Spatial Data Processing Research Articles

Identifikasi Perubahan Luasan Lahan di Wilayah Sub-DAS Cikeruh Menggunakan Citra Landsat 8 dengan Google Earth Engine (GEE)

Land cover information is the data neede in the management of watersheds. Identification to obtain land cover using a cloud-based spatial data processing platform Google Earth Engine (GEE). This study aims to identify changes in land area in the Cikeruh sub-watershed area by classifying them using a machine learning basis on GEE. Utilization of landsat imagery is applied in the operation of the Google Earth Engine (GEE) platform using landsat 8 imagery. The analysis method used is the interpretation of Support Vector Machine (SVM) imagery with the identified years since 2015 until 2020. This research still has deficiencies, especially in the validation of land cover classes and area mapped and analyzed.

The Implementation of Bantu Warga Apps and Metabase for Spatial Data Processing In Surabaya

Civil registration and vital statistics (CRVS) is known as an essential supporting system for effective policy-making and service delivery. Its primary purpose is establishing an individual's legal identity and vital events to ensure all citizens get their rights well. Furthermore, an advanced level of CRVS is equipped with a forecasting system to serve more useful data. This paper discusses the potential benefits and challenges of using Metabase and Bantu Warga as civil ministry support systems. The spatial data visualization system using open-source Metabase ran well and resulted in many visualization geospatial maps like birth, marriage and divorce, education, and employment. The forecasting autoregression model configuration and cumulative sum dataset reach the best error result in 1056618. The other aspects, like the self-isolation management system, civil documents classification system, and OCR system, have a good result.

Application of Spatial Data in Three-dimensional Computer Graphics

Digital three-dimensional modeling technologies are actively developing in all areas of industry and business. Three-dimensional models allow you to get visual information about complex objects, phenomena, processes and technical systems, and the scale of modeling can reach entire cities or enterprises. Because, when modeling the environment (cities, enterprises, complex technical systems), there is a spatial component, and there is a tendency to integrate technologies from different areas within one 3D model. Thus, within the framework of this article, the mechanism of using spatial data in the framework of computer graphics applications is considered. The main areas of application of three-dimensional modeling technologies and the trends of their further development are considered in detail. The main terms and definitions that underlie geoinformation technologies that allow processing spatial data are given. Using the example of computer graphics Blender, an example of the use of spatial data for the construction of terrain is given.

Mining Geomatics

This paper attempts to define a name for an area of science and technology that encompasses the acquisition, processing and application of spatial data in the mining industry. A comparative study of the evolution of spatial data exchange methods between Geographic Information Systems (GISs) and General Mining Planning (GMP) software is carried out to define the problem and name it. Subsequent modifications of the acronym GIS towards the specialisation of its application in mining are then reviewed. This is followed by the identification of three terminological postulates designed to formulate constraints and rules for the creation of a new definition. The subsequent analysis identifies the nomenclatural basis of the research area of geomatics and determines its applicability in the context of mining. The results of the research made it possible to formulate a new definition of “mining geomatics”. The final section of the article presents an initial proposal for an inventory of the basic concepts of mining geomatics in the form of a Body of Knowledge for mining geomatics.

Assessment of Using UAV Photogrammetry Based DEM and Ground-Measurement Based DEM in Computer-Assisted Forest Road Design

