Land Parcels Research Articles

A hybrid modelling approach for detecting seasonal variations in inland Green-Blue Ecosystems

Deforestation, environmental pollution, and the overexploitation of resources, in addition to the Earth's natural cycles, are scaling up the impacts of climate change in the provision of Ecosystem Services (ES). Green-Blue Ecosystems (GBE) are impacted by climatic conditions, topography, and water presence. Data-driven modelling techniques may effectively capture the effects of seasonal variations while modelling natural ecosystems. This research proposes a hybrid modelling approach that combines Deep Learning and traditional Machine Learning, Sensitivity Analysis and Feature Importance Evaluation (FIE) to investigate seasonality effects on mapping GBE. The models, built using satellite imagery from the Spring and Summer seasons of the Mediterranean climate zone, included spectral indices, topography (DEM), and groundwater depth (GD). The model that best suited the analysis was selected using sensitivity tests and hyperparameter optimization. The study shows that land cover classes of transitional woodland shrubs, inland marshes, cultivated land parcels, and watercourses are better classified in the Spring, with an accuracy of 0.814. FIE indicates that spectral indices are the most important predictors for detecting green ecosystems in both seasons. Additionally, DEM and GD are the most relevant predictors to classify watercourses in the Summer. An analytical examination of the input data and hyperparameter settings facilitates understanding of models' behaviour while improving models' prediction. This research provides an advanced understanding of the effects of seasonal variations on the status of GBE and enhances understanding of modelling ES in areas with a growing need for changes in land use and high water supply demand.

The influence of farmland distribution on the performance of the agglomeration bonus

Coordination incentives like the agglomeration bonus have been proposed to induce the spatial agglomeration of biodiversity conservation efforts and counter the loss and fragmentation of species habitats. Most theoretical and empirical analyses of the agglomeration bonus make unrealistic assumptions about the spatial structure of landholdings. This paper presents a spatially explicit agent-based simulation model to explore how the spatial structure of landholdings affects the performance of the agglomeration bonus. It turns out that if the number of land parcels per landowner is large and their land is spatially cohesive, a higher proportion and agglomeration of conserved land parcels can be achieved for the given budget, implying a higher level of cost-effectiveness. This also has implications for the cost-effective design of coordination incentives. The observed effects are especially high if the conservation costs vary strongly in space.

A geospatial and archaeological investigation of an African–American cemetery in Raleigh, North Carolina, USA

AbstractOberlin Cemetery, located near downtown Raleigh, North Carolina, USA, was founded in 1873 following the American Civil War (1861–1865). This 3.2 ac (~1.29 ha) parcel of land served as the main cemetery for the people of Oberlin Village—the largest freedmen's community in Wake County. Today, descendants of the village founders and other neighbourhood residents, organized as the Friends of Oberlin Village (FOV), are preserving this community landmark and working to have its historical significance recognized. In support of these efforts, terrestrial laser scanning, global‐positioning‐system‐enabled pedestrian and ground‐penetrating radar (GPR) surveys were conducted during the winter and summer of 2016. We inventoried 276 formal grave markers identifying 221 individuals, 296 elongate depressions without a formal marker interpreted as sunken graves, and 130 fieldstones interpreted as burial markers, resulting in an estimate of 517‐to‐660 persons interred within the cemetery. The GPR survey supported the interpretation of topographic depressions as sunken graves; however, the undulating topography, as well as the density of trees and shrubs, limited this survey to ~12% of the site. Based on the birth dates listed on monuments, ~23% of these persons were born before the end of the Civil War. Death dates show the community's continued use of the cemetery throughout the early 1970s and less frequent use after that, with the most recent burials in 2009. A comparison with a 2012 inventory of monuments within Oberlin Cemetery suggests that ~3% of the markers were lost or displaced in 4 years, highlighting the importance of survey and preservation efforts. This work contributed to the FOV's successful nomination of the cemetery to the US National Register of Historic Places and was used to support several grants received for its preservation.

