Progress towards Open Standards-Based Agro-Geoinformatics

®
Progress Towards
Open Standards-Based
Agro-Geoinformatics
George Percivall
Chief Engineer and CTO, OGC
Agro-Geoinformatics 2015
20 July 2015
Copyright © 2015 Open Geospatial Consortium

OGC
®
Its about turning data into information
Copyright © 2015 Open Geospatial ConsortiumSource: http://techcrunch.com/2015/04/01/the-new-queen-of-green/

OGC
®
What is Agro-Geoinformatics?
Farming decisions relying
on geospatial data
Source: Agriculture Ad Hoc Report to OGC TC Plenary March 2014

OGC
®
Geospatial Tech and Agriculture
Source: The Geo-Green revolution, Mark Noort and Anand Kashyap, Geospatial World, September 2013

OGC
®
Agriculture Geo-Information Exchange
• Efficient exchange of data on utilization of farmland,
soil and crop characteristics, water availability,
environmental impacts, …
• Many user roles: growers, advisors, landowners, foodstuff
processors, regulators and all levels of government
• Major challenges to agricultural: climate change, increasing
population, shortage of water and arable land
• Increasing need for information standards to support
transparency in agricultural goods and services markets

OGC
®
Agriculture Info Exchange Environment
Agriculture System
Product,
Production
Information
Equipment-based
Recording
In-situ
and Remote
Sensing
Maps
Geo-data
Source: Frans van Diepen, frans.vandiepen@rvo.nl OGC TC March 24, 2014

OGC
®
• Urgent need for more
information on soils at varying
geographic scales
• Diversity of data makes
integration and harmonisation
difficult
• Soil data needs to be freely
available and in formats that
can be readily used for a wide
range of purposes
• Need for harmonization of
methods
UN General Assembly declared 2015
The International Year of Soils

OGC
®
• Fundamental data for understanding Earth-system
processes
– How much arable land will be available in coming decades?
– How much food and fiber can it produce?
– How do landuse decisions in one district, country or region have
consequences elsewhere?
• Pillar Four – Enhance quantity & quality of soil information
– Global system to monitor and forecast condition of Earth’s soil
resources
– Standard “ISO 28258 requires tests by a broader community of soil
data holders to gain acceptance and become routinely applied”

OGC
®
ISO 28258:2013 Soil quality –
Digital exchange of soil-related data
Submodels
• Project
• Spatial relation
• Site
• Plot
• Soil mapping
• Soil observation
• Soil sampling
• Profile description
• GML implementation
Terminology
• Feature:
– Feature type SoilProfile.
• Soil Profile elements:
– horizons and layers
• Soil feature types
• Soil body
• Soil map
– Soil mapping unit

OGC
®
SoilML information model scope
(features of interest)
Input data -
Soil sites/profiles
Co-variates
Context
Attribute ‘surfaces’
90m resolution grid/stack
standard
depths
spline
+ uncertainty
Site (x3)
Profile
Horizons
Transect
Mapped
polygon
Components
Reference profiles
Layers
Outputs
Source IUSS presentation to OGC, December 2010

OGC
®
Confirm with Peter Wilson
International Activities on Soil Information
International Union of Soil Sciences (IUSS)
Working Group on Soil Information Standards (WG-SIS)

OGC
®
OGC Soil Interoperability Experiment
International Union of Soil Sciences (IUSS) proposed
the IE to OGC in May 2015
• IE Initiators
– Commonwealth Scientific and Industrial Research Organisation
(CSIRO)
– Landcare Research
– ISRIC World Soil Information
• Participating Organizations
– Agriculture & Agri-Food Canada, Agrobiology and Pedology
Research Centre, Alterra - Wageningen UR, Federation University
Australia, Geomatics & Cartographic Research Centre, Carleton
Univ. Harvard Univ., IIASA, JRC, USGS, USDA
– Open to additional participants

OGC
®
OGC Soil Interoperability Experiment
• Testing standards for exchange soils data
– Soil feature data: soil bodies, profiles, horizons, and related entities.
– Transfer between databases, allowing easy access and analysis.
• Use Cases
1. Technologic - soil data integration & publication
2. Commercial & public - soil sensor data
3. Policy - soil property modelling and predictions
4. Scientific - pedo-transfer functions
• Develop and test a Soil Markup Language: GML encoding
– Prepare OGC/IUSS engineering report
– Demonstration at OGC TC meeting, e.g,. Sydney, December 2015

OGC
®
ISRIC - ICSU World Data Centre for Soils
Source: Jorge Mendes de Jesus – ISRIC
http://www.isric.org/content/faq-soilgrids
GlobalSoilMap.net

OGC
®
SoilGrids1km
Global Soil Information Based on Automated Mapping
Predicted global distribution of the soil organic carbon stock
in tonnes per ha for 0–200 centimetres.
SoilGrids1km — Global Soil Information Based on Automated Mapping Tomislav Hengl , et.al. PLOS one, August 29, 2014
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105992
Sinusoidal equal area projection to give a realistic presentation of areas.

