scholarly journals DEVELOPMENT OF A CITSCI AND ARTIFICIAL INTELLIGENCE SUPPORTED GIS PLATFORM FOR LANDSLIDE DATA COLLECTION

2020 ◽  
Vol XLIII-B5-2020 ◽  
pp. 43-50
Author(s):  
R. Can ◽  
S. Kocaman ◽  
C. Gokceoglu
Keyword(s):  
Artificial Intelligence ◽  
Data Collection ◽  
Geographical Information Systems ◽  
Landslide Hazard ◽  
Geographical Information ◽  
Geospatial Technologies ◽  
Hazard And Risk ◽  
Hazard Assessments ◽  
Landslide Data ◽  
Gis Platform

Abstract. Geospatial data are fundamental to understand the relationship between the geographical events and the Earth dynamics. Although the geospatial technologies aid geodata collection, the increasing possibilities yield new application areas and cause even a greater demand. Considering the increment in data quantity and diversity, to be able to work with the data, they must be collected, stored, analysed and presented with the help of specifically designed platforms. Geographical Information Systems (GIS) with mobile and web support are the most suitable platforms for these purposes. On the other hand, the location-enabled mobile, web and geospatial technologies empowered the rise of the citizen science (CitSci) projects. With the CitSci, mobile GIS platforms enable the data to be collected from almost any location. As the size of the collected data increases, considering automatic control of the data quality has become a necessity. Integrating artificial intelligence (AI) with the CitSci based GIS designs allows automatic quality control of the data and helps eliminating data validation problem in CitSci. For this reason, the purpose of the present study is to develop a CitSci and AI supported GIS platform for landslide data collection because landslide hazard mitigation efforts require landslide susceptibility, hazard and risk assessments. Especially, landslide hazard assessments are necessary the time of occurrence of a landslide. Although this information is crucial, it is almost impossible to collect time of occurrence in regional hazard assessment efforts. Consequently, use of CitSci for this purpose may provide valuable information for landslide hazard assessments.

scholarly journals From paper maps to digital maps: enhancing routine immunisation microplanning in Northern Nigeria

2019 ◽  
Vol 4 (Suppl 5) ◽  
pp. e001606 ◽  
Author(s):  
Leanne Dougherty ◽  
Masduq Abdulkarim ◽  
Fiyidi Mikailu ◽  
Usman Tijani ◽  
Kazeem Owolabi ◽  
...  
Keyword(s):  
Data Collection ◽  
Geographical Information Systems ◽  
Service Providers ◽  
Secondary Data ◽  
Geospatial Data ◽  
Geographical Information ◽  
Routine Immunisation ◽  
Digital Maps ◽  
Vaccination Strategies ◽  
Catchment Areas

Geographical information systems (GIS) can be effective decision-support tools. In this paper, we detail a GIS approach implemented by the Bauchi and Sokoto state primary healthcare development agencies in Nigeria to generate and convert routine immunisation (RI) paper maps to digital maps for microplanning. The process involved three stages: primary and secondary data collection and reconciliation, geospatial data processing and analysis, and production and validation of maps. The data collection and reconciliation stage identified a number of challenges with secondary data sources, including the need to standardise and reconcile health facility and settlement names. The study team was unable to apply population estimates generated from the Global Polio Eradication Initiative to RI planning because operational boundaries for polio activities are defined differently from RI activities. Application of open-source GIS software enabled the combination of multiple datasets and analysis of geospatial data to calculate catchment areas for primary health centres (PHCs) and assign vaccination strategies to communities. The activity resulted in the development of PHC catchment area digital maps, and captured next steps and lessons learnt for RI microplanning in the two states. While the digital maps provided input into the microplanning process, more work is needed to build capacity, standardise processes and ensure the quality of data used to generate the maps. RI service providers and communities must be engaged in the process to validate, understand the data, the contextual factors that influence decisions about which vaccination strategies RI microplans include and how resources are allocated.

