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Tools for Hazard Monitoring, Assessment, and Response Jesslyn F. Brown, U.S. Geological Survey, Earth Resources Observation and Science, South Dakota, USA
Landsat 8
In the face of hazards, what can people and organizations do to help our situation?Better access to information
Responsive to a changing situationHave the proper content, latency, spatial detail
PlanTake actions to reduce vulnerability
Specific actions to address hazard management within integrated assessment and planning
1. An assessment of the presence and effect of natural events on the goods and services provided by natural resources
2. Estimates of the potential impact of hazard events on development activities3. Include measures to reduce vulnerability in the proposed development activities
Organization of American States
Drought is a kind of climate hazard, and it is one that dramatically effects agriculture. Generally more costly than other hazards especially when we consider the impacts and costs at multiple scales.Multiple tools are needed to access information about hazards
Where, When, How severe?Remote sensing is one tool
Remote Sensing AdvantagesCost-effective and rapid of acquiring up-to-date information over a large geographical areaPractical way to obtain data for inaccessible placesHigh repetition rate and continuous coverage (time and space)Standard methods and techniques
Remote Sensing LimitationsIndirect measure of the phenomenaAtmosphere noise needs to be correctedGeometric and sensor calibration issues
Effect Accuracy
StackingSmoothing
Anomaly DetectionMetrics Calculation(SOS, SG, PASG)
GeoregistrationCompositing
Surface Reflectance
AVHRR
MODIS
User/DecisionSupport System
Satellite Systems
Data/products to partners >> Regular and Quick
Data Services
Data Translation
Vegetation Dynamics
and VegDRIModels
2009>
Existing
EMODIS System
Vegetation Dynamics System
Drought Impacts•Annual direct losses to the U.S. due to drought are, on average, $6-8 billion (FEMA) 2012 $$150 billion•Drought severity can be significantly under- or over-estimated due to inadequate drought observations. This affects Planning, Prediction, Mitigation, and Response.•Impacts are evident at multiple scales (local, regional, national, global) and in multiple sectors
Drought Impacts
Health problemsBankruptcy
ServiceFarm IncomeYields
Migration
Tax Base
State/Regional Economic
Productivity
RegionalProduction
Trade Balance
Inflation
Food PricesDistribution
National Economy
U.S. FoodSupply
Famine
Social Conflict
Food PricesDistribution
Foreign Economies
GlobalFood
Supply
Health problemsBankruptcy
ServiceFarm IncomeYields
Migration
Tax Base
State/Regional Economic
Productivity
RegionalProduction
Trade Balance
Inflation
Food PricesDistribution
National Economy
U.S. FoodSupply
Famine
Social Conflict
Food PricesDistribution
Foreign Economies
GlobalFood
Supply
Local
Regional
National
Global/Multinational
Agricultural Economic SocialWarrick and Bowden, 1981
U.S. requirements for operational drought monitoring—geospatial productsProduct coverage National synoptic
Product schedule Weekly, circa Monday a.m.Spatial scale 1-4 km2, sub-county detailsProduct latency <24-48 hoursLength of record (providing climatology)
~30 years for climate data, information framed related to climatology or history
Start of SeasonEnd of SeasonLength of SeasonSeasonal “greenness” –cumulative productivity
Multi-year time-series observations support National monitoring of land change
Normalized Difference Vegetation Index (NDVI)
Integrating Satellite and Climate DataSeasonal greenness condition from satellite highlights areas with anomalous vegetation condition
Deficits (compared to average condition) might be caused by drought, flooding, late greennup, land cover conversion, etc. Climate information is needed to provide evidence that enables interpretation of the satellite data anomalies
1) land use/land cover type
2) soil available water capacity (STATSGO)
3) ecoregion type
4) irrigation status
5) elevation
* Models developed from a 20-year historical record (1989 – 2009)
of climate and satellite observations at 3,000+ weather
station locations.
Biophysical variables are static over time.
RegressionTree
Model (*)
Satellite Data
1-km2 VegDRI Map
1) Percent Annual Seasonal Greenness (PASG)
2) Start of Season Anomaly (SOSA)
1) Palmer Drought Severity Index (PDSI)
2) Standardized Precipitation Index (SPI)
Climate Data
Biophysical Data
Data Input Variables
1. Historical Database Development
2. Model Development
3. Map Generation
Vegetation Drought Response Index MethodologyBrown, J.F., et al. (2008). The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation. GIScience and Remote Sensing, 45, 16-46.
eMODIS Expedited
Terra MODIS
LANCE
T+11hrs
EDOS
MODIS L0 Data
T+3hrs
T+6hrs
MODISL2, L1B Data
MODAPS
LAADS
eMODIS Historical
Input Data Target: Monday 10:30 a.m.
