benthic photo survey: software for geotagging, depth-tagging, and classifying photos from survey data and producing shapefiles for habitat mapping in gis

benthic photo survey: software for geotagging, depth-tagging, and classifying photos from survey data and producing shapefiles for habitat mapping in gis

;Jared Kibele
society of petroleum engineers - spe international heavy oil conference and exhibition 2018, hoce 2018 2016 Vol. 4 pp. e10-e10
264
kibele2016journalbenthic

Abstract

Photo survey techniques are common for resource management, ecological research, and ground truthing for remote sensing but current data processing methods are cumbersome and inefficient. The Benthic Photo Survey (BPS) software described here was created to simplify the data processing and management tasks associated with photo surveys of underwater habitats. BPS is free and open source software written in Python with a QT graphical user interface. BPS takes a GPS log and jpeg images acquired by a diver or drop camera and assigns the GPS position to each photo based on time-stamps (i.e. geotagging). Depth and temperature can be assigned in a similar fashion (i.e. depth-tagging) using log files from an inexpensive consumer grade depth / temperature logger that can be attached to the camera. BPS provides the user with a simple interface to assign quantitative habitat and substrate classifications to each photo. Location, depth, temperature, habitat, and substrate data are all stored with the jpeg metadata in Exchangeable image file format (Exif). BPS can then export all of these data in a spatially explicit point shapefile format for use in GIS. BPS greatly reduces the time and skill required to turn photos into usable data thereby making photo survey methods more efficient and cost effective. BPS can also be used, as is, for other photo sampling techniques in terrestrial and aquatic environments and the open source code base offers numerous opportunities for expansion and customization.

Citation

ID: 202774
Ref Key: kibele2016journalbenthic
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
202774
Unique Identifier:
10.5334/jors.104
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet