ABSTRACT The official national Swiss land use statistics constitutes an important instrument of spatial planning and classify land use (LU) and land cover (LC) through manual expert annotation across a grid of over 4.1 million sample points, resulting in 46 LU and 27 LC classes. We investigate whether machine learning (ML) can streamline this process by integrating multimodal and multitemporal datasets. Aerial RGB and FCIR image-based Convolutional Neural Network (CNN) probability outputs are fused with multispectral Landsat-derived time series indices, digital elevation data, vegetation canopy models and cadastral information using a Random Forest (RF) post-classification step. This integrated CNN-RF pipeline achieved overall accuracies of 83% for LU and 86% for LC. Large classes, such as dense forest and agricultural areas, reached individual F1 scores above 90%, effectively reducing the manual workload. Our results show that fusing multiple data sources can substantially improve accuracy over CNN-only aerial image classification, demonstrating the potential of application to similar national or regional LU/LC mapping efforts worldwide.
Abstract. In Turkiye, a diverse range of organizations, including public institutions and private sector entities, are actively engaged in the production and management of geospatial information. To enhance coordination, minimize duplication of efforts, and optimize resource use, the Metadata GeoPortal (Map Information Bank) was developed. This web-based platform acts as a central hub for both public and private users to enter, update, and share metadata connected to their mapping activities. It offers quick access to essential map data, supports decision-making processes, and underpins various e-government initiatives. Operating in accordance with the Large-Scale Map and Map Information Production Regulation, the Metadata GeoPortal aims to prevent redundant map production and ensure efficient utilization of national resources. Designed to comply with the ISO 19115 Metadata Standard, the platform allows users to register mapping projects, assign unique project numbers, and generate endpoint numbers (SNN) for coordinate data. The GeoPortal improves data sharing and coordination across different sectors. For instance, data entered by entities such as the General Directorate of Land Registry and Cadastre (TKGM) and the General Directorate of Mapping (HGM) can be shared with other stakeholders through web services following established protocols. This facilitates seamless access to critical geospatial data, including control points, aerial photographs, orthophotos, elevation models, and topographic maps. Since its launch in July 2008, the Metadata GeoPortal has undergone continuous improvements. It is now widely used by ministries, public institutions, municipalities, and private entities, extending its impact in mapping, cadastral work, and geographic information systems. The February 2022 update introduced a new user interface, allowing TKGM units to download map data directly without formal correspondence. Additional features, such as direct access through the Parcel Inquiry System, have further increased the platform’s usability. Looking ahead, the upcoming “Phase 4” updates will expand the platform’s functionalities, enhancing geospatial data management and collaboration across sectors. The Metadata GeoPortal is a pivotal tool in Turkiye’s efforts to modernize and centralize geospatial data management, reduce redundancy, and maximize resource efficiency.
ABSTRACT In contemporary agriculture and environmental management, the need for precise and accurate crop maps has never been more vital. Although object-based (OB) methods within Google Earth Engine (GEE) improve accuracy and output quality in contrast to pixel-based approaches, their application to crop classification remains relatively rare. Therefore, this study aimed to develop an OB classification methodology for crops located in central Italy’s Lake Trasimeno area. This methodology employed spectral bands, spectral indices (Normalized Difference Vegetation Index and Modified Radar Vegetation Index), and textural information (Gray-Level Co-occurrence Matrix) derived from Sentinel-2 L2A (S2) and Sentinel-1 GRD (S1) data within the GEE platform. Moreover, European Common Agricultural Policy (CAP) data associated with cadastral parcels were employed and served as ground information during the training and validation stages. The CAP crop classes were aggregated into three levels (Level 1–3 crop types, Level 2–5 crop types, and Level 3–7 crop types). Subsequently, optimized Random Forest (RF) classifiers were applied to map crops effectively. Feature selection analysis highlighted the importance of certain textural features. Additionally, findings demonstrated high overall accuracy results (89% for Level 1, 86% for Level 2, and 82% for Level 3). It was found that winter crops achieved the highest F-score at Level 1, while specific subclasses, such as winter cereals and warm-season cereals, excelled at Level 2. Overall, this study provides a promising approach for improved crop mapping and precision agriculture in the GEE environment.