Geographic Element Extraction for Supporting Kota Lengkap Using Deep Learning

An indicator of accelerating the ease of investment in land registration as legal certainty and protection of property assets. Pendaftaran Tanah Sistematis Lengkap (PTSL) is an effort to quickly and accurately develop data on all land parcels, both physical and legal. The use of deep learning to speed up mapping is a concrete example of how we are entering a new era of industrial revolution. The advantage of deep learning is to speed up the process of creating a Kota Lengkap map as a manifestation of a complete Pendaftaran Tanah Sistematis Lengkap (PTSL). The limitation in the number of human resources is a significant problem in measuring the road network to realise Kota Lengkap. This can be overcome by using automation to extract the road network. An orthophoto can more accurately show the location of all visible phenomena, thus enabling precise and accurate measurements of area, distance and direction. Deep learning methods can be applied to orthophotos and LIDAR to detect topographic features such as roads or rivers. Using the deep learning method and a split ratio of 80:20, it takes a total of 11 hours 45 minutes to automatically extract road features, while for river features it takes a total of 2 hours 38 minutes, resulting in an overall accuracy of 96.15%. The automated extraction of road and river networks from orthophotos cannot yet be applied directly to planar maps, as it requires post-processing to obtain gapless polygons.

Implementation of Community-Based Surveying and Mapping of Land Parcels through Field Work Practice to Support Complete Systematic Land Registration (PTSL)

Cadastral surveying and mapping field work practice is an activity for National Land Collage (STPN) as one of the units under the Ministry of ATR/BPN to develop innovation that can be used as a basis for recommendations for the success of Complete Systematic Land Registration (PTSL). In the year of 2021, the Diploma I of Cadastral Surveying and Mapping Program carried out field work practice of cadastral surveying and mapping in Pagerharjo Village. This field work practice was designed by optimizing the Fit for Purpose Land Administration (FFP-LA) approach to accelerate the land parcel surveying and mapping process. The method used in the research underlying this article is a qualitative method to find out the extent to which the FFP concept can be implemented in land registration of Indonesia during the field work practice. The result of the field work practice shows several factors that determine the success of the land parcels surveying and mapping based on FFP-LA concepts, including the requirements of open areas for implementing photogrammetry-based measurements, the need of easily identified boundaries marker on Photo Map, the awareness of protecting property by the land owners, and the strength of legal guarantees based on the accuracy of measurements.

Synergistic exploitation of localized spectral-spatial and temporal information with DNNs for multisensor-multitemporal image-based crop classification

The challenge of performing efficient and reliable crop classification with multisensor multitemporal (MSMT) images in mixed land cover scenarios i.e. presence of small land parcels (area < 20,000-meter square) of crops and other land covers such as built-up or grasslands, is significant. Specially in countries (ex. India) where diverse crops are practiced in small land parcels. This challenge can be addressed if deep neural network (DNN) based models can exploit all three i.e. spatial, spectral, and temporal information of a crop, present in the MSMT images, efficiently and effectively. Therefore, this study presents a novel DNN based model that exploits all three information in a synergistic fashion to achieve improved crop classification. At first, the model increases the significance of local spectral information via a strategy that creates versions of spectral band set wherein neighbourhood of spectral bands is permuted. Then, the model utilizes three-dimensional convolutions, in a time-distributed fashion, to extract local spectral-spatial features. Finally, the model utilizes bidirectional long short-term memory or LSTM-RNNs to extract the temporal information embedded in the time-distributed feature-space created after the convolutions. The developed model is trained and evaluated on Sentinel-1 and Sentinel-2 MSMT data to achieve a 6-class classification including two major crops grown in the region. One of the proposed models namely Perm-3D-CRNN-v1 showed a 97.77 % overall accuracy on test samples and reflected satisfactory on quantitative analysis. The localized spectral-spatial convolutions created prominent class-specific features whereas the bidirectional information flow in the recurrent layer improved the exploitation of crop-phenology type features making the model perform efficiently.

