, TN, C:N ratio, CaCO₃ content and pH were measured. Microbial communities (bacteria and fungi) were characterized through NGS, while nematodes and microarthropods were isolated and identified. Obtained data highlighted a relationshipbetween bacteria, fungi and nematodes with soil chemistry, and an effect of the different soil management on the single and total edaphic communities. Network analysis evidenced a positive effect of the application of sustainable soil managements on the relationships among the different investigated soil trophic levels, suggesting that more natural soil managements allow a better interaction between soil organisms. In conclusion, this work confirms the importance of the application of sustainable and natural soil management practices in agricultural ecosystems, with the aim of conserving and improving soil biodiversity. Full article

The “Content-Identifying Methodology”, or CIM, is an approach developed by environmental psychologists Rachel and Stephen Kaplan to understand the landscape characteristics that people find visually attractive. The Kaplans did this by surveying people’s landscape preferences and then analyzing the preferences to develop sets of landscape scenes to which people reacted in a similar pattern. The underlying assumption is that a common stimulus or content exists in the photographs of a set responsible for the preference. However, identifying the common stimulus or content in each set or grouping of scenes and how it affects preference can still be challenging. Eye-tracking is a tool that can identify what the survey participants were looking at when indicating their preference for a landscape. This paper demonstrates how eye-tracking was used in two different landscape preference studies to identify the content important to people’s preferences and provide insights into how the content affected preference. Eye-tracking can help identify a common stimulus, help determine if the stimulus is a physical or spatial characteristic of the landscape, and show how the stimulus varies in different landscape contexts. Full article

The quantitative evaluation and prediction of ecosystem service value (ESV) in the Lhasa River Basin can provide a basis for ecological environment assessment and land-use optimization and adjustment in the future. Previous studies on the ESV in the Lhasa River Basin have focused mainly on static assessment and evolution analysis based on historical data, and have not considered future development trends. Moreover, most of the current driving factors selected in land use and ESV prediction studies are homogeneous, and do not reflect the geographical and cultural characteristics of the study area well. With the Lhasa River Basin as the research focus, 20 driving factors were selected according to the characteristics of the plateau alpine area, and the land-use changes under three developmental orientations, namely, natural evolution, ecological protection, and agricultural development, were predicted for the year 2030 with the FLUS-Markov model. Based on these predictions, the values of ecosystem services were calculated, and their spatiotemporal dynamic characteristics were analyzed. The results show that the model has high accuracy in simulating land-use change in the Lhasa River Basin, with a kappa coefficient of 0.989 and an overall accuracy of 99.33%, indicating a high applicability. The types of land use in the Lhasa River basin are dominated by the existence of grassland, unused land, and forest, with a combined proportion of 94.3%. The change trends of each land-use type in the basin under the three scenarios differ significantly, with grassland, cropland, and building land showing the most significant changes. The area of cropland increased only in the agricultural development scenario; the areas of forest and grassland increased only in the ecological protection scenario; and the expansion of building land was most effectively controlled in the ecological protection scenario. The ESV increased in all three scenarios, and the spatial distribution of the ESV per unit area in the middle and lower reaches was greater than that in the upper reaches. The ESV was the greatest in the ecological protection scenario, with grasslands, forests, and water bodies contributing more to the ESV of the basin. This study provides decision-making references for the effective utilization of land resources, ecological environmental protection planning, and urban construction in the Lhasa River Basin in the future. Full article

Daily time series with continuous records of mean air and soil temperature from 127 meteorological stations—fairly distributed over the country—were used to compute monthly temperature trends, as well as changes in the timing of the first and the last frost days over Romania since 1961. Results show that the frequency of the number of days with daily temperature averages below 0 °C in case of air and soil surface temperature is stable for most months, except for January, when (for both soil and air temperature), the number of days with a temperature below 0 °C is decreasing in the majority of the stations. The occurrence of the first day with (mean air and soil surface) temperatures below 0 °C, presents a delay in the south, south-east, and west, and an earlier occurrence in eastern and central regions. The occurrence of the last day with a mean air and soil surface temperature below 0 °C shows a stable trend for most stations (except for some small areas in the north, south-east and south-west of Romania). The regime of the land temperature is more stable, due to the physical characteristics of the soil, compared to the more versatile atmosphere. Linkages between thermal parameters and large-scale atmospheric circulation are also discussed. Full article

Exploring the impact of economic modernization on carbon balance is an essential endeavor to achieve carbon neutrality and combat climate change. However, the spatial impact of economic modernization on carbon balance remains ambiguous. Therefore, this study aims to explore the spatial spillover effects of agricultural modernization, industrialization, and urbanization on carbon balance during the economic modernization process in China, taking 30 provinces and cities in China as examples from 2010 to 2021. This study utilizes the spatial Durbin model to derive the following results: In the past decade, the carbon balance ratio has shown a fluctuating and decreasing dynamic evolution trend. There is an increase in regions with serious carbon deficits. Further investigation into the spatial spillover effect of carbon balance unveils that for every 1% increase in the carbon balance ratio of a province, neighboring provinces experience a decrease of 0.833%. Additionally, the spatial spillover effects of the three modernizations in China on the carbon balance ratio behave differently. Agricultural modernization and urbanization demonstrate negative spatial spillover effects on the carbon balance in neighboring regions, while industrialization exerts a significant positive spatial spillover effect on the carbon balance of neighboring regions. Regarding control variables, the level of innovation solely contributes to local carbon balance realization without generating a trickle-down effect, whereas infrastructure development operates inversely. At the same time, there are differences in the spatial effects of agricultural modernization and industrialization on the carbon balance between the eastern region and the central and western regions. The study underscores the importance of economic modernization and development processes focusing on fostering synergistic growth between economic and environmental benefits within both local and neighboring areas. Full article

