Hasil untuk "Cadastral mapping"

Corrado Pisani

The Earth Observation sector is undergoing a structural transformation driven by the convergence of large satellite constellations, historical data archives and in-orbit artificial intelligence. Solutions such as ImageryPack enable seamless access to multi-source satellite imagery through a flexible credit-based model, supporting a wide variety of operational needs. At the same time, the AI-eXpress in-orbit processing platform dramatically shortens the traditional EO value chain by executing analytics directly in space, reducing latency and data transmission requirements. These innovations turn Earth Observation into an actionable geo-intelligence capability for public administrations, infrastructure operators, environmental monitoring, urban planning and emergency management.

A. Martyn

Стаття пропонує цілісну рамку подолання пострадянської інерції у взаємодії землеустрою та топографо-геодезичної діяльності в Україні. Показано, що радянська освітньо-професійна традиція звузила геодезію до вимірювально-інженерних практик і водночас маргіналізувала європейське розуміння землеустрою як проєктно-правової діяльності з формування меж та режимів користування, що мають юридичні наслідки. На основі аналізу міжнародних рамок (FIG, CLGE, INSPIRE, LADM), чинного українського законодавства та довготривалих спостережень автора за професійними дискусіями у соціальних мережах обґрунтовано: (1) необхідність термінологічної уніфікації (surveyor як родове поняття, з розмежуванням land/cadastral surveyor → «землевпорядник», engineering/topographic surveyor → «інженер-геодезист/топограф», «геодезист» — не синонім surveyor); (2) переосмислення функціональних ролей: топографо-геодезична діяльність є інфраструктурним інструментом створення доданої вартості в інших секторах, тоді як землеустрій безпосередньо формує нові об’єкти нерухомості, планувальні структури та управляє цінністю майна через RRR-підходи; (3) інституційну інтеграцію даних і процесів на основі моделей INSPIRE/LADM. Визначено структурні причини «кризи» галузі після 1991 р.: різке скорочення державного попиту на «централізовану геодезію» та технологічна автоматизація вимірювань (GNSS, ДЗЗ, БПЛА, ГІС). Запропоновано модернізацію вищої освіти за спеціальністю G18 («Геодезія та землеустрій») через міждисциплінарні навчальні траєкторії (геодезія × землеустрій × кадастр × просторове планування × оцінка), впровадження семантичних моделей даних, етики та процедур публічної довіри до меж, а також розвиток постійних професійних комунікацій як механізму зняття уявних конфліктів між спільнотами. Ключові слова: землеустрій; геодезія; топографо-геодезична діяльність; кадастр; межі; RRR (права-обмеження-обтяження); INSPIRE; LADM; термінологічна уніфікація; професійні кваліфікації; НІГД/NSDI; інституційна інтеграція; просторове планування; оцінка нерухомості.

V. Bogdanets, V. Nosenko, N. Mizerna et al.

The topicality of the topic is due to significant changes in the state of the components of the environment, namely the soil cover, and the use of agricultural land under the influence of the consequences of military operations in 2022-2023. There is a need to assess the scale of changes in the environment, primarily the soil cover, as the most disturbed as a result of hostilities, under the influence of these factors, to determine their respective scales, spatial localization and ecological and legal consequences. The main negative factors that lead to damage to agricultural land include (according to Kondratenko A.F. 2022): 1. Driving through the territory of heavy equipment (tanks and other types of tracked equipment, which leads to soil compaction and degradation); 2. The use of anti-tank and anti-personnel mines, which leads to changes in landscapes, relief and soil degradation; 3. Shelling and bombing of the territory, which leads to the formation of craters (funnels) and mixing of soil horizons. Sinkholes in places where shells fall are not only a factor of landscape damage and destruction of vegetation, but also a factor of soil pollution: they leave in the soil a significant amount of metal, sulfur and sulfur compounds, heavy metals, ammonia, phosphorus, coal dust, sulfuric acid and sulfate compounds, formaldehydes, lead, mercury; 4. Construction of trenches and other protective shelters for military personnel and equipment (soil disturbance and degradation); 5. Fires in natural areas and agricultural fields. As a result, the fertile soil layer burns out, dehydration and "sterilization" occurs - both pathogenic microorganisms and useful biota die, nutrients are lost. In our opinion, this classification generally covers well the spectrum of factors affecting the soil cover of military operations. At the same time, this classification is incomplete and does not cover some common cases, for example, the creation of systems of defensive structures leads to the violation of soil horizons and changes in the structure of the soil, the spread of erosion (Makarenko N. A., et al., 2022). Also, since it was developed for the conditions of military operations in Donetsk region as of 2014-2017, it needs to be supplemented and clarified, for example, it is worth adding the concepts of ecocide and destruction of infrastructure. The use of indicators of soil condition, monitoring of the development of degradation processes based on operational data and the possibility of using geoportals, dashboards and other means of public access to open data plays a particularly important role in the context of the impact of the consequences of military actions on the soil cover, prospects for agricultural production and, in general, on the quality of life. Key words: agricultural lands, soil cover, soil degradation, dynamics of land use, military operations.