PENDAFTARAN TANAH SISTEMATIS LENGKAP (PTSL) BERDASARKAN PERATURAN MENTERI AGRARIA DAN TATA RUANG/KEPALA BADAN PERTANAHAN NASIONAL REPUBLIK INDONESIA NOMOR 35 TAHUN 2016 DI WILAYAH LOMBOK TIMUR

Most of the land parcels in East Lombok Regency have not been registered, the basis of rights used by land rights holders as proof of land ownership is only in the form of continuous and hereditary. Therefore, it is necessary to formulate a problem, namely how to implement a complete systematic land registration in East Lombok Regency. The research method used is empirical law with three approaches, namely: statutory approach, conceptual approach and sociological approach. In its implementation, the Complete Systematic Land Registration (PTSL) program in Selong District, East Lombok Regency refers to the provisions in PERKABAN Number 1 of 2017 concerning Amendments to PERKABAN Number 35 of 2016 concerning the Acceleration of the Implementation of Complete Systematic Land Registration and PERKABAN Number 37 / Kep-7.1 / I / 2017 concerning Technical Guidelines for Complete Systematic Land Registration where there are several stages in the implementation of the PTSL starting from Preparation (socialization, location determination, manpower planning and formation of an accelerated adjudication committee, training), counseling, juridical data collection, juridical data processing and proof of rights, land inspection, announcement, ratification, issuance of rights determination decrees and rights affirmation/recognition decisions, rights bookkeeping, issuance and submission of certificates, management of warrants/documents and reporting.

University Land Grabs: Indigenous Dispossession and the Universities of Toronto and Manitoba

Whether leased or sold, Indigenous land provided the endowment capital for new universities in the nineteenth century. Many institutions of higher learning – including the universities of Toronto and Manitoba – began as large-scale landowners. By 1828, Toronto’s university still held more than two hundred thousand acres of land, an area larger than the present-day city of Toronto. The extent of university landholding in settler societies, however, has often been missed because the land parcels assigned to universities were both larger than, and distinct from, their campuses. This article accordingly examines how landholding undergirded Canadian universities’ development in the nineteenth century, taking the University of Toronto and the University of Manitoba as its focus. It argues that land was the essential ingredient in university building in both Ontario and Manitoba, linking these new universities’ establishment and subsequent wealth to Indigenous dispossession. Using Indigenous land to finance higher education was not unique to these universities nor to Canada. Yet, across settler societies, university landholding made institutions of higher education the beneficiaries of Indigenous removal and agents of colonization. In addition, once in operation, these new universities would also produce knowledge about land and its cultivation. Inspired by the growing field of European agricultural science, Canadian universities with land endowments professionalized the study of branches of knowledge like agriculture and engineering, displacing Indigenous ways of being and thinking about land. The effect of this knowledge valuation is still felt today. The products of university agricultural research – from nitrogen fertilizers to hybridized corn – profoundly transformed landscapes and altered local ecologies in line with settler knowledge systems and desires.

Urban Revitalization as a vision for the future? : A Comparative Study of Small- Scale Interventions of Hong Kong and Taiwan

As many cities undergo urban revitalization, spatial decision-makers disregarding urban vitality has resulted in numerous adverse outcomes. While some cities opt for large-scale development of new districts, others infuse vitality into aging neighbourhoods through small-scale projects. These latter efforts face considerable constraints, including preserving historical continuity, respecting historical landscapes, and accommodating irregular land parcels. However, such initiatives also present opportunities to invigorate cities. Well-organized urban spaces often prioritize macro-level geometric order, overlooking the nuanced internal order that shapes human activities and finer-grained spatial structures. This study focuses on the crucial elements that can steer revitalization efforts toward a virtuous cycle without disrupting existing social networks. Employing qualitative research methods, including case studies and interviews, this study will extend the examination of urban revitalization in highly urbanized East Asian cities, highlighting strategies that respect and harness historical, spatial, and social complexities to foster sustainable urban vitality.

Mapping Urban Flood-Prone Areas’ Spatial Structure and Their Tendencies of Change: A Network Study for Brazil’s Porto Alegre Metropolitan Region

Historically, the main cause of urban disasters in Brazil is flooding events, which are becoming more recurrent due to climate changes and intensive urbanization, causing extensive infrastructure, economic and life losses. The formation of Brazilian Metropolitan Areas goes back to the early twentieth century, with urban expansion following river basins, as regional transportation relied on inland navigation. The transition to road-based transport structured further urban sprawl from the mid-twentieth century onward, as road-circulation axes expanded across flood-prone areas. Mapping those hydrogeological risks is important to understand their effect on the existent road-circulation network structure cohesiveness. From the hydrogeological risk assessment data, this article evaluates potential changes imposed by extreme flood events on the road infrastructure at municipal and metropolitan scales. Space Syntax methods applied to an empirical case – the Porto Alegre Metropolitan Region – allow for comparative analyses between the urban network of current and flooding-event simulations and depict (a) the urban grids’ structural transformations under flooding, (b) the road elements at risk, and (c) the system’s spatial integrity and circulation disruptions. The resulting cartography can subside governance and urban planning strategies to cope with floodings at different territorial scales, addressing changes on local–regional circulation patterns, system breaking points and tendencies of urban land parcelling on vulnerable areas.

