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Spatial Databases with Application to GIS
... На примјер, заједничка граница између сусједних полигона мора бити забиљежена два пута. Ригокс са сарадницима (Rigaux, 2002) закључује да је геометрија било ког просторног објекта дефинисана независно од геометрије других просторних објеката. Због тога, оваква структура доводи до редундантности података. ...
... На примјер, граница између два сусједна полигона је представљена два пута, два пута се складишти у одређени формат или базу података. Такође, Ригокс са сарадницима (Rigaux et al., 2002) закључује да овај модел обезбјеђује хетерогену структуру која комбинује тачке, линије и полигоне без ограничења. Конкретно, линије се могу укрштати у равни, а да тачке њиховог пресјека нису експлицитно сачуване у бази података. ...
... Ригокс са сарадницима (Rigaux et al., 2002) даје осврт на позитивне и негативне карактери стике "шпагети" модела података. Главна предност овакве структуре је једноставност. ...
The textbook is designed in an innovative way, where theoretical and methodological elaborations are followed by practical examples that help to understand them efficiently and simply. On one hand, the textbook aligns with the curriculum of the subject it relates to, while on the other hand, it synthesizes all contemporary advancements in the field of GIS analysis. As such, it can be suitable for acquiring new theoretical and practical knowledge, not only for students studying GIS analysis but also for all other experts working with spatial data and geoinformation technologies.
The textbook consists of seven chapters. The first chapter discusses the basic theoretical and methodological foundations of the concept of GIS analysis as a scientific sub-discipline of geographic information science. It provides an overview of all previous achievements in this field through a review of the literature. Finally, it presents an innovative theoretical-methodological concept aligned with contemporary achievements and the syllabus of the GIS analysis course.
The second chapter covers GIS data models, which are a prerequisite and the initial step in any analytical procedure. Raster and vector data models are discussed in detail. The third chapter deals with vector analyses. In addition to theoretical and methodological elaborations, all segments are also presented with practical examples.
The fourth chapter pertains to raster analyses. Using the same approach of theory-methodology-examples, the role of raster analyses in spatial modeling is illuminated. The importance of analyzing satellite and other imagery is highlighted in the fifth chapter, adhering to the theory-methodology-examples concept.
In the sixth chapter, complex GIS analyses, in the form of geostatistical analyses, are discussed in the same way. The final, seventh chapter, provides an overview of analytical modeling and the automation of GIS analytical procedures.
... Then, we present three techniques for representing these abstract models in a computer: raster data, vector data, and constraints. The concept presented can also be explored in dept in Geospatial data science books, [97], in geographic information systems (GIS) books [105], or books on geospatial DBMS [122,123]. ...
... Quantitative geographic knowledge is generally represented using geometries, such as points, lines, and polygons [122,123]. These geometries serve as abstractions of spatial features in the real world. ...
... [55] Generally, the GIS systems' spatial data are presented as points, lines, and polygons. [56] Point data typically represent locations (x, y -latitude and longitude) of distinct features like schools and hospitals. Line data represent linear features such as rivers and streets and are represented by a string of coordinates (x 1 , y 1 ; x 2 , y 2 ;…; x n , y n -a sequence of latitude and longitudes), where (x 1 , y 1 ) is the starting position and (x n , y n ) is the ending position. ...
... In GIS systems, a network is a connected set of linear features representing some geographic entity, typically of the transportation type. [56,59] GIS-based sets of algorithms related to network analysis allow one to solve common network problems, such as finding the best/less-constrained route, finding the closest facility, analyzing a service area around a point of interest, and servicing a set of orders with a fleet of vehicles. [59] In this research, a GIS-based network analysis method has been adopted to find the possibility of transporting the injured anywhere on the circuit of a national highway to the nearest healthcare unit within 30 minutes. ...
Background:
Highways represent the most significant capital asset that any country’s public sector holds. A system of national highways with easy access to ambulance and trauma centers is termed emergency rescue ready and helps reduce the mortality due to road accidents. Given the rich impetus for road infrastructure development by the government of India, there is a need to consider emergency rescue readiness on highways. Previous research suggests that on typical Indian highways, an ambulance can reach the accident scene within 30 minutes; the remaining 30 minutes of golden hour is essential for saving the life of the injured by admitting to a healthcare facility with a trauma unit.
Objective:
To investigate the emergency rescue readiness for a stretch of highway between two cities in India. The main objective is to determine the possibility of transporting the injured due to the accident on the highway to the nearest available trauma center within 30 minutes.
Methods:
A Geographic Information System (GIS)‑based network analysis method has been adopted to find the possibility of transporting the injured anywhere on the circuit of a national highway to the nearest healthcare unit within 30 minutes.
Results:
A map representing the status of emergency rescue readiness has been presented for the study area. For a circuit of national highway with a length of 805 km, in a stretch of 89.5% (718.5 km), the injured can be transported to the healthcare unit within 30 minutes. In the remaining 10.5% of the highway, the healthcare units are significantly far from the highways and may hamper the post‑crash rescue operations.
Conclusion:
There exists a wide disparity in trauma care delivery in the study area. Currently, the healthcare units established to serve the areas with dense populations also serve as emergency rescues during accidents on the national highways. Using GIS techniques for highway stretches with difficulty reaching the trauma centers, a national‑level assessment is highly recommended.
... 18 A formal definition is given in [45]. 19 This term appears in [103] in the context of spatial databases. 20 E.g. a spatial grid. ...
... Note that systems for certain types of vector retrieval, such as time series or spatial databases, can often exploit correlations and patterns in the series[53] as well as low-dimensional indexing techniques[103]. ...
There are now over 20 commercial vector database management systems (VDBMSs), all produced within the past five years. But embedding-based retrieval has been studied for over ten years, and similarity search a staggering half century and more. Driving this shift from algorithms to systems are new data intensive applications, notably large language models, that demand vast stores of unstructured data coupled with reliable, secure, fast, and scalable query processing capability. A variety of new data management techniques now exist for addressing these needs, however there is no comprehensive survey to thoroughly review these techniques and systems. We start by identifying five main obstacles to vector data management, namely the ambiguity of semantic similarity, large size of vectors, high cost of similarity comparison, lack of structural properties that can be used for indexing, and difficulty of efficiently answering “hybrid” queries that jointly search both attributes and vectors. Overcoming these obstacles has led to new approaches to query processing, storage and indexing, and query optimization and execution. For query processing, a variety of similarity scores and query types are now well understood; for storage and indexing, techniques include vector compression, namely quantization, and partitioning techniques based on randomization, learned partitioning, and “navigable” partitioning; for query optimization and execution, we describe new operators for hybrid queries, as well as techniques for plan enumeration, plan selection, distributed query processing, data manipulation queries, and hardware accelerated query execution. These techniques lead to a variety of VDBMSs across a spectrum of design and runtime characteristics, including “native” systems that are specialized for vectors and “extended” systems that incorporate vector capabilities into existing systems. We then discuss benchmarks, and finally outline research challenges and point the direction for future work.
