Land Parcels Research Articles

Integrating agricultural land suitability and farmers' perception on crop selection in a water-stressed region of eastern India

CONTEXTThe choice of crops for cultivation should be ideally based on the appropriateness of a specific parcel of land for a particular crop. This is a multi-criteria problem associated with a host of natural conditioning variables including topography, climate and pedology. However, in a country like India, where agriculture is often traditional and subsistence-based, the farmers' choice of crop selection is usually influenced by numerous factors and therefore, may not be explained solely by the spatial variation in the agricultural land suitability. OBJECTIVEThis study is an attempt to understand the intricacies involved in the farmers' selection of crops by integrating the dual aspects of agricultural land suitability and the farmers' understanding of the land. The Kumari River Basin in eastern India has been selected for this study. This area is characterized by acute scarcity of water. METHODSThe basic methodology involved extracting systematic information on conditional factors such as topography, climate and soil. After normalizing different parameters by the Fuzzy Membership Function, a reiterative Principal Component Analysis modified Analytical Hierarchy Process was applied to these conditional rasters to derive an index of agricultural land suitability of the studied basin. Furthermore, the crop-specific suitability of paddy and maize was also considered by employing the Boolean Logic. RESULTS AND CONCLUSIONSIt is observed that the lower domain of the Kumari Basin is characterized by greater land suitability as compared to the upper and middle domains and the most important factors behind this distribution include slope, potential evapotranspiration and soil fertility. Crop-specific land suitability suggests that, by and large, the suitability of maize is greater than that of paddy in the basin, except for the lower domain where paddy is more suitable to cultivate. However, a study of the perception of the local farmers reveals that although they are aware of this fact, they prefer paddy over maize and are more inclined towards cultivating paddy. The chief reasons cited by them include the high demand for paddy in the area and the absence of a Minimum Support Price for maize. SIGNIFICANCEThis study is possibly an instance where the agricultural land suitability analysis has been substantiated by a field-based perception survey of the farmers which is expected to help in understanding the complexities of crop selection in this part of India.

Impact of Tree Geometry on the Growth and Yield Performance of Black Gram (Vigna mungo L.) under Kadam (Neolamarckia cadamba Roxb.) based Agroforestry System

Agroforestry is an environmentally conscious and comprehensive method of land management that entails cultivating agricultural crops, forest trees, and animals in conjunction on the same parcel of land through the implementation of suitable management strategies. The present study entitled “Impact of tree geometry on the growth and yield performance of Black Gram (Vigna mungo L.) under Kadam (Neolamarckia cadamba Roxb.) based Agroforestry System” was conducted during the Kharif season of 2022-23 within an already established 2-year-old plantation situated at Forestry research farm, RLBCAU, Jhansi. The study encompasses three different spacings, i.e., S1- 5 m x 5 m, S2- 5 m x 4 m and S3- 5 m x 3m. A randomized block design having four treatments each replicated five times was laid out, Outcomes of research revealed that sole cropping of black gram exhibited higher plant height (77.44 cm), leaf and branch numbers (6.38 and 5.32, respectively), dry matter accumulation (17.05 g/plant for above-ground and 2.12 g/plant for below-ground), leaf area (2183.06 cm2), root nodules (11.54), shorter phenological duration viz., 50% flowering, 50% pod setting and maturity (40.11 days, 54.49 days, and 70.84 days, respectively). It also demonstrated significantly higher yield attributes such as number of pods and seeds per pod (27.28), number of seeds per pod (5.82), test weight (36.73 g), grain yield (0.79 t ha-1), straw yield (1.78 t ha-1), biological yield (2.57 t ha-1), harvest index (30.63 %), and grain-to-straw ratio (0.44) compared to the intercropped. Among all the agroforestry treatments Neolamarckia cadamba at 5 m × 5 m with Vigna mungo, found to perform better than closer spacing (i.e., 5 m x 4 m and 5 m x 3 m) spatial arrangements. The study encountered challenges in achieving an optimal balance between tree-crop interactions and resource competition, which are critical factors in agroforestry systems. Nevertheless, it provides significant contributions by offering insights into the optimization of tree geometry, enhancing both yield performance and the sustainability of such integrated systems.