Tumpang Tindih Sertifikat Tanah

Overlapping land certificates (Overlapping) is a situation where there are land parcels that overlap with other land parcels and there are multiple certificates for the same land parcel. This study aims to determine the causes of overlapping land certificates (overlapping) both in terms of internal factors and external factors and legal remedies for settlement and future legal remedies to overcome overlapping land certificates (overlapping). This research uses empirical juridical methods or research in the field that examines the implementation or implementation of applicable legal provisions and facts that occur in society. Data collection was carried out by field studies. Data analysis was carried out using qualitative analysis methods and using a qualitative approach. The results of this study indicate that the causes of overlapping certificates (overlapping) are digitalization and also a lack of land maintenance by the community. The legal effort that can be taken to resolve the dispute is by canceling the certificate which of course has gone through several stages of the process and the future legal action is to routinely conduct outreach to certificate holders and the Ministry of Agrarian Affairs/BPN will immediately carry out electronic certificates in order to reduce overlapping land certificates (overlapping).

Nationwide indicators reflecting the current problems of the agricultural landscape in Slovakia: large agricultural parcels, farm size structure and share of woody vegetation

The main problems of the agricultural landscape in Slovakia are the largest parcels in the EU, the share of agricultural land managed by large agro-holdings, and the low proportion of woody vegetation. The authors have analysed these issues using agricultural beneficiary data and remote sensing products. The parcel size and farm sizes were analysed from agricultural beneficiaries’ data, woody vegetation was analysed from the combined layer of Copernicus products and data from the Land Parcel Identification System. Regarding all three indicators, the situation is more problematic in the lowlands and partially in hilly areas. The proposed indicators could be applied to assess the impact of the new CAP (2023-2027), which supports the reduction of parcel size, improves conditions for small and medium farmers, and improves the share of green infrastructure in agricultural landscapes.

A conceptual framework for automatic modelling and conflict detection of 3D land-use regulation restrictions to support issuing planning permits

There are a wide variety of Land-use Regulation (LuR) restrictions, ranging from those that need simple 2D spatial analyses to be verified (e.g., area calculation), to those that need complex 3D analyses (e.g., overshadowing and overlooking). Assessing LuR restrictions to automatically detect LuRs’ potential conflicts with physical objects, such as building elements, could be a challenging task in 2D land administration systems relying on 2D drawings and 2D representations, especially when 3D/vertical analyses are required. Land administration systems can include 3D representations of LuR restrictions to identify their impacts on land parcels and vice versa since the LuRs contain legally binding restrictions for all parties including governments and citizens. As part of the transition from the 2D representation of LuR restrictions and manual conflict detection between LuR restrictions and physical objects such as building elements towards a 3D digital representation and automatic conflict detection, this paper proposes a three-stage conceptual framework for automatic 3D modelling and conflict detection of 3D LuR restrictions. The three-stage conceptual framework, as a generic approach, proposes required principles and procedures to automatically (1) model 3D LuR restrictions (called 3D CityLuR), (2) combine them with other sources of information (e.g., zoning maps, 3D city models, and BIM), and (3) detect LuRs’ potential conflicts between the modelled LuRs and physical objects (i.e., proposed/existing building elements). For modelling and verifying 3D LuRs automatically, the framework organises all the required information for IFC (Industry Foundation Classes) as the proposed building, CityGML as the existing buildings, and most importantly, the planning and zoning requirements. It proposes two categories of required information as “level of information need” for (1) modelling and combing 3D CityLuR with other sources of information automatically and (2) automatically detecting potential spatio-semantic conflicts between LuR restrictions and physical objects such as proposed/existing building elements. Based on a case study in Victoria, Australia, 3D LuR restrictions subject to planning approvals and building subdivisions are investigated. The paper concludes with a discussion arguing the feasibility of automating the verification of LuR restrictions to support decision-making in planning permit applications and building subdivisions.

