Southern Ontario
Top: In 2001 in Southern Ontario, conditions were mixed during the growing season, with wet conditions in
early spring, and drier conditions emerging in mid to late summer. This is evident in the increased drought
stress seen in areas later in the season.
Middle: Crop reports describe above normal precipitation in the spring of 2002, particularly in eastern
Ontario. Conditions became hot and dry as the summer progressed. Maps show some localized impacts of
hot weather, which is consistent with crop reports.
Bottom: In 2008 in Ontario conditions were generally favourable with persistent wet weather and high yields
across the region. Maps show excess moisture, which appears to be incorrect since the moisture in this
case was beneficial to crop growth. Some disease related to moisture was reported, but this did not have a
significant impact on crop yields.
Monitoring Agricultural Drought in Canada using the Vegetation Drought Response Index (VegDRI) Catherine Champagne1,Jesslyn Brown2, Tsegaye Tadesse3, Trevor Hadwen1, Andrew Davidson1, and Richard Warren1.1 Agroclimate, Geomatics and Earth Observation Division, Agriculture and Agri-Food Canada2 Earth Resources Observation and Science Center, U.S. Geological Survey, Sioux Falls SD, USA3 National Drought Mitigation Center, University of Nebraska, Lincoln NB, USA
Poster ID 81191: GC13H: Sustainable Global Agricultural Production Monitoring Practices and Methods II Posters
The Vegetation Drought Response Index (VegDRI)• Drought conditions vary tremendously from place to place and week to week. Accurate drought monitoring is
essential to understand a drought, its progression and potential effects, and to provide information to support
drought mitigation decisions. Monitoring is improved by integrating information that is timely and region specific to
identify droughts where and when they are happening.
• The Vegetation Drought Response Index or VegDRI is a hybrid drought monitoring and mapping tool that integrates
satellite observations of vegetation status and climate data with information on land cover, soil characteristics, and
other environmental factors. This allows for more precise identification of anomalies in satellite-measured vegetation
health that are directly related to drought
• Developed by the U.S. Geological Survey (USGS)'s Earth Resources Observation and Science (EROS) Center and
the National Drought Mitigation Center (NDMC), VegDRI reveals vegetation conditions as plants respond to solar
energy, soil moisture and other limiting factors. Researchers used integrated VegDRI products to produced detailed
VegDRI maps that show levels of drought stress on vegetation across the conterminous United States. With a
relatively high degree of spatial detail, VegDRI maps support near-real-time monitoring of drought effects at state
and county levels. These maps combine the higher spatial resolution of the satellite data (<1 square kilometer) with
the sparser climate station information to provide a detailed picture of drought impacts on vegetation.
Developing a VegDRI for Canadian Agriculture• In 2013, a pilot study was conducted along the Canada-US border areas to assess seamless integration of data
from Canada and the US for VegDRI
• Climate data from 881 stations with long historical records in border regions of Canada and the US were used (77 in
Canada, 804 in the US) to calculate two drought indices: the Self Calibrated Palmer Drought Severity Index
(PDSI) and the Standardized Precipitation Index (SPI). A 36 –week SPI was chosen after evaluation of SPI for
numerous time scales since the provided the best predictive accuracy.
• Satellite data from the Advanced Very High Resolution Radiometer (AVHRR) sensor were used to calculate bi-
weekly composited Normalized Difference Vegetation Index (NDVI) over a 20 year period from 1989 – 2008. Two
metrics were calculated from the time series NDVI: the Start of Season Anomaly (SOSA) and the Seasonal
Greeness (SG).
• A database was built using the dynamic climate and satellite derived data in additional to biophysical data (soil
available water holding capacity, land cover, irrigation, ecozones) to train a model for VegDRI in Canada using a
Classification and Regression Tree (CART) method in Cubist software.
• Models classify each pixel into one of eight VegDRI categories, ranging from Extreme Drought, through to Normal,
through to Extreme Moist (Figure 1).
Next Steps• VegDRI model training and testing will be extended into Canada south of 60°N
using NDVI composites from the Moderate-resolution Imaging Spectroradiometer
(MODIS) satellite compiled at weekly time steps, and an increased number of climate
station with historical data records in Canada (~900 stations in Canada and ~800 in
the United States)
• New models will be trained using climate and satellite data which cover a period from
2000 – 2014.
Challenges
• Data on climate and soils is much less available north of 60°N. These areas are
largely uninhabited boreal forest and tundra
• The shorter growing season and prevalence of snow requires unique methods to
calculate satellite variables such as Start and End of SeasonFig. 1 Overview of VegDRI model training and development
Impact of Data Inputs on VegDRI Model Development
Validation of VegDRI Maps for Canadian Agricultural Regions
• Cubist models were trained two ways: (1) Using only
Canadian climate data and (2) using Canadian and U.S.
climate data
• Comparisons of (1) and (2) showed agreement over
71% of the pixels, with 93% within one VegDRI category
and 98% within two categories
• Canada has far fewer climate stations with long
historical records; this could be improved by gap filling
historical stations using gridded climate data sets
• Discontinuities in national data sets were found between
the two countries (soils data in particular), and these
should be minimized to have a seamless and consistent
mapping across borders
Southern Alberta
Top: Southern Alberta region in 2001 shows accelerating drought impacts over the season resulting from a dry winter
which led to low soil moisture reserves, lack of germination due to dryness and high winds led to reseeding of fields in
early June and some late June rains. Low precipitation in July and pest infestations led to high crop losses, low
irrigation water reserves; crop yields were 20-40% below average; dry fall led to early harvest
Middle: Southern Alberta region in 2002 had a cool wet spring, flooding in southern region, some fields left unseeded
due to excess moisture. Dry conditions led to crop deterioration in July, which is not evident in the VegDRI maps. Cool
damp conditions in September with average yields. Damage from long term drought not evident in maps.
Bottom: Southern Alberta region in 2008: Cool weather in early June, with adequate moisture reserves for seed
germination; some crop damage mid season due to hail storms; average yields; crops 10-14 days behind normal due
to cool spring, yields 29% above 10 year average. Maps show primarily normal conditions, consistent with crop reports
Maps were validated against provincial crop reports that summarized seasonal
climate, soil moisture and impacts.
2001
2002
2008
Late June Late July Late August Late June Late July Late August
Pilot Area for VegDRI Modelling with MODIS NDVI
VegDRI Categories
2001
2002
2008
