Javad Shahidinejad, Mohsen Kalantari, Abbas Rajabifard
Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is, therefore, necessary to develop an efficient system for storing and managing multidimensional cadastral data. While there have been attempts to develop 3D cadastral database schemas, a comprehensive solution that meets all the requirements for effective data storage, manipulation, and retrieval has not yet been presented. This study aims to analyse the literature on 3D cadastral databases to identify approaches and technologies for storing and managing these data. Based on a systematic literature review integrated with a snowballing methodology, 108 documents were identified. During the analysis of the related documents, different parameters were extracted, including the conceptual data model, query type, and evaluation metrics, as well as the database management system (DBMS) used and technologies for visualisation, data preparation, data transformation, and the ETL (extract, transform, and load) process. The study emphasised the importance of adhering to database design principles and identified challenges associated with conceptual design, DBMS selection, logical design, and physical design. The study results provide insights for selecting the appropriate standards, technologies, and DBMSs for designing a 3D cadastral database system.
Gruppo Ferrovie dello Stato Italiane, has been the first Italian
engineering company to equip itself, since the 1990s, with its
own staff of professional archaeologists capable of managing all
archaeological activities functional to the design and construction
of railway works and to resolve any interference between new
railway works and the archaeological heritage. The team works
in collaboration with the territorially competent Archaeological
Superintendencies in Italy and is registered in the Ministry of
Culture’s list of operators qualified to draw up the Archaeological
Assessment Document, bringing the latest non-invasive archaeological
investigation methods.
In the context of the Italian PNRR (National Recovery and Resilience Plan), the M1C2 component, financed by the European Union (EU) through Next Generation EU-RFF and by the Presidency of the Council of Ministers of the Italian Republic through the Complementary Fund of the Presidency of the Council, is dedicated to digitalisation, innovation and competitiveness. It includes (in the M1C2.4.2 intervention) objectives dedicated to space activities for Earth Observation, to be achieved in the period 2022-2026, in particular the creation of an end-to-end Space System, called IRIDE, composed of: Upstream Segment, Downstream Segment and Service Segment toprovide geospatial services at national and European level.
The IRIDE System will, therefore, be one of the public assets developed in recent years by the investments of the PNRR and,
consistently, its design has been based on the needs expressed by the Italian National Authorities (whose collection is coordinated by the National Forum of Copernicus Users and represented in the “Needs Analysis” Annex to the National Earth Observation Plan) with the aim of contributing with the Geo-Spatial component to the development of products useful for the innovativeness and operation of the services provided by the Public Administration for the management of the territory,
emergencies and security.
Rock-falls are catastrophic phenomena, which have been studied widely through remote sensing data and special software analysis. Rock-fall investigation is quite crucial and especially the rock-fall prediction, as these phenomena cause serious damages and fatalities that could be avoided with a correct susceptibility mapping. In this paper, the RocFall software was chosen aiming to achieve a rock-fall simulation. Kinetic energy illustration, velocity calculation, end points detection and bounces heights depiction can be calculated by the specific program. A well-studied landslide in Moira settlement, near to the city of Patras (Western Greece) was selected for the simulation as many geo-data sets already exist. Slope maps and elevation profiles were extracted, in GIS environment, from different Digital Surface Models (DSMs). Those derived products were implemented in RocFall software for further simulations. More specifically, free available DSMs such as DSM from the Greek Cadastral DSM, ALOS AW3D30 DEM, ASTER GDEM, SRTM30 DEM, SRTM90 DEM, TanDEM_X as well as UAV DSM created by field campaigns were used for slope profile extraction. The results were assessed based on the spatial resolution of DSMs and were validated with in situ observations and measurements. The current study has two objectives: Firstly, to evaluate RocFall software outcomes with the field measurements and secondly, to estimate the influence of the DSM spatial resolution and accuracy to rock-fall simulation. According to previous studies, the spatial resolution is affecting the vertical accuracy of the DSMs. Among the aforementioned DSMs, UAV DSM was proved more appropriate for landslides simulation.
Abstract. UAV imagery has a big role in environmental mapping: various indices regarding plant health, soil condition or geological objects can be determined, or 3D models can be built for accurate measurements. Automatic vectorization of satellite images is widely applied nowadays for land coverage determination purposes. However, larger resolution UAV images are hard to process following this theory: too many details result in a long computing time. We propose a FOSS (free and open-source software) analytical solution for detecting and vectorizing quasi-rectangular shaped (mainly manmade) objects on relatively high-resolution images. Our sample area is the cemetery and its surroundings in Istenmezeje, Heves County, Hungary. The graves are good examples of regular, rectangular manmade objects. The traditional cadastral mapping of these sites means a large amount of digitizing work. We have used Python environment for conducting image analysis: delineating and vectorizing the grave outlines for the large-scale mapping of the cemetery. Open-source programming libraries were used during the process: OpenCV and GDAL/OGR. With these tools, we were able to digitize the graves automatically with systematic errors. Approximately 70–80 of 100 graves were correctly recognised (their number varies depending on the adjustable variables: the size and detailedness of the contours to be detected). Our approach is a relatively new methodology in large-scale cartography: computer vision tools have not been used widely for mapmaking purposes. The development of artificial intelligence and open-source tools connected to it may contribute to the broader dissemination of similar methodologies in cartography and GIS.