Computer-assisted forest road design mainly relies on a high-resolution digital elevation model (DEM), which provides terrain data for supporting the analysis of road design features. The resolution and accuracy of the DEM in representing the terrain structures vary depending on the preferred dataset, which then reflects some of the essential road features such as alignment, road slope, and earthwork. In this study, three forest road sections were designed by using high-resolution DEMs generated from UAV photogrammetry data, GNSS-GPS data and Total Station data. NetCAD 7.6 software, developed in Turkey and mostly used in road design applications, was used to perform the road design while calculating horizontal profiles, vertical profiles, curves, cross sections, and earthwork. The DEM generation capabilities for three datasets were compared based on spatial resolution, data collection and data processing stage. Then, the differences between three road sections were evaluated by considering specified road features such as alignment properties, road slope, and earthwork. The results indicated that the UAV (Unmanned Aerial Vehicles) based DEM generation method provided the highest resolution (10 cm), followed by the Total Station (56 cm) and GNSS-GPS (61 cm) based methods. When comparing the time for data collection procedure, it took 14 minutes, 70 minutes, and 110 minutes for UAV data, GNSS-GPS data, and Total Station data, respectively. On the other hand, UAV based method falls into a disadvantageous situation in data processing stage, due to high data processing time (3 hours). However, GNSS-GPS and Total Station based methods work only with spatial point data, so they require less processing time of 15 minutes and 25 minutes, respectively. The results indicated that road lengths were 294.8, 272.4 and 282.1 m and the average road slopes were 3.41%, 3.39%, and 3.31% for the road sections designed by using UAV, GNSS-GPS, and Total Station based DEMs, respectively. The excavation and landfill volumes were 369.16 m3 and 166.98 m3, 285.86 m3 and 201.83 m3, and 433.17 m3 and 183.95 m3, respectively. The results indicated that UAV photogrammetry data generates high-resolution DEMs that can be effectively used to design forest roads.

Open spatial data for the exploration of territories and digital services for accessing them

«Open Data» concept is presented considering its application for wide public access to spatial data. It is shown that some principles of the «Open Data» may not be applicable to spatial data due to their peculiarities. The information source «Navigator of Open Spatial Data» is being created at Moscow State University of Geodesy and Cartography to simplify access to geodata for training specialists in this field. Some aspects of the use of open spatial data are shown on the example of the Lunar data, since planetary data has the status of freely distributed. Digital services for access to planetary data are presented. Formats used for storage of spatial planetary data are discussed. Created interactive services and open lunar data accumulated at Moscow State University of Geodesy and Cartography provide free online access to the «Digital Moon» system, which can be considered as a collection of Lunar data, digital tools and infrastructure for processing of spatial data in the field of territory exploration. With growing artificial intelligence and machine learning technologies, the potential of the created «Digital Moon» system can be expanded, and the accumulated planetary spatial data will gain additional interdisciplinary connections.

MEMBANGUN KEMAMPUAN SPASIAL LEWAT PELATIHAN PEMETAAN DENGAN TEKNOLOGI DRONE

Drone technologys are now widely used not only for taking photos, videos, but also for mapping. Therefore, it is necessary to conduct mapping training activities with drone technology so that participants can improve their competence in using drones for mapping. Training purposes are 1) To provide an understanding of spatial knowledge through training with drone technology, 2) To increase competence related to Mapping using drones and 3) To produce high resolution maps. The methods or stages of training activities are 1) Coordination of training implementation with cooperation partners, 2) Preparation of training materials, 3) Opening of registration, 4) Opening of Training Classes, 5) Training of spatial data retrieval using drones, 6) Training of Spatial Data Processing from Drones. The results of the mapping training activity with drone technology were attended by 73 participants, of which 29 participants were declared passed and received certificates. Participants who passed were participants who had followed all the training materials and submitted aerial photography and contour maps assignments. Mapping training activities are carried out in online and offline blended learning. Online activities are carried out when opening classes, delivering material, processing data and closing classes, while offline activities are when the practice of taking aerial photos using drones will be used as data processing material. In addition, the results of the training activities include aerial photo maps and high-resolution contour maps from aerial photographs with drones made by training participants.

