Title: Harlan Shannon
1GEOSPATIAL APPLICATIONS IN AGROMETEOROLOGY
An Overview of the USDA World Agricultural
Outlook
Board Geographic Information System
Harlan Shannon Meteorologist U.S. Department of
Agriculture Office of the Chief Economist World
Agricultural Outlook Board Washington D.C., U.S.A.
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Introduction
- Several analytical techniques can be used to
assess agricultural weather - time series analyses
- analog comparisons
- maps
- Historically, many maps were static depicted
just one variable, making it difficult to - overlay data sets
- visualize and evaluate relationships
- easily assess crop weather conditions
- Geographic Information Systems (GIS) have helped
overcome these obstacles
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GIS Described
Simple GIS
- GIS defined integrated system for organizing,
displaying, and analyzing spatial data using
computers and compatible technologies - GIS incorporates quantitative data directly into
the system, helping users - overlay multiple data sets
- create precise maps
- statistically evaluate relationships
- Numerous organizations use GIS to study, monitor,
and model agricultural and meteorological
processes
Robust GIS
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WAOB Geographic Information System
- Software
- ArcView 3.x older software still used to run
some operational applications - ArcGIS 9.x majority of operations transitioned
to this newer software - Hardware
- Pentium D desktop computers
- 3.4 GHz processing speed
- 2 GB RAM
- Windows XP operating system
- PCs connected via local area network
- Oracle 11g database
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GIS Activities
- Manually generate maps of important agricultural
meteorological variables - Automate product creation to maximum extent
possible - Overlay analyze agrometeorological data sets,
establish relationships, determine impacts
where applicable
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GIS Activities
manual labor
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Crop Production Data Internet
NASS crop production data posted on the Internet
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Crop Production Data Excel
Data can be converted into a GIS-compatible
format using a spreadsheet
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Crop Production Data ArcView
Agricultural data can then be imported into GIS
and mapped
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Crop Maps United States
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Crop Maps United States
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Crop Maps Brazil
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Crop Maps Russia
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Automating Applications
- Crop production areas shift slowly over time,
thus maps of major crop areas are updated
infrequently - automated updates not necessary
- In contrast, crop progress conditions vary on
much shorter time scales, requiring more frequent
map updates - manual map production can be time consuming and
tedious if a large number of products are
required - Automation is necessary to effectively and
efficiently produce such products
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Crop Progress Condition Maps
Crop progress and condition maps previously
prepared by hand
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VBA Macros
- Object-oriented programming language, enables
users to automate various tasks associated with
mapping - Examples of automation
- importing data
- spatial analysis (e.g., contouring)
- defining map scale/extent
- annotation
- creating a map legend
- exporting/printing a map
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Crop Progress Condition Maps
Programming significantly reduces product
generation time and ensures product consistency
from run-to-run
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Crop Progress Condition Maps
Once initial programming accomplished, often
little additional code needed to expand/enhance
suite of products
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Crop Progress Condition Maps
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Crop Progress Condition Maps
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Automating More Applications
same principles apply to automating weather
analyses
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Maps of Daily Data
Green number precipitation
Red number maximum temperature
Blue number minimum temperature
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Color Contour Maps
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Color Contour Maps
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Crop Moisture Index
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MODIS Crop Condition Analyses
Western Australia September 3, 2007
Western Australia September 2, 2008
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MODIS Winterkill Analyses
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Overlaying Analyzing Data
real power in GIS is ability to overlay and
analyze multiple data sets
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Thank You !