The U.K. food system exhibits strong unsustainability indicators across multiple dimensions, both in terms of food and nutritional insecurity and in terms of adverse climate change, biodiversity, and physical resource impacts. These indices of an unsustainable and inequitable social metabolism are the result of capitalist agriculture and society in general and, more specifically, of neoliberal and austerity policies adopted with vigour since the global financial crisis. The causal, capitalistic, and, latterly, more neoliberal bases of the U.K. food system are delineated in the first section of the paper. These bases are then detailed in terms of their impacts in exacerbating climate change, biodiversity (and resource) decline and loss, and food and nutritional insecurity. The political narratives and policy frameworks available to dissemble, mitigate, or, more rarely, to address (resolve) these impacts are then delineated. It is argued that the only policy framework available that strongly integrates food security (social equity) with ecological sustainability is political agroecology and an accompanying degrowth strategy. The final section of the paper details what political agroecology and degrowth might entail for the U.K. food system. Full article

Urban environments face escalating challenges due to uncontrolled urbanization, rapid population growth, and climate changes, prompting the exploration of sustainable solutions for enhancing urban green spaces (UGSs). For this reason, poplars (Populus L.), due to their rapid growth, wide range adaptability to environmental conditions and versatility of use, have emerged as very promising. This comprehensive review synthesizes current knowledge regarding poplar’s application in urban landscapes, emphasizing its multifaceted contributions and benefits. However, challenges arise from the variable lifespans of different poplar cultivars, necessitating strategic management approaches. Selecting cultivars based on growth rates, root system characteristics, and adaptability to urban conditions is pivotal. Adaptive replanting strategies, incorporating species with varying lifespans, offer solutions to maintain continual greenery in urban landscapes. Collaborative efforts between researchers, urban planners, and policymakers are essential for devising comprehensive strategies that maximize benefits while addressing challenges associated with their variable lifespans. In conclusion, harnessing poplar’s potential in urban greenery initiatives requires a balanced approach that capitalizes on their benefits while mitigating challenges. Further research and adaptive strategies are crucial for sustained and effective utilization to create resilient and vibrant urban landscapes. Full article

Terraced historical landscapes have multiple functions in mountain land, limiting erosion, enabling agricultural production and constituting cultural heritage. Currently, they are largely abandoned in Mediterranean regions and facing the ongoing impacts of climate change. Our aim is to reconstruct the evolution of land use on the terraces in order to test the hypothesis of the resilience of these landscapes and their age in recent history (17th–21st century). To achieve this, we used various current and archive spatial datasets and GIS knowledge to detect and map terraces and the changes in land use. We tested this hypothesis in a territory impacted by a recent extreme event, facing the challenge of its reconstruction. Our main outcome showed that the optimal use of the terraces corresponded to the demographic optimum of the mid-19th century, and they were gradually abandoned after the Second World War, with significant differences between Mediterranean and mountain lands. Despite this evolution, the terraces persisted and withstood an extreme event, validating our resilience hypothesis and opening avenues for the revitalization of this territory based on this heritage. These findings are drawing perspectives for the future of terraced landscapes in Mediterranean mountains in the context of climate change. Full article

This study estimates relative pollen productivity (RPP) for plant taxa from Southern Anatolia, an important region in the Mediterranean with a long history of human settlements. RPP estimates are required for quantitative pollen-based reconstruction of past land cover modelling. The application of the reconstruction by the REVEALS model in the Mediterranean basin is constrained due to the scarcity of the RPP values specific to the region. To better understand the relationship between vegetation cover and land use in the Mediterranean area, the present study aims to provide a set of RPPs for Turkey and the Mediterranean region. The study area centres around Gölhisar Lake in southwestern Turkey. Modern pollen data are collected from moss pollsters from 21 sites together with vegetation surveys. RPP estimates for the main taxa characteristic of the Mediterranean region are obtained (referenced to evergreen Quercus t.) using the extended R-value (ERV) model through the analysis of modern pollen assemblages. The most reliable results are acquired with the ERV sub-model 2 and Prentice’s taxon-specific method (using a Gaussian plume dispersal model) to distance-weighted vegetation data, corresponding to a Relative Source Area of Pollen (RSAP) value of 102 m. RPPs of dominant taxa in the study area are obtained for Quercus coccifera/Fagaceae (1 ± 0), Juniperus/Cupressaceae (0.279 ± 0.001), Fabaceae (0.008 ± 0.000), Pinus/Pinaceae (5.782 ± 0.011), and Poaceae (0.112 ± 0.001) and are comparable with other RPPs obtained in the Mediterranean region. Full article