Calculation of rainfall thresholds for debris flow prediction

Due to the fact that debris flow movements, commonly known as "huaycos," represent a potential threat worldwide, especially in Peru, it is necessary to analyze and study this hazard, as well as the ability to forecast these movements. Therefore, the objective of this research was to determine the precipitation thresholds that trigger debris flow movements in the Rosayoc/Batán ravine, in order to contribute to Disaster Risk Management (DRM). As a means of processing spatial data, this study used an approach that combines Geographic Information Systems (GIS), remote sensing, and satellite image analysis. Additionally, through the hierarchical analysis process, the most susceptible areas to debris flow in the Rosayoc/Batán ravine were evaluated and determined. In conclusion, the True Skill Statistic (TSS) of the thresholds was calculated through calibration and validation. This indicates that the model's ability to predict future outcomes was evaluated. Additionally, through the analysis and evaluation of hazard levels for debris flow movements using the hierarchical analysis process (CENEPRED 2014), it was established that the lower part has very high and high levels of hazard, the middle part has high and medium levels, and the upper part has a high level of hazard. Furthermore, these levels have the highest predominance of area in each part of the ravine. Moreover, hazard maps were also created for debris flow movements triggered by the maximum 24-hour precipitation and the critical threshold of accumulated rainfall (LA1) over 18 days, based on the maximum depths and velocities generated by the debris flow.

Design of an Automated Algorithm for Delimiting Land Use/Soil Valuation Classes as a Tool Supporting Data Processing in the Land Consolidation Procedure

The consolidation of land to improve the agrarian structure and provide for sustainable rural development is a complex and multi-faceted process, and its efficiency depends on a considerable number of factors associated with its respective stages of desk studies and fieldwork. In order to ensure the highest-quality concepts and their efficient implementation, various measures are undertaken to improve, among other things, the methods for acquiring, collecting, and processing spatial data representing elements of reality saved in cadastral databases. There are a wide variety of available solutions oriented towards land consolidation improvement, but most of them refer to modifications that are difficult to implement due to, for instance, high costs, high technical requirements, and the absence of relevant legal regulations. Our study aimed to find a practical and applicable solution to a material problem in terms of land consolidation projects in Poland, a task associated with the necessity of converting cadastral database objects so that they were suitable for appraising the value of land, and designing new farmsteads based on the value of land held by particular participants of the land consolidation project. It involved the development and implementation of a self-designed algorithm for automated processing of auxiliary land-use/soil-valuation class objects into separate classes representing soil class contours and land use contours, in compliance with the current regulations governing the structure of the cadastre in Poland. The work resulted in the development of an innovative tool, making it possible, among other functions, to align object-generating methods as preferred by the administrator of the cadastral database. The designed algorithm model reduces data processing time to several seconds, while simultaneously eliminating the risk of error. The tool was thoroughly evaluated and then implemented at the Subcarpathian Office of Land Surveying and Agricultural Areas in Rzeszów, which is in charge of land consolidation projects in south-eastern Poland.

Современные подходы к автоматизации операций по редактированию пространственных данных

The features of automating the processing of spatial data using geographic information systems are discussed. The main directions of automation at spatial data processing, including the use of artificial intelligence technologies, are identified. Possible technical approaches to that in geoinformation systems are identified and described. The software implementation of the listed techniques involving open source software is considered, using the example of a typical sequence of actions at working with spatial information

GIS-based calculation method of surge height generated by three-dimensional landslide

Combined with the spatial data processing capability of the Geographic Information Systems (GIS), the Pan Jiazheng method is extended from two-dimensional (2D) to three-dimensional (3D), and a 3D landslide surge height calculation method is proposed based on grid column units. First, the data related to the landslide are rasterized to form grid columns, and a force analysis model of 3D landslides is established. Combining the vertical strip method with Newton's laws of motion, dynamic equilibrium equations are established to solve the surge height. Moreover, a 3D landslide surge height calculation expansion module is developed in the GIS environment, and the results are compared with those of the 2D Pan Jiazheng method. Comparisons showed that the maximum surge height obtained by the proposed method is 24.6% larger than that based on the Pan Jiazheng method. Compared with the traditional 2D method, the 3D method proposed in this paper better represent the actual spatial state of the landslide and is more suitable for risk assessment.

