A presentation detailing the AusPlots data collection process

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22/10/14, Andrew Tokmakoff
AusPlots Rangelands field data
collection and publication
Infrastructure for Ecological Monitoring

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Objectives
✤ To cover:
✤ what AusPlots is, and why it exists
✤ how AusPlots data is collected, handled and
published
✤ the AusPlots system architecture, its key functions
and the technical path we’ve have taken
✤ For you to consider what our work might mean for you

3. What is AusPlots Rangelands?
✤ AusPlots is based at Adelaide University and is one of 12
Terrestrial Ecosystem Research Network (TERN) facilities
✤ AusPlots identifies, prioritises, and fills data gaps in environmental
monitoring of Australian rangelands bioregions (81% of the
continent)
✤ AusPlots has defined a standardised survey methodology and
undertakes surveys over a national network of permanent 1
hectare plots, collecting baseline vegetation and soils ecological
data.
✤ This work facilitates ongoing evidence-based decision making at
local, regional, national and international levels.
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4. So, what do Australian
Rangelands look like?
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6. Collecting field data in a
prescribed methodology
✤ Prescribes a survey methodology for
collecting plot-based vegetation and
soils data
✤ consistency of both data and collection
method
✤ allows analysis of consistent data
over time, by future researchers
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7. What is collected? General
✤ High accuracy (DGPS) location
data for the plot’s corners, centre
and transect start/end points
✤ Site observations in
regard to condition,
erosion, drainage,
micro-relief, lithologies
and landform
pattern/element.
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8. What is collected? Vegetation
✤ Vouchering
✤ Vouchered vegetation
species (barcoded) over
the plot; later sent for
Herbarium Determinations.
✤ Genetic vouchering
(barcoded) of species and
extra sampling of dominant
species (up to 4 samples).
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9. What is collected? Vegetation
✤ Point Intercept
✤ consists of 1010 points,
where each point records:
✤ the substrate;
✤ any vegetation intercept(s),
indicating the species and intercept
height
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10. ✤ Basal Area
✤ recordings in each of the 9 segments of the plot, each consisting
of:
✤ a set of vegetation species under observation, the associated
wedge factor and the number of ‘hits’
What is collected? Vegetation
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11. What is collected? Vegetation
✤ PhotoPoints
✤ stitched from 3 sets of 360 degree high resolution images taken
from 3 points at the plot centre
✤ used to automatically calculate basal area using computer vision
(experimental)
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12. Trunk Identification and
Basal Area Calculation
12
Ben Sparrow and Ben Ward

13. What is collected? Vegetation
✤ Leaf Area Index (LAI)
✤ Site Structural Summary
✤ recording the three most dominant species in the Upper, Middle
and Lower strata, (with floristics comments).
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14. What is collected? Soils
✤ Characterisation of soils (barcoded)
✤ 1 metre deep pit, in 10cm increments (ec, ph, texture and colour)
✤ 9 subsite samples:
✤ barcoded meta-genomics surface soil samples
and soil samples in 10cm increments to 30cm depth
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15. What is collected? Soils
✤ 3 bulk density measurements, which quantify soil fine earth and
gravel.
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16. Where are the plots?
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17. Australian Transect Network
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18. 2
The AusPlots Approach: tooling
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19. Some requirements..
✤ Core function: support data collection according to the protocol
✤ Minimise data double-handling
✤ Maximise integrity of data (e.g. transcription errors)
✤ Use ‘off-the-shelf’ where appropriate (rapid development)
✤ Be able to function without a network (remote locations)
✤ Offer efficiency gains vs. traditional data collection methods
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20. System
Architecture
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cron
Internet
Data
Upload
Apach
e/PHP
Field App
Web-based Admin Interface
(Cloud) SWARM Server

21. 2
AusPlots Rangelands
Field Data Collection App
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22. Field App: Plot Creation
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23. Field App: Site Description
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24. Field App: Veg. Vouchering
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25. Field App: Point Intercept
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26. Field App: Basal Wedge
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27. Field App: Structural Summary
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28. Field App: Plot Upload
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29. AusPlots Rangelands
Data management
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30. Data Management
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ingestion
✤ Two databases that are synchronised through regular and
automated ingestion of newly uploaded plot data (from Field App).
(Cloud) SWARM Server

31. Data Management: CouchDB
✤ CouchDB acts as a ‘landing-spot’ for Field App
Data.
✤ 24/7 availability
of upload service
✤ Data uploaded via
internet
(WiFi or 3G)
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ingestion
(Cloud) SWARM Server

32. Data Management: PostgreSQL
✤ PostgreSQL acts as the ‘permanent’ AusPlots data repository
(Vault).
✤ Data uploaded by
the Field App into
CouchDB is
periodically
“ingested”
✤ Relational DB
✤ 24/7 availability,
scheduled backups.
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ingestion
(Cloud) SWARM Server

33. Data Management: Curation
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Field App
Web-based Admin Interface
cron
REST/
JSON
Apach
e/PHP
(Cloud) SWARM Server
✤ Apache/PHP web “site”
provides a User Interface
for data curation.
✤ Allows “cleaning” of data
and
entry of new items such as
herbarium determinations.

34. 2
Publishing curated data
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35. ✤ Soils 2 Satellites offers visualisation
✤ (e.g. for land managers, consultants)
✤ Aekos offers raw data access,
data enrichment and search
✤ (e.g. for ecological scientists)
Publishing to external services
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Field App
cron
REST/
JSON
(Cloud) SWARM Server

36. ÆKOS data warehouse and portal
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37. Motivation: data entropy
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38. Motivation: overcoming
barriers to ecological data re-
use
Identify
problem
Draft
approac
h
Search
for data
Acquire
data
Assess
suitability
Modify
approach
Prepare
data
Conduct
analysis
Interpret
results
Dispersed:
Data is stored in many
storage locations and formats
Source:Forestcheck:
www.dec.wa.gov.au
Complex:
Data usually needs
explanation and context before
it can be accurately used
www.nswrail.net
Diverse and fragmented:
Ecological data covers a wide range of topics and there are
many different ways of measuring, observing and
expressing different concepts
* Rapidly evolving with few measurement standards
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Soils to Satellites
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image of 2s2 map page

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Reflecting..
✤Benefits:
✤ Integrity of data
✤ Speed of data availability
✤Challenges:
✤ getting the UI right; resistance when it is slower than “recording
audio” (with subsequent data entry later on).
✤ dealing with legacy data at the same time as introducing new
tools.
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47. 2
Looking ahead…
✤ New Woodlands module w/ protocols (Forests not)
✤ Veg Condition, Fauna and Soils are likely to be first
✤ iOS support
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48. Summary
✤ The AusPlots field data collection App generates clean data that is
readily curated and easy to publish.
✤ The solution was developed iteratively, based upon experience
from field use and adopted a component-based design for fast
results.
✤ Complexity of the data collected led to a custom solution.
✤ ÆKOS provides a publishing platform for AusPlots.
✤ Together, we have a field-to-web solution that
makes data accessible for use in long-term
studies and facilitates informed ecological
decision-making.
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49. Any Questions?
andrew.tokmakoff@adelaide.ed
u.au
Andrew Tokmakoff
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