Search Results (406)

Like in many countries, the transfer of increased land value created by public actions without landowner contributions back to the public is under debate in Türkiye. Although various Land Value Capture (LVC) mechanisms are employed worldwide to finance infrastructure investments, no comprehensive system has been established in Türkiye for this purpose. In this study, an improved LVC model that integrates land value and development rights is proposed. This model, termed Hybrid Land Readjustment (hLR), is designed to ensure that land value increases triggered by public investments are returned to the public. To this end, existing Turkish value capture instruments with potential are examined. Under the proposed hLR framework, equal basic development rights are granted to cadastral parcels, parcel and building-block value maps are utilized, basic rights are adjusted according to land-value changes, and a portion of additional development rights is transferred to the public. A practical application scenario is provided to illustrate the model’s operation. The system is configured for seamless integration into Türkiye’s existing legal and planning framework, offering a sustainable mechanism for financing infrastructure and implementing zoning plans. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

In the case of forest inventory, heterogeneous areas are particularly challenging due to variability in vegetation structure. This is especially true in Galicia (northwest Spain), where land is highly fragmented, complicating the planning and management of single-species plantations such as Pinus radiata. This study proposes a cost-effective strategy using open-access tools and data to characterize and estimate wood volume in these plantations. Two stratification approaches—classical and cluster-based—were compared to a modeling method based on Principal Component Analysis (PCA). Data came from open-access national LiDAR point clouds, acquired using manned aerial vehicles under the Spanish National Aerial Orthophoto Plan (PNOA). Moreover, two volume estimation methods were applied: one from the Xunta de Galicia (XdG) and another from Spain’s central administration (4IFN). A Generalized Linear Model (GLM) was also fitted using PCA-derived variables with logarithmic transformation. The results show that although overall volume estimates are similar across methods, cluster-based stratification yielded significantly lower absolute errors per hectare (XdG: 28.04 m³/ha vs. 44.07 m³/ha; 4IFN: 25.64 m³/ha vs. 38.22 m³/ha), improving accuracy by 7% over classical stratification. Moreover, it does not require precise field parcel locations, unlike PCA modeling. Both official volume estimation methods tended to overestimate stock by about 10% compared to PCA. These results confirm that clustering offers a practical, low-cost alternative that improves estimation accuracy by up to 18 m³/ha in fragmented forest landscapes. Full article

Accurate land parcel segmentation in remote sensing imagery is critical for applications such as land use analysis, agricultural monitoring, and urban planning. However, existing methods often underperform in complex scenes due to small-object segmentation challenges, blurred boundaries, and background interference, often influenced by sensor resolution and atmospheric variation. To address these limitations, we propose a dual-stage framework that combines an enhanced YOLOv5s detector with the Segment Anything Model (SAM) to improve segmentation accuracy and robustness. The improved YOLOv5s module integrates Efficient Channel Attention (ECA) and BiFPN to boost feature extraction and small-object recognition, while Soft-NMS is used to reduce missed detections. The SAM module receives bounding-box prompts from YOLOv5s and incorporates morphological refinement and mask stability scoring for improved boundary continuity and mask quality. A composite Focal-Dice loss is applied to mitigate class imbalance. In addition to the publicly available CCF BDCI dataset, we constructed a new WuJiang dataset to evaluate cross-domain performance. Experimental results demonstrate that our method achieves an IoU of 89.8% and a precision of 90.2%, outperforming baseline models and showing strong generalizability across diverse remote sensing conditions. Full article

3D (three-dimensional) property volume is an important data carrier for 3D land administration by using 3D cadastral technology, which can be used to express the legal space (property rights) scope matching with physical entities such as buildings and land. A 3D property volume is represented by a dense set of 3D coordinate points arranged in a predefined order and is displayed alongside the parcel map for reference and utilization by readers. To store a 3D property volume in the database, it is essential to record the connectivity relationships among the original 3D coordinate points, the associations between points and lines for representing boundary lines, and the relationships between lines for defining surfaces. Only by preserving the data structure that represents the relationships among points, lines, and surfaces can the 3D property volume in a parcel map be fully reconstructed. This approach inevitably results in the database storage volume significantly exceeding the original size of the point set, thereby causing storage redundancy. Consequently, this paper introduces a reversible 3D property volume compression coding method (called 3DPV-CC) to address this issue. By analyzing the distribution characteristics of the coordinate points of the 3D property volume, a specific rule for sorting the coordinate points is designed, enabling the database to have the ability of data storage and recovery by merely storing a reordered point set. The experimental results show that the 3DPV-CC method has excellent support capabilities for 3D property volumes of the vertical and slopped types, and can compress and restore the coordinate point set of the 3D property volume for drawing 3D parcel maps. The compression capacity of our method in the test is between 23.66% and 38.42%, higher than the general data compression methods (ZIP/7Z/RAR: 8.37–10.32%). By means of this method, land or real estate administrators from government departments can store 3D property volume data at a lower cost. This is conducive to enhancing the informatization level of land management. Full article

