Enhancement of the U.S. Drought Monitor Through the Integration of NASA Vegetation Index Imagery

Transcription

1 Enhancement of the U.S. Drought Monitor Through the Integration of NASA Vegetation Index Imagery Project and Related Activities at USGS/EROS Jim Verdin, Jesslyn Brown, Yingxin Gu, Gail Schmidt, Troy McVay U.S. Department of the Interior U.S. Geological Survey NASA JPL Drought Project Meeting Boulder, Colorado September 30, 2008

2 Objective Integration of MODIS VI and derivative products into the U.S. Drought Monitor Decision Support System, and the emerging National Integrated Drought Information System (NIDIS)

3 Water Management: National Drought Monitoring System Earth System Models Land Surface Models: Vegetation Drought Response Index Predictions/Forecasts Information products Vegetation Indices MODIS NDVI MODIS NDWI AVHRR NDVI Phenological Metrics Start of Season Start of Season Anomaly Seasonal Greenness Decision Support Systems, Assessments, Management Actions National Integrated Drought Information System US Drought Monitor Weekly map and narrative NIDIS web portal Value & Benefits to Society Quantitative and qualitative benefits from improved decisions Wider dissemination of drought information Improved understanding of drought effects at sub-county scale Earth Observations Land Surface Vegetation: MODIS and AVHRR Precipitation: Weather Station networks, RADAR observations Land Use/Land Cover: Landsat, MODIS Percent of Average SG Gridded Rainfall Products Calibrated RADAR Standardized Precipitation Index Observations, Parameters & Products Analyses Early Drought Detection Drought Spatial Extent Drought State/Drought Severity Decisions / Actions Drought Plans Activated Urban Water Restrictions Drought Assistance Programs Agricultural Choices for Water Conservation Quicker response for State Drought Task Forces and State Governors Increased spatial precision in drought emergency designations Better informed state and local decision making leading to more effective use of available water and drought relief program resources

4 Topics FY 2008 Progress Data Continuity (AVHRR to MODIS) Data Production System Data Validation Project Team Support Presentations Publications FY 2009 Plans Data Continuity (AVHRR to MODIS) Data Validation Data Production System Data Delivery Project Team Support Presentations Publications

5 FY 2008 Progress emodis System/Drought System Development 2008 emodis expedited data stream, latency Historical data for data translation Terra MODIS data (Aqua provides redundancy) System integration for seamless drought data production (from satellite to decision-maker) System testing Staffing challenges

6 FY 2008 Progress Data Continuity Methodology* Translation equation based on a combination of canonical correlation analysis (CCA) and geometric mean regression (GMR) Data used: 1-km AVHRR/3 and emodis NDVI for year 2005 One translation equation based on 2005 weekly composited NDVI The final equation is of the form: NDVIp = x ( x NDVI x NDVI 2 ) where NDVIp is the predicted, "MODIS-like" AVHRR-NDVI and NDVI is the AVHRR-NDVI. *Collaboration with T. Miura, Univ. of Hawaii

7 FY 2008 Progress Data Continuity Data translation algorithm work parsed by phenoclasses Majority analysis for phenoclasses (7-by-7 Windows) Total of 40 phenoclasses => 39 classes Original 1 km By: T. Miura Class 15 not considered (mainly ocean, lake, and river systems) Majority Analysis Results

8 By: T. Miura After translation Before translation

9 Before translation By: T. Miura After translation

10 FY 2008 Progress Data validation evaluation Performed comparisons between emodis and AVHRR-based drought products (apparent differences because of historical coverage, evaluation will be extended in FY2009) Oklahoma mesonet study

11 Percent of Average Seasonal Greenness (July 14, 2008)

12 FY 2008 Progress Project Support Provided MODIS irrigation layer and MODIS NDVI and NDWI to D. Allured, NOAA

13 FY 2008 Progress Publications Gu, Y., Hunt E., Wardlow, B., Basara, J., Brown, J.F., and Verdin, J.P., Evaluation and validation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data, In Press, Geophysical Research Letters. Brown, J.F., Pervez, S., and Maxwell, S., Mapping Irrigated Lands across the United States using MODIS Satellite Imagery, In Global Mapping of Irrigated and Rainfed Cropland Areas using Remote Sensing, edited by P. Thenkabail and J. Lyon, In Press, Taylor and Francis.

