Spatial Data Management Research Articles

Factors influencing integrated information management: Spatial data infrastructure in Pakistan

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond.

Assessing the Performance of Current Strategic Policy Directions towards Unfolding the Potential of the Culture–Tourism Nexus in the Greek Territory

In the UN Agenda 2030, tourism acquires a salient position as a critical sector, directly or indirectly influencing a number of Sustainable Development Goals (SDGs). The pursuit of Sustainable Tourism (ST) is founded on the respectful exploitation of the sector’s core ‘raw material’, i.e., the precious and vulnerable nexus of natural and cultural heritage, and a cooperative multi-actor endeavor of all those having a stake in this shared good. Strategic tourism policy decisions, formulated at the state level, frame actors’ actions, favoring a balance among economic, societal and environmental goals; and a transparent, concrete and supportive investment landscape, allowing the tourism sector to blossom. But how successful are these policy decisions in promoting a sustainable, resilient and durable tourism model by instigating the entrepreneurial community to invest in the vibrant culture–tourism complex? An effort to respond to this concern is made in this work, grounded in the ‘Culture–Tourism–Policy’ triptych and their interaction, the ‘policy cycle’ as a means of assessing policy performance towards establishing a sustainable/resilient ‘marriage’ of ‘Culture–Tourism’, and GIS-enabled spatial data management for an evidence-based assessment of policy outcomes. These three factors are closely intertwined in the assessment of strategic tourism policy decisions’ performance in a culturally vibrant and highly reputed destination, Greece.

Geoportal for highways as a basic element of spatial data infrastructure

This article is devoted to the development of geographic information systems, WEB-mapping and information integration into the spatial data infrastructure (SDI). The analysis of the history of the creation of spatial data infrastructure in the world community and in Russia is carried out, the specifics of the development of Web-GIS and SDI are revealed. As part of the study, the analysis of the world experience of using the Web-GIS of highways, as well as the current state of applied geoinformation systems in Russia was carried out. The key issue considered in the article is the development of the architecture of a Web GIS (geoportal) of highways for the purposes of accounting, analysis and systematization of spatial data. The main features of the formation of systems for recording data on highways are determined, the main tasks solved by these systems are given. The automobile road is a complex and lengthy object, which should become the spatial basis for the development of spatial data infrastructure in Russia. A block diagram of the main modules of the geoportal has been developed and proposed. The main functionalities implemented at each stage of the Web GIS operation are highlighted. As a result of the implementation of the proposed architecture of the geoportal, a system of analysis, systematization and management of spatial data of a road enterprise was introduced. The use of a geoportal significantly affects the optimization of the performance of various works on highways. Also, the result of the work (Web-GIS) can be implemented as a system for analysis, accounting and systematization of data on other extended linear objects (power lines, gas pipelines, water pipelines, etc.). A user interface of a geoportal, a structure for storing spatial data, modules for transforming coordinates and information, blocks for loading, analyzing and unloading data have been developed. The proposed architecture is versatile and easy to use, which is a clear advantage over the analog systems described in the study. Further study of the research topic opens up prospects for the rapid development of integrated geoinformation software tools on the Internet and a deeper understanding of the need to develop spatial data infrastructure.

An Indoor Navigation Methodology for Mobile Devices by Integrating Augmented Reality and Semantic Web.

Indoor navigation systems incorporating augmented reality allow users to locate places within buildings and acquire more knowledge about their environment. However, although diverse works have been introduced with varied technologies, infrastructure, and functionalities, a standardization of the procedures for elaborating these systems has not been reached. Moreover, while systems usually handle contextual information of places in proprietary formats, a platform-independent model is desirable, which would encourage its access, updating, and management. This paper proposes a methodology for developing indoor navigation systems based on the integration of Augmented Reality and Semantic Web technologies to present navigation instructions and contextual information about the environment. It comprises four modules to define a spatial model, data management (supported by an ontology), positioning and navigation, and content visualization. A mobile application system was developed for testing the proposal in academic environments, modeling the structure, routes, and places of two buildings from independent institutions. The experiments cover distinct navigation tasks by participants in both scenarios, recording data such as navigation time, position tracking, system functionality, feedback (answering a survey), and a navigation comparison when the system is not used. The results demonstrate the system’s feasibility, where the participants show a positive interest in its functionalities.