Infrastructure facility development and modernization highly contribute to national economic growth, but at the same time, such development also causes local negative impacts on the use of specific land plots, creating losses for their right holders. In Russia, some prerequisites have already been laid down on the issue of compensation for the losses associated with restrictions on the rights and prohibitions of economic activity within zones with special territory use conditions (ZSTUCs). However, the impacts of such facilities lead to environmental pollution and land use disadvantages, such as irregular parcels. The aim of this work is to substantiate a set of approaches to compensating for the cumulative negative impact of infrastructure facilities. The factors causing the negative impacts of infrastructure facilities are grouped into three areas: rights restrictions, territorial deficiencies and environmental pollution. This work uses the SWOT analysis method with the possibility of element-by-element analysis, as a result of which the approaches to the compensation for negative impacts under different external and internal conditions are determined. As a result of this study, a justification for a set of approaches to compensating for the negative impacts of infrastructure facilities on land use was executed, and a new algorithm to compensate the right holders of the land, industry sector or state for such negative impacts was developed. The following approaches to compensating for negative impacts were identified: loss assessment; the establishment of environmental payments; cadastral value adjustment; compensation for industry sector losses; and the use of state regulation tools. The first two approaches were identified as the main ones. The proposed algorithm can be realized only with the help of the abovementioned methodological approaches, which form a basis for further research. Full article

In recent decades, the deployment of quadcopters has significantly expanded, particularly in outdoor applications such as parcel delivery. These missions require highly stable aerial platforms capable of maintaining balance under diverse environmental conditions, ensuring the safe operation of both the drone and its payload. This paper focuses on the stabilization of a quadcopter designed for outdoor use. A detailed dynamic model of a compact vertical takeoff and landing (VTOL) drone forms the basis for a non-linear control strategy targeting stability during the critical takeoff phase. The control law is designed using a quasi-linear parameter-varying (quasi-LPV) model that captures the system’s non-linear dynamics. Lyapunov theory and linear matrix inequalities (LMIs) are employed to validate the stability and design the controller. Numerical simulations demonstrate the controller’s effectiveness, and a comparative study is conducted to benchmark its performance against a reference quadrotor model. Full article

The world is characterised by the growing volumes and flow of goods, which, amid benefits to economic development, result in negative externalities affecting the sustainability of cities. Although numerous studies have analysed the locational patterns of logistics facilities in cities, further research is required to examine their real estate patterns and trends. The aim of the paper is, therefore, to analyse the value of land accommodating logistics facilities in the City of Cape Town municipality, South Africa. Given the lack of dedicated geo-spatial data, logistics firms were searched on Google Maps, utilising a combination of aerial photography and street view imagery. Three main attributes of land parcels hosting logistics facilities were thereafter captured from the municipal cadastral information: property extent, street address, and property number. The latter two were used to extract the 2018 and 2022 property market values from the valuation rolls on the municipal website, followed by statistical, spatial, and geographically weighted regression (GWR) analyses. Zones near the central business district and seaport, as well as areas with prime road-based accessibility, had high market values, while those near the railway stations did not stand out. However, GWR yielded weak relationships between market values and the locational variables analysed, arguably showing a disconnect between spatial planning and logistics planning. Towards augmenting sustainable logistics, it is recommended that relevant stakeholders strategically integrate logistics into spatial planning, and particularly revitalise freight rail to attract investment to logistics hubs with direct railway access. Full article