... Το βασικό στοιχείο που διαφοροποιεί τα ΓΣΠ από τα άλλα πληροφοριακά συστήματα ή τα συστήματα διανυσματικής σχεδίασης (CAD), είναι το ό,τι λειτουργούν με πραγματικές γεωγραφικές συντεταγμένες. Η σημαντικότερη δυνατότητα που παρέχουν τα ΓΣΠ είναι το ό,τι μπορούν να συνδέσουν ποικιλοτρόπως τη χωρική με την περιγραφική πληροφορία, η οποία δεν έχει από μόνη της χωρική υπόσταση (Ανδρεάδης, Θ. 2008 (Rigaux, Ph. et al. 2002) ...
... Συχνά χρησιμοποιείται από το λογισμικό για τη μετατροπή των δεδομένων από ένα ή περισσότερα layers διανυσματικών στοιχείων σε ένα χάρτη εξόδου σε μορφότυπο bitmap γραφικών, αλλά μπορεί επίσης να χρησιμοποιηθεί για να δημιουργήσει ένα raster ΓΣΠ layer από ένα vector layer. Εικόνα 3.6: Χρήση χωρικών δεδομένων από διαφορετικές πηγές (Rigaux, Ph. et al. 2002) ...
... There are also plenty of spatial indices for spatial data [2], of which the most typical is R-tree [3]. However, with the increasing complexity of spatial big data, the bottlenecks of traditional spatial indices are emerging [4], such as a large cost on storage and queries. ...
... (3) Partition data: the partitioned index, with a higher overall accuracy, are mainly divided into two types, i.e., data-based partition and spatial-based partition [12]. (4) Handle update: the update strategies of spatial learned indices basically follow that of the normal learned index. ...
The spatial learned index constructs a spatial index by learning the spatial distribution, which performs a lower cost of storage and query than the spatial indices. The current update strategies of spatial learned indices can only solve limited updates at the cost of query performance. We propose a novel spatial learned index structure based on a Block Range Index (SLBRIN for short). Its core idea is to cooperate history range and current range to satisfy a fast spatial query and efficient index update simultaneously. SLBRIN deconstructs the update transaction into three parallel operations and optimizes them based on the temporal proximity of spatial distribution. SLBRIN also provides the spatial query strategy with the spatial learned index and spatial location code, including point query, range query and kNN query. Experiments on synthetic and real datasets demonstrate that SLBRIN clearly outperforms traditional spatial indices and state-of-the-art spatial learned indices in the cost of storage and query. Moreover, in the simulated real-time update scenario, SLBRIN has the faster and more stable query performance while satisfying efficient updates.
... Para cada cobertura (variable) se realizó la interpolación en el sistema de información geográfica Arc-GIS 10.8 a partir de tres algoritmos diferentes comúnmente utilizados para el medio marino (Urcádiz-Cázares et al. 2017): la Distancia Inversa Ponderada, la regresión del proceso Gaussiano llamado Kriging y, el Vecino Natural (Isaak y Srivastava, 1989;Franke y Nielson, 1991). Para el método de Distancia Inversa Ponderada se emplearon los ajustes comúnmente utilizados en literatura de acuerdo con Rigaux et al. (2001), para lo cual, el parámetro de peso se mantuvo en dos (el valor predeterminado), el radio de búsqueda fue un máximo de cinco puntos. Para los modelos con Kriging se utilizó un análisis de semivariogramas empíricos calculados a partir del modelo esférico (Isaak y Srivastava, 1989). ...
... Los modelos presentaron valores entre 2.7 a 95% de contenido de carbonato de calcio, -0.9 a 7.8 Φ de tamaño medio de grano (donde Φ es una transformación logarítmica del diámetro de sedimento, la cobertura de algas (Tapia-Silva et al. 2015;Valley et al., 2005), hábitat asociados a zonas de corriente (Sheehan y Welsh, 2009) incluso para cobertura de plantas terrestres (Mkrtchyan, 2004). Sin embargo, para el arrecife La Sorpresa el algoritmo de Distancia Inversa Ponderada resultó ser la aproximación más adecuada para representar la variabilidad espacial de los porcentajes de cobertura, por un lado, debido a que presentó el menor error en las métricas y asumiendo que las variables que se representan disminuyen su influencia al aumentar la distancia desde el punto (Rigaux et al. 2001). Este último aspecto lo convierte en el método de interpolación adecuado para esta zona, dado que concede mayor peso a los valores cercanos al punto a estimar y menos peso los puntos lejanos. ...
La clasificación ambiental representa uno de los primeros pasos en el desarrollo de cualquier tipo de estudio sobre una región en particular. El uso del mapeo del hábitat se ha adoptado cada vez más para representar las características del medio pues permite identificar regiones homogéneas basadas en características únicas. La Sorpresa es un arrecife rocoso altamente heterogéneo, sin embargo, las caracterizaciones realizadas hasta el momento no han capturado dicha propiedad. El objetivo del presente estudio es desarrollar un producto cartográfico apegado a la manifestación espacial del hábitat en este arrecife rocoso. Para ello se llevó a cabo un muestreo en el que fueron obtenidos datos del entorno bentónico útiles para caracterizar la zona, al interpolar los valores de porcentaje de las coberturas abióticas y bióticas. En el presente trabajo se demostró que el uso de datos puntuales obtenidos a partir de censos visuales junto con los métodos de interpolación, resultaron ser una estrategia eficaz, con un buen desempeño para la caracterización de los arrecifes. Además, se conformaron los mapas de hábitats de la zona. El método interpolación Distancia Media Ponderada (IDW) mostró mayor fidelidad para representar las características del ambiente. Gracias a este, fue posible comprobar que el arrecife presentó elevada heterogeneidad de hábitats. De manera general el arrecife rocoso presenta una composición con tepetate y las rocas como los sustratos duros predominantes en el área, en estos se soporta la cobertura de algas coralinas, coral y macroalgas.
... A database is a collection of related data constructed and populated for a specific purpose in a computer environment ( Rigaux et al., 2001 ;Pressbook, 2024 ). A database management system (DBMS) allows various database processes such as definition, creation, querying, updating, administration and sharing of data among multiple users and computer applications ( Elmasri and Navathe, 2015 ). ...
Soil erosion is a crucial environmental issue affecting agricultural productivity, water quality, and ecosystem sustainability. Deforestation and human activities have led to excessive soil erosion. A webGIS-based decision support system (DSS) was developed to provide complete information on soil erosion in the Guder watershed forming a part of the Abay River Basin in Ethiopia. The parameters employed were estimated using remote sensing data. Sub-watersheds were prioritised based on soil erosion risk through a Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information Systems (GIS). The study employed high-resolution spatial data, including rainfall, soil properties, and topography, to model erosion rates across the watershed. Results indicate that the annual soil loss in the watershed varied significantly from 0 to 8021 t ha−1 yr−1, with an average loss of 97.5 t ha−1 yr−1. About 33.3% of the watershed experienced very high soil loss (>50 t ha−1 yr−1), accounting for 91.3% of the total eroded. In contrast, 25.5% of the area exhibited medium soil erosion rates (<5 t ha⁻¹ yr⁻¹). The webGIS tool developed is powerful and user-friendly portal that enables non-technical users to access real-time soil erosion data and better understand soil conservation programs, helping them identify measures to reduce soil erosion in the watershed. Moreover, this information also supports land managers, policymakers, and farmers in adopting targeted soil erosion control measures, promoting sustainable land management in the region.