SatelliteSkill5—An Augmented Reality Educational Experience Teaching Remote Sensing through the UN Sustainable Development Goals

Advances in visualisation techniques provide new ways for us to explore how we introduce complex topics like remote sensing to non-specialist audiences. Taking inspiration from the popularity of augmented reality (AR) apps, a free, mobile digital AR app titled SatelliteSkill5, has been developed for both Androids and iPhones in Unity AR. SatelliteSkill5 helps users conceptualise remote sensing (RS) theory and technology by showcasing the potential of datasets such as multispectral images, SAR backscatter, drone orthophotography, and bathymetric LIDAR for tackling real-world challenges, with examples tackling many of the United Nations’ Sustainable Development Goals (SDGs) as the focus. Leveraging tried and tested pedagogic practices such as active learning, game-based learning, and targeting cross-curricular topics, SatelliteSkill5 introduces users to many of the fundamental geospatial data themes identified by the UN as essential for meeting the SDGs, imparting users with a familiarity of concepts such as land cover, elevation, land parcels, bathymetry, and soil. The SatelliteSkill5 app was piloted in 12 Irish schools during 2021 and 2022 and with 861 students ranging from 12 to 18 years old. This research shows that both students and teachers value learning in an easy-to-use AR environment and that SDGs help users to better understand complex remote sensing theory.

The German Verkehrswert (market value) of land: Statutory land valuation, spatial planning, and land policy

In Germany, statutory land valuation has developed over the course of almost 60 years into a powerful tool of spatial planning and land policy. The key to statutory land valuation is the concept of Verkehrswert (market value). The Verkehrswert equals the likely selling price of a cadastral parcel of land in the usual course of business at the time of valuation, and considers the legal situation, the actual disposition of the parcel, any other relevant conditions, and the location of the land, but does not take into account unusual or personal circumstances. The article explains the elements of Verkehrswert (market value) which account for the plural values of land such as exchange value, use value, territorial value, and existence value. The German Verkehrswert is not merely an instrument of plan implementation (e.g., land readjustment or compensation for expropriation), but also an analytical tool that helps planners and land policymakers understand when their interventions in land markets are necessary and how they can be helpful.

Double Certificates and Its Resolution in (Study of Supreme Court Decision Number 976 K/PDT/2015)

One of the goals of the Basic Agrarian Law (Undang-Undang Pokok Agraria, UUPA) is to provide legal certainty for all individuals and to facilitate the functioning of the earth, water, and space, as well as natural resources. In reality, however, the law has not yet provided legal certainty over land in the case of double certificates, as stated in Supreme Court Decision No. 976 K/PDT of 2015. The problem posed by this study is how and what the obstacles are for prevent the development of duplicate certificates. This is normative legal research employing secondary data, the statute approach, and the conceptual approach. To prevent the occurrence of double certificates, it is necessary to implement a computerization/digitization program for land registration maps to reduce error by humans, acquire data on land parcels that have certificates, make plotting efforts utilizing GPS (Global Positioning System) technology, restrict the land registration process and administration pertaining to village land, and implement blockchain technology in land administration. Meanwhile, the public's lack of interest in registering their land through the Comprehensive Systematic Land Registration (Pendaftaran Tanah Sistematis Lengkap, PTSL) scheme, procedural errors in the land assessment procedure, a negative land publication system in which the data presented is not necessarily valid, and the state's inability to guarantee the accuracy of the data presented are impediments to these efforts. Moreover, the present agrarian law is a colonialist relic that is not in the community's best interests.

The promising future of developing large-scale PV solar farms in China: A three-stage framework for site selection

Large-scale Photovoltaics (PV) play a pivotal role in climate change mitigation due to their cost-effective scaling potential of energy transition. Consequently, selecting locations for large-scale PV power plants has gained worldwide prominence in recent decades. Although massive studies have examined various siting criteria, land consolidation and cost-benefit feasibility issues are not often included due to the lack of a comprehensive and discretionary decision-making system. In this study, we introduced a three-stage framework combining DBSCAN clustering and cost-benefit analysis to identify the most efficient and cost-effective land parcels. The results indicate that while a total area of 425,191 km2 is considered developable for PV installation in China, only 23% of that area (128,588 km2) are consolidated land parcels which are suitable for developing large-scale PV power plants. Moreover, the potential of these consolidated land parcels (8,289,662 gWh/year) can supply about 90% of China's electricity demand. However, when considering the infrastructure investment per kWh, high-potential land parcels doubled the moderate-potential ones. These results emphasize the importance of large-scale PV plant siting as it impacts the efficiency of PV integration and the optimal land use. Hence, this methodology equips decision-makers with a practical and efficient tool for economically developing large-scale solar PV.

