Search Results (25)

In pursuit of the Sustainable Development Goals (SDGs)’s objective of eliminating slum cities, the government of Indonesia has initiated a survey-based slum mapping program. Unfortunately, recent observations have highlighted considerable inconsistencies in the mapping process. These inconsistencies can be attributed to various factors, including variations in the expertise of surveyors and the intricacies of the indicators employed to characterize slum conditions. Consequently, reliable data is lacking, which poses a significant barrier to effective monitoring of slum upgrading programs. Remote sensing (RS)-based approaches, particularly those employing deep learning (DL) techniques, have emerged as a highly effective and accurate method for identifying slum areas. However, the reliance on RS alone is likely to encounter challenges in complex urban environments. A substantial body of research has previously identified the merits of integrating land surface data with RS. Therefore, this study seeks to combine remote sensing imagery (RSI) with street view imagery (SVI) for the purpose of slum mapping and compare its accuracy with a field survey conducted in 2024. The city of Bandung is a pertinent case study, as it is facing a considerable increase in population density. These slums collectively encompass approximately one-tenth of Bandung City’s population as of 2020. The present investigation evaluates the mapping results obtained from four distinct deep learning (DL) networks: The first category comprises FCN, which utilizes RSI exclusively, and FCN-DK, which also employs RSI as its sole input. The second category consists of two networks that integrate RSI and SVI, namely FCN and FCN-DK. The findings indicate that the integration of RSI and SVI enhances the precision of slum mapping in Bandung City, particularly when employing the FCN-DK network, achieving an accuracy of 86.25%. The results of the mapping process employing a combination of the FCN-DK network, which utilizes the RSI and SVI, indicate the presence of 2294 light slum points and 29 medium slum points. It should be noted that the outcomes are contingent upon the methodological approach employed, the accessibility of the dataset, and the training data that mirrors the distribution of slums in 2020 and the specific degree of its integration within the FCN network. The FCN-DK model, which integrates RSI and SVI, demonstrates enhanced performance in comparison to the other models examined in this study. Full article

In this research, we have compiled and analysed the organisations and studies that jointly address the issue of land administration, fundamentally in the cartographic aspects related to the cadastre and land registry, in the international environment, and at the Ibero-American level. Through qualitative social research, interviews were conducted with internationally recognised experts on issues of general cartography, cartography and legal security, and related to cadastral valuation, obtaining conclusions that allow a general diagnosis of the situation of the Land Administration System in Ibero-America. In this environment, problems such as the heterogeneity of systems, overlapping of competencies, instability, lack of sustainability, need for standards, lack of transparency, etc., should be highlighted, among others. Finally, based on the compilation of existing data from the Cadastre Data survey conducted in 2011 by the Permanent Committee of Cadastre in Ibero-America, and with information from its members and member organisations of the Pan-American Association of Professional Surveyors, the geoportal Diagnosis of the Situation of the Land Administration System in Ibero-America has been created. This geoportal allows the initial identification of the different organisations and general regional data. Full article

Since 1990, approximately 420 million hectares of forest have been lost worldwide due to land conversion for various uses, including agriculture, infrastructure development, urbanization, and other human activities. This study aims to investigate the critical drivers contributing to deforestation and forest degradation (DFD) in Ondo State, Nigeria, thereby identifying areas where REDD+ (Reducing Emissions from Deforestation and Forest Degradation) interventions could be most effective in reducing greenhouse gas emissions, particularly carbon dioxide (CO₂), which is released through forest loss and degradation. A questionnaire survey was used to obtain data from construction professionals such as architects, engineers, builders, quantity surveyors, and project managers. Collected data were analyzed using frequencies and percentages to report the background information of professionals, Mean Item Scores (MIS) to rank critical drivers of DFD, and Fuzzy Synthetic Evaluation (FSE) to identify the most critical drivers. FSE analysis revealed that DFD is primarily motivated by agricultural expansion (including cattle ranching and shifting cultivation) and infrastructure extension (particularly transportation networks and market and service infrastructure) among the proximate drivers. The analysis also identified demographic, economic, and policy and institutional factors as the most significant underlying drivers. The emphasis on agricultural expansion and infrastructure extension suggests that targeted interventions in these areas could significantly mitigate DFD in the study site under consideration. This may involve implementing stricter regulations and incentives to promote sustainable land use practices among farmers and landowners. Additionally, integrating environmental impact assessments into infrastructure projects can help minimize forest loss associated with road construction and urban expansion. This study introduces an innovative approach by applying the Geist and Lambin conceptual framework of ‘proximate causes and underlying driving forces’. It is among the pioneering studies conducted in the study area to comprehensively analyze the drivers contributing to DFD using these frameworks. Although conducted in Ondo State, Nigeria, the findings can be extrapolated to similar regions facing similar challenges of DFD worldwide. Full article