OGC
®
2www.foodie-project.eu
One platform for all the most common tasks
• Production planning
• Production monitoring, alerting and analyses
• Subsidies management
• Environmental burden monitoring
Ownership of farmer’s data
• Farmer’s data are private and sensitive data
• Remains farmer’s property
Modularity
• Customizable and scalable platform
User needsFOODIE project
• Creating a platform where spatial and non-spatial data
related to agricultural sector are available in the cloud
for agri-food stakeholders
• One Platform for most Common Tasks
– Production Planning
– Production monitoring, alerting and analyses
– Subsidies Management
– Environmental Burden Monitoring
• Project is defining Data Models and APIs

OGC
®
Copyright © 2015 Open Geospatial Consortium 16www.foodie-project.eu
Core Data Model
• Management zones
• Interventions
• Treatments
• …
Sensor Data Model
• ISO 19156 O&M
• also VGI
Transport Data Model
• OSM for navigation
FOODIE Data Models
edge
edge
vertex
vertex
vertex
edge
edge edge
edge
Road segment attributes
Identifier, e.g. http://foodie-project.eu/dat/tn/654787
National code, e.g. 43
Road width, e.g. 5 meters
Maximum height, e.g. 2.1 meters
Maximum weight, e.g. 2 tons
Speed limit, e.g. 20 km·h-1
Surface category, e.g. asphalt, unpaved,…
HAZMAT limitation, i.e. flammable/explosive/corrosive/toxic/oxidizing
www.foodie-project.eu
Core Data Model
class Foodie Core Data Model v
«featureTy
Agricultural and Aquacultu
Site
+ code :Identifier
+ geometry :GM_Object
+ activity :EconomicActi
+ validFrom :DateTime
+ validTo :DateTime [0.
+ beginLifespanVersion
+ endLifeSpanVersion :D
«voidable»
+ includesAnimal :FarmA
«dataT
Agricultural and Aquacul
FarmAnima
«voidable»
+ livestock :LivestockSp
+ aquaculture :Aquacul
«featureTyp
Plot
+ code :Identifier
+ validTo :DateTime [0.
+ beginLifeSpanVersion
+ endLifeSpanVersion :D
+ description :CharacterS
+ originType :OriginTyp
«featur
Treat
+ quantity :Measure [1..*]
+ tractorId :CharacterStrin
+ machineId :CharacterSt
+ motionSpeed :Measure
+ pressure :Measure [0..1]
+ flowAdjustment :Measu
+ applicationWidth :Meas
+ areaDose :DoseUnit [0..
+ formOfTreatment :Form
+ treatmentPurpose :Trea
+ treatmentDescription :C
«codeList»
OriginTypeValue
+ manual
+ system
«featureTy
Interventi
+ type :CharacterString
+ description :CharacterS
+ notes :CharacterString
+ status :CharacterString
+ creationDateTime :Da
+ interventionStart :Date
+ interventionEnd :DateT
+ interventionGeometry
+ supervisor :CI_Respons
+ operator :CI_Responsib
+ evidenceParty :CI_Res
«dataType
ActiveIngredi
+ code :CharacterString [
+ ingredientName :Chara
+ ingredientAmount :Me
0..*
+containsPlot 1..
HoldingPlots
Data Model compliant to:
• Directive 2007/2/EC (INSPIRE)
• ISO standards 19100 series
Open and scalable