... If MBRs do not overlap, the two polygons do not intersect. Otherwise, a line segment intersection test is used to check if any pairs of line segments (edges) are intersected (Rigaux et al., 2001;Liu & Puri, 2020). If no pairs of line segments intersect, a point-in-polygon test can determine if one polygon is fully contained within the other (Heckbert, 2013). ...
How can we estimate the result size for a given query on complex spatial objects like polygons? Estimating a query’s result size, also known as the cardinality estimation, plays a significant role in query scheduling and optimization. Accurate and fast cardinality estimation substantially improves query efficiency. Existing compatible solutions, mainly histogram-based, deal with polygons as their minimal bounding rectangles for easier processing, which leads to inaccurate estimation. To address this issue, we present PolyCard, a learned cardinality estimator for intersection queries on spatial polygons. We successfully apply learning techniques to spatial polygons with variable sizes. PolyCard has the following properties. (i) Accurate: PolyCard improves 30% accuracy compared with existing solutions, (ii) Fast: PolyCard takes only 4 microseconds for an estimation, and (iii) Stable: PolyCard is robust against datasets and queries of different cardinalities. Our experiments on four real-world datasets of millions of polygons demonstrate the efficiency and effectiveness of PolyCard.
... High precision can adversely affect the graph's performance in terms of storage, indexing, and query efficiency [Regalia et al., 2017], while reducing precision can impact the quality of spatial querying. Algorithms determining topological relations using geometries operate with polynomial time complexity relative to the number of nodes in the geometries being tested [Rigaux et al., 2002]. Graph databases that implement popular space-dividing indexing mechanisms, such as quadtrees and geohashing (e.g., GraphDB), still encounter limitations in spatially pruning search spaces. ...
Geospatial Knowledge Graphs (GeoKGs) have become integral to the growing field of Geospatial Artificial Intelligence. Initiatives like the U.S. National Science Foundation's Open Knowledge Network program aim to create an ecosystem of nation-scale, cross-disciplinary GeoKGs that provide AI-ready geospatial data aligned with FAIR principles. However, building this infrastructure presents key challenges, including 1) managing large volumes of data, 2) the computational complexity of discovering topological relations via SPARQL, and 3) conflating multi-scale raster and vector data. Discrete Global Grid Systems (DGGS) help tackle these issues by offering efficient data integration and representation strategies. The KnowWhereGraph utilizes Google's S2 Geometry -- a DGGS framework -- to enable efficient multi-source data processing, qualitative spatial querying, and cross-graph integration. This paper outlines the implementation of S2 within KnowWhereGraph, emphasizing its role in topologically enriching and semantically compressing data. Ultimately, this work demonstrates the potential of DGGS frameworks, particularly S2, for building scalable GeoKGs.
... Spatial Database Management Systems (SDBMSs) aim to store, manipulate, and retrieve spatial data, which describes objects and locations under a coordinate system [15]. SDBMSs are employed in various modern applications, such as geographic information systems [34], computer-aided design [23], location-based services [47], and scientific simulations [27,39]. SDBMSs are typically implemented as spatial extensions or build-in features of widely-used relational DBMSs. ...
Spatial Database Management Systems (SDBMSs) aim to store, manipulate, and retrieve spatial data. SDBMSs are employed in various modern applications, such as geographic information systems, computer-aided design tools, and location-based services. However, the presence of logic bugs in SDBMSs can lead to incorrect results, substantially undermining the reliability of these applications. Detecting logic bugs in SDBMSs is challenging due to the lack of ground truth for identifying incorrect results. In this paper, we propose an automated geometry-aware generator to generate high-quality SQL statements for SDBMSs and a novel concept named Affine Equivalent Inputs (AEI) to validate the results of SDBMSs. We implemented them as a tool named Spatter (Spatial DBMS Tester) for finding logic bugs in four popular SDBMSs: PostGIS, DuckDB Spatial, MySQL, and SQL Server. Our testing campaign detected 34 previously unknown and unique bugs in these SDBMSs, of which 30 have been confirmed, and 18 have already been fixed. Our testing efforts have been well appreciated by the developers. Experimental results demonstrate that the geometry-aware generator significantly outperforms a naive random-shape generator in detecting unique bugs, and AEI can identify 14 logic bugs in SDBMSs that were totally overlooked by previous methodologies.
... Sistem za upravljanje bazom podataka je softver koji upravlja strukturom i kontroliše pristup podacima uskladištenim u bazi. Ovaj sistem omogućuje definisanje baze podataka, kreiranje baze podataka, manipulaciju bazom podataka, vršenje upita i ažuriranje baze podataka [3]. ...
U radu su analizirane teorijske osnove rješenja knjige polja. Analiza obuhvata model podataka i kreiranje jednog modela za slučaj knjige polja. Analizirana je mogućnost primjene sa praktičnim primjerima podataka koji sadrže rasterske i vektorske podatke, kroz implemetaciju i publikovanje takvih podataka na Geoportalu. Rješenje je dokumentovano.
... While grids have been used in brain mapping in various ways since these early efforts, our use of grids is based on a different motivation. Specifically, we sought to establish a conceptual framework for the datasets reported by our laboratory that allowed for the recording of spatial locations in atlas-dependent and -independent formats (i.e., locations referring to specific features or entities versus locations referring to an invariant grid or field; see Rigaux et al., 2002). This was born from the "need to compute across spatial territory, not just named variables for territories, because certain [immunoreactivity] patterns cut across known territories and spill into unlabeled portions" (Khan, unpublished laboratory blog post, 21 May 2020). ...