The popularity of mobile laser scanning systems as a surveying tool is growing among construction contractors, architects, land surveyors, and urban planners. The user-friendliness and rapid capture of precise and complete data on places and objects make them serious competitors for traditional surveying approaches. Considering the low cost and constantly improving availability of Mobile Laser Scanning (MLS), mainly handheld surveying tools, the measurement possibilities seem unlimited. We conducted a comprehensive investigation into the quality and accuracy of a point cloud generated by a recently marketed low-cost mobile surveying system, the MandEye MLS. The purpose of the study is to conduct exhaustive laboratory tests to determine the actual metrological characteristics of the device. The test facility was the surveying laboratory of the University of Agriculture in Kraków. The results of the MLS measurements (dynamic and static) were juxtaposed with a reference base, a geometric system of reference points in the laboratory, and in relation to a reference point cloud from a higher-class laser scanner: Leica ScanStation P40 TLS. The Authors verified the geometry of the point cloud, technical parameters, and data structure, as well as whether it can be used for surveying and mapping objects by assessing the point cloud density, noise and measurement errors, and detectability of objects in the cloud. Full article

Soil compaction is one of the most important and readily mitigated threats to soil health. Digital Soil Mapping (DSM) has emerged as an efficient method to provide broad-scale maps by combining soil information with environmental covariates. Until now, soil information input to DSM has been mainly composed of point-based quantitative measurements of soil properties and/or of soil type/horizon classes derived from laboratory analysis, point observations, or soil maps. In this study, we used field estimates of soil compaction to map soil behavior to compaction at a national scale. The results from a previous study enabled clustering of six different behaviors using the in situ field observations. Mapping potential responses to soil compaction is an effective land management tool for preventing future compaction. Random forest was used to make spatial predictions of soil behavior to compaction over cultivated soils of mainland France (about 210,000 km²). Modeling was performed at 90 m resolution. The map enabled us to spatially identify clusters of possible responses to compaction. Most clusters were consistent with known geographic distributions of some soil types and properties. This consistency was checked by comparing maps with both national and local-scale external sources of soil information. The best spatial predictors were available digital maps of soil properties (clay, silt, sand, organic carbon (SOC) content, and pH), some indicators of soil structural quality using SOC and clay content, and environmental covariates (T °C and relief-related covariates). Predicted maps were interpretable to support management recommendations to mitigate soil compactness at the soil–scape scale. Simple observational field data that are usually collected by soil surveyors, then stored and available in soil databases, provide valuable input data for digital mapping of soil behavior to compaction and assessment of inherent soil sensitivity to compaction. Full article

The natural boundary is intuitively understood to be the line dividing the bed of a water body from the adjacent land. It is used in many jurisdictions to define the boundary of ownership between a land parcel and a state-owned watercourse. It is typically defined on the ground through observations by a professional surveyor. Predicting changes to the natural boundary has obvious utility (e.g., with climate change); however, its’ observational nature does not lend itself to such predictions. This paper uses a case study of a large lake to explore the relationship between shoreline morphology and hydrology, and the elevation of the natural boundary. Significant correlation was found between the natural boundary elevation and average wave power, but not with variables beach slope, sediment type, or presence of vegetation. Below 0.4 W/m of average wave power, the correlation with natural boundary elevation is very weak, suggesting a lower limit of influence. Two process-based methods for estimation of natural boundary change are proposed, one based on the observed statistical relationship between the average wave power and the natural boundary elevation, and another method based on detailed analytical modelling of bottom stress from breaking waves using the Xbeach software (v1.23). Both methods were used to estimate natural boundary change under a hypothetical change in water level regime due to proposed weir upgrades. While observational data are not available to support evaluation, both approaches predict similar changes to the natural boundary despite their significantly different basis. While the modelling approach requires significant analyst and computational effort, the parametric approach is comparatively efficient, making it practical to apply at high resolution over very large shorelines. Full article

