Journal Description
Land
Land
is an international and cross-disciplinary, peer-reviewed, open access journal on land system science, landscape, soil–sediment–water systems, urban study, land–climate interactions, water–energy–land–food (WELF) nexus, biodiversity research and health nexus, land modelling and data processing, ecosystem services, and multifunctionality and sustainability etc., published monthly online by MDPI. The International Association for Landscape Ecology (IALE), European Land-use Institute (ELI), Landscape Institute (LI) and Urban Land Institute (ULI) are affiliated with Land, and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SSCI (Web of Science), PubAg, AGRIS, GeoRef, RePEc, and other databases.
- Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q2 (Nature and Landscape Conservation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 14.8 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.9 (2022);
5-Year Impact Factor:
4.0 (2022)
Latest Articles
Growing in Scarcity: Pre-Hispanic Rain-Fed Agriculture in the Semi-Arid and Frost-Prone Andean Altiplano (Bolivia)
Land 2024, 13(5), 619; https://doi.org/10.3390/land13050619 - 03 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Current and Future Trends of Socio-Economic Values in Terrestrial Ecosystem Services)
Open AccessArticle
Tracking Land-use Trajectory and Other Potential Drivers to Uncover the Dynamics of Carbon Stocks of Terrestrial Ecosystem in the Songnen Plain
by
Lei Chang, Han Luo, Huijia Liu, Wenxin Xu, Lixin Zhang and Yuefen Li
Land 2024, 13(5), 618; https://doi.org/10.3390/land13050618 - 03 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Land Use Effects on Carbon Storage and Greenhouse Gas Emissions)
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Open AccessArticle
Land Characterization System Software: Implementing Land Cover Ontology
by
Nicola Mosca, Fatima Mushtaq, Victor Munene, Peter Maleh, Ndyebo Mnyanda, Rashed Jalal and Amit Ghosh
Land 2024, 13(5), 617; https://doi.org/10.3390/land13050617 - 03 May 2024
Abstract
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,
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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
(This article belongs to the Special Issue Advances on Land Cover/Land Use Ontologies for Innovative Production/Utilization of Land Information)
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Open AccessArticle
Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta
by
Jun Cao, Yangfei Zhu, Haohao Zhu, Sidong Zhao and Junxue Zhang
Land 2024, 13(5), 616; https://doi.org/10.3390/land13050616 - 02 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Urban Land Use Change and Its Spatial Planning)
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Open AccessArticle
Research on Drought Monitoring Based on Deep Learning: A Case Study of the Huang-Huai-Hai Region in China
by
Junwei Zhou, Yanguo Fan, Qingchun Guan and Guangyue Feng
Land 2024, 13(5), 615; https://doi.org/10.3390/land13050615 - 02 May 2024
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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
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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.
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Open AccessArticle
Spatial Analysis of Point Clouds Obtained by SfM Photogrammetry and the TLS Method—Study in Quarry Environment
by
Ľudovít Kovanič, Patrik Peťovský, Branislav Topitzer and Peter Blišťan
Land 2024, 13(5), 614; https://doi.org/10.3390/land13050614 - 02 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Advances in the Evolution of the Geomorphological Landscape of Urbanized Areas)
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Open AccessArticle
Redefining Benggang Management: A Novel Integration of Soil Erosion and Disaster Risk Assessments
by
Xiqin Yan, Shoubao Geng, Hao Jiang, Zhongyu Sun, Nan Wang, Shijie Zhang, Long Yang and Meili Wen
Land 2024, 13(5), 613; https://doi.org/10.3390/land13050613 - 02 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Assessment and Monitoring of Land Degradation: Current Trends and Future Directions)
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Open AccessArticle
Nonlinear Effects of Land-Use Conflicts in Xinjiang: Critical Thresholds and Implications for Optimal Zoning
by
Jinhua Wu, Can Wang, Xiong He, Chunshan Zhou and Hongwei Wang
Land 2024, 13(5), 612; https://doi.org/10.3390/land13050612 - 02 May 2024
Abstract
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
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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 article belongs to the Special Issue Spatial Optimization and Sustainable Development of Land Use)
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Open AccessArticle
Estimating the Aboveground Fresh Weight of Sugarcane Using Multispectral Images and Light Detection and Ranging (LiDAR)
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Charot M. Vargas, Muditha K. Heenkenda and Kerin F. Romero
Land 2024, 13(5), 611; https://doi.org/10.3390/land13050611 - 01 May 2024
Abstract
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
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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
(This article belongs to the Special Issue Digital Earth and Remote Sensing for Land Management)
Open AccessReview
Consequences of Land Use Changes on Native Forest and Agricultural Areas in Central-Southern Chile during the Last Fifty Years
by
Alejandro del Pozo, Giordano Catenacci-Aguilera and Belén Acosta-Gallo
Land 2024, 13(5), 610; https://doi.org/10.3390/land13050610 - 01 May 2024
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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
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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.