USGS Drought Monitoring
NDMC Vegetation Drought Response Index
NIDIS Drought Portal
U.S. Drought Monitor
VegDRI
VegDRI Flow: Providing Near-real time Delivery of Information
2001, 2006 National Land Cover Datasets
20 LC ClassesOnly 2 Agricultural Classes
~78% Overall Accuracy
Crop Type Classification of the U.S. Great Plains: An Application of Regression Tree Modeling using Remote Sensing and Environmental Data
• Spatial coverage: U.S. Great Plains• Temporal coverage: 2000 – 2011• Spatial resolution: 250 meter• Overall model classification
accuracy: 87%• Linear agreement with county
results from the USDA NASS Survey Program: R2 = 0.76
D. Howard, B. Wylie
Global Agricultural Monitoring System of Systems:
GEOSS ActivitySatellite observations, in-situ observations and model outputs are needed. Standardization and coordination among countriesCombined information (seasonal forecast models, agro-meterological data [precip, temp, humidity], in-situ obs, satellite obs at various scales, optical, thermal, microwave…Planted area, crop condition, crop type, crop yield
SummaryRemotely sensed observations (spatial detail and synoptic coverage) are a critical tool for monitoring hazardsNeed to understand limitations and accuracyNeed for continued development of tools that fit national needs, and also enhance a global systemInternational cooperation and technical advancement is being supported through GLAM
U.S. Department of the InteriorU.S. Geological Survey
2006 Satellite Vegetation Phenology for the Conterminous U.S.
April 2, 2006 April 30, 2006 May 28, 2006
June 25, 2006 July 23, 2006 August 20, 2006
September 17, 2006 October 15, 2006 October 29, 2006
March 2007
Earth Observing Systems
VIIRS optical band widths will be similar to MODIS
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
NOAA-11 AVHRR
(1:30pm at launch, 5:00pm at the end)
NOAA-14 AVHRR
(1:30pm at launch, 5:00pm at the end)
NOAA-16 AVHRR
(2:00pm)
NOAA-17 AVHRR
(10:00am)
SPOT-4 VEGETATION
(10:30am)
Terra MODIS
(10:30am)
Aqua MODIS
(1:30pm)
NPP VIIRS
(1:30pm)
Landsat-5 TM
(10:00am)
Landsat-7 ETM+
(10:00am)
Jan 1995 Sep 2001
Jan 2001
Aug 2002
Feb 2000
Jun 2002
Apr 1998
Sep 2011
Sep 2003*
Dec 2002
Jan 1989 Sep 1994
Not Recommended
(Operating as Secondary)
(Operating as Secondary)
Since March 1984
April 1999 May 2003
SLC-of fSLC-on
Examples of Federal Policy Decisions
Allocation of Federal Emergency Relief Funds
U.S. Drought Monitor used as primary tool in allocating federal emergency drought relief
Bureau of Reclamation for American Indian Nations of the Southwest
Use of US Drought Monitor to trigger several key drought mitigation programs (including livestock assistance under the non-Fat Dry Milk Initiative and the Conservation Reserve Program)
Examples of Agribusiness Decisions
Federal Drought Information in Agribusiness
Used by Farmers and Ranchers in making purchasing decisions
Making crop planting decisionsIdentifying areas of greatest demand for hayEvaluating feed supplies and potential for shortages
Kansas Association of Wheat Growers and other agriculture-related groups rely on US Drought Monitor products
Examples of Agribusiness Decisions
Futures pricing of U.S. CommoditiesKansas City and Chicago Boards of Trade use federal drought monitoring and forecast information in futures pricing for U.S. CommoditiesOther Futures brokering companies (e.g., Allendale Inc.) use the USDM for assessing impacts to grain futures and for providing advisories to customers
Examples of Water Management Decisions
•Bonneville Power Administration with $3B in annual revenues depends on water supply forecasts/drought information for hydro power management decisions•Critical water management decisions that affect agriculture and wildlife resources in Klamath Basin are heavily dependent on accurate and timely drought information
Examples of Energy Decisions
Federal Energy Regulatory CommissionUse Drought Monitor information for the oversight of energy marketsHold drought workshops to improve and maintain coordination and cooperation among licensees, agencies, stakeholders, and Commission staff during developing drought
State and Local DecisionsState and local drought planning
Requires higher spatial resolution and improved method for communicating drought classification categoriesEnhanced coverage of surface observing networks along with improvements in reporting frequency and timeliness will support decision-making at the county level