Wednesday Show and Tell
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Transcript of Wednesday Show and Tell
Wednesday Show and Tell
Theresa CrimminsChristina WrightCuyler SmithDave PressGareth RowellJohn BoetschLisa NelsonJohn Gross
Theresa Crimmins USA National Phenology
Network
USA-NPN Progress To-Date
• Plant protocols available online (200+ species)• Phenology data/information system functional• Data entry available online• Data visualization tools in development• Animal protocols in development (available
2010)– Mammals, birds, amphibians, reptiles, fish, insects
(>150 species)
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Example USA-NPN Plant Phenology Protocol (≈ I&M ‘how to observe’ SOP)
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NPS-NPN Partnership Strategy
• Monitoring and research: Establish wide-spread monitoring of phenology in NPS units (NPS scientists, staff, visitors…) – develop training materials, encourage research in parks
• Information management: Develop databases, data transfer mechanism, metadata requirements, “one-stop shopping” site for NPS
• Communications: Widely disseminate information and knowledge of the importance and management implications of phenology – develop interp & education messages, fact sheets…
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Pilot in NETN Parks – Summer 2009• Goal: Find the appropriate fit for phenology monitoring and
use of phenology data within NETN parks. • Status:
– Currently identifying target audiences, locations, methods– Identifying major ecological, methodological questions
• Products: Draft field methods standard operating procedures for phenology protocols following Oakley et al. (2003) guidelines
• Evaluation of pilot program – end of 2009• Participants: NETN, Appalachian Trail, Acadia NP,
Appalachian Mtn Club, Appalachian Trail Conservancy, The Wildlife Society, USA-NPN
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CA/PWR Cooperative Efforts• Recent call to engage interested parties• I&M, park biologists and resource managers,
interpreters represented (as well as NPN, UCSB, Project BudBurst)
• Working group established to pilot plant phenology monitoring
• Next steps:– Select plant species & develop protocol for pilot
monitoring– Collaborate with UCSB on two phenology
monitoring training sessions – fall 2009
Christina WrightSoutheast Coast Network
E X P E R I E N C E Y O U R A M E R I C A
SECN SharePoint
2009 Data Management ConferenceShow and Tell
National Park ServiceU.S. Department of the Interior
News and Updates
Project Tracking
Completed Projects Repository
Data Management
Data Entry using
InfoPath Forms
Generate Reports
Links to Monitoring Data
Resource Briefs
Cuyler Smith Southwest Alaska Network
Bear-A-Where…Aerial Bear Survey Software Tools at the Southwest Alaska Network
Cuyler SmithData Manager - SWAN
Data Manager’s Conference 2009
“Beaerial” survey events…• Generate random transects
(initial flight paths)• Fly random transects with 1/2
observers and 1 pilot• Spot bear!• Deviate from flight path to
count/identify attributes• Return to transect• Continue survey
Data Manager’s Conference 2009
Software Involved
• Existing– ArcMap 9.3– ArcPad 7.1
• Custom (GeoNorth)– ArcMap Random Transect
Generator (Pre-survey transects to be flown)
– ArcPad Bear Tracking Applet (During survey to catalog attributes)
Data Manager’s Conference 2009
Data Manager’s Conference 2009
Random Transect Generator (ArcMap)…
Aerial Survey Tracking (ArcPad)… Data Manager’s Conference 2009
For more info…
• Contact Bill Thompson, PI– [email protected]
Data Manager’s Conference 2009
“No matter how much you push the envelope, it’ll still be stationery!”
Dave Press San Francisco Area Network
Streamflow Monitoring Database: A FAB Example
David PressEcologist / Data Manager
San Francisco Area Network
SFAN Streamflow MonitoringThe specific monitoring objectives are to:
1. Monitor the variability and long-term trends in streamflow using fixed, continuous, water stage recording stations by producing annual mean daily and monthly discharge estimates for core streamflow monitoring stations in GOGA, PRES, PINN, and PORE.
2. Monitor the frequency, magnitude and duration of peak flow events at fixed, surface water level monitoring stations by producing peak and daily summaries of stage height and discharge for core streamflow monitoring stations in GOGA, PORE and PINN.
3. Monitor the timing, frequency, magnitude and duration of unnatural or extreme low water/low flow events in stream reaches known to support threatened and endangered aquatic species in the dry season in GOGA, PORE, and PINN watersheds.
Simplified Data Work Flow
Download raw datalogger files in field
Transfer data to recording gaging station
spreadsheet template Perform QA/QC measures
Identify data gaps, erroneous data
Correct recorded stage
(instantaneous)
Develop Stage-Discharge Rating
CalculateDischarge (instantaneous)
Import Mean Gage Height &
Measured Discharge
Streamflow Measurements
Once a month at each sampling siteHigh stream flow eventsOnce a month at water quality sampling sites also
Gareth Rowell Heartland Network
Monitoring Databases, ODBC and R
Access Bird MonitoringDatabase
qry_BirdSppRich ODBC R
>library(RODBC)>channel <- odbcDriverConnect()>BRich <- sqlFetch (channel, "qry_BirdSppRich")>attach(BRich)>names(BRich)>summary(SppRich_Yr+1)>hist(main="Bird Species Richness, All Parks x Years", SppRich_Yr+1)
Some R code…
• Data displayed in R • Data from ODBC Connection to Access
Why use ODBC and R
• Easy to “re-select” database for data exploration• Data are clean (not corrupt) going from database to R• R provides extensive collection of statistical tests and graphics• R and ODBC are widely used -- excellent documentation• R and ODBC are free
John BoetschNorth Coast and Cascades
Network (Olympic NP)
Reusable Project Application Components
John Boetsch - NCCN / Olympic NP
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
What and Why?1. Multiple project database applications2. Faster development & more consistent look & feel
for project staff3. Why not?