B. Fetai, D. Grigillo, A. Lisec

One of the main concerns of land administration in developed countries is to keep the cadastral system up to date. The goal of this research was to develop an approach to detect visible land boundaries and revise existing cadastral data using deep learning. The convolutional neural network (CNN), based on a modified architecture, was trained using the Berkeley segmentation data set 500 (BSDS500) available online. This dataset is known for edge and boundary detection. The model was tested in two rural areas in Slovenia. The results were evaluated using recall, precision, and the F1 score—as a more appropriate method for unbalanced classes. In terms of detection quality, balanced recall and precision resulted in F1 scores of 0.60 and 0.54 for Ponova vas and Odranci, respectively. With lower recall (completeness), the model was able to predict the boundaries with a precision (correctness) of 0.71 and 0.61. When the cadastral data were revised, the low values were interpreted to mean that the lower the recall, the greater the need to update the existing cadastral data. In the case of Ponova vas, the recall value was less than 0.1, which means that the boundaries did not overlap. In Odranci, 21% of the predicted and cadastral boundaries overlapped. Since the direction of the lines was not a problem, the low recall value (0.21) was mainly due to overly fragmented plots. Overall, the automatic methods are faster (once the model is trained) but less accurate than the manual methods. For a rapid revision of existing cadastral boundaries, an automatic approach is certainly desirable for many national mapping and cadastral agencies, especially in developed countries.

E. Hämäläinen, Pauliina Krigsholm

In many western countries, publicly led mapping activities and recording information of land parcels and buildings and the related rights, restrictions, and responsibilities have established their roles as important pillars of a functioning society. National mapping, cadastral, and land registry authorities as public agencies responsible for conducting these tasks are in a key position in shaping the development of the whole land administration sector. Most of these authorities have formulated their purposes, directions, and goals in the form of strategies. There is, however, a lack of understanding of the type of goals these authorities pursue through their strategies and why. Using an online questionnaire as a method, this study explores the strategy goals as well as the strategy drivers of national mapping, cadastral, and land registry authorities. We find that the strategy goals converge to a great extent and relate particularly to digitalization, data properties, customers and needs of society, and organizational development. Further, we observe that the strategy work of these authorities is most often driven by changes in the customer needs and by changes in the government’s policies. The contribution of the study lies in providing an overview of how national mapping, cadastral, and land registry authorities frame their near-future development and in highlighting that albeit the goals, for the most part, align with the qualities of a good, neutral land administration system, the authorities show low tendency to pursue transformative or paradigmatic changes through their strategies.

S. Crommelinck, R. Bennett, M. Gerke et al.

Unmanned Aerial Vehicles (UAVs) have emerged as a rapid, low-cost and flexible acquisition system that appears feasible for application in cadastral mapping: high-resolution imagery, acquired using UAVs, enables a new approach for defining property boundaries. However, UAV-derived data are arguably not exploited to its full potential: based on UAV data, cadastral boundaries are visually detected and manually digitized. A workflow that automatically extracts boundary features from UAV data could increase the pace of current mapping procedures. This review introduces a workflow considered applicable for automated boundary delineation from UAV data. This is done by reviewing approaches for feature extraction from various application fields and synthesizing these into a hypothetical generalized cadastral workflow. The workflow consists of preprocessing, image segmentation, line extraction, contour generation and postprocessing. The review lists example methods per workflow step—including a description, trialed implementation, and a list of case studies applying individual methods. Furthermore, accuracy assessment methods are outlined. Advantages and drawbacks of each approach are discussed in terms of their applicability on UAV data. This review can serve as a basis for future work on the implementation of most suitable methods in a UAV-based cadastral mapping workflow.