As climate change exacerbates wildfire risks globally, innovative geospatial technologies are becoming crucial for effective fire management.
This article discusses a groundbreaking project by the California Department of Forestry and Fire Protection (CAL FIRE) in collaboration with Ecopia AI, which utilizes AI-generated mapping data to assess wildfire hazards across California's Fire Hazard Severity Zones. Covering over 32 million acres, this comprehensive dataset includes detailed information on buildings, infrastructure, and environmental features that influence fire behavior. The project enhances wildfire preparedness, supports
rapid post-fire recovery, and offers a scalable model for fire-prone regions worldwide. By integrating high-resolution aerial imagery with advanced AI analysis, this initiative exemplifies the potential of geospatial solutions to improve community safety and infrastructure resilience in the face of escalating wildfire threats.
Graz has emerged as a pioneer in climate-responsive urban planning, combining decades of
research with innovative geospatial applications. Within the EU-funded USAGE project, the
city validated satellite thermal imagery against aerial surveys and applied the “3-30-300 rule”
to map access to green infrastructure, feeding results into its Klimainformationssystem. A complementary
aerial thermal campaign captured high-resolution rooftop data to identify energy
loss, supporting both municipal strategies and citizen-led renovations. These initiatives illustrate
how integrating satellite, aerial, and ground-based data can transform climate monitoring into
practical planning tools. Graz’s approach offers a scalable model for European cities seeking
sustainable development and greater climate resilience.
У статті розглянуто актуальну проблему деградації ґрунтів та обґрунтовано необхідність застосування біомеліораційних методів як ключового інструменту для відновлення їхньої родючості. Метою статті є аналіз та систематизація даних впливу біомеліораційних методів на основі показників родючості деградованих ґрунтів. У процесі дослідження використано комплексний підхід, що передбачає аналіз наукових публікацій, а також практичних прикладів застосування методів біомеліорації для підвищення показників родючості деградованих ґрунтів. Родючість визначається як сукупність трьох основних властивостей, а саме фізичних, хімічних та біологічних. Відзначено вплив біомеліораційних методів на відновлення родючості через накопичення органічної речовини, стимуляцію біологічної активності, покращення структури ґрунту. Досліджено основні біомеліораційні методи та їхній вплив. Розглянуто фіторемедіацію як захід, який направлений на зменшення токсичних елементів у забруднених ґрунтах, завдяки вирощуванню спеціальних рослин, здатних виводити або локалізувати токсичні речовини в кореневій зоні або надземній частині. Визначено роль органічного землеробства як методу біомеліорації. Представлено схему механізму впливу біомеліорації на родючість ґрунтів та рекомендації з впровадження комплексу біомеліораційних систем, для ефективного відновлення деградованих ґрунтів в Україні. Зазначено, що подальші дослідження мають бути спрямовані на розробку регіонально адаптованих біомеліораційних систем та оцінку довгострокового економічного ефекту від їхнього впровадження.
Ключові слова: деградація ґрунтів, родючість ґрунту, біомеліорація, сидерати, фітомеліорація, фіторемедіація, мікробні препарати, органічне землеробство.
Tristan Karch, Jakhongir Saydaliev, I. Lenardo
et al.
Cadastral data reveal key information about the historical organization of cities but are often non-standardized due to diverse formats and human annotations, complicating large-scale analysis. We explore as a case study Venice's urban history during the critical period from 1740 to 1808, capturing the transition following the fall of the ancient Republic and the Ancien R\'egime. This era's complex cadastral data, marked by its volume and lack of uniform structure, presents unique challenges that our approach adeptly navigates, enabling us to generate spatial queries that bridge past and present urban landscapes. We present a text-to-programs framework that leverages Large Language Models (\llms) to process natural language queries as executable code for analyzing historical cadastral records. Our methodology implements two complementary techniques: a SQL agent for handling structured queries about specific cadastral information, and a coding agent for complex analytical operations requiring custom data manipulation. We propose a taxonomy that classifies historical research questions based on their complexity and analytical requirements, mapping them to the most appropriate technical approach. This framework is supported by an investigation into the execution consistency of the system, alongside a qualitative analysis of the answers it produces. By ensuring interpretability and minimizing hallucination through verifiable program outputs, we demonstrate the system's effectiveness in reconstructing past population information, property features, and spatiotemporal comparisons in Venice.