Quality Assurance Tool• Uses pre-built queries to check the completeness, structural
integrity and logical consistency of the data set
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance ToolWhat you don’t know CAN hurt you(r analysis)!
• Missing records– List of scheduled sites that weren't visited … were they simply not
entered? • Missing values
– Field coordinate source = 'GPS' but missing GPS model or GPS file name
• Duplicate records– Locations with more than one coordinate record per sampling date -
verify that these are intended • Illogical data combinations
– Marker status = 'removed' but no removal date, or with a removal date and status <> 'removed'
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance Tool• We talk a lot about how relational databases
are useful for this type of quality assurance ...• This is a tool for rigorously checking data
against a set of project-specific rules
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance ToolThree types of QA queries:
1. Critical– structural issues, missing critical fields, etc … must fix to
complete data certification 2. Warning
– may affect summary output and analysis routines … missing values, etc. (fixes not always possible)
3. Information– list of taxa observed, list of locations visited, range of
dates for sampling events, etc.
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance ToolFunctionality:
1. Filter the data being validated – uncertified data, certified data, or both
2. Each query result set may be documented - resolved issues and lingering problems
3. Open the appropriate forms for fixing or exploring the problem for an individual record (may run an update query to fix the problem after the user has reviewed the records)
4. Export results to Excel5. Opens a formatted report object for inclusion in the year's
"certification report"
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance Tool1. Filter the data being validated – uncertified data,
certified data, or both
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance Tool2. Each query result set may be documented -
resolved issues and lingering problems
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance Tool3. Open the appropriate forms for fixing or exploring
the problem for an individual record (may run an update query to fix the problem after the user has reviewed the records)
4. Export results to Excel
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Quality Assurance Tool5. Opens a formatted report object for inclusion in the
year's "certification report"
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Data BrowserData entry forms weren’t providing sufficient access to
data:Mirror field form structure - often more complex than
they would otherwise be for simply displaying data Goal: Total data access through front end• Simple data browser for more hierarchical data viewing and
editing by a “power user”• Filter by park, location, location status, location type, etc.• Subforms and tabs• Most users satisfied with this, advanced users can still build
queries as they wish
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Data Browser
Data Browser
Data Browser
Managing Data Access PrivilegesGoal: Avoid unnecessary risk to data (more valuable
as data accumulate)• Application mode based on user roles (application
side, NOT SQL Server roles)• Different application components hidden/exposed• User login tied to a user role in a system table
– Admin – may create new application versions– Power user – may edit certified data, view the back-end, add new
user roles– Data entry – may enter new (uncertified) data for current season– Read only – view data only
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Notification for Application VersionsHelps with far-flung field crews and outdated front-end
versions sitting on hard drives • On opening ...
– Application log of user and version number– User is notified if a new release is available
• User downloads new version from our SharePoint site
– Current – no notification– Supported – notifies user on opening, but they can continue to use
the application– Not supported – application closes after notification; MAJOR
changes, previous versions may endanger data quality
2009 I&M Data Management ConferenceTucson, Arizona – April 2009
Lisa Nelson I&M Program - Fort Collins
NPS Natural Resource & GIS ProgramsInventory and Monitoring Program
DM Meeting - 2009
Vital Signs Internet Map Services (VSIMS)
• FY2009 Activities:– NRDT upload and map display functions– Integration with IRMA frameworks for web
version– Development staff:
• Position closes April 27
NPS Natural Resource & GIS ProgramsInventory and Monitoring Program
DM Meeting - 2009
Upload from NRDT
NPS Natural Resource & GIS ProgramsInventory and Monitoring Program
DM Meeting - 2009
Display Uploaded Data
NPS Natural Resource & GIS ProgramsInventory and Monitoring Program
DM Meeting - 2009
Comments/Questions• NRDT User Board Meeting:
Wednesday, 4:30 – 5:30pm• Are We Building 32 Silos?
Thursday, 2:45 – 4:00pm
• See Lisa Nelson or Peter Budde
John Gross I&M Program - Fort Collins
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PALMS:A NASA-NPS partnership to monitor
landscape dynamics
John GrossOffice of Inventory, Monitoring, and Evaluation
Ft Collins, Colorado
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TOPS: Common Modeling Framework
Monitoring, modeling,
& forecasting at multiple scales
Nemani et al., 2003 and 2007
TOPS Products forNPS:• Ecosystem productivity /
carbon flux• Trends and anomalies in
vegetation condition and phenological indicators
• Soil moisture / vegetation water stress
• Climate and weather surfaces and forecasted impacts of climate change
TOPS Products for Sierra Greater Park Ecosystems
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Snow Cover
Soil Moisture
EVI
Leaf Area Index
Maximum Temp.
MODIS DirectBroadcast
TOPS GPP
Vapor Pressure Def.
FPAR Anomaly
Satellite Climate Ecosystem Model
Trends &Anomalies
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TOPS Data Gateway
• Using the query interface, users can access, graph, and download timeseries of data for locations of interest.
NASA Project (in 3rd & final year)• Focus on four prototype parks• Uses park-specific data and local knowledge• Sophisticated measurement • State-of-the art processing and modeling• TOPS: http://ecocast.arc.nasa.gov/ & RSE issue
I&M Project:• All I&M parks• Limited to analyses of large data sets• Processing capability is limited • No image classification• http://www1.nrintra.nps.gov/im/monitor/npscape/