Urban Renovation from Precarious to Sustainable Districts: Study Case of Mvog-Ada in Yaounde

This article explores the possibility of transforming precarious neighbourhoods, commonly known as slums, into good-living and environmentally- friendly places by rethinking their layout. It examines the state of the study case and highlights the relationships between the road system, parcels of land and other components of the urban fabric, with the aim of resolving the problems caused by the poor occupation of urban space and the lack of architectural knowledges and basic infrastructure necessary for people's lives in Cameroon. This research addresses the problems of anarchic urbanisation, urban densification and unhealthy living conditions, it proposes concrete solutions for decongesting the area, strategically redeveloping the space and ensuring the sustainable development of the site, while incorporating a biomimetic and circular approach. To achieve this goal, it was important to put in place a renovation strategy that is both up-to-date and adapted to the local context. With this in mind, this work presents a comprehensive and innovative master plan designed to solve the problems of development, bad urban traffic and degradation of the area through the use of an appropriate methodology of sustainable urban planning. Finally, the concept of sustainable district is presented as a pillar of the development of precarious districts and as an opportunity of growth for the development of their country.

Research on Complete Coverage Path Planning of Agricultural Robots Based on Markov Chain Improved Genetic Algorithm

Due to the limitations of low coverage, high repetition rate, and slow convergence speed of the basic genetic algorithm (GA) in robot complete coverage path planning, the state transition matrix of the Markov chain is introduced to guide individual mutation based on the genetic mutation path planning algorithm, which can improve the quality of population individuals, enhancing the search ability and convergence speed of the genetic algorithm. The proposed improved genetic algorithm is used for complete coverage path planning simulation analysis in different work areas. The analysis results show that compared to traditional genetic algorithms, the improved genetic algorithm proposed in this paper reduces the average path length by 21.8%, the average number of turns by 6 times, the repetition rate by 83.8%, and the coverage rate by 7.76% in 6 different work areas. The results prove that the proposed improved genetic algorithm is applicable in complete coverage path planning. To verify whether the Markov chain genetic algorithm (MCGA) proposed is suitable for agricultural robot path tracking and operation, it was used to plan the path of an actual land parcel. An automatic navigation robot can track the planned path, which can verify the feasibility of the MCGA proposed.

Herd-Level Risk Factors Associated with Mycoplasma bovis Serostatus in Youngstock on Irish Dairy Farms.

Mycoplasma bovis is a globally significant pathogen of cattle associated with a wide range of clinical syndromes, including respiratory disease, mastitis, arthritis, otitis, and reproductive failure. Since its detection in Ireland in 1994, M. bovis has become a significant contributor to morbidity and mortality in Irish cattle. This study aimed to investigate herd-level risk factors associated with M. bovis seropositivity in replacement dairy heifers, using data from 105 Irish dairy herds. Ten heifers per herd were sampled on three occasions: spring 2018, spring 2019, and autumn 2019. Seropositivity was evaluated using two thresholds: ≥1 positive heifer (Model ≥ 1POS) and ≥3 positive heifers (Model ≥ 3POS). M. bovis seropositivity varied over time, with at least one positive heifer in 50.4% (95% confidence interval (CI): 40.5-60.3) of herds in spring 2018, 35.2% (95% CI: 26.2-45.1) in spring 2019, and 45.7% (95% CI: 36.0-55.7) in autumn 2019. Herds with three or more positive heifers increased from 31.4% (95%CI: 22.7-41.2) in spring 2018 to 42.9% (95% CI: 33.2-52.9) by autumn 2019. Risk factors for M. bovis seropositivity included the purchase of cattle, which significantly raised the odds of seropositivity across multiple visit periods (Model ≥ 1POS: Odds ratio (OR) 3.84, p = 0.02; Model ≥ 3POS: OR 3.69, p = 0.02). Managing more than three land parcels, housing heifer calves separately from bull calves, and sharing airspace between calves and older animals also increased seropositivity risks. Conversely, more colostrum feeds reduced the risk of seropositivity (Model ≥ 1POS: OR 0.81, p = 0.05), while colostrum quality assessment and feeding waste milk showed a trend toward increased risk. These findings suggest the importance of robust biosecurity measures, including limiting cattle purchases, improving calf management, and enhancing colostrum feeding practices, to control the spread of M. bovis. This study provides valuable insights into the epidemiology of M. bovis in Irish dairy herds, emphasising the need for targeted biosecurity and surveillance to safeguard herd productivity.