The hypothalamus and zona incerta of the brown rat ( Rattus norvegicus ), a model organism important for translational neuroscience research, contain diverse neuronal populations essential for survival, but how these populations are structurally organized as systems remains elusive. With the advent of novel gene-editing technologies, there has been a growing need for high-spatial-resolution maps of rat hypothalamic neurochemical cell types to aid in their functional interrogation by virus-directed cell type-specific gene manipulation or to validate their expression in transgenic lines. Here, we present a draft report describing Chemopleth 1.0 , a chemoarchitecture database for the rat hypothalamus (HY) and zona incerta (ZI), which will eventually feature downloadable interactive maps featuring the census distributions of five immunoreactive neurochemical systems: (1) vasopressin (as detected using its gene co-product, copeptin); (2) neuronal nitric oxide synthase (EC 1.14.13.39); (3) hypocretin 1/orexin A; (4) melanin-concentrating hormone; and (5) alpha-melanocyte-stimulating hormone. These maps are formatted for the widely used Brain Maps 4.0 (BM4.0) open-access rat brain atlas. Importantly, this dataset retains atlas stereotaxic coordinates that facilitate the precise targeting of the cell bodies and/or axonal fibers of these neurochemical systems, thereby potentially serving to streamline delivery of viral vectors for gene-directed manipulations. The maps will be presented together with novel open-access tools to visualize the data, including a new Python programming language-based workflow to quantify cell positions and fiber densities for BM4.0. The workflow produces heat maps of neurochemical distributions from multiple subjects: 1) isopleth maps that represent consensus distributions independent of underlying atlas boundary conditions, and 2) choropleth maps that provide distribution differences based on cytoarchitectonic boundaries. These multi-subject cartographic representations are produced in Python from exported atlas maps first generated in the Adobe® Illustrator® vector graphics environment, which are then reimported and placed directly into the BM4.0 atlas. The soon-to-be-released files can also be opened using the free vector graphics editor, Inkscape. We also introduce a refined grid-based coordinate system for this dataset, register it with previously published spatial data for the HY and ZI, and introduce FMRS (Frequencies Mapped with Reference to Stereotaxy) , as a new adaptation of long-used ephemeris systems for grid-based annotation of experimental observations. This database, which includes all data described in greater detail in Navarro (2020) and Peru (2020), provides critical spatial targeting information for these neurochemical systems unavailable from mRNA-based maps and allows readers to place their own datasets in register with them. It also provides a space for the continued buildout of a community-driven atlas-based spatial model of rat hypothalamic chemoarchitecture, allowing experimental observations from multiple laboratories to be registered to a common spatial framework.
... Database tables can also contain spatial geometries (both vector and raster). In this case the database is called Geodatabase (or also "spatial database"; see [22,23]). The spatial extension that manages the stored geometries enriches the database with GIS functionalities like spatial queries. ...
... Initially, it involves the gathering of all relevant data pertaining to a specific property. This is followed by the processing, updating, and effective dissemination of land-related information, which is stored in a geographically referenced and organized database [5] . Central to the LIS is the implementation of a uniform referencing system, which forms the foundation for linking various types of data and connecting diverse databases associated with land information [6,7] . ...
To address the critical challenges of manual land records and paper maps in Pakistan and similar developing countries, this research introduces a novel web-based Digital Cadastral Land Information System (DCLIS). Leveraging advanced GIS capabilities, including map georeferencing, data visualization, and interactive queries, DCLIS provides a robust and accessible platform for efficient land data management. It overcomes the limitations of traditional systems by eliminating time-consuming procedures, minimizing data duplication, and ensuring data integrity through rigorous validation against field measurements (conducted on 20% of cadastral plots) and cross-checking with existing records. By empowering decision-makers in administration (improved land policy planning), land management (streamlined land ownership verification), and agriculture (precision farming, resource optimization), DCLIS facilitates efficient land resource utilization and promotes sustainable development practices. Moreover, its alignment with responsible land management and renewable energy integration contributes to the global drive towards environmental sustainability. This research bridges the digital divide in land record management and paves the way for more informed decision-making, ultimately promoting the development of sustainable land practices in Pakistan and beyond.
... A spatial database is a database where geospatial data are stored. The desktop GIS application accesses the database and allows certain operations on the data (Rigaux et al., 2002;Swift and Goldberg, 2019). Points, lines, and polygons marked on the map indicate spatial data. ...
... Spatial indices are used to efficiently retrieve multidimensional objects or objects with spatial extents. Hierarchical tree-based spatial index structures [19], [20] are a popular type of spatial index that can be classified into two categories: (a) Grow-and-Post trees [21] such as R-tree [22] and R*-tree [23], which extend the B-tree structure. The main idea is to recursively partition the spatial data based on spatial proximity clustering [24]. ...
Frequent pattern mining (FPM) has played an important role in many graph domains, such as bioinformatics and social networks. In this paper, we focus on geo-social graphs, a kind of social network augmented by geographical information. However, in addition to the exponential time complexity of the problem, we face the challenge of efficient subgraph retrieval since we are interested in patterns in a specific region in such a network. For this reason, we formulate the top-k FPM problem in large geo-social networks. Specifically, we devise a novel framework for subgraph retrieval and FPM mining with a series of optimizations. First, we propose a neighboring-aware R-tree (NaR-Tree) index structure to alleviate the challenge of retrieving subgraphs from a large graph. NaR-Tree is a variant of R-tree in which each nonleaf tree node further maintains some edge statistics information for the rectangle related to it. Second, we define the concept of minimum image-based support of edges (MNIE). With the help of the NaR-Tree and MNIE-based pattern extension approach, a mining algorithm that addresses the problem of exponential candidate patterns is proposed. We also present a lazy retrieval strategy to reduce the frequency of subgraph retrieval. Finally, we adopt an edge sampling approach to further accelerate the mining process. Extensive experiments on real-world and synthesized datasets are conducted to demonstrate the effectiveness and efficiency of our solution.
... Geospatial data are an important subset of spatial data that deals with the locations on surface of Earth. Geographic Information Systems (GIS) are able to work with geospatial data [29]. In some cases, spatial data is combined with temporal data to form spatio-temporal data that offers more dimensions to store and manipulate data. ...
Databases are considered to be integral part of modern information systems. Almost every web or mobile application uses some kind of database. Database management systems are considered to be a crucial element from both business and technological standpoint. This paper divides different types of database management systems into two main categories (relational and non-relational) and several sub categories. Ranking of various sub categories for the month of July, 2021 are presented in the form of popularity score calculated and managed by DB-Engines. Popularity trend for each category is also presented to look at the change in popularity since 2013. Complete ranking and trend of top 20 systems has shown that relational models are still most popular systems with Oracle and MySQL being two most popular systems. However, recent trends have shown DBMSs like Time Series and Document Store getting more and more popular with their wide use in IOT technology and BigData, respectively.
... If this condition holds true, the incident edges are elongated until they hit an input polygon or the bounding box of the whole set B of input polygons. For an efficient implementation we store the polygons in a Sort-Tile-Recursive (STR) packed R-tree [42]. ...
An important task of pattern recognition and map generalization is to partition a set of polygons into groups and to aggregate the polygons within each group to a representative output polygon. We introduce a new method for this task called bicritria shapes. Following a classical approach, we define the output polygons by merging the input polygons with a set of triangles that we select from a conforming Delaunay triangulation of the input polygons’ exterior. The innovation is that we control the selection of triangles with a bicriteria optimization model that is efficiently solved via graph cuts. In particular, we minimize a weighted sum that combines the total area of the output polygons and their total perimeter. In a basic problem, we ask for a single solution that is optimal for a preset parameter value. In a second problem, we ask for a set containing an optimal solution for every possible value of the parameter. We discuss how this set can be approximated with few solutions and show that it is hierarchically nested. Hence, the output is a hierarchical clustering that can be used to obtain multiple levels of detail. An evaluation with building footprints as input concludes the article.
... BBSDLP ditunjuk sebagai walidata peta tanah dan peta lahan gambut yang ditindaklanjuti dengan penguatan pengelolaan data dalam suatu sistem basisdata sedemikian sehingga data cepat tersedia jika diperlukan, lestari serta nilaigunanya bertambah. Basisdata adalah kumpulan data yang banyak yang saling berhubungan yang disimpan dalam suatu lingkungan komputer (Rigaux et al. 2002). Pengelolaan basisdata terkomputerisasi di BBSDLP telah dimulai tahun 1990-an yang terus diperkuat dan tahun 2013 diterapkan revitalisasi (Sulaeman et al. 2014;. ...
