Overview

AI GIS is the integration of AI and GIS. It includes the following features:
1) GeoAI: Spatial analysis algorithm and related process tools integrated with AI.
2) AI for GIS: enhances the function and interactive user experience of GIS software based on AI technology, and improves the intelligence of GIS software.
3) GIS for AI: Management, visualization and analysis of GeoAI results based on GIS.

Highlights

AI GIS capability
  • Augmented intelligent image interpretation on the server, and supports intelligent interpretation based on image services.
  • Augmented video AI on the desktop, and supports training of YOLO v7 series models.
  • Supports remote sensing image intelligent interpretation for model training, reasoning, evaluation in component terminal.
  • Supports AI object detection and classification in mobile terminal.

AI GIS workflow tools
  • Support batch generation of training data at the data preparation stage.
  • Supports automatic initialization of learning rate at the model construction stage.
  • Supports batch reasoning and reasoning based on range at the model application stage.

Geospatial sampling and statistical inference function
  • Supports simple random sampling, systematic sampling and stratified sampling.
  • Supports geospatial random sampling, geospatial stratified sampling and sandwich sampling.
  • Spports SPA model and B-Shade model.

Geospatial machine learning functions
  • Cluster analysis: supports geospatial hotspot analysis, geospatial density clustering, k-means clustering, shift mean clustering, etc.
  • Classification analysis: supports map matching, address element identification, forest-based classification, etc.
  • Regression analysis: supports geosimulation, geographically weighted regression, Spatiotemporal geographical weighted regression, forest-based regression, etc.

Deep learning model
  • Image analysis target detection: Cascade R-CNN, Faster R-CNN, RetinaNet.
  • Binary classification of image analysis: FPN, DeepLabv3+, U-Net, D-LinkNet, SFNet, Segformer.
  • Image analysis ground-object classification: FPN, DeepLab V3+, U-Net, SFNet, Segformer.
  • Image analysis scene classification: EfficientNet.
  • Image analysis object extraction: Mask R-CNN.
  • Image general change detection: DSAMNet, Siam-SFNet, Siam-Segformer.

Articles

What is AI GIS (Artificial Intelligence GIS) ?

What is AI GIS (Artificial Intelligence GIS) ?

AI GIS is a combination of AI technology with various GIS functions, including spatial data processing and analysis algorithms (GeoAI) that incorporates AI technology, and a general term for a series technologies of the mutual empowerment of AI and GIS.
How to Make GIS Smarter in the AI Era

How to Make GIS Smarter in the AI Era

AI technology can be applied in the field of GIS from the perspectives of Data Mining, Natural Language Processing and Computing.?It can?provide functions of spatial density clustering and intelligent identification of address elements, the extr…
AI GIS + Remote Sensing Enhances the Ability of Natural Resources Monitoring

AI GIS + Remote Sensing Enhances the Ability of Natural Resources Monitoring

Natural resource survey and monitoring application based on AI+ remote sensingThe AI+ remote sensing detection of image target, the natural resource category segmentation and classification, and natural resource multi-temporal change will provide importan…