Local Climate Zone in Xi’an City: A Novel Classification Approach Employing Spatial Indicators and Supervised Classification

The Local Climate Zone (LCZ), as a foundational element of urban climate zone classification proposed by Oke and Stewart, categorizes urban surface types based on 10 influential parameters affecting the urban heat island effect, such as building density, surface reflectivity, sky view factor, and surface roughness length. This method divides cities into 17 different Local Climate Zones (LCZs) to standardize climate observations and promote global climate research exchange, offering valuable insights for heat island studies. In this study, we enhance the existing local climate zones spatial classification approach by focusing on Xi’an city’s urban layout and architectural features. By using urban spatial indicators and employing a supervised classification approach and a spatial clustering method with land parcels as statistical units, we investigate typical urban areas and classify Xi’an’s land parcels into 17 or 15 distinct local climate zones. Subsequently, through the evaluation of two distinct classification methods, the most suitable urban microclimate zoning method for Xi’an city was selected. This optimization of the local climate zoning representation introduces a spatial classification method tailored to urban climate planning and control, utilizing urban spatial indicators and remote sensing data. The resulting urban climate zoning map not only supports sample selection for urban heat environment parameter observation but also aids urban planners in identifying spatial distribution patterns for climate zoning.

Research on CLUFS and Its Application in Rapid Prediction of the Impact of Regulating Services Value in Construction Projects

With the development of human society and the acceleration of urbanization, the impact of construction projects on the ecological environment is increasingly attracting attention. Conducting an ecological environmental impact assessment of construction projects is crucial to protect the ecological environment and achieve sustainable development. To estimate how construction projects would affect the value of ecosystem services, this paper develops the China Land Use Feature Data Sets (CLUFS) and uses the Beijing “One Line Four Mines” project as an example. Research found that the project’s conservation and restoration zone and the landscape construction zone will significantly enhance the ecosystem regulation services value. The conservation and restoration zone will increase by 30% from the current 1.413 billion yuan per year to 1.836 billion yuan per year, and the landscape construction zone will increase by 69% from the current 400 million yuan per year to 676 million yuan per year. The tourism development zone, dominated by urban construction, will result in a decrease in ecosystem regulation services, from 19.26 million yuan per year to 17.60 million yuan per year by 9%. Overall, the “One Line Four Mines” project achieved a balance of ecological value and surplus. The method proposed in this paper for predicting the impact of ecosystem regulation services value on construction projects can be used to quickly evaluate the effects of different planning schemes on the ecosystem services value of land parcels to help urban planning decision-makers control the condition of land use. It can provide new indicators for the ecological environment department to incorporate ecological benefits into the evaluation system of planning schemes and new methods for evaluating the ecological protection effectiveness of projects.

Green Infrastructure and Urban Vacancies: Land Cover and Natural Environment as Predictors of Vacant Land in Austin, Texas

Urban vacancies have been a concern for neighborhood distress and economic decline and have gained more recent attention as potential green infrastructure is known to benefit communities in diverse ways. To investigate this, this study looked into the relationship between land cover, natural environment, and urban vacancies in Austin, Texas. Additionally, we investigated the spatial patterns of green infrastructure and urban vacancies by different income groups to see if low income communities would potentially lack the benefits of green infrastructure. To measure green infrastructure, we used different land covers such as forests and shrublands, as well as natural environments such as tree canopies and vegetation richness, using remote sensing data. Urban vacancy information was retrieved from the USPS vacant addresses and parcel land uses. Through a series of multivariate analyses examining green infrastructure variables one by one, the study results indicate that green infrastructure interacts with residential and business vacancies differently. Additionally, low-income communities lack green infrastructure compared with the rest of the city and are exposed to more urban vacancies in their neighborhoods. Further study is required to understand the dynamics of vacancies in underserved communities and examine how existing vacant land can benefit the communities as ecological resources.