Formulasi kebijakan spasial dan perakitan teknologi lahan rawa memerlukan informasi spasial dan karakteristik lahan rawa. Balai Besar Litbang Sumberdaya Lahan Pertanian (BBSDLP) telah dan terus melakukan survei dan pemetaan di lahan rawa termasuk lahan gambut, yang menghasilkan banyak data. Selain itu, BBSDLP telah melakukan revitalisasi pengelolaan basisdata sejak 2013, termasuk pengembangan basisdata spasial lahan rawa (InaWetSoils). Tulisan ini melaporkan status terkini InaWetSoils dan mendiskusikan tantangan serta strategi pengembangannya ke depan. Revitalisasi dilakukan pada 3 pilar, yaitu: (i) pembaruan perangkat keras dan lunak, sistem jaringan, dan manajemen, (ii) penguatan sumberdaya manusia pengelola, dan (iii) kolasi, konservasi, restorasi dan restrukturisasi data. Struktur dan desain InaWetSoils mengacu pada soil geographic database yang dikemukan Zinck dan Valenzuela tahun 1990 dengan modifikasi, dimana basisdata terdiri atas beberapa file, yaitu: landform, titik pengamatan, profil pewakil, nama polipedon, dan satuan peta (peta tanah, lahan gambut, dan lahan rawa). Dataset berasal dari hasil kegiatan pemetaan BBSDLP, kerjasama dengan pihak ketiga, dan sumbangan sukarela para pemilik data. Pengembangan basisdata meliputi: (i) pengumpulan, seleksi, harmonisasi dan standarisasi data, dan (ii) geovisualisasi dan delivery informasi. Saat ini, InaWetSoils berisi data pengamatan tanah, peta lahan gambut berbagai versi, dan peta tanah. Sebanyak 11.264 titik pengamatan di lahan rawa dikoleksi dalam basisdata ini. Tantangan yang dihadapai saat pengembangan adalah: (i) data pengamatan yang tidak standar, (ii) teknik positioning data titik pengamatan dari deskripsi profil tanah, (iii) teknik joining antara data koordinat dengan deskripsi profil. Basisdata ini perlu terus diperkaya isinya dan diperlihara keberadaannya sehingga fungsinya sebagai pengelola arsip data spatial dan tabular lahan rawa termasuk lahan gambut dapat maksimal. Strategi ke depan meliputi: (i) akselerasi harmoninasi data melalui perbaikan pengelolaan entry data, (ii) pengkayaan data melalui pengembangan dan penguatan kerjasama antar lembaga, (iii) ujicoba dan adopsi teknik geovisualisasi dan spatial data mining untuk penurunan informasi secara otomatis
... In general, the functionality of PostGIS is comparable to Esri ArcSDE, Oracle Spatial, and DB II spatial extender. Like other spatial databases [84], PostGIS combines the advantages of classical GIS software, mainly the possibility of spatial analysis [85], with the advantages of database management systems (DBMS) like indexing, transactions, and concurrency [86,87]. The implementation of the Open Geospatial Consortium (OGC) "Simple Features for SQL" [82] provides powerful features for managing, retrieving, and analyzing geospatial data. ...
This chapter provides an overview over the current spectrum of free and open source licensed geospatial software tools and communities.
The number of available open source geospatial tools continues to grow and diversify, while new fields of application emerge. This chapter presents a selection of well-established free and open source software (FOSS) tools as reference cases, including software libraries, desktop applications, web mapping, databases, and use with portable devices, mostly based on the portfolio of FOSS tools, which is curated and maintained by the metaproject OSGeoLive, which is also discussed in this chapter.
FOSS software options are available for almost any kind and magnitude of geospatial task, for some niche tasks, they can even be the only options. Geospatial FOSS are available for portable devices, desktop machines, high-performance cluster environments, as Web-based applications or Software-as-a-Services (SaaS) in cloud environments. While a range of different open source licenses exists and are applied to geospatial software, they all adhere to the same key principles of openness and freedom for the user, most notably the rights to run the program, access the source code for study and improvements, and to redistribute copies of the program and its modifications.
This allows for transparency of the computations, as the source code implementation of all algorithms can be verified and possibly improved when necessary. Also public access to the code base ensures sustainable long term availability of the software tool to the users.
FOSS geospatial software has proven to be just as reliable and suitable for professional use as closed-source software alternatives.
... The real world is composed of geographic objects (roads, cities, etc.). In geographic information science, geographic information systems (GIS) enable the representation of geographic objects in their environment using two components [48]. ...
The real world and its geographic objects are modeled and represented in different spatial databases. Each of these databases provides only a partial description (in space and time) of the geographic objects represented. Sometimes, producers and users of databases need to connect several of them for updates or comparisons. Much of the work in spatial database management focuses on matching these spatial databases and more particularly network databases, such as road networks. With regard to network data, one situation remains neglected, that of matching a linear database (with polylines objects) with a surface database (with polygons objects). In any case, users also need to connect these two types of spatial database. In this paper, a case study is made using French examples (Cachan, near Paris), as well as international case studies (Bordeaux in France, Victoria in Canada, and Copenhagen in Denmark), to propose an approach intended to make coherent network geographical objects in two different reference frames (linear and surface). This issue is addressed here through the example of road data. The surface data are then formalized in order to adapt them to linear data describing the same geographical objects. In the end, a polygon in the surface data corresponds to a single polyline in the linear data. This consistency should simplify the transfer of information from one reference frame (linear or surface) to the other. In other words, the methodology developed aims to make linear and surface geographic data interoperable.
Context: Social mapping applications are essential tools for understanding regional needs. In addition to physical geography, these maps integrate data on infrastructure, activities, and social demands— visualizing regions, points of interest, and relevant layers. This approach provides a clear and comprehensive view to support business, government, and social decisions. Problem: Managing social mapping data presents challenges, especially when storing sets of coordinates. This limits specialized database functions, impacting application performance in advanced geospatial functions. In particular, it is difficult to define which technologies are most appropriate to handle such data. Solution: We propose to use geographic databases such as PostgreSQL and MySQL Spatial. To do this, we propose to identify which functionalities are facilitated by these two technologies and compare their performance in executing these functionalities. IS Theory: Guided by the sociotechnical theory of Innovations Theory, this study examines how IS technologies interact in social contexts. Method: This study used a qualitative survey of professionals to propose functionalities considered useful for social analysis and an empirical experiment on the performance of the functionalities using PostGIS and MySQL Spatial databases. Results: Using a geographic database improved data processing, especially for large data. PostGIS showed better scalability and faster response times than MySQL Spatial as data volumes increased. Contributions and Impact on the IS field: This research improves the handling of geospatial data in IS, offering a practical solution to optimize queries, benefiting academia and industry.