OGC
®
Core Data Model
class Foodie Core Data Model v4.1 proposal
«featureType»
Agricultural and
Aquaculture Facilities
Model::Holding
«featureType»
Agricultural and Aquaculture Facilities Model::
Site
+ code :Identifier
+ activity :EconomicActivityNACEValue [1..*]
+ validTo :DateTime [0..1]
+ beginLifespanVersion :DateTime
+ endLifeSpanVersion :DateTime [0..1]
«voidable»
+ includesAnimal :FarmAnimalSpecies [0..*]
«dataType»
Agricultural and Aquaculture Facilities Model::
FarmAnimalSpecies
«voidable»
+ livestock :LivestockSpeciesValue [0..*]
+ aquaculture :AquacultureSpeciesValue [0..*]
«featureType»
Activity Complex::ActivityComplex
+ inspireId :Identifier
+ thematicId :ThematicIdentifier [0..*]
+ function :Function [1..*]
+ userId :CharacterString
«voidable»
+ name :CharacterString [0..1]
«voidable, lifeCycleInfo»
+ beginLifespanVersion :DateTime
+ endLifespanVersion :DateTime [0..1]
«featureType»
Plot
+ code :Identifier
+ beginLifeSpanVersion :DateTime
+ geometry :GM_Object [1..*]
+ description :CharacterString [0..1]
+ originType :OriginTypeValue
«featureType»
Treatment
+ quantity :Measure [1..*]
+ tractorId :CharacterString [0..*]
+ machineId :CharacterString [0..*]
+ motionSpeed :Measure [0..1]
+ pressure :Measure [0..1]
+ flowAdjustment :Measure [0..1]
+ applicationWidth :Measure [0..1]
+ areaDose :DoseUnit [0..1]
+ formOfTreatment :FormOfTreatmentValue [1..*]
+ treatmentPurpose :TreatmentPurposeValue [0..*]
+ treatmentDescription :CharacterString [0..1]
«dataType»
NutrientsType
+ N :Measure [0..1]
+ P2O5 :Measure [0..1]
+ K2O :Measure [0..1]
+ MgO :Measure [0..1]
+ CaO :Measure [0..1]
+ S :Measure [0..1]
+ Zn :Measure [0..1]
+ Cu :Measure [0..1]
+ Fe :Measure [0..1]
+ B :Measure [0..1]
+ Mn :Measure [0..1]
+ Mo :Measure [0..1]
«codeList»
TreatmentPurposeValue
+ weed
+ pest
+ disease
«featureType»
CropSpecies
+ beginDate :Date
+ endDate :Date [0..1]
+ cropArea :GM_Object
+ cropSpecies :CropType [1..*]
+ production :ProductionType [0..*]
«featureType»
Product
+ productCode :CharacterString [0..*]
+ productName :CharacterString [1..*]
+ productType :CharacterString
+ productSubType :CharacterString [0..*]
+ productKind :ProductKindValue
+ manufacturer :CI_ResponsibleParty [1..*]
+ nutrients :NutrientsType [0..*]
+ safetyInstructions :CharacterString [0..1]
+ storageHandling :CharacterString [0..1]
+ registrationCode :CharacterString [0..*]
+ registerUrl :URL [0..*]
«featureType»
SoilNutrients
+ nutrientName :GenericName
+ nutrientAmount :Measure
+ nutrientMeasure :CharacterString
«codeList»
ProductKindValue
+ organic
+ mineral
«dataType»
SoilTextureType
+ clay :Percent
+ silt :Percent
+ sand :Percent
«dataType»
ProductionType
+ productionDate :Date
+ variety :CharacterString
+ productionAmount :Measure
+ productionAnalysis :ProductionAnalysisType [0..*]
«dataType»
ProductionAnalysisType
+ productionAnalysisDate :Date
+ property :Measure
«codeList»
OriginTypeValue
+ manual
+ system
«featureType»
Alert
+ code :Identifier
+ type :CharacterString [1..*]
+ checkedByUser :Boolean
+ alertDate :Date
+ alertGeometry :GM_Object
«featureType»
Intervention
+ description :CharacterString
+ notes :CharacterString [0..1]
+ status :CharacterString
+ creationDateTime :DateTime
+ interventionStart :DateTime
+ interventionEnd :DateTime [0..1]
+ interventionGeometry :GM_Object [1..*]
+ supervisor :CI_ResponsibleParty [0..1]
+ operator :CI_ResponsibleParty [0..*]
+ evidenceParty :CI_ResponsibleParty [1..*]
«featureType»
TreatmentPlan
+ treatmentPlanCode :CharacterString [0..*]
+ description :CharacterString [1..*]
+ campaign :TM_Period [1..*]
+ treatmentPlanCreation :DateTime
+ notes :CharacterString [0..1]
«featureType»
ProductPreparation
+ productQuantity :Measure
+ solventQuantity :Measure [0..*]
+ safetyPeriod :TM_Period
«dataType»
ActiveIngredients
+ code :CharacterString [0..1]
+ ingredientName :CharacterString
+ ingredientAmount :Measure
«codeList»
DoseUnit
+ minimumDose :Measure
+ maximumDose :Measure
«codeList»
FormOfTreatmentValue
+ manual
+ applicationMachine
+ aerial
«featureType»
ManagementZone
+ code :Identifier
+ validFrom :DateTime [0..1]
+ beginLifeSpanVersion :DateTime
+ geometry :GM_Object [1..*]
+ dateOfAnalysis :DateTime [0..*]
«featureType»
SoilType
+ soilType :CharacterString [1..*]
«featureType»
SoilTexture
+ soilTexture :SoilTextureType [1..*]
«featureType»
pH
+ pH :Measure [1..*]
«featureType»
OrganicMatter
+ organicMatter :Percent
«featureType»
ElectricConductivity
+ electricConductivity :Measure [1..*]
«featureType»
ZonePolygon
+ area :Measure
«dataType»
CropType
+ name :CharacterString
+ scientificName :CharacterString
+ description :CharacterString
+ seedingAdvice :CharacterString
+ harvestingAdvice :CharacterString
0..*
1..*
+contains
1..*
HoldingSites
1..*
0..*
+containsZone
0..*
+HoldingPlot
0..*
+containsPlot 1..*
HoldingPlots
0..*
0..1 0..1
0..*
0..*
+crop 0..*