INTEGRATION OF URBAN SPATIAL DATA MANAGEMENT AND VISUALIZATION WITH ENTERPRISE APPLICATIONS USING OPEN-SOURCE SOFTWARE

Abstract. In recent years, efficient management of urban spatial data has played a major role in improving urban planning projects both in terms of cost and time savings. Since urban planning projects involve various disciplines like city planning and architecture as well as working with different spatial data, one of the main challenges is how to integrate and manage these multimodal data for a proper workflow. Currently, the involved companies are using project management and accounting systems, so called Enterprise Resource Planning (ERP) systems to handle these complex urban projects - that partly handle the same data objects as stored in urban spatial databases but without any spatial reference. Embedded in the application example of an urban redevelopment area, which according to the German Urban Development Promotion Act aims at financially promoting urban districts in need of renewal, project-related spatial and non-spatial data that were previously kept separate are linked and integrated. Therefore, our work presented here bridges the gap between these two types of application systems, the non-spatial accounting system called Finanz Management System (FMS) and the urban spatial databases. FMS manages information related to parcels, buildings, property owners, as well as the legally required payments connected to urban development, while an urban spatial database manages the geodata. We describe the prerequisites, procedures, and software development steps for coupling different types of applications by providing an example of the Enterprise Application Integration System (EAI). Our innovative integration process aims at making information from the spatial database available in FMS and vice versa, and allows updating the corresponding databases. Our work shows the potential of open-source software for cadastral data processing and visualization as well as accounting procedures for urban planning projects.

A Special Collection: Drones to Improve Insect Pest Management.

The Special Collection Drones to Improve Insect Pest Management presents research and development of unmanned (or uncrewed) aircraft system (UAS, or drone) technology to improve insect pest management. The articles bridge from more foundational studies (i.e., evaluating and refining abilities of drones to detect pest concerns or deliver pest management materials) to application-oriented case studies (i.e., evaluating opportunities and challenges of drone use in pest management systems). The collection is composed of a combination of articles presenting information first-time published, and a selection of articles previously published in Journal of Economic Entomology (JEE). Articles in the Collection, as well as selected citations of articles in other publications, reflect the increase in entomology research using drones that has been stimulated by advancement in drone structural and software engineering such as autonomous flight guidance; in- and post-flight data storage and processing; and companion advances in spatial data management and analyses including machine learning and data visualization. The Collection is also intended to stimulate discussion on the role of JEE as a publication venue for future articles on drones as well as other cybernectic-physical systems, big data analyses, and deep learning processes. While these technologies have their genesis in fields arguably afar from the discipline of entomology, we propose that interdisciplinary collaboration is the pathway for applications research and technology transfer leading to an acceleration of research and development of these technologies to improve pest management.

A ECOLOGIA DE PEIXES DE RIACHO SOB A PERSPECTIVA DA ECOLOGIA DE PAISAGENS

Landscape ecology emphasizes the interaction between spatial patterns and ecological processes, i.e., the consequences of spatial heterogeneity across various scales. It is an interdisciplinary science that seeks to understand the relationships between ecological patterns and processes considering different spatial and temporal scales. This understanding has been supported by the rapid development of a methodological framework, largely based on Geographic Information Systems (GIS). Thus, it has allowed understanding how ecological processes are affected by anthropogenic activities that trigger profound changes in ecosystems, such as habitat loss and fragmentation. Although commonly applied to studies in terrestrial ecosystems, there is a time lag in both theoretical development and methodological adaptation of landscape ecology applied to studies in streams, especially in Brazil. Methodological adaptations are necessary considering the particularities of aquatic environments in relation to terrestrial ones. For example, streams have a hierarchical spatial organization that results in local conditions dependent on the regional context. In fact, streams are connected to the landscape in which they are inserted through multiple spatial and temporal scales. This hydrologic connectivity, and the low ratio/proportion of aquatic/terrestrial areas, in turn results in anthropogenic impacts accumulating along the hydrographic networks. Considering the above, the objectives of this chapter are: (1) Introduce the general concepts of landscape ecology; (2) Present the main methods of spatial data acquisition and management relevant to stream approaches; (3) Describe the spatial and temporal scales relevant to stream ecology and (4) Discuss the potential of landscape ecology to assess human impacts on streams. Landscape ecology has much to offer to the study of stream fish in Brazil and has shown to be a promising approach for advancing this frontier of knowledge.