Permanent pastures identification in Portugal using remote sensing and multi-level machine learning

IntroductionThe Common Agricultural Policy (CAP) is a vital policy framework implemented by the European Union to regulate and support agricultural production within member states. The Land Parcel Identification System (LPIS) is a key component that provides reliable land identification for administrative control procedures. On-the-spot checks (OTSC) are carried out to verify compliance with CAP requirements, typically relying on visual interpretation or field visits. However, the CAP is embracing advanced technologies to enhance its efficiency.MethodsThis study focuses on using Sentinel-2 time series data and a two-level approach involving recurrent neural networks (RNN) and convolutional neural networks (CNN) to accurately identify permanent pastures.ResultsIn the first step, using RNN, the model achieved an accuracy of 68%, a precision of 36%, a recall of 97% and a F1-score of 52%, which indicates the model’s ability to identify all the true positive parcels (correctly identified permanent pasture parcels) and minimize the false negative parcels (non-identified permanent pasture parcels). This occurs due to the difficulty in distinguishing between permanent pastures and other similar land covers (such as temporary pastures and shrublands). In the second step, it was possible to distinguish the permanent pasture parcels from the others. The obtained results improved significantly from the first to the second step. Using CNN, an accuracy of 93%, a precision of 89%, and a recall of 98% were achieved for the “Permanent pasture” class. The F1-score was 94%, indicating a balanced measure of the model’s performance.DiscussionThe integration of advanced technologies in the CAP’s control mechanisms, as demonstrated, has the potential to automate the verification of farmers’ declarations and subsequent subsidy payments.

Applying portfolio theory to benefit endangered amphibians in coastal wetlands threatened by climate change, high uncertainty, and significant investment risk

The challenge of selecting strategies to adapt to climate change is complicated by the presence of irreducible uncertainties regarding future conditions. Decisions regarding long-term investments in conservation actions contain significant risk of failure due to these inherent uncertainties. To address this challenge, decision makers need an arsenal of sophisticated but practical tools to help guide spatial conservation strategies. Theory asserts that managing risks can be achieved by diversifying an investment portfolio to include assets – such as stocks and bonds – that respond inversely to one another under a given set of conditions. We demonstrate an approach for formalizing the diversification of conservation assets (land parcels) and actions (restoration, species reintroductions) by using correlation structure to quantify the degree of risk for any proposed management investment. We illustrate a framework for identifying future habitat refugia by integrating species distribution modeling, scenarios of climate change and sea level rise, and impacts to critical habitat. Using the plains coqui (Eleutherodactylus juanariveroi), an endangered amphibian known from only three small wetland populations on Puerto Rico’s coastal plains, we evaluate the distribution of potential refugia under two model parameterizations and four future sea-level rise scenarios. We then apply portfolio theory using two distinct objective functions and eight budget levels to inform investment strategies for mitigating risk and increasing species persistence probability. Models project scenario-specific declines in coastal freshwater wetlands from 2% to nearly 30% and concurrent expansions of transitional marsh and estuarine open water. Conditional on the scenario, island-wide species distribution is predicted to contract by 25% to 90%. Optimal portfolios under the first objective function – benefit maximization – emphasizes translocating frogs to existing protected areas rather than investing in the protection of new habitat. Alternatively, optimal strategies using the second objective function – a risk-benefit tradeoff framework – include significant investment to protect parcels for the purpose of reintroduction or establishing new populations. These findings suggest that leveraging existing protected areas for species persistence, while less costly, may contain excessive risk and could result in diminished conservation benefits. Although our modeling includes numerous assumptions and simplifications, we believe this framework provides useful inference for exploring resource dynamics and developing robust adaptation strategies using an approach that is generalizable to other conservation problems which are spatial or portfolio in nature and subject to unresolvable uncertainty.