OGC
®
Two kinds of APIs
• Open (interoperable, typically based on OGC and/or INSPIRE)
• Lightweight (proprietary, fast)
Open
• So far OGC CSW, WMS, WFS, WCS, WPS, SOS, SPS
Lightweight
• Following best practices like OGC/ESRI GeoServices REST
Specification
• REST interface (resource oriented)
• (Geo)JSON as the exchange format
Initial Development of APIs

OGC
®
GeoWebAgri Project - FMIS interoperability
• Interoperability with commercial FMIS demonstrated with
real farm data exchange via WFS and WFS-T (ISO 19142)
• Proved that agricultural machines can request and update
field operational data on-line, in real time and at high
update rate using open standards.
• Agricultural machinery supporting a web client platform can
use several services simultaneously (‘scalability’)
• However, complex feature mapping is needed, i.e.
knowledge of the domain via GML application schema (ISO
19109) used with SoilML and many others
Source: Nørremark, M. et.al., “Data interchange between Web client based task controllers and
management information systems using ISO and OGC standards”, EFITA-WCCA-CIGR Conference:
Sustainable Agriculture through ITC Innovation, Torino, Italy, June 2013

OGC
®
GeoWebAgri Spatial Data Components
Implement
actuator
Interface InterfaceService FMIS
SQL database
Web client
Electronic control
unit (ECU) and
terminal
Controller
Data acquisition
Web serverGML
(ISO
19136)
XML
(SOAP)
Web client
Web browser
Task
management
Data utilisation
WFS
(ISO 19142)
Transactional-
WFS (ISO19142)
Source: Nørremark, M. et.al., “Data interchange between Web client based task controllers and
management information systems using ISO and OGC standards”, EFITA-WCCA-CIGR Conference:
Sustainable Agriculture through ITC Innovation, Torino, Italy, June 2013

OGC
®
Sensor Web-Enabled Precision Farming
• Research on sensor data infrastructure for precision farming
• Open source software and OGC Sensor Web Enablement
• Mobile & stationary observations from same infrastructure
• Source: Jakob Geipel, et.al. Institute of Crop Science, University of Hohenheim,
ISPRS Int. J. Geo-Inf. 2015, 4,

OGC
®
Sensor Web-Enabled Precision Farming
• Collection and storage of spatio-temporal agricultural
sensor data, accessible by SWE services and user
applications
• Open source software, offering the possibility to deploy
numerous sensor systems and SWE services.
Source: Geipel, et.al., ISPRS Int. J. Geo-Inf. 2015, 4, http://www.mdpi.com/2220-9964/4/1/385

OGC
®
Real-time In-situ Soil Monitoring in Canada
• Agriculture and Agri-Food Canada deployed network of
monitoring stations for soil moisture, soil temperature and
meteorological data for the main crop types, soil textures
• Near real-time data helps researchers develop better
predictive models for crop yield or flooding using soil
moisture values from satellite imagery
• Canadian producers can use this information in adjusting
their operational decisions based on changing weather,
water and climate conditions.
• SMAP Validation Site - Data sharing will occur for the
duration of the Soil Moisture Active Passive (SMAP)
Source: Allan Howard, Agriculture and Agri-Food Canada

