SH35 Main Repository

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Contains two subprojects... frontend & backend.

Team Members:

Ruari O'Hara, 2666047o@student.gla.ac.uk, 07939544510

Benjamin Parsons-Willis, 2664758P@student.gla.ac.uk, 07529606324

Anwar Abdullah, 2666539a@student.gla.ac.uk, 07709939510

Finlay Gray, 2677288g@student.gla.ac.uk, 07938625301

Calum Robertson, 2665639r@student.gla.ac.uk, 07368119260

Yangruizhe Jiang, 2665049j@student.gla.ac.uk, 07421723178

Frontend

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Frontend in react, allows for queries to be made to backend.

Requirements:

• Select Bounding Box
• Convert Box to coordinates in Longitude & Latitude decimal format
• Allow direct inputs of various longitude/latitude formats, skipping the box step if user should so choose.
• Save this query to history.
• Send this query onwards to the backend. (Via REST API)
• Poll/Check for results in progress, and display them to the user.
• Upon full results, should be able to export to some predefined structure.

Backend

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Backend in Rust, allows for search/query of files based on geospatial criterion.

Requirements:

• Should be able to take a directory and recursively explore it, indexing geospatial files based on their overall longitude/latitude decimal extent.

  • Requires parsing of various formats, see <----------->
  • Use of R* Tree enables quick indexing.
  • Use of Serde will enable quick saving/loading of index.

• Receive coordinates in standard longitude/latitude decimal format

• From these coordinates, should be able to find all files which overlap the given area.

• Return these to the frontend in a standardized format, with enough information to fetch/export these files.

Progression:

• RStar Implementation [x]
• Region Parsing: [ X]
  • KML [x]
  • GEOTIFF w/o sidecar [x]
  • DTED [x]
  • GEOJSON [x]
  • GPKG [X]
  • MBTILES [X]
  • SHAPEFILE [X ]
• File Searching [X]
• Index save/read [X ]

Requirements:

• Must run in acceptable time, over multiple TB of raw data.
• Must not modify the data directly (Can have a local working dir)
• Must read files of various types (unknown as of yet; including TIFF), and find the lat/long they contain.
• Will be interfacing with a local python HTTP API, should have some form of IPC.

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Solutions:

• In order to run in acceptable time, we must build an index of the raw-unordered data.

• This index will store 2 sets of lat/long coordinates for each file, and must be queried with 2 sets of coordinates, to find all files that intersect.

• This index will follow the R* Tree data structure, will store opposite corners of each file as seperate points, if any point is contained within the queried range, this is an overlap.

• How will we manipulate this data structure in Rust? Use the rstar library.

• This structure can implement serde, to allow for saving of index to disk.

• Interfacing with python server will be done over ZMQ.

• Reading files will be handled by pluggable readers, all implementing a common trait defining a std input of file descriptors, and a std output of 2 lat/long coords representing the boundaries of the file.

Implementation Notes:

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Kinds of failure:

• UnexpectedFormat - Should be displayed clearly to the user.
• MissingRequiredData - Should be ignored, and a small warning. ( In the case of GeoTiff, should look for a sidecar? )