Green Infrastructure (GI) defined as a strategically planned network of natural and semi-natural areas is a key strategy in the European biodiversity strategy and the landscape connectivity agenda. To implement this approach in Central Europe’s (CE) landscape planning policies the Interreg project MaGICLandscapes (ML) tried to operationalise the GI concept in CE as well as in nine case studies, to provide land-managers, policy makers and communities with tools and knowledge, at different spatial levels. Based on the example of the Austrian case study area, the aim of this paper is to present an easy to use approach, as implemented in ML, for producing a highly-detailed regional GI database to overcome the difficulty of realising comprehensive biotope mapping surveys as well as the rather coarse resolution of CORINE Land Cover (CLC). By compiling regional cadastral and agricultural information, highly detailed data on the water network as well as Pan-European High Resolution Layers (HRL), this detailed representation of the regional GI network allows to enhance the regional applicability and acceptance of GI initiatives and provides a crucial foundation for assessing GI connectivity and functionality to develop evidence-based strategies and action plans through stakeholder involvement to direct future actions and investment in GI.
Namibia currently undergoes a rapid process of urbanisation of 4% annually, visible through an exponential informal settlement growth. Alternative measurement methods in cadastral mapping could secure land tenure in these settlements and fasten land registration. This article investigates the performance of five alternative measurement methods within the Flexible Land Tenure System (FLTS): orthophoto-based boundary demarcation, mapping applications on mobile devices, hand-held GPS, low-cost GNSS with u-blox receiver and GNSS RTK based on the Namibian CORS. The article evaluates all five methods on technical performance, affordability, time efficiency, feasibility, and simplicity. Based on the evaluation, all methods are appropriate for Namibia except for the hand-held GPS method. Low-cost approaches are appropriate for starter titles, whereas high-technology methods are better when requiring higher positioning accuracy (land hold title). Orthophoto-based boundary demarcation is surprisingly less suitable for the Namibian case. Overall, the results support a fit-for-purpose land administration in Namibia.
A region-based convolutional neural network image segmentation approach (Mask R-CNN) was applied to identification of flat rooftops from satellite imagery in the city of Jeddah in Saudi Arabia. The model was trained on a small sample of rooftops (202) digitized from a 0.5 m resolution image (covering 0.21 km2) and then was applied to an independent area 4.5 km away. The precision and recall of the model were 0.98 and 0.96 respectively in terms of identifying rooftops in the independent area. A spatially stratified sample of rooftops was drawn from those identified by the model and the median roof area of the sample was not significantly different from the area as a whole. The results, although at a small scale, demonstrate the effectiveness of this approach for selecting buildings with appropriate rooftops for solar photovoltaic (PV) installation, in the context of closely spaced flat-roofed buildings, without requiring cadastral mapping or LIDAR datasets.
Paulo Jorge Pires Moreira, L. Duarte, M. Cunha
et al.
This work aims to integrate Remote Sensing (RS) and cadastral data in QGIS software to perform the spatiotemporal mapping of Wine Yield (WY) cluster zones in the Douro region. Spatiotemporal modelling approach for prediction of wine yield was based on Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and topographic data. The results showed that 74% $(\mathrm{R}^{2}=0.744,\ \mathrm{n}=128,\ \mathrm{p} < 0.000)$ WY interannual variability at administrative division could be explained by the developed model. This information allows establishing wine production region pattern which can improve the agronomic and economic efficiency of vineyard and winery operations.
Ing. Jhon Jairo Castro Afanador, A. J. L. Rivero, Jesús Ángel Román Gallego
Abstract: Currently, mobile devices, tablets and smartphones, among others, integrate geolocation systems supported by GPS or A-GPS sensors that have digital mapping functionalities, with the possibility of storage, routing and location information systems, among those, called location-based services (LBS). This technology allows the user to integrate approximate apparent position in real time between 3 and 6 meters. This approximation to the real position is valid for the LBS in applications of routing and tourism among others, but not for cadastral type surveys, urban inventories, cartographic updating or topographic support points among others. The article presents the integration of the processes required to obtain sub metric precisions in geolocation with mobile devices, in order to make accessible to all the professional use and the integration of new services.
