1. David R. Maidment Unidata Program Center, Boulder CO 6 Feb 2004
From netCDF to GIS
David R. Maidment
Unidata Program Center, Boulder CO
6 Feb 2004

2. NetCDF and GIS
NetCDF describes atmospheric and water properties varying continuously in (x,y,z,t)
GIS describes the physical landscape,
Vector GIS has spatially discrete features (point, line area)
Raster GIS is spatially continuous (in 2D)
How do we connect the “water” with the “water environment”

3. NetCDF File for Model Output
dimensions:
lat = 5, lon = 10, level = 4, time = unlimited;
variables:
float rh (time, lat, lon);
int lat(lat), lon(lon);
lat:units = “degrees_north”;
long:units = “degrees_east”;
short time(time);
time:units = “hours since ”;
data:
lat = 20, 30, 40, 50, 60;
long = -160, -140, -118, -96, -84, -52, -45, -35, -25, -15;
time = 12;
rh = .5,.2,.4,.2,.3,.2,.4,.5,.6,.7,
.1,.3,.1,.1,.1.,.1,.5,.7,.8,.8,
.1,.2,.2,.2,.2,.5,.7,.8,.9,.9,
.1,.2,.3,.3,.3,.3,.7,.8,.9,.9
.0,.1,.2,.4,.4,.4,.4,.7,.8,.9;

4. Relative Humidity Points

5. Interpolate to Raster
GeoTiff format, cell size = 0.5º

6. Zoom in to the United States

7. Average Rh in each State
Determined using Spatial Analyst function Zonal Statistics with
Rh as underlying raster and States as zones

8. Unidata Toolbox Relative Humidity Analysis Model Created in
Arc 9 Model
Builder

9. Model Output Geodatabase
(Grids)
Geodatabase
Feature Dataset
Feature class
Feature class
Raster Catalog
Relationship
Raster
Table
Table

10. Raster Catalog has Types of Data

11. Scenarios for Data Dissemination
ArcSDE and ArcIMS
Leveraging the Unidata Local Data Manager (LDM)
Access through Unidata Internet Data Viewer (IDV)
Direct downloads from ArcGIS

12. Scenario 1: ArcIMS & ArcSDE
Underlying data are stored in a relational database (e.g. Oracle)
Accessed through Arc Spatial Data Engine (ArcSDE)
Web access through Arc Internet Map Server (ArcIMS)
Used for National Elevation Dataset, National Land Cover Dataset, National Hydrography Dataset
Suitable for large static databases
Possibly a good approach for historical climate datasets, e.g. VEMAP (NCAR: Nan Rosenbloom, Dave Schimel, Tim Kittel)
National Elevation Dataset

13. Scenario 1: ArcIMS & ArcSDE
User Experience
Go to a web site, browse available data and select a geographic region and desired data themes
“Download” means that a data product is created off-line and user is notified by when it is ready
If < 100MB download via ftp for free
If > 100MB write to CD-ROM and mail ($$)
Contacts: Paul Wiese, USGS, Denver (NHD); Sue Greenlee, USGS, EROS Data Center (NED, NLCD)
National Elevation Dataset

14. Scenario 2: Leverage the LDM
File is disseminated through LDM network e.g. netCDF format
Unidata publishes an Arc Toolbox for converting file (or adds a decoder to LDM to convert to Grid)
Good for GIS analysis of existing real time data stream

15. Scenario 3: Access through IDV
IDV is used to browse remote datasets
Protocol to access Geography Network is added to IDV
Geographic data added to IDV displays
Atmospheric data converted to GeoTIFF for GIS analysis
Build Raster Catalog of atmospheric datasets
Data Publisher 1
Data Publisher 4
Data Publisher 2
Data Publisher 3
Meteorologix publishes atmospheric
data on the Geography Network

16. Scenario 4: Direct Downloads from ArcGIS
Select region and time period
Launch query to access
Download data
Import to geodatabase
Run models
Nexrad data for
July 30, 2001,
Rosillo Creek

17. Nexrad for Rosillo Creek

18. GIS in Water Resources Consortium
CRWR
GIS
Water Resources
Bringing together these two communities by using a common geospatial data model

19. Arc Hydro — Hydrography

20. Arc Hydro — Hydrology

21. Arc Hydro Framework Data Model
The Arc Hydro framework is built on a Hydro Network made up of HydroEdges (stream lines) and HydroJunctions (points of interest on the lines). The watersheds, waterbodies and hydropoints are connected to the hydronetwork using relationships with the hydro junctions (blue lines in the diagram).

22. Arc Hydro Framework For South Florida
Basins
Waterbody
(NHD)
The Arc Hydro Framework is a simplified version of the full Arc Hydro data model designed for an entry level user who just wants to put together a basic data set for streams, watersheds, waterbodies and hydro points like stream gages and water quality monitoring points
Hydro Points
National Hydrography
Dataset, NHD

23. Arc Hydro Components Drainage System Hydro Network Time Series
Flow
Time
Time Series
Channel System
Hydrography

24. Connecting Arc Hydro and Hydrologic Models
GIS
Interface data models
HMS
Geo
Database
Arc Hydro
data model
RAS
WRAP

25. Nexrad Map to Flood Map in Arc 9 Model Builder
FLOODPLAIN MAP
Flood map
as output
Model for
flood flow
HMS
Model
for flood
depth
Nexrad rainfall map as input

26. Time and Space in GIS Time Series Feature Series Attribute Series
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t1 t2 t2 t1 t3 y x

27. Time Series and Temporal Geoprocessing
DHI Time Series Manager
Time Series
Feature Series
Time
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t3 t2 t1 t2 t1 y x
ArcGIS Temporal Geoprocessing

28. Time series from gages in Kissimmee Flood Plain
21 gages measuring water surface elevation
Data telemetered to central site using SCADA system
Edited and compiled daily stage data stored in corporate time series database called dbHydro
Time series downloaded from dbHydro and stored for all gages as Arc Hydro Attribute Series

29. Arc Hydro Attribute Series
Map features have a time varying attribute
HydroID
2906
Feature Class (HydroID)
Attribute Series Table (FeatureID)

30. Raster Series
Ponded Water Depth
Kissimmee River
June 1, 2003

31. Arc Hydro Attribute Series Object
TSDateTime
Feature Class
(point, line, area)
TSValue
FeatureID
TSType
TSType Table

32. NetCDF Data Model Time Dimensions and Coordinates Value Space (x,y,z)
Variable
Attributes

33. Conclusions Good time to make progress
Unidata THREDDS research done at Unidata and some experience accumulated
Arc 9.0 is about to be released with Model Builder; planning for Arc 9.1 about to begin
Fairly sound understanding of how to develop time series in ArcGIS
Lots of cool weather and climate data that we really, really would like to use more!!