INTEGRATING SCAT DATA AND GEOGRAPHICAL INFORMATION SYSTEMS TO SUPPORT SHORELINE CLEANUP OPERATIONS

1997 ◽  
Vol 1997 (1) ◽  
pp. 499-506 ◽  
Author(s):  
Alain Lamarche ◽  
Edward H. Owens
Keyword(s):  
Decision Making ◽  
Information System ◽  
Data Analysis ◽  
Data Collection ◽  
Software Package ◽  
Geographical Information Systems ◽  
Data Entry ◽  
Decision Makers ◽  
Geographical Information ◽  
Gis Technology

ABSTRACT An analysis of the work performed by the various teams involved in shoreline cleanup operations has been applied to the design of an approach for the integration of data collected by the SCAT process with electronic maps produced by geographical information system (GIS) technology. This has led to the implementation of a PC-based system that incorporates a database of SCAT information, a knowledge base on oil behavior and shoreline cleanup, and a GIS. The system provides support to data collection using the SCAT approach for field teams and to map-based data analysis for planners and managers. In the course of this work, a set of the maps that are considered the most useful for summarizing information about shoreline conditions was designed and evaluated. This evaluation initially involved consultation with individuals experienced in shoreline cleanup. The applicability of the map representation for decision making was further tested during spill drills. SCAT surveys generate a large volume of data that need to be captured and integrated. There is a risk that this large amount of information might overwhelm decision makers involved in the management of shoreline cleanup operations. The paper describes the various modifications that were made to the SHORECLEAN software package to provide some solutions to these problems. These include providing specialized SCAT data entry forms, automating the links between a SCAT database and a GIS, and producing map representations that provide clear, useful, and nonmisleading information for decision makers.

scholarly journals Mixed Reality: A Reconsideration Based on Mixed Objects and Geospatial Modalities

2021 ◽  
Vol 11 (5) ◽  
pp. 2417
Author(s):  
Konstantinos Evangelidis ◽  
Theofilos Papadopoulos ◽  
Stella Sylaiou
Keyword(s):  
Physical Properties ◽  
Geographical Information Systems ◽  
Laser Scanning ◽  
Mixed Reality ◽  
Geographical Information ◽  
Geospatial Technologies ◽  
Positioning Systems ◽  
Common Space ◽  
Digital Objects ◽  
Processing Techniques

We put forward a conceptualization of Mixed Reality as a blend of digital objects with real ones that coexist and interact with each other and they are also spatially referenced so that they are properly perceived in space by an observer that could potentially be at any position any time. In accordance with this statement, we have adopted the concept of a Mixed Object which is composed of a set of physical properties linked with a set of digital ones. In our case, the physical properties are acquired by employing geospatial technologies such as photogrammetry, laser scanning, unmanned aerial vehicles and positioning systems and are further processed in order to be visually displayed by utilizing Geographical Information Systems and Geovisualization frameworks in combination with traditional image processing techniques. We show that the Mixed Object approach is in conformance with Microsoft’s approach on Mixed Reality as the common space between humans, computers, and the environment and we further incorporate in these the Geospatial Linking Modalities. We finally provide an affordable MR experience as a proof of concept, by utilizing a smartphone for capturing and visualizing the environment, a visual tag for positioning purposes and freely available photogrammetrically mapped content and virtual objects to form a digital scene blended with the real environment.

scholarly journals Ένα παράδειγμα σύζευξης γεωγραφικών συστημάτων πληροφοριών (Γ.Σ.Π) με μεθόδους τεχνητής νοημοσύνης (ασαφής λογική & νευρωνικά δίκτυα): εφαρμογή στη γεωμορφολογία.

2005 ◽  
Vol 38 ◽  
pp. 101
Author(s):  
Θ. ΓΚΟΥΡΝΕΛΟΣ ◽  
Ν. ΕΥΕΛΠΙΔΟΥ ◽  
Α. ΒΑΣΙΛΟΠΟΥΛΟΣ
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Spatial Database ◽  
Risk Index ◽  
Geographical Information ◽  
Erosion Risk

In this paper we are studying the erosional procedures on the basis of Geographical Information Systems (GIS) and Artificial Intelligence (Al) methods. More precisely we use fuzzy logic rules to estimate the erosion risk index for the surface rocks and a model of neural networks to spatially categorise the erosion risk index. The described procedure is applied at Zakynthos island, where a complete spatial database already exists.