Mapping Imprecision: How to Geocode Data from Inaccurate Historic Maps

This paper aims to present and discuss the method of geocoding historical place names from historic maps that cannot be georeferenced in the GIS environment. This concerns especially maps drawn in the early modern period, i.e., before the common use of precise topographic surveys. Such maps are valuable sources of place names and geocoding them is an asset to historical and geographical analyses. Geocoding is a process of matching spatial data (such as place names) with reference datasets (databases, gazetteers) and therefore giving them geographic coordinates. Such referencing can be done using multiple tools (online, desktop), reference datasets (modern, historical) and methods (manual, semi-automatic, automatic), but no suitable approach to handling inaccurate historic maps has yet been proposed. In this paper, selected geocoding strategies were described, as well as the author’s method of matching place names from inaccurate cartographic sources. The study was based on Charles Perthées maps of Polish palatinates (1:225,000, 1783–1804)—maps that are not mathematically precise enough to be georeferenced. The proposed semi-automatic and curated approach results in 85% accuracy. It reflects the manual workflow of historical geographers who identify place names with their modern counterparts by analysing their location and proper name.

GDAL and PROJ Libraries Integrated with GRASS GIS for Terrain Modelling of the Georeferenced Raster Image

Libraries with pre-written codes optimize the workflow in cartography and reduce labour intensive data processing by iteratively applying scripts to implementing mapping tasks. Most existing Geographic Information System (GIS) approaches are based on traditional software with a graphical user’s interface which significantly limits their performance. Although plugins are proposed to improve the functionality of many GIS programs, they are usually ad hoc in finding specific mapping solutions, e.g., cartographic projections and data conversion. We address this limitation by applying the principled approach of Geospatial Data Abstraction Library (GDAL), library for conversions between cartographic projections (PROJ) and Geographic Resources Analysis Support System (GRASS) GIS for geospatial data processing and morphometric analysis. This research presents topographic analysis of the dataset using scripting methods which include several tools: (1) GDAL, a translator library for raster and vector geospatial data formats used for converting Earth Global Relief Model (ETOPO1) GeoTIFF in XY Cartesian coordinates into World Geodetic System 1984 (WGS84) by the ‘gdalwarp’ utility; (2) PROJ projection transformation library used for converting ETOPO1 WGS84 grid to cartographic projections (Cassini–Soldner equirectangular, Equal Area Cylindrical, Two-Point Equidistant Azimuthal, and Oblique Mercator); and (3) GRASS GIS by sequential use of the following modules: r.info, d.mon, d.rast, r.colors, d.rast.leg, d.legend, d.northarrow, d.grid, d.text, g.region, and r.contour. The depth frequency was analysed by the module ‘d.histogram’. The proposed approach provided a systematic way for morphometric measuring of topographic data and combine the advantages of the GDAL, PROJ, and GRASS GIS tools that include the informativeness, effectiveness, and representativeness in spatial data processing. The morphometric analysis included the computed slope, aspect, profile, and tangential curvature of the study area. The data analysis revealed the distribution pattern in topographic data: 24% of data with elevations below 400 m, 13% of data with depths −5000 to −6000 m, 4% of depths have values −3000 to −4000 m, the least frequent data (−6000 to 7000 m) <1%, 2% of depths have values −2000 to 3000 m in the basin, while other values are distributed proportionally. Further, by incorporating the generic coordinate transformation software library PROJ, the raster grid was transformed into various cartographic projections to demonstrate distortions in shape and area. Scripting techniques of GRASS GIS are demonstrated for applications in topographic modelling and raster data processing. The GRASS GIS shows the effectiveness for mapping and visualization, compatibility with libraries (GDAL, PROJ), technical flexibility in combining Graphical User Interface (GUI), and command-line data processing. The research contributes to the technical cartographic development.