Keeping the real estate cadastre’s database up to date is a very important process. The scope of the modernization works includes, among other things, fieldwork and office (chamber) work carried out by surveyors to update information about land and buildings. Therefore, modernization may result in changes to plot areas; changes to the marking of plots and land use (and, consequently, a change in the property tax); and the disclosure or deletion of buildings and premises, as well as changes to their technical data. The research, based on a case study (rural municipality Serniki, Poland), and supported by a literature review, remote sensing, and digital photogrammetry, clearly showed the importance of initiating the cadastre modernization procedure and obtaining funds for this purpose, which will be beneficial for both parties. Landowners will gain by bringing the current image of their real estate closer to the actual state (e.g., by paying taxes for the real utility of the land), while administrative units will become the beneficiaries of higher tax revenues (up to over 500%). Thus, the analysis carried out on the case study shows positive effects for both parties, and justifies the financial outlay incurred by the administrative units for this process. Moreover, the analysis revealed that, due to the possibility of obtaining funding from other sources, the cost to the public administration may be marginal. Thus, the cadastre modernization procedure should be integrated into regional and national policies. Full article

Deep space exploration has risen in interest among scientists in recent years, with soft landings being one of the most straightforward ways to acquire knowledge about the Moon. In general, landing mission success depends on the selection of landing zones, and there are currently few effective quantitative models that can be used to select suitable landing zones. When automatic landing zones are selected, the grid method used for data partitioning tends to miss potentially suitable landing sites between grids. Therefore, this study proposes a new engineering-constrained approach for landing zone selection using LRO LOLA-based slope data as original data based on the sliding window method, which solves the spatial omission problem of the grid method. Using the threshold ratio, mean, coefficient of variation, Moran’s I, and overall rating, this method quantifies the suitability of each sliding window. The k-means clustering algorithm is adopted to determine the suitability threshold for the overall rating. The results show that 20 of 22 lunar soft landing sites are suitable for landing. Additionally, 43 of 50 landing sites preselected by the experts (suitable landing sites considering a combination of conditions) are suitable for landing, accounting for 90.9% and 86% of the total number, respectively, for a window size of 0.5° × 0.5°. Among them, there are four soft landing sites: Surveyor 3, 6, 7, and Apollo 15, which are not suitable for landing in the evaluation results of the grid method. However, they are suitable for landing in the overall evaluation results of the sliding window method, which significantly reduces the spatial omission problem of the grid method. In addition, four candidate landing regions, including Aristarchus Crater, Marius Hills, Moscoviense Basin, and Orientale Basin, were evaluated for landing suitability using the sliding window method. The suitability of the landing area within the candidate range of small window sizes was 0.90, 0.97, 0.49, and 0.55. This indicates the capacity of the method to analyze an arbitrary range during blind landing zone selection. The results can quantify the slope suitability of the landing zones from an engineering perspective and provide different landing window options. The proposed method for selecting lunar landing zones is clearly superior to the gridding method. It enhances data processing for automatic lunar landing zone selection and progresses the selection process from qualitative to quantitative. Full article

With the advancements in remote sensing, satellite images have become a popular data modality and are widely used in many applications. Among others, satellite images are used by surveyors and engineers for urban planning and asset management, e.g., for rapidly growing cities, urban sprawl, and informal settlement. A preliminary step in satellite image analysis is identifying the regions of interest or target objects in the scene and extracting them from irrelevant objects for further processing. This image segmentation task is challenging due to various factors, e.g., occlusions, lighting conditions, and noises. To address these issues, many researchers have proposed different approaches, e.g., UNET, which is regarded as a state-of-the-art method. However, it has high memory consumption, low accuracy, and poor quality prediction when applying satellite images. Thus, we propose a multi-channel decomposition semantic segmentation method, MNET, for object classification. We used the dataset obtained by MBRSC satellites and divided the scene objects into six classes (vegetation, water, road, building, land, unused). The study area is in Dubai. We compared our approach with UNET++, U2NET, and 2D-VNET. Experimental findings show that: (1) MNET outperforms others with a mIoU score of 79.4%, whereas UNET gives 75.1%, and (2) accurate patch generation is a crucial part of the model performance, as ignoring less informative patches during training increases the accuracy by 5%. In conclusion, our proposed method offers a lightweight structure, is a computationally less expensive model, and is simple to deploy in industry applications. In this work, we conducted an extensive analysis of domain transferability, class bias, and class co-occurrence. We also compared the best and worst predictions with a number of current methods. We believe that our MNET can also benefit other domains, such as in floodwater detection using Interferometric Synthetic Aperture Radar (InSAR) data, building extraction, and crop segmentation, due to the prediction accuracy and memory consumption efficiency of MNET. Full article