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Open AccessArticle
Exploring Urban Service Location Suitability: Mapping Social Behavior Dynamics with Space Syntax Theory
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Saleh Qanazi, Ihab H. Hijazi, Isam Shahrour and Rani El Meouche
Land 2024, 13(5), 609; https://doi.org/10.3390/land13050609 - 30 Apr 2024
Abstract
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
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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
(This article belongs to the Section Land Planning and Landscape Architecture)
Open AccessArticle
Simulation and Attribution Analysis of Spatial–Temporal Variation in Carbon Storage in the Northern Slope Economic Belt of Tianshan Mountains, China
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Kun Zhang, Yu Wang, Ali Mamtimin, Yongqiang Liu, Lifang Zhang, Jiacheng Gao, Ailiyaer Aihaiti, Cong Wen, Meiqi Song, Fan Yang, Chenglong Zhou and Wen Huo
Land 2024, 13(5), 608; https://doi.org/10.3390/land13050608 - 30 Apr 2024
Abstract
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
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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
(This article belongs to the Special Issue Land-Based Greenhouse Gas Mitigation for Carbon Neutrality)
Open AccessArticle
Trends and Factors Influencing the Evolution of Spatial Patterns of Cropland toward Large-Scale Agricultural Production in China
by
Xinyan Wang, Qingyu Feng, Boyong Li, Yinlin Fan, Huihui Fan, Nengliang Yang, Yuan Quan, Huanru Ding and Yunlu Zhang
Land 2024, 13(5), 607; https://doi.org/10.3390/land13050607 - 30 Apr 2024
Abstract
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
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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.
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Open AccessArticle
Unveiling the Complexities of Land Use Transition in Indonesia’s New Capital City IKN Nusantara: A Multidimensional Conflict Analysis
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Alfath Satria Negara Syaban and Seth Appiah-Opoku
Land 2024, 13(5), 606; https://doi.org/10.3390/land13050606 - 30 Apr 2024
Abstract
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
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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 article belongs to the Collection Land Use Transitions and Land System Science)
Open AccessReview
Cultural Landscapes: Exploring the Imprint of the Roman Empire on Modern Identities
by
Marianna Olivadese and Maria Luisa Dindo
Land 2024, 13(5), 605; https://doi.org/10.3390/land13050605 - 30 Apr 2024
Abstract
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
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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 article belongs to the Special Issue The Forming of Cultural Landscapes and Urbanscapes)
Open AccessArticle
Unveiling the Dynamics of Rural Revitalization: From Disorder to Harmony in China’s Production-Life-Ecology Space
by
Ningning Liu, Qikang Zhong and Kai Zhu
Land 2024, 13(5), 604; https://doi.org/10.3390/land13050604 - 30 Apr 2024
Abstract
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
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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
(This article belongs to the Special Issue Interrelations in Urban–Rural Transects: Planning Sustainable Transformations for Human Wellbeing)
Open AccessArticle
Research on the Optimization of Multi-Class Land Cover Classification Using Deep Learning with Multispectral Images
by
Yichuan Li, Junchuan Yu, Ming Wang, Minying Xie, Laidian Xi, Yunxuan Pang and Changhong Hou
Land 2024, 13(5), 603; https://doi.org/10.3390/land13050603 - 30 Apr 2024
Abstract
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.
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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.
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(This article belongs to the Special Issue Digital Mapping for Ecological Land)
Open AccessArticle
Analysis of Factors Influencing Housing Prices in Mountain Cities Based on Multiscale Geographically Weighted Regression—Demonstrated in the Central Urban Area of Chongqing
by
Yiduo Chen, Qingyuan Yang, Li Geng and Wen Yin
Land 2024, 13(5), 602; https://doi.org/10.3390/land13050602 - 30 Apr 2024
Abstract
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
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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.
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(This article belongs to the Section Land Environmental and Policy Impact Assessment)
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Open AccessArticle
The Evaluation of Sustainable Development Projects in Marginal Areas: An A’WOT Approach
by
Rubina Canesi and Chiara D’Alpaos
Land 2024, 13(5), 601; https://doi.org/10.3390/land13050601 - 30 Apr 2024
Abstract
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
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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.
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(This article belongs to the Special Issue The Other Perspective. City Networks and Territorial Justice towards a Landscape Ethics)
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Open AccessArticle
Green Infrastructure Fluctuations in Urban Agglomeration of Shanxi Province, China: Implications for Controlling Ecological Crises
by
Cheng Gong, Huijun Pang, Aruhan Olhnuud, Fan Hao and Feinan Lyu
Land 2024, 13(5), 600; https://doi.org/10.3390/land13050600 - 30 Apr 2024
Abstract
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
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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.
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(This article belongs to the Section Landscape Ecology)
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