Accuracy Assessment of Large-Scale Topographic Feature Extraction Using High Resolution Raster Image and Artificial Intelligence Method

Feature extraction is the most important application in spatial data management for updating of topography databases. The importance of features extraction from high resolution raster imagery arises from the fact that it enhances the efficiency of map generation and map production. Presently many studies have been addressed to extract topographic using semi-automated methods using various types of technologies. The objective of the study is to evaluate the planimetry accuracy of topographic features extracted using combination of high resolution and artificial intelligence algorithm. Conventional methodology for features extraction is time consuming and costly. Therefore, automated methods are crucial needed for efficient large area mapping with cost efficient. Maxar 0.3 cm high resolution raster imagery is an important issue in many application domains. The Maxar-Ecopia method is applied in this study to update the large-scale topographic map. Maxar-Ecopia method demonstrates the potential use of high-resolution raster imagery as main source and artificial intelligence algorithm for topographic feature extraction. The planimetric accuracy (RMSEr) of vector extraction is 0.882m. This method is highly accepted to be applied for rapid updating of large-scale topographic map.

Selection of Potential Sites for Sustainable Development of Solar Photovoltaic Plants in Northeastern Brazil Using GIS and Multi-Criteria Analysis

Brazil has one of the highest percentages of solar radiation in the world and which it is a favorable condition to generate electricity using solar photovoltaic systems. The construction of photovoltaic plants depends on the site selection that influences the electricity generation capacity and the socio-economic benefits that can be derived from it in the future. This article proposes to combine Spatial analysis that involves the acquisition and management of spatial data using a Geographic Information System (GIS), and the fuzzy multi-criteria AHP-TOPSIS model to identify potential locations for the installation of solar photovoltaic systems in the northeastern region of Brazil, State of Pernambuco. The combination of GIS and fuzzy AHP-TOPSIS offers the user the possibility of assigning merit categories to the mapping according to multiple assessment criteria. The GIS include factors of the restrictions and criteria. The restrictions are inserted into the GIS using layers defined from current legislation (urban areas, undeveloped land, community sites, infrastructure, etc.), which reduce the study area by eliminating zones in which PV installation is not permitted. The results show that 22 and 40% of the area of the state of Pernambuco has the very high and high potential, respectively, for the implantation of PV.

SPEAR: Dynamic Spatio-Temporal Query Processing over High Velocity Data Streams.

With the advent of IoT and emerging 5G technology, real-time streaming data are being generated at unprecedented speed and volume, and coming with both temporal and spatial dimensions. Effective analysis at such scale and speed requires support for dynamically adjusting querying capabilities in real-time. In spatio-temporal domain, this warrants for data as well as query optimization strategies especially for objects with changing motion states. Contemporary spatio-temporal data stream management systems in distributed domain are mostly dominated by specified-once-applied-continuously query model. Any modification in query state requires query restart limiting system responsiveness and producing outdated or in worst case erroneous results. In this paper, we propose adaptations of principles from streaming databases, spatial data management and distributed computing to support dynamic spatio-temporal query processing over high velocity big data streams. We first formulate a set of spatio-temporal data types and functions to seamlessly handle changes in distributed query states. We develop a comprehensive set of streaming spatio-temporal querying methods, and propose geohash based dynamic spatial partitioning for effective parallel processing. We implement a prototype on top of Apache Flink, where the in-memory stream processing fits nicely with our spatio-temporal models. Comparative evaluation of our prototype demonstrates the effectiveness our strategy by maintaining high consistent processing rates for both stationary as well as moving queries over high velocity spatio-temporal big data streams.