Geographic Information Systems (GIS) are among the sciences and technologies that have experienced remarkable growth in recent decades. Today, it can be confidently stated that few earth-related sciences do not utilize the capabilities and functionalities of GIS for processing spatial data. It is precisely this widespread demand that has driven the rapid development of GIS, equipping it with the tools needed to process spatial data for users. In line with this, specific academic disciplines focusing on the application of GIS have also expanded significantly alongside this technology.
A new trend currently observed is the use of this technology by the general public to meet their informational needs in various fields, such as tourism, road weather forecasting, route planning in urban and intercity roads, property buying and renting, and thousands of other applications, exemplifying this new perspective.
Given the scientific and academic community's need for resources to familiarize various audiences with the principles and foundations of this field, numerous books have been written globally, each explaining its functionalities from different angles. Fortunately, some of these books have been translated into Persian and made available to users. However, the absence of a comprehensive book in Persian that could convey all aspects of GIS to diverse users has been the primary motivation for compiling this book. In writing this book, efforts have been made to utilize all available Persian and English resources, including books, articles, and websites, a complete list of which is provided at the end of the book for further reading by interested readers.
This book is organized into nine chapters. The first chapter introduces the basic concepts of this scientific field, while the second chapter examines the characteristics of geographic databases from various perspectives. The third chapter discusses coordinate systems and projection systems. Chapters four and five elaborate on different methods of analyzing spatial data in vector and raster environments. The preparation and processing of digital terrain models and network analysis, as the most critical operational components of GIS, are discussed in chapters six and seven, respectively. The ninth chapter explores the concept and methodology of modeling in a GIS environment, and the final chapter explains the features of mobile GIS as one of the emerging trends in this field.
سيستم هاي اطلاعات جغرافيايي از جمله علوم و فناوري هايي است كه در طي ده هاي اخير از
رشد بسيار چشمگيري برخوردار شده است و شايد امروزه به جرات بتوان گفت كه كمتر علومي مرتبط با زمين باشد كه از امكانات و توانايي هاي آن در پردازش داده هاي مكاني استفاده ننمايد. با توجه به همين نياز گسترده بوده است كه سيستم هاي اطلاعات جغرافيايي توسعه روزافزوني پيدا كرده و خود را به امكانات پردازش داده هاي مكاني موردنياز كاربران مجهز كرده است. با توجه به اين موضوع رشته هاي علمي خاص در زمينه بكارگيري سيستم اطلاعات جغرافيايي به موازات اين فناوري توسعه زيادي يافته است. رويكردهاي جديدي كه در حال حاضر مشاهده مي شود رويكرد استفاده از اين فناوري توسط عموم مردم براي رفع نيازهاي اطلاعاتي آنها در زمينه هاي گوناگون از جمله گردشگري، هواشناسي جاده اي، تعيين مسير حركت در جاده هاي شهري و بين شهري، خريد و اجاره املا ك موردنياز و هزاران كاربرد ديگر مصداق اين نگرش جديد مي باشد.
نظر به نياز جامعه علمي و دانشگاهي به منابع علمي براي آشنايي مخاطبين مختلف با اصول و مباني اين رشته علمي، كتابهاي متعددي در سطح جهاني به رشته تحرير درآمده است كه هريك از آنها با زواياي مختلف كاركردهاي آن را تبيين نموده اند كه خوشبختانه بخشي از اين كتابها به فارسي نيز ترجمه شده و در اختيار كاربران مختلف قرار گرفته است، ولي نبود كتاب جامع به زبان فارسي كه بتواند تمامي زواياي آن را به كاربران مختلف انتقال دهد انگيزه اصلي تدوين كتاب حاضر بوده است. در تاليف اين كتاب سعي گرديده از كليه منابع فارسي و انگليسي در اختيار از جمله كتب، مقالات و وب سايت هاي اينترنتي استفاده شود كه فهرست همه آنها در انتهاي كتاب براي مطالعه بيشتر خوانندگان ارائه گرديده است.
اين كتاب در نه فصل تدوين گرديده است كه فصل اول آن به بيان مفاهيم پايه اين رشته علمي پرداخته و در فصل دوم ويژگي هاي پايگاه اطلاعات جغرافيايي از ابعاد مختلف مورد بررسي قرار گرفته است. در فصل سوم سيستم هاي مختصات و سيستم هاي تصوير مورد بررسي قرار گرفته و فصول چهارم و پنچم به تشريح انواع روش هاي تحليلي داده هاي مكاني در محيط برداري و رستري پرداخته است. تهيه و پردازش مدلهاي رقومي زمين و تحليل شبكه به عنوان مهمترين اجزاء عملياتي سيستم اطلاعات جغرافيايي به ترتیب در فصول شش و هفت مورد بحث قرار گرفته است. فصل نهم از اين كتاب به بررسي مفهوم و چگونگي ساخت مدل در محيط سيستم اطلاعات جغرافيايي پرداخته و در فصل آخر نيز به تشريح ويژگي هاي سيستم اطلاعات جغرافيايي همراه به عنوان يكي از رويكردهاي جديد اين رشته پرداخته شده است.
Today, the processing of large amounts of spatial data in distributed systems plays a crucial role in many areas of our life. Large data are often unstructured, and special algorithms are required for its processing. One of the methods for analyzing large data is a spatial analysis. The source of large data in this case is often the geographical information system. In this article, a benchmark is considered to evaluate the frameworks that work with such data. Also, the evaluation results of three frameworks according to developed benchmark are presented: GeoSpark, STARK, SpecialSpark. In the course of this paper, we considered a benchmark of two types: macrobenchmark and microbenchmark. In the paper, testing of topological predicates on various topological data is also considered. The comparison was made using the DE-9IM model. This model is used to determine the types of topological relationships, such as intersection, equality, etc. The main problem of comparing the data frameworks was that not all of them support the operations of the selected model, which influenced the formation of scenarios for the microbenchmark and macrobenchmark, since it was impossible to compare all the DE-9IM items.
Spatial Database Management Systems (SDBMSs) aim to store, manipulate, and retrieve spatial data . SDBMSs are employed in various modern applications, such as geographic information systems, computer-aided design tools, and location-based services. However, the presence of logic bugs in SDBMSs can lead to incorrect results, substantially undermining the reliability of these applications. Detecting logic bugs in SDBMSs is challenging due to the lack of ground truth for identifying incorrect results. In this paper, we propose an automated geometry-aware generator to generate high-quality SQL statements for SDBMSs and a novel concept named Affine Equivalent Inputs (AEI) to validate the results of SDBMSs. We implemented them as a tool named Spatter ( Spat ial DBMS Tes ter ) for finding logic bugs in four popular SDBMSs: PostGIS, DuckDB Spatial, MySQL, and SQL Server. Our testing campaign detected 34 previously unknown and unique bugs in these SDBMSs, of which 30 have been confirmed, and 18 have already been fixed. Our testing efforts have been well appreciated by the developers. Experimental results demonstrate that the geometry-aware generator significantly outperforms a naive random-shape generator in detecting unique bugs, and AEI can identify 14 logic bugs in SDBMSs that were totally overlooked by previous methodologies.