Contamination between photogrammetry and computers vision is a process which began at least a decade ago and yes is now in a mature stage, though not yet complete. Also, we are currently assisting at the entrance of technologies arising from robotics in the field of topography, such as i portable mapping systems mobile (MMS – Mobile Mapping Systems).
Behnam Atazadeh, Abbas Rajabifard, Yibo Zhang
et al.
There has been significant research on the intersection of 3D cadastre and building information modelling (BIM) over the recent years. BIM provides a multidimensional environment for capturing, curating and communicating the physical and functional aspects during a building’s lifecycle. A BIM-based solution for 3D cadastre provides a rich repository of legal and physical datasets in a common environment. The knowledge encapsulated inside a cadastral BIM model should be tapped to unlock the value of 3D cadastral information. Therefore, this article aims to develop BIM-based queries for interrogating questions about the legal ownership of properties inside multistorey buildings. These queries include identifying legal spaces that belong to a private or common property; querying physical elements that bound a legal space; and finding legal spaces that are adjacent to each other at a specific building element.
Abstract In Poland, the cadastre is the basic register which is the source of information on cadastral entities and their property. Therefore, it should constitute a reliable source of information in the scope of establishing the range of law, its nature, but also the subject of its ownership. However, it is necessary to be able to not only check the current information on the legal status and its scope, but also review past statuses or determine the rights that will influence real estate in the future. The cadastre and related rights are changing very dynamically over time, and each state has a very strict reference to the previous state. Therefore, in order to manage real estate in the most effective way, it is necessary to record temporal attributes of cadastre objects. The main objective of this paper is to define the legal issues related to the possibility of registration at the time of creation or modification of object in the Polish cadastre. This paper includes analyses of both Polish legal regulations and European standards and norms. Moreover, the article presents the results of comparative analyses concerning the data model of cadastre and INSPIRE and Land Administration Domain Model (LADM) data models for the theme cadastral parcel in terms of temporal aspect.
The state of legislative support as a basis for holding land auctions in Ukraine is analysed and the requirements for organizing and holding land auctions for creating, above all, conditions for their conducting on a competitive basis and in accordance with the economic interests of the state are found. In order to remedy the current situation, we collected, systematized and analysed statistical data on the conduct of land auctions during 2017-2019, the level of revenue for the right to lease or sell land, the effectiveness of the auction. It has been found that the purchase and sale of the right to lease land and land themselves through a land auction is a of selling them in the shortest possible time, but not at the best possible price. The not received funds for the right to lease or sell land during the period under review amounts to UAH 746 million 989 thousand, which is primarily indicative of the absence of financially viable buyers among Ukrainians. Against this background, problems with land bidding were identified, and proposals were made to address them.
M. Katsianis, Stamatina Lampraki, A. Theocharaki
et al.
The fortifications of Athens have been a recurrent theme of archaeological investigation. In the past two centuries, parts of the walls have been located during rescue interventions at numerous sites in the urban fabric. At present, the visibility of the entire monument remains rather low as the traces of the walls are hidden beneath the modern city, marginalized within larger archaeological sites or preserved entirely by record. Despite the high level of scholarly work devoted to synthesize the available material, the volume of information accumulated over the years requires a novel approach that would systematize different types of evidence using digital media. In this respect, we attempt to revisit the city walls of Athens through the use of geospatial technologies. We target the informed development of an efficient GIS platform to record, store, integrate, explore and eventually disseminate resources on the Athenian fortifications. Our research employs published and archival sources (e.g. excavation drawings) in combination with historical maps (e.g. early cadastral maps, first maps of modern Athens) and complementary historical evidence (e.g. writings, illustrations, photography) to locate, document and integrate in space and time available data on lost and surviving fortification remains.