A Machine-Learning Approach to Generalisation of GIS Data

The automation of map generalisation in this study involves an expert system approach that consists of four main components including knowledge acquisition, an inference engine, knowledge representation and a user interface. The acquired knowledge was then utilised to build a knowledge-based solution: a ‘Generalisation Expert System’ (GES) developed in Java, Python and C programming environments for the delivery of generalised geographical features. Its capabilities are demonstrated in a case study through generalising several line and polyline databases over the study area in Canberra, Australia. The cartographic and GIS software communities will benefit from this study through access to a set of tools, guidelines and protocols that incorporate a standardised cartographic generalisation methodology. The results of the trials utilising GES were analysed: a series of generalisation routines were performed to assess the quality of simplification results for different spatial layers. Cartometric measures such as the total length and number of line or polyline segments were used as indices of generalisation to quantify generalisation performance for the target small scale. For example, there are 101,228 segments in 1:250,000 scale and 9,491 segments in 1:500,000 scale contours over the study area. This requires a reduction in the complexity and the density of elevation data. Changes in the representation of contour features at 1:250,000 and 1:500,000 scales as a result of generalisation were quantified. Outputs from map derivation have been analysed applying the Radical Law, this determines the retained number of objects for a given scale change and the number of objects of the original source map. Testing demonstrated that the implemented algorithms in GES are able to extract characteristic vertices on the original entity lines and polylines (e.g. for roads) while excluding non-characteristic lines and polylines to reduce irrelevant computation. This study has demonstrated reasonable improvements in Vertex Reduction, Classification and Merge, Enhanced Douglas-Peucker and Douglas-Peucker-Peschier algorithms. The test results show that GES generalises line features accurately while still maintaining their geometric relations. Existing generalisation software requires advanced technical skills from users; GES however, has a basic and user friendly Graphical User Interface (GUI) which is an advantage to users with basic technical skills and understanding of spatial data management. Changes to geographic parameters should be updated in multi-scale maps and spatial databases in near real-time. GES can be developed as a potential tool for generalising large-scale maps into smaller scales, and creating maps of different themes across a variety of scales. Test results have also demonstrated that the methodology developed improves the efficiency of line and polyline generalisation. This study aims to contribute to generalisation system design and the production of a clear framework for users. Experiments presented in this book can be applied to real world problems such as the generalisation of road networks and area features using GES. Future research should be directed towards developing web mapping platforms with generalisation functionality at varying scales.

Spatial Data Management in IoT Systems: Solutions and Evaluation

As the Internet of Things (IoT) systems gain in popularity, an increasing number of Big Data sources are available. Ranging from small sensor networks designed for household use to large fully automated industrial environments, the IoT systems create billions of measurements each second making traditional storage and indexing solutions obsolete. While research around Big Data has focused on scalable solutions that can support the datasets produced by these systems, the focus has been mainly on managing the volume and velocity of these data, rather than providing efficient solutions for their retrieval and analysis. A key characteristic of these data, which is, more often than not, overlooked, is the spatial information that can be used to integrate data from multiple sources and conduct multi-dimensional analysis of the collected information. We present here the solutions currently available for the storage and indexing of spatial datasets produced by the IoT systems and we discuss their applicability in real-world scenarios.

Preface of GSKI2020

The 8th Annual 2020 International Conference on Geo-Spatial Knowledge and Intelligence (GSKI2020) was held on December 18-19th, 2020 at Xi’an, Shanxi, China (Virtual Conference) Due to the COVID-19 situation and travel restrictions via Zoom event platform. Every authors and Committees can be received a Zoom meeting username and password from the organizer who located on Wuhan, China. Every person can attend the conference using these information. The time spent to deliver the talks by each keynote speaker is 30 minutes, 25 min presentation and 5 min question time.The time spent to deliver the talks by each oral speaker is 15 minutes, 10 min presentation and 5 min question time. Every authors can discuss with others about their session after the speech. It was held very successfully. It aims to bring researchers, engineers, and students to the areas of Geo-Spatial Knowledge and Intelligence.GSKI2020 features unique mixed topics of smart city, spatial data acquisition, processing and management, modeling and analysis, and recent applications in the context of building healthier ecology and Resource Management. The conference will provide a forum for sharing experiences and original research contributions on those topics. Researchers and practitioners are invited to submit their contributions to GSKI2020.We received a total of 293 submissions from various parts of the world. The International Program Committee worked very hard to have all papers peer-peer reviewed before the review deadline. The conference program is extremely rich, profound and featuring high-impact presentations of selected papers and additional late-breaking contributions. We sincerely hope that the conference would not only show the participants a broad overview of the latest research results on related fields, but also provide them with a significant platform for academic connection and exchange. All the keynote speakers are internationally recognized leading experts in their research fields, who have demonstrated outstanding proficiency and have achieved distinction in their profession. The proceedings were published by IOP Conference Series. We would like to mention that, due to the limitation of the conference venue capacity, we are not able to include many fine papers in the program. Our apology goes to those authors.We would like to express our sincere gratitude to all the members of International Program Committee and organizers for their enthusiasm, time, and expertise. Our deep thanks also go to many volunteers and staffs for the long hours and hard work they have generously given to GSKI2020. Finally, we would like to thank all the authors, speakers, and participants of this conference for their contributions to GSKI2020. GSKI2020 Committee Committee of GSKI2020 List of Editors, Keynote Speakers, Honorary-Chair, Co-Chair, The Editorial Committee, Internatinal Technical Program Committee are available in the pdf