A bi-objective model for territorial design

The clustering of spatial-geographic units, zones or areas has been used to solve problems related to Territorial Design. Clustering adapts to the definition of territorial design for a specific problem, which demands spatial data processing under clustering schemes with topological requirements for the zones. For small sized instances, once the geographical compactness is attended to as an objective function, this problem has been solved by exact methods with an acceptable response time. However, for larger instances and due to the combinatory nature of this problem, the computational complexity increases and the use of approximated methods becomes a necessity, in such a way that when geographical compactness was the only cost function a couple of approximated methods were incorporated giving satisfactory results. A particular case of this kind of problems that has had our attention in recent years is the classification by partitioning of AGEBs (Basic Geographical Units by its initials in Spanish). Some work has been made related to the formation of compact groups of AGEBs, but additional re-strictions were often not considered. A very interesting and highly demanded application problem is to extend the compact clustering to form groups with for some of its descriptive variables. This problem translates to a multi-objective approach that has to pursue two objectives to attain a balance between them. At this point, to reach a set of non-dominated and non-comparable solutions, a method has been included that allows obtaining the Pareto front through the Hasse diagram, which implies proposing a mathematical programming model and the synthetic resulting between compactness and homogeneity.

Impact of Urbanisation on the Spatial and Temporal Evolution of Carbon Emissions and the Potential for Emission Reduction in a Dual-Carbon Reduction Context

Urbanisation is accelerating under the new economic development trend, but the global warming exacerbated by greenhouse gases has caused a certain degree of constraint on the speed and quality of economic development, among which anthropogenic emissions, mainly from transportation, are more obvious. Therefore, based on the background of urbanisation and taking urban agglomerations as the research object, this study investigates the spatial and temporal mechanisms and dynamics of carbon emissions through the construction of carbon emission models, the identification of influencing factors, and the processing of spatial data and proposes relevant measures for carbon emission control mechanisms. This study finds that the improvement of the per capita economic level and the urbanisation rate will correspondingly lead to an increase in carbon emissions and that the spatial distribution of carbon emissions under passenger and freight transport modes shows a pattern of “low at the ends and high in the middle”, with the predicted carbon emission levels remaining balanced over a long period of time, with a variation rate of less than 1%. The model idea proposed in this study can effectively provide new perspectives and ideas for the differentiated formulation of emission reduction policies, and the government ought to focus more on the dynamic changes of urbanised carbon emissions in future development so as to realise the potential of urban emission reduction.

Global Topology Concept Neighborhood Graph and Its Application in Topological Similarity Measurement

A topological relationship is a key factor in the spatial data processing. Aiming at the problem of topological similarity measurement when the dimension of spatial objects changes in the process of map generalization, this paper proposes a topological similarity measurement method based on the global topological concept neighborhood graph. Firstly, all the topological relationships that can be described by the nine intersection model are abstracted, generalized, and classified, and the classified point/point, point/line, point/polygon, line/line, line/polygon, and polygon/polygon local topological concept neighborhood graphs are established. Then, according to the map generalization rules, the mapping between different types of topological concept neighborhood graphs is established, and the global topological concept neighborhood graph is obtained, Finally, the similarity of the topological relationship between different morphological objects is measured. The experimental results show that the proposed method can better meet the topological similarity measurement when the shape of spatial objects changes.

Scheduling distributed multiway spatial join queries: optimization models and algorithms

Multiway spatial joins are a commonly occurring and fundamental type of query for spatial data processing. This article presents models and algorithms to schedule this type of query in distributed database systems while attempting to strike a balance between makespan and communication costs. We propose three algorithms based on combinatorial optimization methods: the well-known linear relaxation technique of rounding a solution generated by linear programming (LP), a more sophisticated Lagrangian Relaxation method (LR), as well as a greedy heuristic (GR) for baseline comparison. Our evaluation shows that a schedule built using GR consumes, on average, 22% more processing and communication resources than a more elaborate schedule constructed via the LR method, when scheduling a query for 64 machines. The schedule provided by LR is also, on average, an order of magnitude closer to the optimal schedule for a query compared to GR. We show that scheduling Gigabyte-size multiway queries before execution can reduce its processing time by an order of magnitude compared to state-of-the-art frameworks for spatial data processing that do not have this capability, and can significantly reduce the amount of shuffled data in the network.