Locations of In-Situ Monitoring Sites
25
Real-Time In-Situ Soil Monitoring for Agriculture (RISMA)

Data Collection and Dissemination
26
Data recorded at 15 min intervals
and transmitted hourly:
 Soil Moisture (m3/ m3)
 Soil Temperature (oC)
 Precipitation (mm)
 Air Temperature (oC)
 Relative Humidity (%)
 Wind Speed (m/sec)
 Wind Direction (deg)
 Solar Radiation (MJ/ m2)*
*At some sites
Datalogger
Telecom
AAFC Firewall
Data Receiver
LoggerNet &
Adcon Gateway
Processing
& Storage
Server
Internet
SOS Server
Raw and QC
Data
AAFC Internet
Server
Download
via User-
Friendly
Website
Download
via AAFC
FTP
Real-Time In-Situ Soil Monitoring for Agriculture (RISMA)

OGC
®
Soil Observations from UAVs
• UAVs increasingly more
common and economical for
geospatial observations
• Sensor types on UAVs
– Visual RGB camera for soil
surface characteristics
(Corbane et al.2012)
– Multispectral to monitor soil
composition (Biasio et al. 2010)
– SAR for monitoring soil
resources
(Ouchi 2013). (Koo et al. 2012)
Figure 1. Left: The UAS is hand launched
At 50 m altitude the autopilot is engaged
predefined flight route. Right. Willow fields
The preliminary results show that it was p
homogeneity with high spatial precision us
generated with the UAS, when considering
was also possible to differentiate between
provided that single images were used for
were sufficiently large.
Source: NJF Seminar 438 Sensors for soil and plant mapping and terrain
analysis, Skara, Sweden, 27-28 October 2010
Source: https://www.techinasia.com/ci-agriculture-precision-farming-indonesia/
Source: https://amergeog.wordpress.com/2015/02/19/10-non-aggressive-uses-of-drones/

OGC
®
SMAP's Radiometer
captures views of
Global Soil Moisture
• SMAP = Soil Moisture
Active Passive
– NASA spacecraft
– Rotating 6-m reflector
– L-band radar and
L-band radiometer
• Global soil moisture
– 3 Day Composites of
SMAP radiometer data
– Volumetric water
content in top 5 cm

OGC
®
SMAP EASE-Grid 2.0
• Equal-Area Scalable Earth Grid (EASE-Grid)
• Global-scale gridded data
– Defined on WGS 84 ellipsoid
– GeoTIFF compatibility
– Simplified nested grids
• Data from various sources
expressed as digital arrays
of varying grid resolutions
• Visualization and intercomparison are
simplified, making analysis more convenient
Source: Brodzik, et. al., ISPRS Int. J. Geo-Inf. 2012, 1, 32-45; doi:10.3390/ijgi1010032

OGC
®
Discrete Global Grid Systems
National
Nested
Grid
SCENZ-Grid
Earth System Spatial Grid
Snyder
Grid

OGC
®
Discrete Global Grid Systems (DGGS)
Standards Working Group (SWG)
• Develop common criteria that will
define conformant DGGSs
– Considering Goodchild criteria
• Develop conceptual standard to
facilitate data fusion between
DGGSs using OGC Standards
– to make them interoperable – with
conventional and other DGGS data
– to standardize operations on them
• Engage stakeholders to encourage
new use cases and adoption of
interoperability through DGGSs
http://www.opengeospatial.org/projects/groups/dggsswg

OGC
®
Geoprocessing for Crop Information
Source: GMU, AIP-6 Agriculture/Disaster Engineering Report, 2014

RFCLASS – Remote Sensing based Flood Crop
Loss Assessment Service Systems
• Online system supported with
Open Geospatial Web services
• OGC WCS, WMS, WFS are the
backbone components
• Crop loss assessment using crop
condition profiles
• Flood time series analyses

GADMFS - Global Agricultural Drought Monitoring
and Forecasting System
• Low latency information production
with Open Geospatial Web
services
• OGC WCS, WMS, WFS supports
data access
• Global coverage
• Interactive query, visualization and
data retrieval