An Efficient Algorithm for Spatio-Textual Object Cluster Join

With the proliferation of GPS-based equipments and location-based services, spatio-textual objects have been playing an indispensable role in spatial data management. It is of great importance to enable the join operation among spatio-textual object groups. In this paper, we propose to study a novel problem of spatio-textual object cluster join (STOC-Join). Given two sets of spatio-textual objects D 1 and D 2 and a similarity threshold θ , the STOC-Join problem finds all object cluster pairs whose spatio-textual similarities are no less than θ . The problem of STOC-Join is practical in a variety of application scenarios, including location-based event detection, location-based data cleaning, and location-based social media data pre-processing in general. Efficient processing of STOC-Join is challenging in the following three aspects: (1) How to define and compute the spatio-textual similarity between two clusters of spatio-textual objects effectively; (2) How to efficiently cluster a large number of spatio-textual objects; (3) How to efficiently find similar cluster pairs and filter out unqualified pair candidates. To address the challenges, we define an effective and easy-to-compute similarity metric that measures the aggregated similarities between two groups of spatio-textual objects. Based on the similarity metric, we propose a novel two-phase matching algorithm that is able to cluster a large number of spatio-textual objects and find all cluster pairs efficiently. Our experiments on large real-life datasets confirm that our proposed two-phase matching algorithm is capable of achieving high efficiency compared with straightforward methods.

Spatial landuse planning for developing sustainable food crop areas using land evaluation approach and GIS application (a case study of Pulang Pisau Regency, Central Kalimantan)

The need of landuse planning become apparent since the lands have the opportunity to be developed. Appropriate landuse planning based on spatial land resource data management is then required, in order to achieve sustainable landuse. The objective of this study was to design and allocate appropriate agricultural land regions for land use policy through extensification and intensification programs in order to support sustainable food crops development areas. The procedure of land resource evaluation consisting of land capability evaluation (LCE) and land suitability evaluation (LSE) was applied to determine land allocation of arable lands for rice farming development. The use of geographic information system (GIS) technology was also employed not only for spatial data management but it can also be applied to support decision making within establishing landuse planning. In the case of Pulang Pisau District, land allocation for extensification and intensification regions are mainly found in southern part and mostly located at watershed areas with each total area of 380,261 ha (36.81%) and 29,941 ha (2.90%), respectively. In order to support these potential areas, specific programs can then be formulated to increase the yield and productivity for these regions.

Development of A Spatial Decision System for Irrigation Management

Spatial decision system provides a framework for integrating database management systems, analytical models, and graphics to improve the decision-making process from a farm-scale to a regional level. In this study, a graphical user interface for irrigation management has been developed with the support of a geographical information system (GIS) customization using Visual Basic for Application (VBA). Inverse distance weighted (IDW) method is employed to interpolate spatial inputs through an embedded environment provided by the GIS for customization with VBA technique. The developed Interface was used to analyze, simulate, handle, and integrate the irrigation management's spatial data. It can be used effectively from a farm-scale to a regional level and temporal data with interpolation techniques to generate thematic maps of rainfall, effective rainfall, reference evapotranspiration (ETo), crop evapotranspiration (ETc) using weather, crop, and soil data. The tool allows visualization of the spatial distribution of water requirements in the specified region and facilitates the localization of any discrepancies in water management, indicating whether interventions are required. Finally, interface was applied to estimate spatial irrigation water requirement to provide output, i.e., spatial maps of rainfall, effective rainfall, daily ETo, daily ETc, and net irrigation requirement (NIR). ETo was higher at Bhopal, Tikamgarh and Jhansi and lowered at Raisen and Sagar. The generated NIR map shows that the area nearby Khurai station has a higher irrigation requirement. On the other hand, the area covered by Begumganj, Sironj, Tikamgarh, and Banda has lower irrigation requirements. This information may help irrigation management's decision-making from a farm-scale to a regional level in the Betwa River Basin, India.

A comprehensive overview of RDF for spatial and spatiotemporal data management

AbstractCurrently, a large amount of spatial and spatiotemporal RDF data has been shared and exchanged on the Internet and various applications. Resource Description Framework (RDF) is widely accepted for representing and processing data in different (including spatiotemporal) application domains. The effective management of spatial and spatiotemporal RDF data are becoming more and more important. A lot of work has been done to study how to represent, query, store, and manage spatial and spatiotemporal RDF data. In order to grasp and learn the main ideas and research results of spatial and spatiotemporal RDF data, in this paper, we provide a comprehensive overview of RDF for spatial and spatiotemporal data management. We summarize spatial and spatiotemporal RDF data management from several essential aspects such as representation, querying, storage, performance assessment, datasets, and management tools. In addition, the direction of future research and some comparisons and analysis are also discussed in depth.