An important task of pattern recognition and map generalization is to partition a set of disjoint polygons into groups and to aggregate the polygons within each group to a representative output polygon. We introduce a new method for this task called bicriteria shapes. Following a classical approach, we define the output polygons by merging the input polygons with a set of triangles that we select from a conforming Delaunay triangulation of the input polygons’ exterior. The innovation is that we control the selection of triangles with a bicriteria optimization model that is efficiently solved via graph cuts. In particular, we minimize a weighted sum that combines the total area of the output polygons and their total perimeter. In a basic problem, we ask for a single solution that is optimal for a preset parameter value. In a second problem, we ask for a set containing an optimal solution for every possible value of the parameter. We discuss how this set can be approximated with few solutions and show that it is hierarchically nested. Hence, the output is a hierarchical clustering that corresponds to multiple levels of detail. An evaluation with building footprints as input and a comparison with α -shapes that are based on the same underlying triangulation conclude the article. An advantage of bicriteria shapes compared to α -shapes is that the sequence of solutions for decreasing values of the parameter is monotone with respect to the total perimeter of the output polygons, resulting in a monotonically decreasing visual complexity.
Following two successful editions, the third edition of GIS: A Computing Perspective has been completely revised and updated, with extensive new content reflecting the significant progress that has been made in the realm of GIS within the last 20 years. Major new topics covered for the first time in this edition include: graph databases and graph query languages, ontology engineering and qualitative spatial reasoning, geosensor networks and GeoAI, decentralized computing and online algorithms, and critical GIS and data sovereignty.
Features
Includes an entirely new chapter on AI and GIS, including ontologies and the Semantic Web, knowledge representation (KR) and spatial reasoning, machine learning and spatial analysis, and neural networks and deep learning
Presents new material reflecting the advances made in cloud computing, stream computing, and sensor networks, as well as extensively revised and updated content on cartography, visualization, and interaction design
Connects the technology to the social aspects and implications of GIS, including privacy and fair information practices, FATE (fairness, accountability, transparency, and ethics), and codes of conduct for responsible use of GIS
Integrates the necessary background to foundational areas, such as databases and data structures, algorithms and indexes, and system architecture and AI, provided in context so readers new to those topics can still understand the concepts being discussed
Incorporates over 20 carefully explained spatial algorithms; over 60 inset boxes with in-depth material that enriches the central topics; and more than 300 color figures to support the reader in mastering key concepts
Welcomes a new coauthor, Qian (Chayn) Sun, to the third edition, who brings her expertise in topics such as web mapping, cloud computing, critical geography, and machine learning with big spatial data
Intended for anyone interested in understanding GIS, especially students taking upper-level undergraduate and graduate courses in computer science and geography, as well as academics, researchers, practitioners, and professionals working in the field and involved in advanced GIS projects.
A query language for Building Information Models allows users and third-party application programmers to not only analyze the digital building under specific criteria but also to extract partial models from a full building model. This functionality is of crucial importance, since the full BIM is meant to comprise the information of all domains involved in the planning process, but an individual user or programmer is normally interested in only a small subset of it. To specify this subset, a formal language is required which makes it possible to formulate conditions the resulting data set has to fulfill. This concept is also known as providing a certain view of the data available. This chapter gives an overview of the currently available query technologies for BIMs and compares the different options in terms to expressive power and ease of use. The emphasis of the chapter, however, lies in the introduction of spatial query technology for BIMs that has been developed by the authors. Spatial operators extend the analysis and submodel specification capabilities of a query language substantially by providing an intermediate level of abstraction that is close to the human understanding of the geometric-toplological properties of building components and the relationships between them.
GIS technology has enabled the possibility to analyze and define decision making by managing geospatial information. With the rapid development of the technology, GIS tools and analysis can be operated through internet communications. GIS as web services enables us to implement tools and services which are accessible trough the web and can be used and managed by every user. Web GIS technologies has enabled the possibility to manage and analyze geospatial information through web services. In this article we are showing a web-based GIS solution for managing local government property taxes through analyzing different geospatial data. The GIS application will facilitate property tax collection and administration through creation of the tax-related elements of a working territory register. The web-based application's primary functionality is to support parcel-and building-based query, selection, display, and mapping.
In previous units, you learned about GIS concepts, spatial data, data models and data structures. In a typical GIS, both spatial and non-spatial data are used. Spatial data describes the location of features, whereas non-spatial data describes their characteristics. Attribute data is another name for non-spatial data. Geospatial data is a combination of both types of data. It means that both (spatial and non-spatial) data are required for a GIS to function properly. In this chapter, we will go over the concept of non-spatial data in depth. On the completion of this chapter students will be able to learn the following concepts about non-spatial data/attribute data:
Introduction
Basics of the Non-Spatial Data in geoinformatics
Concept of the Relational Model
Understanding the concept of joins, relates and relationship classes within GIS
Spatial Join
Concept of the entry of attribute (tabular data)
Fields and attribute data modification.
KeywordsNon-spatial dataDatabaseSSURGONormalizationRelationshipData entry
Background Recent agricultural innovations have cast question on the sustainability of current production techniques, which have felt the brunt of the coronavirus pandemic's devastating impact on the country's economy and agriculture. A lack of available labour and other inputs, as well as falling output prices due to falling commodity demand in some markets, have all disrupted production in the sector. To better the economic situation of the farmers who have registered with the fisheries biosecurity division, off-farm employment is referred to as a significant approach for supplementing farm household income and maintaining rural livelihoods. For rural communities and families, making a living from the land is as important as farming.
Remote sensing data, especially satellite observations make available large databases related to marine biosphere. This tremendous amount of the data causes a difficulty to acquisition, processing and evaluation processes. Google Earth Engine (GEE) platform make possible to overcome this difficulty by its state of art structure. Thus, GEE platform was included to study to process and evaluate the chlorophyll-a data for the sea of Marmara. The Sea of Marmara was considered in 2 main parts as North and South Marmara. These parts also divided into 6 sub-regions and analyzed as 12 different regions in total. MODIS (Moderate Resolution Imaging Spectroradiometer)-Aqua data were acquired between the years 2003-2021 with the GEE platform for all examined sub-regions and make them available for analysis. Approximately 19 years of arranged chl-a concentration data were visualized and evaluated by grouping them according to sub-regions, months and years. As expected, the highest concentration of chl-a was observed in the Sea of Marmara in square KM6, which includes the Gulf of Izmit and has limited regeneration The lowest concentration values throughout the years were found in the areal average values of the KM4 square under the influence of the jet stream formed by the upper water from the Black Sea. When the monthly data are examined, it can be said that the primary production in general takes place intensively in the whole of the Marmara Sea in the spring season. In the context of this study, the accuracy of the division of the Sea of Marmara in two main axes as North and South is clearly seen in the analyzes within the time series. We evaluate that the similarity of chl-a concentrations in the Marmara Sea to the period before 2007 and 2020 requires a special attention as evidence of a repetitive process rather than an ecological coincidence.