OGC
®
Cropland monitoring program - CropScape
• United States Department of Agriculture (USDA)
National Agricultural Statistics Service (NASS)
• CropScape: web access to Cropland Data Layer products
– Open accessibility, visualization, and geospatial analytics
– Free and open access to digital geospatial data layers.
– Utilizes open web standards, supporting transparent and
collaborative government initiatives.
• Determine planted agricultural cropland area at the field
level for any given year across the landscape of US

OGC
®

OGC
®
CropScape architecture
Source: Weiguo Han, et.al., IEEE J-STARS, V.7., N.11., November 2014

OGC
®
Copyright © 2015 Open Geospatial Consortium© CERSGIS - GMV, 20152015/02/24
Supporting Agriculture Development in Ghana
with Geospatial Technologies Page 16
SERVICE CHAIN
Source: Foster Menash, Centre for Remote Sensing and Geographic Information Services, www.cersgis.org
Service Chain - Kenya

OGC
®
Copyright © 2015 Open Geospatial Consortium© CERSGIS - GMV, 20152015/02/24
Supporting Agriculture Development in Ghana
with Geospatial Technologies Page 17
Source: Foster Menash, Centre for Remote Sensing and Geographic Information Services, www.cersgis.org
- Kenya

DEMAND INCREASES FOR
FOOD, ENERGY & WATER
2010 2050
FOOD
2010 2050
ENERGY
2010 2050
WATER
Food-energy-water nexus risk
The 2050 perfect storm
33% to >9
BILLION
WORLD’S POPULATION
BOOMS
biofuels
hydro-
electric
http://www.ecoclimax.com/2010/06/2030-perfect-storm.html
20102050
URBAN AREAS ABSORB
GROWTH
70% LIVE IN
CITIES
2010 2050
DEMAND
increases
50%
DEMAND
increases
50%
DEMAND
increases
30%
Presented by Brant Foote, NCAR to to WWHGD WG Meeting –
Climate and Human Security Symposium: June 03 & 04 - Univ of Colorado, Boulder

OGC
®
IPCC 5th Assessment Report - Chapter 5.
Coastal Systems and Low-Lying Areas
• Seawater inundation has become a major problem for
traditional agriculture in Bangladesh (Rahman et al., 2009),
and in low-lying island nations (e.g. Lata and Nunn, 2012).
• The combination of rice yield reduction induced by climate
change and inundation of lands by seawater causes an
important reduction in production (Chen et al., 2012).

OGC
®
OGC Testbed 12
Urban Climate Resilience
GCAM Model access using WPS

OGC
®
Standards-Based Agro Geoinformatics
with a focus on soil Information
• SoilML for information exchange
• Soil information platforms
• Precision Agriculture and In-situ networks
• Remote sensing from satellites and drones
• Big Data processing for decision support
• Climate - Food - Water nexus

OGC
®
OGC support of Agro-Geoinformatics
• Agriculture Domain Working Group
– Identify geospatial interoperability challenges in agriculture domain
– Forum to identify standards-based solutions, new standards
• Discrete Global Grid Systems standards development
– Geometric partitioning of Earth surface into cells with identifiers
– Enable fusion of disparate data for spatial analysis and modeling
• Soil Data Interoperability Experiment (SoilIE)
– Testing standards for exchange of soils data
– Results to converge and mature soil information standards.
– Get involved as participant or an observer, contact:
• David Medyckyj-Scott Medyckyj-Scottd@landcareresearch.co.nz
• …and others

OGC
®
The OGC Mission
Global forum for collaboration of developers and
users of spatial data products and services
Advance development of international standards for
geospatial interoperability.
Source: 3d Stadtmodell Berlin
Source: One GeologySource: Space Time Toolkit

OGC
®
“Civilization advances by extending the
number of important operations we can
perform without thinking of them.”
- Alfred North Whitehead

OGC
®
For More Information
Open Geospatial Consortium
www.opengeospatial.org
OGC Standards - freely available
www.opengeospatial.org/standards
OGC on YouTube
http://www.youtube.com/user/ogcvideo
George Percivall
gpercivall@opengeospatial.org

Progress towards Open Standards-Based Agro-Geoinformatics

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à Progress towards Open Standards-Based Agro-Geoinformatics

Similaire à Progress towards Open Standards-Based Agro-Geoinformatics (20)

Plus de George Percivall

Plus de George Percivall (10)

Dernier

Dernier (20)

Progress towards Open Standards-Based Agro-Geoinformatics