Improvement of information technology to increase the functional stability of the network using graph theory

Improvement of information technology for increase of functional stability of a network by means of the theory of graphs is offered and the geoinformation system of monitoring of a condition of a network on the basis of the theory of stability is developed. The essence of improving information technology is to ensure constant access of users to the network. The work uses the construction of a network based on graphs, consisting of nodes and communication lines between them using a geographic information system for network monitoring. With the development of information technology, geographic information systems have emerged that provide management and display of spatial data. The use of GIS leads to an increase in the number of users of these systems, which increases the amount of information transmitted by networks. The main factor of GIS is fault tolerance - a property of the system that allows it to continue to work in case of error. The effective operation of the network depends on the resistance to external and internal factors affecting the network. Functional stability is determined by the timely redistribution of resources between nodes in order to perform their main tasks during a given time interval. An analysis of existing methods has shown that the methods have a rather complex implementation algorithm and calculation for path connectivity. This does not allow you to detect the problem quickly and provide access to the network in a short time. A monitoring system has been developed that will allow timely detection of breakdowns on the line, report it, and transfer the signal to other lines and nodes. The objectives of the development are: monitoring the functional stability of the network, fault reporting, finding new optimal ways to transmit signals. The created system provides the possibility of reliable network operation at all times. The system contains all the necessary toolkit for a specialist who will work with the application.

The Effect of Using Multiple Coordinate Systems and Datum Transformations on the Calculated Coordinates in Palestine

Abstract The recent developments in spatial data collection, management and software require the availability of proper geodetic infrastructures for integrating different types and sources of coordinates without causing effective changes in positions. Nowadays, positions are mostly collected by GNSS data collectors based on WGS84/ITRF reference systems. The data are then subjected to transformations and projections to a locally used system. Another possibility is direct data collection based on the local coordinate system by classical surveys using land surveying, photogrammetry, laser scanning, etc. The spatial data management is commonly operated using Geographic Information Systems (GIS) software for mapping, analysis, planning, and other services. The conversions between different coordinate systems should be well defined to guarantee the consistency of the coordinates on all systems and tools. In Palestine, the classical and local surveys are all based on the local coordinate system Pal1923Grid for engineering, cadastral and planning applications. The different GNSS RTK-service providers use different definitions and transformation methods between WGS84 or the International Terrestrial Reference Frames (ITRF) and the local Palestine1923Grid, whereas the Land authority has adopted a group of parameters to be implemented on the Global Navigation Satellite Systems (GNSS) data collectors, which do not fit with Palestine1923Grid properties. Additionally, different transformation methods are used in GIS applications for converting the coordinates between the different systems using WGS84 as an intermediate system. Here, the coordinates of a group of the geodetic network in the West Bank of Palestine are used to assess the accuracy of the different transformations and systems by comparing the transformed coordinates using the GNSS system and the originally registered coordinates. Furthermore, a grid of points covering the coordinate system extents is used to describe the differences between the transformations and systems. It was found that the parameters provided by GNSS service providers have results that are consistent with each other and the geodetic network in the West Bank of Palestine compared to GIS-software parameters. By contrast, all systems have extremely deteriorated coordinates in the Gaza strip and the further parts of the Pal1923Grid extents.

Exhibiting of geospatial attribute data using popup template Java-script application programming interface

<p>Arc-GIS server is used in creating web, desktop, mobile applications. Arc-GIS for server provides end user applications and services for spatial data management, visualization and spatial analysis. The proposed work deals with exhibiting of geo-spatial attribute data using the facility of Java script application programme interfaces (API’s) from Arc-GIS server. Popup-layout API reference is utilized in the work and furthermore two of its properties are utilized relying upon the need of the work. All the programming interfaces have their advantages for encouraging clients work to connect with the geo-spatial information. Keen web maps make an extraordinary method of envisioning complex data. They assist with beating up apparently disconnected data, uncover concealed examples, mine enormous datasets. Information can be composed on the work area, sent to the cloud, and shared utilizing Arc-GIS server on the web.</p>