Spain has a tax-oriented cadastre with legal data about properties (ownership, rights, liens, charges, and restrictions) recorded in a separate property rights registry (henceforth called land registry). This paper describes the Spanish cadastre and land registry by focusing on the new coordination system set by Law 13/2015. Since Law 13/2015 came into force in Spain, cadastral cartography is the basis for knowing where land registry units are located. The new coordination system sets a procedure to update the cadastral parcel boundary of a property when it does not match with reality. In these cases, the free-profession land surveyor sends the new property boundary through the Internet in order to update the corresponding cadastral parcel boundary. Currently, neither the cadastre nor the land registry has considered storing geographical metadata for each property boundary in a standardised way. As boundaries show the limits of individual properties, boundary metadata denote the accuracy with which such ownership rights are indicated. We propose that, for these boundary update cases, the Spanish cadastre also allows the upload of qualitative and quantitative instances of the data quality class of the Spanish Metadata Core standard, and this information be available for users, for example in an XML file. These metadata provide justified information about how the boundary has been obtained and its accuracy. Software has been developed to manage this metadata of each property boundary, in order to allow us to evaluate whether or not this information is useful. We present the conclusions about some real-life tests of property delimitations. Full article

Land surveying projects (LSPs) suffer from the effects of many risk factors on the time and accuracy of these projects. Using field surveys, the main objective of this study was identifying the major activities and risk factors associated with LSPs’ execution, as well as assessing and analyzing the effects of the risk factors on the LSPs’ time and accuracy. Furthermore, the study aimed to classify and determine the responsibility of each risk factor and evaluate the responsibilities. Four main activities were categorized and presented, including reconnaissance works, planning works, data collection works, and data adjustment works. Moreover, forty-three risk factors that control the main activities and affect the time and accuracy of LSPs were recognized. The probabilities of occurrences for the risk factors and impacts on the time and accuracy of LSPs were determined as well as their combined effects. Key risk factors that had high threats on LSPs and affect time and accuracy were highlighted as the most critical risk factors. Many correlations were determined among risk factors affecting LSPs’ activity groups and their various effects on time and accuracy. The responsibilities of the surveying crew (chief, surveyor, assistance, office engineer) for each risk factors were correspondingly defined. The results showed that “Data collection works” is considered the riskiest activity group in LSPs and most of the key risk factors belonged to this group. Around 25% of the LSPs face time overrun and do not meet the required specifications. On the other hand, the surveyor was found to be responsible for most of the risk factors and the office engineer was signified by the lowest responsibility, while the responsibilities for most risk factors were single responsibility and few were shared by only dual responsibility. Full article

We demonstrate an end-to-end application of the in-house deep learning-based surface modelling system, called MADNet, to produce three large area 3D mapping products from single images taken from the ESA Mars Express’s High Resolution Stereo Camera (HRSC), the NASA Mars Reconnaissance Orbiter’s Context Camera (CTX), and the High Resolution Imaging Science Experiment (HiRISE) imaging data over the ExoMars 2022 Rosalind Franklin rover’s landing site at Oxia Planum on Mars. MADNet takes a single orbital optical image as input, provides pixelwise height predictions, and uses a separate coarse Digital Terrain Model (DTM) as reference, to produce a DTM product from the given input image. Initially, we demonstrate the resultant 25 m/pixel HRSC DTM mosaic covering an area of 197 km × 182 km, providing fine-scale details to the 50 m/pixel HRSC MC-11 level-5 DTM mosaic. Secondly, we demonstrate the resultant 12 m/pixel CTX MADNet DTM mosaic covering a 114 km × 117 km area, showing much more detail in comparison to photogrammetric DTMs produced using the open source in-house developed CASP-GO system. Finally, we demonstrate the resultant 50 cm/pixel HiRISE MADNet DTM mosaic, produced for the first time, covering a 74.3 km × 86.3 km area of the 3-sigma landing ellipse and partially the ExoMars team’s geological characterisation area. The resultant MADNet HiRISE DTM mosaic shows fine-scale details superior to existing Planetary Data System (PDS) HiRISE DTMs and covers a larger area that is considered difficult for existing photogrammetry and photoclinometry pipelines to achieve, especially given the current limitations of stereo HiRISE coverage. All of the resultant DTM mosaics are co-aligned with each other, and ultimately with the Mars Global Surveyor’s Mars Orbiter Laser Altimeter (MOLA) DTM, providing high spatial and vertical congruence. In this paper, technical details are presented, issues that arose are discussed, along with a visual evaluation and quantitative assessments of the resultant DTM mosaic products. Full article