Evaluation of the urban heat island effect based on 3D modeling and planning indicators for urban planning proposals

ABSTRACT Urban planning plays an important role in the formation of urban space and microclimate. As a middle-level planning in the Chinese urban planning system, regulatory planning has a direct impact on the shaping of 3D urban space and can maximize the operability of urban planning. However, 3D space formation is not considered in the present preparation of regulatory plans, which leads to a misunderstanding of possibly formed 3D landscapes and microclimatic effects after the plan implementation. To support 3D visualization and quantitative analysis of the urban heat island effect (UHI) for regulatory planning, this study proposes a rule-based 3D modeling method to efficiently generate 3D models. The main elements of 3D models (terrain, building, road, vegetation, and land parcel) and their content were determined after analyzing the characteristics of 3D models in the regulatory plan. The 3D modeling process was constructed and combined with an UHI evaluation model through CGA programming. An index called heat island potential (HIP) was used as the UHI evaluation index and can be quantified using the correlation equations between planning indicators and HIP. The proposed method can support the planners to generate 3D models for a planning proposal, and simultaneously analyze 3D spatial effect and UHI.

A land parcel segmentation method for remote-sensing images based on an improved U-Net network

A land parcel segmentation method for remote-sensing images based on an improved U-Net network

Cadastral-to-Agricultural: A Study on the Feasibility of Using Cadastral Parcels for Agricultural Land Parcel Delineation

Agricultural land parcels (ALPs) are essential for effective agricultural management, influencing activities ranging from crop yield estimation to policy development. However, traditional methods of ALP delineation are often labor-intensive and require frequent updates due to the dynamic nature of agricultural practices. Additionally, the significant variations across different regions and the seasonality of agriculture pose challenges to the automatic generation of accurate and timely ALP labels for extensive areas. This study introduces the cadastral-to-agricultural (Cad2Ag) framework, a novel approach that utilizes cadastral data as training labels to train deep learning models for the delineation of ALPs. Cadastral parcels, which are relatively widely available and stable elements in land management, serve as proxies for ALP delineation. Employing an adapted U-Net model, the framework automates the segmentation process using remote sensing images and geographic information system (GIS) data. This research evaluates the effectiveness of the proposed Cad2Ag framework in two U.S. regions—Indiana and California—characterized by diverse agricultural conditions. Through rigorous evaluation across multiple scenarios, the study explores diverse scenarios to enhance the accuracy and efficiency of ALP delineation. Notably, the framework demonstrates effective ALP delineation across different geographic contexts through transfer learning when supplemented with a small set of clean labels, achieving an F1-score of 0.80 and an Intersection over Union (IoU) of 0.67 using only 200 clean label samples. The Cad2Ag framework’s ability to leverage automatically generated, extensive, free training labels presents a promising solution for efficient ALP delineation, thereby facilitating effective management of agricultural land.

Spatially Explicit Analysis of Landscape Structures, Urban Growth, and Economic Dynamics in Metropolitan Regions

Assuming that settlement morphologies and landscape structures are the result of economic transformations, the present study illustrates a statistical framework investigating metropolitan growth due to the inherent changes in landscape configurations vis à vis socio-demographic functions. Focusing on the evolution of their spatial drivers over time, metropolitan development was studied by adopting land parcels (or ‘patches’, as they are referred to in the ecological literature) as the elementary analysis unit—with the individual surface area and a specific shape indicator as the dependent variables and background socioeconomic attributes as predictors of landscape change over time. We specifically ran a Multiscale Geographically Weighted Regression (MGWR) testing the spatial dependence of the size and shape of landscape parcels on a vast ensemble of socioeconomic factors in a dense region (metropolitan Athens, Greece) with natural landscapes exposed to increasing human pressure. To investigate the spatial direction and intensity of the settlement expansion and landscape change, local regressions using the parcel area and fractal index (perimeter-to-area ratio) as the dependent variables and the elevation, distance from selected economic nodes, transport infrastructures, and natural amenities as the predictors were run separately for 1990 and 2018, representative of, respectively, a mono-centric configuration and a moderately polycentric organization of economic spaces. In a strictly mono-centric setting (1990), the parcel size showed a linear dependence on the distance from business districts, elevation, and wealth. Changes in the relationship between the parcel size and spatial (economic and non-economic) drivers may suggest a latent process of settlement de-concentration, and a possible shift toward polycentric development (2018), as documented in earlier studies. By integrating socioeconomic and ecological dimensions of landscape analysis and land evaluation, the empirical results of this study outline the increased complexity of dispersed landscape structures within dense metropolitan regions and along urban–rural gradients in Europe.