The recent technological advances in geospatial data collection have created massive data sets with better spatial and temporal resolution than ever. To properly deal with these data sets, geographical information systems (GIS) must evolve to represent, access, analyze and visualize big spatiotemporal data in an efficient and integrated way. In this paper, we highlight challenges in temporal GIS development and present a proposal to overcome one of them: how to access spatiotemporal data sets from distinct kinds of data sources. Our approach uses Semantic Web techniques and is based on a data model that takes observations as basic units to represent spatiotemporal information from different application domains. We define a RDF vocabulary for describing data sources that store or provide spatiotemporal observations.
The appraisal discipline places the emphasis on how the characteristics related to the location strongly affect the formation of property prices. These characteristics are attributable to the territorial area of reference, which is characterized by multiple factors of a political, social, economic, institutional nature. This article, starting from this assumption, explores what is instead happening in urban areas following the advent of the “society of globalization”, which has involved the creation of multicultural, multi-ethnic, and multi-religious contexts, trying to capture possible elements of convergence between the disciplines of estimation and social research. The intent is to show and describe the feeling of social distance perceived within the peripheral areas of the urban centre of Cosenza using property prices as a narrative variable. Starting from the collection and analysis of commercial information relating to the area in question, datasets are constructed, and cartographic representations of real estate prices are created according to GIS logic. Without claiming to be exhaustive, but rather to solicit further elements for reflection and debate on the theme of multiculturalism and social distance, the article proposes the use of new types of data, analysis techniques and dynamics of cooperation between disciplines only apparently distant.
The expeditious market transformation to smart portable devices has created an opportunity to support activity recognition using the embedded sensors of these devices. Over the last decade, many activity recognition approaches have been proposed for various activities in different settings. The motion mode recognition or transition in modes of the device is needed in many technological domains. This approach detects a variety of motion modes for a human using a portable device. The approach includes many aspects: usability, mounting and data acquisition, sensors used, signal processing, methods employed, features extracted, and classification techniques. This chapter sums up with a comparison of the performance of several motion mode recognition techniques. In this research, multiple behaviors were distinguished using embedded inertial sensors in portable smart devices. In our experiments, we selected four types of human activity, which are walking, standing, sitting, and running. A combination of one of the embedded mobile sensors and machine learning techniques have been proposed in order to do this kind of classification. The proposed system relies on accelerometer data to classify user activities. The results show that using SVM classifier showed better accuracy for detection compared to the outcomes of the other classifiers like KNN and ensemble classifiers. For future work, classification of other human activities like cycling, driving, and swimming will be investigated
Despite data growth being a known problem for several years, there are more and more people, tools and devices to create and share data, and the need for tools to infer their provenance and quality is even more important than before. Research on data provenance focuses on W3C PROV and databases (where, why, how). However, in the particular case of spatial data, research has mainly focused on handling spatial data provenance from documents and workflows, but there is no literature approaching the topic of spatial data provenance in DBMS and queries.
This paper deals with the computation of How–, Why– and Where– provenance in spatial database queries. It presents an evaluation of how the formalism and methods proposed to deal with general-purpose database queries behave when dealing with spatial data. Two tools are used to manage provenance in databases and a discussion of the results and guidelines for future work are presented. This is a first contribution towards dealing with spatial data provenance by tuple, attribute and query, whereas previous work has only focused on the management of provenance at a coarser level, namely documents and workflows.
Kondisi infrastruktur di Indonesia cukup memprihatinkan, terutama berkaitan dengan infrastruktur jalan dan pendidikan. Di beberapa wilayah khususnya pedalaman atau desa terpencil, sering ditemukan jalan yang rusak sehingga akses kendaraan menjadi terganggu. Selain jalan rusak juga ditemukan beberapa jembatan dengan kondisi membahayakan, padahal jembatan tersebut merupakan satu-satunya akses jalan yang harus dilalui. Tidak hanya kerusakan jalan, namun juga banyak ditemukan kerusakan infrastruktur pendidikan. Seperti halnya kondisi bangunan sekolah yang kurang layak dan fasilitas yang belum memadai. Kerusakan infrastruktur di Indonesia tidak sepenuhnya diketahui oleh pemerintah. Hal ini disebabkan karena minimnya informasi yang beredar. Masyarakat juga mengalami kesulitan terutama dalam menyampaikan keluhan-keluhan kerusakan yang ada di sekitar. Dengan adanya laporan dari masyarakat, akan membantu pemerintah dalam mengawasi kerusakan infrastruktur yang ada di setiap wilayah. Sistem pelaporan dan pemetaan kerusakan infrastruktur menawarkan mekanisme pelaporan dan pemetaan menggunakan metode Volunteered Geographic Information, di mana pengguna dapat berpartisipasi dengan mengirim laporan kerusakan infrastruktur yang ada di mana saja sesuai lokasi keberadaan terkini. Laporan yang telah terkirim akan tersimpan di dalam basis data dan koordinat lokasi akan muncul di halaman peta secara otomatis, sehingga semua pengguna dapat mengetahui titik-titik kerusakan yang ada di sekitar. Sistem dibangun menggunakan platform Android sebagai antarmuka pengguna untuk mengirim laporan dan melihat informasi kerusakan infrastruktur.
An improved understanding of the chronology of Antarctic ice sheet deglaciation since the Last Glacial Maximum (LGM) represents a fundamental tool to better define the origin of past and future meltwater influx in the global oceans. Relict shorelines and other evidence of past Relative Sea Level (RSL) evolution were widely used to understand past ice sheet history and to improve predictions of climate-controlled sea level evolution. In the last decades, RSL data in the Antarctic region have been mostly produced using a wide range of geomorphic evidence such as beach and marine deposits, marine terraces and isolation basins. However, the lack of a geographic common framework that includes
data derived from different sources, limits the accessibility to the information. Here we present a new cartographic approach to create an open access geodatabase of the postglacial paleo-shorelines by using a standard collecting pattern. Cartographic Antarctica Repository (CAR) includes RSL data along the coasts of the Antarctic Peninsula
and South Shetland Islands. Results show the advantages to use CAR for integrating data and supporting spatial analyses, by representing an easy and usable tool for the improvement of shoreline evolution definition and the planning of Antarctic coast investigations. CAR is dynamic repository project that will be further expanded on other Antarctic regions too, integrating fully into the wide reference context of the free access Antarctic datasets.
We live in the information age where spatial information is one of the critical element that provide an edge over other as it supports in decision making, e-governance, business, daily routine tasks etc. From the past few decades, the importance of Geographic Information System (GIS) and spatial data has been realized. This has resulted in the fast growth and high market demand of GIS and georeferenced data. GIS is a computer based system in which data is collected, analyzed, manipulated and stored for future use, and occupies a significant place in our life today. As the GIS evolved, it is noticed that there is a need of easy accessibility of GIS by any one from anywhere. This results in the development of Web GIS that is continuously gaining popularity. Web GIS is a Web application that provides GIS capabilities. In other words, GIS functionality is performed over the Web in Web GIS. A user utilises a Web application through a client which can be a Web browser, a desktop application or a mobile application. Web GIS based applications/ systems helps the government as well as the common public in getting the geospatial information.
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