The value of archival documents quite often extends beyond their original purpose, as evidence contained within these artefacts, whether written or drawn, can provide veracity for new lines of heritage inquiry. Many settlements in the ‘new world’ were set out by land surveyors whose drawings charted the accurate placement and alignment of new streets and block perimeters laid upon drawings of the extant topographical landscape features. The paper discusses three settlement maps of Melbourne, Australia, through the lens of Michel de Certeau’s idea that maps are an instrument of power are not just about recording; maps are actually about appropriating and producing regimes of place. In the Australian context, the settlement drawings, prepared under the direction of the colonial administration, inadvertently depicts Country that had been under the custodial care of the First Nations peoples for millennia, and through the intentions of the settlement maps about to be irrevocably disturbed, altered or destroyed. We raise the prospect that urban and landscape design can reflect on the ‘lost landscapes’ of cultural significance, and discuss new ways of interpreting representation through an approach of design reconciliation. Full article

After the political change in Nepal of 1951, leapfrog land policy improvements have been recorded, however, the land reform initiatives have been short of full success. Despite a land administration system based on cadaster and land registries in place, 25% of the arable land with an estimated 10 million spatial units on the ground are informally occupied and are off-register. Recently, a strong political will has emerged to ensure land rights for all. Providing tenure security to all these occupants using the conventional surveying and land administration approach demands a large amount of skilled human resources, a long timeframe and a huge budget. To assess the suitability of the fit-for-purpose land administration (FFPLA) approach for nationwide mapping and registration of informality in the Nepalese context, the identification, verification and recordation (IVR) of the people-to-land relationship was conducted through two pilot studies using a participatory approach covering around 1500 and 3400 parcels, respectively, in an urban and a rural setting. The pilot studies were based on the FFPLA National Strategy and utilized satellite imageries and smartphones for identification and verification of land boundaries. Data collection to verification tasks were completed within seven months in the urban settlements and for an average cost of 7.5 USD per parcel; within the rural setting, the pilot study was also completed within 7 months and for an average cost of just over 3 USD per parcel. The studies also informed the discussions on building the legislative and institutional frameworks, which are now in place. With locally trained ‘grassroots surveyors’, the studies have provided a promising alternative to the conventional surveying technologies by providing a fast, inexpensive and acceptable solution. The tested approach may fulfill the commitment to resolve the countrywide mapping of informality. The use of consistent data model and mapping standards are recommended. Full article

Land is a scarce resource. It is usually traded as real estate, an economic good with a market value. Often, this market value is not negotiated simply between the seller and the potential buyer, but is based on an assessment performed by a professional valuer, known as a surveyor or appraiser. This article questions the economic role and the emergence of valuers in real estate markets. An institutionally embedded framework for valuation intermediation is developed that elucidates a multi-tiered imperfect information cascade. First, valuers are understood as middlemen, counteracting information uncertainties regarding product quality, namely real estate herein. An additional constraint is constituted by information asymmetries between the valuer and the contractor. The contribution presents a conceptual integration of theories of price formation (and regulation) and theories of intermediation. Investigating new institutional economics concepts considering the emergence of professional associations and the specific formal and informal regulation of nature-related transactions, the contribution then discusses how the valuation professional with regularizations evolves as a superior institutional response to this cascade of information imperfections. Full article