Research on the Correlation between the Dynamic Distribution Patterns of Urban Population Density and Land Use Morphology Based on Human–Land Big Data: A Case Study of the Shanghai Central Urban Area

The dynamic distribution of urban population density and the interaction with land use elements involve mutual constraints and guidance. However, in the existing research on the relationship between urban population density and land use, the discussion on the distribution patterns of urban population density typically spans long time periods and uses large spatial units, lacking analysis of the dynamic changes in population density within high granularity land parcels over a day. In studies related to the urban built environment, the complex relationships between different-dimensional land use elements and the dynamic distribution of population density also need further exploration. To address these bottlenecks, this study takes Shanghai’s central urban area as an example. Based on 24 h mobile signaling data on weekdays, weekends, and typical holidays, as well as urban land use data, clustering algorithms are used to summarize patterns of dynamic population density distribution. Pearson correlation analysis is then employed to study the correlation between dynamic population density distribution patterns and different land use elements. The results indicate that various urban land use factors such as locational centrality, functional diversity, transportation accessibility, compactness, and landscape quality have different impacts on the dynamic distribution of population density in spatial units, and the dynamic distribution patterns of population density in different land use types also vary. This research contributes to guiding the optimization of spatial quality and formulating planning and management measures that more effectively match construction intensity with population activity density.

Segment Anything Model Combined with Multi-Scale Segmentation for Extracting Complex Cultivated Land Parcels in High-Resolution Remote Sensing Images

Accurate cultivated land parcel data are an essential analytical unit for further agricultural monitoring, yield estimation, and precision agriculture management. However, the high degree of landscape fragmentation and the irregular shapes of cultivated land parcels, influenced by topography and human activities, limit the effectiveness of parcel extraction. The visual semantic segmentation model based on the Segment Anything Model (SAM) provides opportunities for extracting multi-form cultivated land parcels from high-resolution images; however, the performance of the SAM in extracting cultivated land parcels requires further exploration. To address the difficulty in obtaining parcel extraction that closely matches the true boundaries of complex large-area cultivated land parcels, this study used segmentation patches with cultivated land boundary information obtained from SAM unsupervised segmentation as constraints, which were then incorporated into the subsequent multi-scale segmentation. A combined method of SAM unsupervised segmentation and multi-scale segmentation was proposed, and it was evaluated in different cultivated land scenarios. In plain areas, the precision, recall, and IoU for cultivated land parcel extraction improved by 6.57%, 10.28%, and 9.82%, respectively, compared to basic SAM extraction, confirming the effectiveness of the proposed method. In comparison to basic SAM unsupervised segmentation and point-prompt SAM conditional segmentation, the SAM unsupervised segmentation combined with multi-scale segmentation achieved considerable improvements in extracting complex cultivated land parcels. This study confirms that, under zero-shot and unsupervised conditions, the SAM unsupervised segmentation combined with the multi-scale segmentation method demonstrates strong cross-region and cross-data source transferability and effectiveness for extracting complex cultivated land parcels across large areas.