The Department of Survey and Mapping Malaysia (JUPEM) developed SmartKADASTER Interactive Portal or SKiP in order to provide a multipurpose cadastral survey information-based platform for accurate spatial analysis. Whether SKiP is viable for its purpose is still undetermined. Therefore, this paper highlights the methodology of assessing the usability of SKiP. A usability test was conducted by using the System Usability Scale or SUS. Fifty-nine participants from various public and private agencies, participated in the assessment and were categorised as Existing, New and Potential users, as well as Familiar and Not Familiar with the spatial analysis concept. The overall SUS score for SKiP is 69.8, which concludes that the usability of SKiP is fit for its purpose and can be perceived as marginal high for acceptance under the Acceptability Range. The SUS score was subsequently extracted to determine additional information on the Learnability and Usability components that resulted as 57.8 and 72.8, respectively. The SUS score implies that SKiP is an excellent platform for Usability and perceived good for Learnability, within the Adjective Ratings. Further analysis of the SUS scores suggests that regardless of which category the users were grouped, those who are familiar with the spatial analysis concept are likely to score higher. The correlation efficient supports the SUS score result as the Learnability components of SKiP requires further improvement. It was also found that the usability test participants are distinct as Passively Satisfied users. In line with the overall SUS and Nett Promoter Score (NPS) scores, additional mitigation and interventions are needed to convert SKiP Passively Satisfied users to Promoters and reduced Detractors. Recommendations from the study are highlighted in this paper to value-add SKiP in the next phase while the prominence on ease of doing the spatial analysis is emphasised.
To tell about the Covid-19 pandemic, both information and in-depth television broadcasts (Porta a Porta, Che tempo che Fa, TG, etc.), and the main information portals (such as, for example, repubblica.it), used
a highly effective visual support, the Dashboard. This is the now sadly famous map of the world on a black background with red spherical markers with dimensions proportional to the spread of the infection and the infographics of the temporal development of the parameters of the epidemic. It is a web application based on Esri technology, the data of which are used
and reported by both journalists and civil protection technicians. Consultation of the application has gradually become a daily habit for citizens, as before
the emergency it could have been the consultation of weather forecasts.
S. C. L. Ribeiro, M. Jarzabek-Rychard, J. Cintra
et al.
Abstract. Cadastral mapping of favela’s agglomerated buildings in informal settlements at Level of Detail 1 (LoD1) usually requires specific surveys and extensive manual data processing. Therefore, there is a demand for including the favelas in the city map production on the basis of Lidar surveys, as well as the detection of their vertical growth. However, the currently developed algorithms for automatically extracting buildings from airborne Lidar data have mainly been tested only for regular building reconstruction. This study aims to develop a Lidar data processing pipeline enabling to compute metrics related to intraurban informal settlements. To do so, we present a procedure to generate favela’s buildings delineation, height, floors’ number and built area and apply them to six case studies in favela typo-morphologies. We conducted an exploratory analysis in order to obtain the adequate parameters of the processing pipeline and its evaluation, using open source, free license and self-developed software. The results are compared to reference data from the manual stereo plotting, achieving a quality index in the building reconstruction about 70%. We also calculated the growth density, measured by gross Floor Area Ratio index inside settlement, revealing values from 29% to 74% considering different time periods.
Emmanuel Nyandwi, Mila Koeva, Divyani Kohli
et al.
The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally has led to the experimental application of Artificial Intelligence in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object-Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from very high-resolution World View-2 images, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for the machine compared to 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data. Thus, these could neither be geometrically compared with human digitisation, nor actual cadastral data from the field. The results of this study provide an updated snapshot with regards to the performance of contemporary machine-driven feature extraction techniques compared to conventional manual digitising. In our methodology, using an iterative approach of segmentation and classification, we demonstrated how to overcome the weaknesses of having undesirable segments due to intra-parcel and inter-parcel variability, when using segmentation approaches for cadastral feature delineation. We also demonstrated how we can easily implement a geometric comparison framework within the Esri’s ArcGIS software environment and firmly believe the developed methodology can be reproduced.
Point clouds, generated by photogrammetry or laser scanning, mainly contain geometric information. This makes them not very useful for different applications.
Artificial Intelligence methods have opened up a new area of research and development, providing automatic solutions for segmentation and classification purposes.
Abstract. Land development processes today have an increasing demand to access three-dimensional (3D) spatial information. Complex land development may need to have a 3D model and require some functions which are only possible using 3D data. Accordingly, the Intergovernmental Committee on Surveying and Mapping (ICSM), as a national body in Australia provides leadership, coordination and standards for surveying, mapping and national datasets has developed the Cadastre 2034 strategy in 2014. This strategy has a vision to develop a cadastral system that enables people to readily and confidently identify the location and extent of all rights, restrictions and responsibilities related to land and real property. In 2014, the land authority in the state of Victoria, Australia, namely Land Use Victoria (LUV), has entered the challenging area of designing and implementing a 3D digital cadastre focused on providing more efficient and effective services to the land and property industry. LUV has been following the ICSM 2034 strategy which requires developing various policies, standards, infrastructures, and tools. Over the past three years, LUV has mainly focused on investigating the technical aspect of a 3D digital cadastre. This paper provides an overview of the 3D digital cadastre investigation progress in Victoria and discusses the challenges that the team faced during this journey. It also addresses the future path to develop an integrated 3D digital cadastre in Victoria.