Challenges in Disaster Data Collection during Recent Disasters

2011 ◽  
Vol 26 (3) ◽  
pp. 196-201 ◽  
Author(s):  
Melinda Morton ◽  
J. Lee Levy
Keyword(s):  
Data Collection ◽  
Hurricane Katrina ◽  
Geographical Information Systems ◽  
Health Data ◽  
Geographical Information ◽  
Indian Ocean Tsunami ◽  
Gis Mapping ◽  
Data Repositories ◽  
Needs Assessments ◽  
Disaster Data

AbstractGathering essential health data to provide rapid and effective medical relief to populations devastated by the effects of a disaster-producing event involves challenges. These challenges include response to environmental hazards, security of personnel and resources, political and economic issues, cultural barriers, and difficulties in communication, particularly between aid agencies. These barriers often impede the timely collection of key health data such as morbidity and mortality, rapid health and sheltering needs assessments, key infrastructure assessments, and nutritional needs assessments. Examples of these challenges following three recent events: (1) the Indian Ocean tsunami; (2) Hurricane Katrina; and (3) the 2010 earthquake in Haiti are reviewed. Some of the innovative and cutting-edge approaches for surmounting many of these challenges include: (1) the establishment of geographical information systems (GIS) mapping disaster databases; (2) establishing internet surveillance networks and data repositories; (3) utilization of personal digital assistant-based platforms for data collection; (4) involving key community stakeholders in the data collection process; (5) use of pre-established, local, collaborative networks to coordinate disaster efforts; and (6) exploring potential civil-military collaborative efforts. The application of these and other innovative techniques shows promise for surmounting formidable challenges to disaster data collection.

scholarly journals Quality Control and Management of Inspection and Data Collection

2000 ◽  
Author(s):  
Robert A. Simmons ◽  
Richard Kania
Keyword(s):  
Quality Control ◽  
Data Collection ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Quality Data ◽  
Inspection Time ◽  
Accurate Information ◽  
Pipeline System ◽  
Complex Data ◽  
Practical Applications

Geographical Information Systems, Data trending, and Risk Assessment Software are now available to help pipeline operators execute safe, cost effective maintenance programs. However, to use these analytical tools effectively, large amounts of data pertaining to the integrity of the pipeline system and its environment are required. For this reason, pipeline rehabilitation programs have evolved into complex data collecting procedures, the success of which depends on the ability to efficiently obtain reliable, consistent and accurate information. This article will describe new software technology and Quality Control programs, relating to inspection personnel, which have been developed to increase the efficiency and reliability of the information collected during a pipeline excavation. The pertinent functions of software programs discussed will involve compatibility between databases, on site data validation, code calculations, communications and CAD drawings for a comparison with In Line Inspection results. As well, the need for quality control or training programs will be discussed addressing both the theoretical and practical applications of pipeline integrity and it’s relevance to quality data collection. Previous projects using these approaches will be presented showing their effectiveness in significantly increasing the efficiency and accuracy of the information collected while reducing overall inspection time and cost.

scholarly journals Integrated use of GIS-based field sampling and modeling for hydrologic and water quality studies

2005 ◽  
Vol 7 (4) ◽  
pp. 235-250 ◽  
Author(s):  
Enrique R. Vivoni ◽  
Kevin T. Richards
Keyword(s):  
Water Quality ◽  
Data Collection ◽  
Geographical Information Systems ◽  
Field Data ◽  
Water Quality Modeling ◽  
Geographical Information ◽  
Watershed Model ◽  
Hydrologic Simulation ◽  
Catchment Scale ◽  
Quality Assessments

Enhancements to traditional catchment-scale water quality assessments can be realized by leveraging geographical information systems (GIS) for both field data collection and hydrologic and water quality (H/WQ) modeling. In this study, we describe a GIS-based data collection system for geo-referenced environmental sampling utilizing mobile, wireless and Internet technologies. Furthermore, sampled field data is combined with historical measurements within a GIS-based semi-distributed watershed model for simulating water quantity and quality in a large regional catchment. The GIS-based sampling and modeling system is intended to streamline water quality assessments as compared to current practices. We describe an application and field study in the Williams River, New South Wales, Australia designed to assess the impacts of point and non-point source pollution on water quality. Historical data were utilized for calibrating and validating the Hydrologic Simulation Program – Fortran (HSPF) with the BASINS GIS interface over the 1988–2000 period. Results from the study indicate that short-duration, spatially extensive field campaigns provide useful data for enhancing modeling studies based on historical measurements at sparse sites. In addition, the study suggests that the conjunctive use of data collection and modeling is a step towards real-time integration of field data in hydrologic and water quality modeling efforts.

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