Prompt and precise cropland mapping is indispensable for safeguarding food security, enhancing land resource utilization, and advancing sustainable agricultural practices. Conventional approaches faced difficulties in complex terrain marked by fragmented plots, pronounced elevation differences, and non-uniform field borders. To address these challenges, we propose DAENet, a novel deep learning framework designed for accurate cropland extraction from high-resolution GaoFen-1 (GF-1) satellite imagery. DAENet employs a novel Geometric-Optimized and Boundary-Restrained (GOBR) Block, which combines channel attention, multi-scale spatial attention, and boundary supervision mechanisms to effectively mitigate challenges arising from disjointed cropland parcels, topography-cast shadows, and indistinct edges. We conducted comparative experiments using 8 mainstream semantic segmentation models. The results demonstrate that DAENet achieves superior performance, with an Intersection over Union (IoU) of 0.9636, representing a 4% improvement over the best-performing baseline, and an F1-score of 0.9811, marking a 2% increase. Ablation analysis further validated the indispensable contribution of GOBR modules in improving segmentation precision. Using our approach, we successfully extracted 25,556.98 hectares of cropland within the study area, encompassing a total of 67,850 individual blocks. Additionally, the proposed method exhibits robust generalization across varying spatial resolutions, underscoring its effectiveness as a high-accuracy solution for agricultural monitoring and sustainable land management in complex terrain. Full article

Resource-exhausted cities face dual crises of economic stagnation and ecological degradation, which is primarily attributable to the inefficient use of industrial land. The redevelopment of industrial land has emerged as a crucial solution to the “resource depletion-urban decline” dilemma. The issue of inefficient industrial land use in resource-exhausted cities is of great significance as it directly impacts both economic development and ecological protection. Therefore, finding effective ways to redevelop this land is essential for the sustainable development of these cities. This research takes Hegang, a representative resource-exhausted city in China, as a case study. A multi-dimensional evaluation framework and an adaptive redevelopment strategy system are constructed in this research. By integrating data related to land use status, land use efficiency, policy constraints, and development potential, a parcel-scale assessment model is established. This model consists of 4 primary indicators and 13 secondary indicators. Through this model, 11.01 km² of inefficient industrial land in the main urban area of Hegang is identified. Standard deviation ellipse and kernel density analysis are employed to reveal the spatial pattern of inefficient land. The results show that the inefficient industrial land in Hegang exhibits a pattern of “overall dispersion with localized agglomeration”. It is found that idle and abandoned land are the dominant types of inefficient industrial land in Hegang’s main urban area, accounting for 69.7% of the total. This finding provides a clear understanding of the nature of the inefficient land use problem in resource-exhausted cities. A strategic framework is proposed, which incorporates classified governance, dynamic restoration, and multi-stakeholder collaboration. This framework offers a governance toolkit with both theoretical depth and practical value for resource-exhausted cities. Breaking the locked relationship between industrial land and resource dependence promotes the deep integration of spatial restructuring and sustainable transformation. The findings of this research provide significant scientific insights for similar cities worldwide to address the challenges they face and achieve harmony between human activities and land use. Future research could focus on further refining the evaluation framework and redevelopment strategies based on different regional characteristics and resource endowments. Full article

Urban vacant land possesses significant yet untapped ecological potential (capacity to support biodiversity, ecological processes, and ecosystem functions) for enhancing urban sustainability and resilience. However, the absence of structured and adaptable frameworks for ecological assessment limits its effective integration into urban planning. This study introduces a novel multi-tier ecological assessment framework, combining expert-driven criteria established through the Fuzzy Delphi Method with GIS-based spatial analysis. The framework ensures flexibility and scalability, enabling planners to perform rapid preliminary assessments and progressively detailed evaluations depending on available resources and specific planning objectives. A case study in Sentul-Manjalara, Kuala Lumpur, demonstrates the framework’s practical application, resulting in an ecological potential map categorising vacant parcels into high, medium, and low revitalisation priorities. This approach effectively connects theoretical ecological insights and actionable urban planning, providing policymakers and planners with an evidence-based decision-making tool for strategically prioritising vacant land revitalisation efforts. The outcome enhances urban biodiversity, ecological connectivity, and long-term urban resilience. Full article

The 1992 reform of the European Common Agricultural Policy (CAP) introduced the Land Parcel Identification System (LPIS), a geodatabase of land parcels used to monitor and regulate agricultural subsidies. Traditionally, the LPIS has relied on high-resolution aerial orthophotos; however, recent advancements in very-high-resolution (VHR) satellite imagery present new opportunities to enhance its effectiveness. This study explores the feasibility of utilizing PlanetScope, a commercial VHR optical satellite constellation, to map agricultural parcels within the LPIS. A test was conducted in Umbria, Italy, integrating existing datasets with a series of PlanetScope images from 2023. A segmentation workflow was designed, employing the Normalized difference Vegetation Index (NDVI) alongside the Edge segmentation method with varying sensitivity thresholds. An accuracy evaluation based on geometric metrics, comparing detected parcels with cadastral references, revealed that a 30% scale threshold yielded the most reliable results, achieving an accuracy rate of 83.3%. The results indicate that the short revisit time of PlanetScope compensates for its lower spatial resolution compared to traditional orthophotos, allowing accurate delineation of parcels. However, challenges remain in automating parcel matching and integrating alternative methods for accuracy assessment. Further research should focus on refining segmentation parameters and optimizing PlanetScope’s temporal and spectral resolution to strengthen LPIS performance, ultimately fostering more sustainable and data-driven agricultural management. Full article