Spatial Mapping Based on the Settlement Carrying Capacity Value in Gunungpati District, Semarang City

Abstract: The City Regional Spatial Plan (RTRW) for Semarang City stipulates that Gunungpati District has a role in developing residential cultivation areas with the determination of several protected area types as well as functioning as a strategic environmental carrying capacity area for the city. Based on Semarang City BPBD, 29 landslides occurred between 2016-2021, which damaged houses, facilities, and residential infrastructure. This study aims to produce spatial mapping for residential area designations through the calculation of its carrying capacity so as to obtain the carrying capacity value or classification of the ability of each village area to accommodate the number of residents. This can then be used as one of the basic considerations in determining the development of residential areas in Gunungpati District. This study uses the quantitative method to determine the residential land's carrying capacity through spatial mapping data processing based on geographic information systems (GIS) using scoring, weighting, and overlay techniques. The spatial mapping produces a landslide vulnerability map with vulnerability classifications covering very low (1.468,17 Ha) to very vulnerable (466.53 Ha) classes as well as cultivation function, buffer, and protected areas distribution in Gunungpati District. The final results show that each region can accommodate the population increase of each village in Gunungpati District, with Jatirejo Village scoring the highest in DDPm value (26.9) and Sukorejo Village scoring the lowest (5.7). Keywords: Landslides, carrying capacity, settlement

Quantitative Morphometric 3D Terrain Analysis of Japan Using Scripts of GMT and R

In this paper, we describe two related scripting methods of cartographic data processing and visualization that provide 2D and 3D mapping of Japan with different algorithm complexity. The first algorithm utilizes Generic Mapping Toolset (GMT), which is known as an advanced console-based program for spatial data processing. The modules of GMT combine the functionality of scripting with the aspects of geoinformatics, which is especially effective for the rapid analysis of large geospatial datasets, multi-format data processing, and mapping in 2D and 3D modes. The second algorithm presents the use of the R programming language for cartographic visualization and spatial analysis. This R method utilizes the packages ‘tmap’, ‘raster’, ‘maps’, and ‘mapdata’ to model the morphometric elements of the Japanese archipelago, such as slope, aspect, hillshade and elevation. The general purpose graphical package ‘ggplot2’ of R was used for mapping the prefectures of Japan. The two scripting approaches demonstrated an established correspondence between the programming languages and cartography determined with the use of scripts for data processing. They outperform several well-known and state-of-the-art GIS methods for mapping due to their high automation of data processing. Cartography has largely reflected recent advances in data science, the rapid development of scripting languages, and transfer in the approaches of data processing. This extends to the shift from the traditional GIS to programming languages. As a response to these new challenges, we demonstrated in this paper the advantages of using scripts in mapping, which consist of repeatability and the flexible applicability of scripts in similar works.

Оценка антропогенной нагрузки на территории Бештаугорского заказника

Introduction. The need for functional zoning of specially protected natural areas (SPNA) is due to the need to choose the most effective methods for protecting landscape and biological diversity, the presence of limited economic activity permitted on the territory of the protected landscape, as well as the recreational attractiveness of the territory of the Beshtaugorsky reserve. The need for zoning is explained by the diversity of natural complexes, the types of impact on them by various groups of visitors and the local population, and the corresponding management methods. Materials and research methods. The information base for the study was the materials of field studies of the influence of recreation on landscape components in the Beshtaugorsky reserve of the growing seasons 2021–2022. To identify the types of economic activity, multi-temporal remote sensing data (Landsat) were used. Spatial data processing was carried out using the geographic information system Qgis 3.10. Research results and their discussion. Modern methods of processing spatial data made it possible to identify the main types of land use of the Beshtaugorsky reserve, to map valuable resources and centers of high biodiversity, the growth of specially protected species. In the course of the work, the recreational load on 38 test sites was studied and mapped. The degree of influence of recreation is described, the stages of recreational digression of sites are determined. The result was the creation of a recommended scheme for the functional zoning of the reserve with the allocation of 4 zones within the boundaries of the protected areas and 2 outside the boundaries of the protected areas. Conclusions. Functional zoning of protected areas is a recognized effective method of territory modeling. The division of the Beshtaugorsky reserve into separate areas with recommended types and modes of use should contribute to the planning of management measures, the elimination of conflicts in nature management and the conservation of valuable biological resources through spatial and temporal restrictions.