Y. Dorosh, A. Barvinskyi, O. Dorosh et al.

The article analyses the regulatory and legal support for the organization of organic land use in Ukraine. It is established that the current regulations in the field of organic production are aimed mainly at regulating the technological processes of organic production, the procedure for its certification and the market of organic products. At the same time, the legislators did not pay attention to the issues related to the organization of the territory of agricultural enterprises for the production of organic products in order to meet the requirements of the relevant standards and rules of IFOAM. It is proved that for the organization of the territory of organic land use and land tenure it is necessary to develop and implement appropriate land management projects. In view of this, it is necessary to amend the Law of Ukraine "On Land Management", supplementing Article 25 with a new type of land management documentation: land management projects for the organization of organic land use (land tenure), and to enshrine the composition and content of such land management projects. Key words: normative-legal regulation, organic land use, buffer zone, crop rotation, land management project.

J. MendisL.N.

C. Hütt, G. Waldhoff, G. Bareth

Accurate crop-type maps are urgently needed as input data for various applications, leading to improved planning and more sustainable use of resources. Satellite remote sensing is the optimal tool to provide such data. Images from Synthetic Aperture Radar (SAR) satellite sensors are preferably used as they work regardless of cloud coverage during image acquisition. However, processing of SAR is more complicated and the sensors have development potential. Dealing with such a complexity, current studies should aim to be reproducible, open, and built upon free and open-source software (FOSS). Thereby, the data can be reused to develop and validate new algorithms or improve the ones already in use. This paper presents a case study of crop classification from microwave remote sensing, relying on open data and open software only. We used 70 multitemporal microwave remote sensing images from the Sentinel-1 satellite. A high-resolution, high-precision digital elevation model (DEM) assisted the preprocessing. The multi-data approach (MDA) was used as a framework enabling to demonstrate the benefits of including external cadastral data. It was used to identify the agricultural area prior to the classification and to create land use/land cover (LULC) maps which also include the annually changing crop types that are usually missing in official geodata. All the software used in this study is open-source, such as the Sentinel Application Toolbox (SNAP), Orfeo Toolbox, R, and QGIS. The produced geodata, all input data, and several intermediate data are openly shared in a research database. Validation using an independent validation dataset showed a high overall accuracy of 96.7% with differentiation into 11 different crop-classes.

C. Potsiou, N. Doulamis, Nikolaos Bakalos et al.

Abstract. With the rapid global urbanization, several multi-dimensional complex infrastructures have emerged, introducing new challenges in the management of the vertically stratified buildings spaces. 3D indoor cadastral spaces consist a zestful research topic as their complexity and geometry alterations during time, prevents the assignment of the corresponding Rights, Restrictions and Responsibilities (RRR). In the absence of the necessary horizontal spatial data infrastructure/floor plans their determination is weak. In this paper a fit-for-purpose technical framework and a crowdsourced methodology for the implementation of 3D cadastral surveys focused on indoor cadastral spaces, is proposed and presented. As indoor data capturing tool, an open-sourced cadastral mobile application for Android devices, is selected and presented. An Indoor Positioning System based on Bluetooth technology is established while an innovative machine learning architecture is developed, in order to explore its potentials to automatically provide the position of the mobile device within an indoor environment, aiming to add more intelligence to the proposed 3D crowdsourced cadastral framework. A practical experiment for testing the examined technical solution is conducted. The produced results are assessed to be quite promising.

