image cataloging as a tool for marine biodiversity discovery
DESCRIPTION
Introduction to image cataloging and metadata tagging as a complement for fisheries surveys with biodiversity analyses.TRANSCRIPT
Claude Nozères
From photos to data:an introduction to image catalogingas a tool for biodiversity
email: [email protected]
Fisheries and Oceans Canada, Maurice Lamontagne Institute850 route de la mer, Mont-Joli, QC, Canada G5H 3Z4
This is not a software review Default programs on PCs:
MS PhotoEditorWindows Live Photo GalleryApple iPhoto
Other softwareGoogle Picasa (free, basic)IrfanView (free, basic)Adobe Photoshop (expensive, complicated)
This is about work examples recent cases with biodiversity projects: using
catalogs to turn photos into reliable data all examples done with Adobe Lightroom
Case study 1
Conservation zones
Several areas in the St. Lawrence are of special interest for marine life
high biological productivitydiversity of benthic habitats
Q: how to document the biodiversity?
Surveys: grabs & tow camera
shrimp often seenin bottom photos
Benthic sled photo transects
keywords: photo 2007, Leptasterias polaris...
keywords: photo 2006, Pandalus borealis, Ophiura sarsii,
individual photos by transect (yellow thumbnails are endpoints)
• photo of sea bottom every 10 s. • identify and count epifauna in view
IKU Grab photos
keywords: sediment, grab, grab IKU 2008
keywords: tray, grab IKU 2008
keywords: Neoamphitrite groenlandica,Polychaeta, Terebellidae, grab IKU 2008
The problem: many images At first, a solution was sought for
organizing the underwater photosselecting good shots for analysisadding or correcting dates and locations
However, the sampling surveys also had photos (field samples, lab examination)these were very useful to consult for
questions about species and stations
Case Study 2
Trawl bycatch Capture a large diversity of organisms
Taxonomic expertise not available while at sea
Q: how to record the diversity in bycatch?
Non-commercial species in capture
Capture sorted by type
Giving an initial ID based on photos
posters produced usingfiles in an image catalog
Individual images by type
keywords: unknown, Ascidiacea, TE-008
do not need a photo for every specimen, but useful for new or uncertain species
The problem: effort for species ID
no time to identify all taxa while at sea BUT need a name & a weight to record
sort by types, give names, take photossave some specimens for validation later
later in the lab, can give correct namesphotos show original appearance & colourphotos can help to correct data, e.g., counts
Solutions: image management
Digital Asset Management (DAM) for images & their databrowsing (sorting & comparing)organizing (grouping)editing (image properties)
DAM makes use of standardized types of metadata intended for commercial photographycan exploit these data fields for marine projects
Image metadata—info. on photosData fields are useful for sorting and comparing: capture date (EXIF) – original camera clock date keyword (IPTC)– subject tags for species, scenes location (IPTC) – tag for station name GPS (EXIF) latitude and longitude coordinates
example of filtering for metadata in a Lightroom image catalog
Why an image catalog?
browser: metadata in images read as they are being examinede.g., Windows Explorer, Photoshop
(Bridge)
catalog: metadata in images is also stored in a database, or catalog, filecan do more with organization & taggingcan work with files offline (files not present)NB: all work here is with Lightroom catalogs
Image catalogs: added value
It takes work to tag & organize photos in a catalog!
Benefits include: rapid browsing and comparison of photos quick confirmation of correct names or values, such
as date, species, station, or GPS coordinates bulk export of image data into database archives and
for use in data analyses easier to generate graphic products on-demand,
e.g., posters and photo galleries
Benefits: ‘Discovered species’
By comparing image results across surveys, severallesser-known species were discovered or corrected from the established records and literature for the region
Notable examples in St. Lawrence Estuary
• bivalves: Mya pseudoarenaria; Panomya vs. Mya truncata• large deepwater amphipod: Neohela monstrosa• sea cucumber: Pentamera calcigera• brittlestars: Ophiacantha, Stegophiura, Amphiura• sea anemones: Actinostola callosa (not Actinauge)• sea pens: Anthoptilum grandiflorum (not Pennatula)
revealed in 2011
Discovering from catalogs
photo 2006
Gulf 8/2011
DFO surveys in 2011 revealed errors in sea pens–was easy to confirm in the image catalog
Confusion with sea pens dates back to 1919
Anthoptilum(not Pennatula)
photo 2006
trawl 2006
Difficult to ID seaanemones in underwater photos - finally validated with trawl photos
Easy to return tocatalog and update records, species keyword
Actinostola(not Actinauge)
Actinauge
Actinostola
Discovering from public images
Blog: BIO’s Offshore Benthic Ecology Group did a cruise blog in June 2011posted images while at sea—became inspiration to
confirm Anthoptilum from captures in the St. Lawrence
Article (Belley et al. 2010) contained images – revealed errors in IDerrors would have continued if kept to internal reports or
publications without images
Photogallery: export images to a web gallerywhen errors are discovered, update catalog & re-export
Web photogallery: CaRMS
• IML collection in LR catalog• export key images to CaRMS
file export
Exporting data for analyses Lightroom uses a sqlite3 database engine
provides a graphical interface for easy to do queries & edits
built-in data tools are limited, but the user community has produced shareware plugins (donation/small fee) Photographer’s Toolbox jfriedl (Jeffrey’s Lightroom Goodies)
in current projects, exported text (csv) is put to use in Excel, Access, Oracle (w/Spatial Database Engine), and Primer (multivariate analyses)
The Photographer’s toolbox
Summarystandard metadata was used to tag images in
a Lightroom catalogbrowsing catalog images across surveys
resulted in more species being identifiedexporting images for public viewing provided
opportunities for verificationexporting image metadata enabled their use
in external databases for analyses
Key resources The DAM Book by Peter Krogh, also a forum:
http://www.thedambook.com/smf/index.php
Best practices for digital photography (website)http://www.dpbestflow.org/
Adobe Photoshop Lightroom 3: The Missing FAQ by Victoria Bampton (paper & PDF)
CaRMS photogallery user guide, Kennedy et al. 2011. DFO Tech. Rep. 2933. (paper & PDF)
NIDM image data guide (report to be published)