Towards a more realistic estimation of urban land take by combining cadastral parcels and building footprints

Despite its importance as a research issue, a widely accepted methodology of estimating land take resulting from urbanization has not yet been reached. Accurate geospatial datasets are currently available at a European and global level; however, different methods of quantifying urban land take could lead to diverse outputs, potentially resulting in underestimation. This can be alarming as encroaching urban sprawl is emerging as a major environmental challenge by destroying natural habitats, consuming productive agricultural land, and contributing to climate change by increasing energy demands. To address this knowledge gap, we propose an estimation of urban land take that combines cadastral parcels and building footprints. Land parcels can be considered as a suitable minimum mapping unit as they are directly related to the spatial level where economic decisions on land use conversion are made. The proposed geospatial method is compared to methods that depend on datasets of High Resolution Layer Imperviousness, Global Building Footprints (alone), Corine Land Cover, Urban Atlas, and Global Human Settlement Layer. The method is exemplified in case studies in Greece, specifically: (a) two islands of the South Aegean Region (Mykonos and Thera), that are heavily impacted by tourism development and sprawl and (b) a peri-urban zone (Thermaikos-Michaniona) within the metropolitan area of Thessaloniki, impacted by intense suburbanization. Results show that urban land consumes important shares of available land since the mid-20th century, this fact highlighting the dynamic encroachment of urban development. Calculation shows that other methods could underestimate urbanized areas by up to 80%–90%. In the discussion section, the advantages of shifting the focus from the pixel to the parcel are further justified, while explicit links to spatial planning policies for sprawl containment are drawn. Such policies could be informed by more realistic estimations of urban land take, in order to proceed with strategic and regulatory measures to support the ‘no net land take’ policy of Europe.

Evaluation of Traditional Land Dispute Resolution Mechanisms in Liberia

Land dispute is ubiquitous in Liberia. Most problems arise from people who squat on land illegally and in some instance sell the same parcel of land to more than one person. Usually, this issue is resolved by traditional land dispute resolution mechanisms. Therefore, this study aimed to evaluate the effectiveness of the traditional land dispute resolution mechanisms in Liberia by employing an empirical and comparative approach and drawing on data collected from 110 farming households. The nature of the conflict, causes of land dispute, individuals’ characteristics, the mandate of the traditional mediators, the linkage between the legal process and traditional land dispute resolution mechanisms, the forms of the resolution mechanisms, the acceptance of the outcomes, and political and social situations were carefully studied. The findings of this study thus supported the notion that traditional means for resolving land disputes are more efficient than the statutory system. Additionally, it was demonstrated that the traditional and the statutory land dispute resolution mechanisms complement one another. However, there is an indication that land dispute will continue to be the biggest concern in the future as many people have started squatting and exploring open areas throughout the country. This is because the country's land laws and policies are not widely known by the citizens. Thus, policy intervention is needed.

A governança fundiária no município de Oiapoque-AP-BR, sob a ótica das transferências de terras da união ao patrimônio fundiário do estado do Amapá

The article analyses the process of land regularization in the municipality of Oiapoque (Amapá’s state), with a theoretical perspective on the discussion of land governance in the municipality based on transfers of land from the Federal Government to the state of Amapá. The methodology was based on the main legal documents that attest to the transfer of land, especially Law No. 10.304/2001. The relevance and importance of the article lies in highlighting the overlapping parcels of land in the territory, and how the municipality is organizing itself to address the issue of a new territorial planning through responsible governance and effective planning.

Tailoring the surface energy balance algorithm for land-improved (SEBALI) model using high-resolution land/use land cover for monitoring actual evapotranspiration

Access to accurate near real-time actual evapotranspiration (ETa) data is crucial for monitoring and planning water uses, contributing to the sustainable management and development of water resources. However, ongoing ETa modeling efforts need to be improved when applied to small-sized farmlands in rugged landscapes like in the upper Blue Nile Basin. This study aimed to customize the Google Earth Engine-based Surface Energy Balance for the Algorithm Land–Improved (SEBALIGEE) model using high-resolution land use and land cover data. Additionally, the model, originally based on JavaScript, was updated to Python (SEBALIGEEpy), thereby enhancing its accessibility to a broader range of users and modelers. The ETa simulated with an updated version of the model was validated over croplands using publicly available AmeriFlux eddy covariance data. Furthermore, the SEBALIGEEpy-based ETa was evaluated over the Koga smallholder irrigation scheme in the Upper Blue Nile Basin, Ethiopia, by comparing it with the ETa obtained from the remote sensing-based Water Productivity Open-Access Portal (WaPOR) over seven seasons (2015/16–2022/23). The validation results show that the updated model provides more accurate ETa estimates with fewer missing records, with 9–11 % using the updated model compared to 14–29 % using the original SEBALIGEE model. The customized model has the potential to be used for agricultural water management in areas with fragmented land parcels like the Upper Blue Nile basin and beyond.

Economic Ties of Russian Settlers and Native Population of Turkestan in the end of the 19th – the beginning of the 20th Centuries

The article analyses the issues of reclaiming of Turkestan by the Russian empire in the second half of the 19th – the beginning of the 20th century by means of creating in the region administrative and military structures as well as by organizing Russian migrant settlements. It was revealed that in the process of organization of urban and rural settlements Turkestan authorities took aim at keeping a distance between native and migrant population. The article characterizes the conditions of granting land parcels for Russian settlers, the different categories and the number of countrymen coming to Turkestan. The article demonstrates various forms of economic interaction of settlers and native people in agricultural activities, everyday life, etc. An accent is put on the changes in the organization of living space under the influence of Turkestan climate peculiarities, different methods of managing agricultural food crops and commercial crops (cotton); the issues of irrigational activities, adoption of farm equipment and particular aspects of everyday life are being analyzed. The author makes a note that the interaction mostly took place in the economic and material spheres, and had fragmentary and episodic character that didn’t lead to cardinal changes in the life of Russian settlers’ community and native people.

Social Injustice Inflicted by Spatial Changes in Vernacular Settings: An Analysis of Published Literature

It is well known that every kind of development has the tendancy to produce spatial disparity or spatial justice. However, usually, it is the demand-driven, rural, non-agricultural transitional area development considered the prime cause of concern for policy planners. Indeed, this is an area where spatial justice needs to be ensured so that development is just for all and not lopsided for any single stakeholder. For example, there is a need to ensure that fair allocation of land development rights rests with the village dwellers. Usually, the market is biased in favour of allocating premium land of the vernacular settlements to expand the city for new city dwellers who wish to get new parcels of land for developing housing. Plan-led spatial changes without corrective mediation between villagers and the city dwellers also lead to bias decision-making. Transition from rural sprawl to urban compactness suggests institutional change need be adopted in governance so that socio-spatial justice for villagers is incorporated into an integrated city. In this context, this paper examines the current knolwdge reflected through academic narratives of social injustice inflicted by spatial change. This paper presents the concept of spatial justice as an umbrella term encompassing all political, social, economic, and environmental forms. Gentrification and peri-urbanization are two spatial changes that do injustice to certain social groups. The paper employs both quantitative and qualitative data gathering techniques. It conducts primarily a document survey, analysing published research related to development and social and spatial justics issues. The documents discussing the role of planning in achieving spatial justice until 2023 are examined. The paper reveals that while formal planning often marginalizes vernacular settlements, participatory and communitydriven planning processes show potential for addressing issues of spatial injustice. The paper concludes that the investigation into spatial justice within vernacular settlements must account for unique socio-cultural, environmental, and economic dynamics.

Application of GIS Based Re-Settlement of Land Record of Mouza Shahbat Khel, District Mardan (Pakistan)

A cadastral information system is a set of processes for parcel/property-based data collection, including land tenure, land use, and land value. The primary goal of the Massavi maps at the time was to depict the distribution, status, and yield of arable fields; other information (such as rivers) was relatively inaccurately drawn, leading to geometrical inaccuracies. It results in a significant loss for revenue collection and other objectives. Secondly, It is difficult to overemphasize how necessary knowledge is to the success of any planning, development, or management work. Having a reliable knowledge base is especially crucial for developing countries with limited resources. Another issue that many developing nations encounter is the lack of accurate land records in the real estate market. The cause can include ownership titles, unclear boundaries between private and collective rights, etc. Thus, there is an urgent need to focus on the creation and deployment of a national digital cadastral information system. Given the preceding context, this article outlines all the obstacles and limits that would arise when combining geometric and legal cadastral data to create a new digital cadastral system. A digital cadastral land information system comprises spatial data that represent legal boundaries of land parcels and provides a vital base layer for integration into other spatial Information systems or as a standalone solution that permits users to retrieve, create, update, store, view, analyze and publish land information.