K. Wong, C. Ellul, J. Morley et al.

<p>The interest in and use of 3D models in built environments is rapidly increasing, and they are now a key component of decision-making in areas including climate change mitigation (e.g., calculating solar panel potential, flood modelling, modelling housing age for retrofitting of thermal insulation), urban planning and cadastral systems (modelling rights, restrictions and responsibilities in complex buildings, streamlining the process to issue planning permits, design of existing or new developments) and infrastructure (construction, transport, utility management and modelling, asset management). 3D models are also an integrator for the data underpinning smart cities – knowing where a sensor is in 3D space allows the data to be integrated with the surrounding context – for example, noise data could be integrated with traffic information. Reflecting this interest, national mapping and cadastral agencies (NMCA) including Ordnance Survey (GB) are now increasingly generating 3D mapping at national scale, and there is extensive research as to how this data can be integrated with another emerging source of 3D models such as building information modelling (BIM).</p><p>These trends were evident during the 3rd BIM/GIS Integration Workshop and 15th 3DGeoInfo 2020 events, which were co-hosted by University College London and Ordnance Survey (GB) in September 2020. The workshop and conference brought together international researchers from academia, industry, government and national mapping and cadastral agencies in the field of 3D geoinformation, in an interdisciplinary gathering of researchers in the fields of data collection, data management, data quality, data analysis, advanced modelling approaches, applications, users, visualisation, augmented reality, artificial intelligence and many more.</p><p>This year’s theme was Users and Use Cases. The workshop and conference covered a wide range of topics including 3D data acquisition and processing, 3D city modelling and related standards, visualisation and dissemination of 3D data, augmented and virtual reality, 3D and Artificial Intelligence/Machine Learning. Three sessions of the BIM/GIS Integration Workshop were dedicated to Applications of BIM/GIS Integration, and an entire day of 3DGeoInfo 2020 to Users and Use Cases within 3DGeoInfo. Additionally, two sessions were specifically aimed at NMCA participants.</p><p>Although initially intended to be a face-to-face event in London, the team rapidly adjusted to the emerging COVID-19 situation, identifying an online solution that facilitated and encouraged participant interaction. This meant that the events could still provide a platform for learning, discussion, and exchange of ideas that they have been able to in previous years, as well as providing opportunities to promote international collaboration in these topics. This special issue of the ISPRS International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences contains 23 papers selected by a double-blind peer review involving a minimum of two reviewers, presenting research on topics including visualisation, point cloud management, virtual reality, data interoperability, data quality, generating national 3D datasets, indoor 3D, urban planning/permits and underground data management.</p>

T. Aditya, Ketut Gede, Fajar ARY SUCAY et al.

Giacomo Martirano, Vittorio Gagliardi

TEMAR is a collaborative research project, aimed at the research, development and testing of an innovative service for monitoring and mitigating the risk of pollution of bathing water, of potential interest for a vast use. It is based on the ability of optical remote sensing satellites to detect biochemical and physical characteristics of bathing waters on large surfaces and to validate them by in-situ measurements performed with aquatic drones. The project is co-funded by the Structural Funds of the European Commission, by means of the POR (Operative Regional Programme) Calabria 2014-2020.

A. Mohamed, Faizal Mohd Isa, Z. Ariff et al.

R. Q. Ismael, Q. Z. Henari, Azad Arshad Abdulwahab

Unmanned Aerial Vehicle (UAV) as a photogrammetric platform provides a new domain for engineers and geospatial professionals with a revolutionary tool for collecting a reliable geodata to be implemented for cadastral mapping. The aim of this study was to find the potential of UAV for cadastral mapping using high resolution aerial images. The study included the utilize of eBee PLUS fixed wing UAV flying at 106m altitude over Arab-Kand village. At the GSD of 2.5cm/pixel spatial resolution the site was covered by UAV images of forward and lateral overlap of 60% and 70% respectively. Horizontal accuracy obtained from generated orthomosaic was 4.8cm. This gives a possibility to create a line map with scale of 1:100 or 1:50. This study proved that the UAV based orthomosaic can be used for cadastral mapping due to high accuracy, low cost, less time consuming, rapid data acquisition, and complying with international standards.

S. Sim, Dongseob Song

Simmons Cms, Gisp, Parrish

D. Kohli, S. Crommelinck, R. Bennett et al.