Herein is presented a systematic review on property documentation in Greece from 1830 to the present, examining the systems used and their impact on spatial data management and land administration policies. This review reveals that the adoption of the person-based land registry system in 1836, versus the parcel-based Cadastre, led to fragmented property documentation and hindered coherent land administration policies. The establishment of the Hellenic Cadastre in 1995 marked the transition to integrated property documentation within the sole official parcel-based system, facilitating spatial data management and sustainable development. The cadastral survey revealed significant spatial and descriptive fragmentation due to incomplete spatial and legal documentation, unregistered administrative acts, and unregistered public property, which also affects the operational Cadastre. This paper contributes to the literature on the full transition from land registries to a Cadastre, and its impact on spatial data management and overall land administration. Full article

Low-impact development (LID) facilities serve as a fundamental approach in urban stormwater management. However, significant variations in land use among different plots lead to discrepancies in runoff reduction demands, frequently leading to either the over- or under-implementation of LID infrastructure. To address this issue, we propose a cost-effective optimization framework grounded in the concept of “Capacity Trading (CT)”. The study area was partitioned into multi-scale grids (CT-100, CT-200, CT-500, and CT-1000) to systematically investigate runoff redistribution across heterogeneous land parcels. Integrated with the Sequential Least Squares Programming (SLSQP) optimization algorithm, LID facilities are allocated according to demand under two independent constraint conditions: runoff coefficient ($\phi$ ≤ 0.49) and runoff control rate ($\eta$ ≥ 70%). A quantitative analysis was conducted to evaluate the construction cost and reduction effectiveness across different trading scales. The key findings include the following: (1) At a constant return period, increasing the trading scale significantly reduces the demand for LID facility construction. Expanding trading scales from CT-100 to CT-1000 reduces LID area requirements by 28.33–142.86 ha under the $\phi$-constraint and 25.5–197.19 ha under the $\eta$-constraint. (2) Systematic evaluations revealed that CT-500 optimized cost-effectiveness by balancing infrastructure investments and hydrological performance. This scale allows for coordinated construction, avoiding the high costs associated with small-scale trading (CT-100 and CT-200) while mitigating the diminishing returns observed in large-scale trading (CT-1000). This study provides a refined and efficient solution for urban stormwater management, overcoming the limitations of traditional approaches and demonstrating significant practical value. Full article

The transfer of development rights (TDR) is a legal instrument, introduced in 1961, that allows transferring of development rights from a land parcel where restrictions are imposed (sending parcel) to another land parcel (receiving parcel). TDRs aim to ensure environmental and cultural heritage protection with respect to the rights of individual land parcel owners, thus constituting a high impact tool in sustainability and urban planning. Although extensive research has been applied in defining development rights’ transfer zones (RTZ), mainly in the proximity of the sending parcels, limited is the research on defining this “proximity”. This research examines the process of identifying the areas that can host RTZs, using as a case study the implementation of TDR in Greece. Greek TDR legislation was challenged by the Hellenic Council of the State as non-conformant to the principles of rational urban and spatial development, thus requiring the identification of the areas that can host rights’ transfer zones. In order to align with the Council’s decisions, the Ministry of Environment and Energy introduced Law 4759/2020 along with Technical Requirements for the delineation of development rights’ transfer zones. Given that restrictions on the transfer of development rights do not exist in all municipalities in Greece, multi-criteria analysis was used to propose municipal units where studies on development rights’ transfer zones (RTZs) could be conducted, based on the number of sending parcels, geographic and urban planning requirements, and funding limitations. The analysis resulted in 83 municipal units, covering about 75% of the country’s need for development rights’ transfer. The deployment of RTZ studies in the selected areas would benefit the owners of the restricted land parcels (where existing TDR titles are currently inactive or where new ones cannot be issued) and assist urban space management. Full article