Aims and Scope

Journal of Geospatial Intelligence and Computing (JGIC)

Publisher: Scientific Innovation Research Group (SIRG)

Journal of Geospatial Intelligence and Computing (JGIC) publishes cutting-edge research that integrates traditional geomatic disciplines—such as geodesy, surveying, photogrammetry, LiDAR, and GNSS—with modern AI techniques, including machine learning, deep learning, computer vision, and knowledge-based systems. The scope emphasizes the development of intelligent algorithms for spatial data acquisition, processing, modeling, and decision-making, as well as the automation of geomatic workflows. 

JGIC particularly encourages submissions in the following research areas:


JGIC welcomes contributions, including:

v  Geospatial Data Science

§  Capturing of Spatial data

§  Spatial data modeling and analysis

§  Spatiotemporal data mining

§  Geostatistics and spatial optimization

v  Artificial Intelligence in Geospatial Systems

§  Machine learning and deep learning for geospatial data

§  Computer vision in remote sensing

§  AI-driven spatial prediction and decision-making

v  Remote Sensing & Earth Observation

§  Satellite image processing

§  Change detection and environmental monitoring

§  Conventional and infrared aerial photography

§  Image Analysis Processing

§   Remotely sensed data, geometric distortion

§  Archaeological prospection high spatial resolution satellites

§   Drones, airplanes, satellite imagery.

§  Three-Dimensional Perspective

§  Hyperspectral, radar (SAR), and LiDAR data analysis

§  Time-series analysis for land use/cover change

v  Intelligent Geographic Information Systems (GIS)

§  Smart GIS platforms

§  Web GIS and cloud-based geospatial systems

§  Real-time spatial data processing

v  Urban & Smart City Applications

§  Mobility and transportation analytics

§  Location intelligence systems

§  Infrastructure monitoring and planning

§  Urban analytics

v  Computational Methods

§  High-performance computing for geospatial analysis

§  Edge computing and IoT in spatial systems

§  Simulation and spatial modeling

§  Assessment of Accuracy Standard in Geospatial Data

v  Aerial Photography: 

§  Vertical Aerial Photograph, Oblique Photography image processing

§  Panchromatic aerial photographs

§  Military surveillance

§  Stereoscopic coverage

v  Cartography & Map Publishing:

§  Study of maps

§  Conventional cartography

§  Thematic maps

§  Cartometric maps and Cartographic Scale

§  Visualization of geographical information

§  Compiling geographic data

§  Geographic features representation.

v  Surveying and Intelligent Geodetic Systems

§  Photogrammetry and terrestrial/aerial laser scanning

§  Integration of inertial navigation systems

§  Geodetic reference frames and deformation monitoring

§  Machine learning for geodetic time-series prediction

§  PCS and GCS

§  Deep learning for gravity modeling and datum transformation

§  Deep learning for feature extraction and image matching

§  Automated camera calibration and orientation using neural networks

§  Real-time object detection in UAV and terrestrial imagery

v  Geographic Information Sciences GIS:

§  Geographically Referenced Data

§  Climate change

§  Public health

§  Transportation safety, and security

§  GIS Analyst and Application

§  Environmental Engineering

§  Geolocation Data

§  Geospatial Programming

§  Spatial databases and data modeling

§  Network analysis and location-based services

§  3D GIS and digital twins

§  Participatory GIS and citizen science

v  GeoPhysics: 

§  The environment in space

§  Earth’s interior using physical properties

§  Earth’s shape its gravitational and magnetic fields

§  Earth’s internal structure

§  Earth composition

§  Geodynamics plate tectonics

§  Generation of magmas volcanism and rock formation

§  Mitigation of natural hazards and environmental protection

§  environmental remediation

§  Gravimetry

v  Image Compression and Processing:

§  Contrast Enhancement algorithm

§   Dithering, and half-toning algorithm

§  Elser difference-map algorithm

§   Feature detection algorithm

§   Blind deconvolution algorithm

§  Seam carving algorithm

§  Segmentation algorithm, detection

§  Error diffusion algorithm

v  Global Navigation Satellite Systems GNSS and precise positioning technologies

§  Global Positioning Systems (GPS)

§  Global Navigation Satellite System  (GLONASS)

§  Europe’s global navigation satellite system (GALILEO)

§  BeiDou Navigation Satellite System(BeiDou)

§  Quasi-Zenith Satellite System (QZSS)

§  Indian Regional Navigation Satellite System (IRNSS)

§  AI-enhanced GNSS positioning and noise filtering

v  Geospatial  Data  and Artificial Intelligence (GeoAI)  Integration

§  Deep learning for feature extraction and scene understanding

§  Spatiotemporal prediction and forecasting using neural networks

§  Knowledge graphs and ontologies for geospatial semantics

§  Reinforcement learning for routing and spatial optimization

§  Explainable AI (XAI) in geospatial applications

§  Knowledge graphs and ontologies for heterogeneous geomatic data

§  Transfer learning between different sensors and geographic regions

§  Explainable AI for quality assessment in geomatic products

v  Big Spatial Data and Cloud Computing

§  Distributed geospatial processing

§  Geo Database and Spatial Quary

§  Spatial data lakes and real-time streaming analytics

§  Cloud-based GIS and Web GIS platforms

§  Interoperability and FAIR principles for geospatial data

v  AI-Driven LiDAR and Point Cloud Processing

§  Semantic segmentation of 3D point clouds

§  Graph neural networks for point cloud classification and registration

§  Generative models for point cloud completion and denoising

v  Autonomous Mapping and Robotics

§  Simultaneous Localization and Mapping (SLAM) with deep reinforcement learning

§  Path planning and navigation for mobile mapping systems

§  Sensor fusion (LiDAR, camera, IMU, GNSS)

v  Digital Twins and Infrastructure Monitoring

§  AI-enabled deformation detection and predictive maintenance

§  Real-time anomaly detection in sensor streams (e.g., bridges, dams, tunnels)

§  Integration of BIM, GIS, and GeoAI for smart cities

v  Ethics, Uncertainty, and Accuracy Standards  in Spatial Data

§  Quantifying and communicating uncertainty in GeoAI outputs

§  Bias and fairness in AI-driven geomatic decision-making

§  Benchmarks and validation protocols for GeoAI models in geomatics

§  Calibration, validation, and uncertainty assessment

§  Positional Accuracy Standards for Digital Geospatial Data

v  Applications Geospatial:

§  Climate change monitoring and carbon mapping

§  Smart cities and infrastructure management

§  Precision agriculture and natural resource management

§  Disaster risk reduction and humanitarian response

§  Health geography and epidemic spread modeling

§  Urban Planning

 

Keywords :

·       Geospatial Intelligence

·       Spatial Data Science

·       Geographic Information Systems (GIS)

·       Remote Sensing

·       Machine Learning

·       Deep Learning

·       Spatiotemporal Analysis

·       Earth Observation

·       Climate Data

·       Smart Cities

·       Location-Based Services

·       Computational Geoscience

·       Geostatistic analysis

·       Validation Geospatial Data

·       Regression Prediction

·       DEM

·       RADAR

·       LIDAR

·       DRONS