14 Ground validation of MODIS vegetation indices for drought monitoring Clay loam BOIS Loam BEAV Silt clay loam NEWK Silt clay loam Clay loam LAHO REDR Sandy clay loam MARE STIL Loam PERKLoam Silt loam VINI MIAM Silt loa TX Clay HOLL Silt loam Loamy sand HINT ELRE Silt loam SHAW Sandy clay loam WASH OK Silt loam STIG Silt loam WIST 17 Oklahoma Mesonet sites were selected for the validation. The geographic location and land cover type (2001 NLCD) of each study site are shown in the figure above.

15 Ground validation of MODIS vegetation indic with soil moisture observations STIG NDVI NDWI 5-cm FWI 25-cm FWI 60-cm FWI 0.80 NDVI/NDWI/FWI /9/02 9/6/02 1/4/03 5/4/03 9/1/03 12/30/03 4/28/04 8/26/04 12/24/04 4/23/05 8/21/05 12/19/05 4/18/06 8/16/06 Date

16 Ground validation of MODIS vegetation indices with soil moisture observations The relationship between satellite-derived vegetation indices and soil moisture was highly dependent on the land cover spatial distribution and soil type. Homogeneous vegetation cover on silt loam soils had the highest correlation between FWI and both satellite indices (R~0.82), while heterogeneous vegetation cover on loam soils had the lowest correlation (R~0.22). Over homogeneous vegetation cover, both NDVI and NDWI were sensitive to changes in soil moisture, which in turn, are strongly related to drought. Results from this study provide useful information for improving capabilities to monitor drought stress on vegetation by evaluating the utility of new indices such as the NDWI for this purpose.

17 FY 2008 Progress Presentations Brown, J.F., EROS Drought Monitoring Activities, U.S. Drought Monitor Forum, October Brown, J.F., et al., Using emodis Vegetation Indices for Operational Drought Monitoring, NIDIS Remote Sensing Workshop, February Gu, Y, et al., Evaluation and validation of MODIS NDVI and NDWI for vegetation drought monitoring over the central Great Plains of the United States, The XXI Congress for the International Society for Photogrammetry and Remote Sensing (ISPRS), Beijing, China, July 2008 [POSTER]. Brown, J.F., and Hayes, M.J. USGS and NDMC: Drought Monitoring Progress, USGS Headquarters, August 2008.

18 End of FY2008 Progress

19 Topics FY 2008 Progress Data Continuity (AVHRR to MODIS) Data Production System Data Validation Project Team Support Presentations Publications FY 2009 Plans Data Continuity (AVHRR to MODIS) Data/System Validation Data Production System Data Delivery Project Team Support Presentations Publications

20 FY 2009 Plans Data Continuity-Data Translation Apply current data translation algorithm to AVHRR history (December 1, 2008) Evaluate retrospective data (2002, 2006 droughts) Examine sensitivity of algorithm to changes in source data or phenoclasses

21 FY 2009 Plans Data Validation Perform validation of emodis vegetation index products (compare emodis [expedited and historical products], standard MODIS, and AVHRR) Compare historical NDVIp and emodis NDVI, PASGp and PASG (predicted products based on historical translated AVHRR)

22 FY 2009 Plans emodis System/Drought Production System testing and validation Planned system tests Historical 2008 growing season testing (Nov 2008) Near-real time testing (Dec 2008 Jan 2009) Near-real time production (Apr 2009)

23 FY2009 Plans Data Delivery [each week by Monday a.m. at 10:30 central time](apr 2009) USGS Drought Monitoring interactive map service Geotiff data delivery to NDMC Graphics data delivery to NDMC project web site

24 php

25 FY 2009 Plans Presentations Pecora Conference (Nov 2008) Conference on Ecosystem Services (Dec 2008) Publications Data translation work (T. Miura) Validation (comparisons between emodis, standard MODIS, and AVHRR VI products)? Open for discussion possible expansion of OK Mesonet study to include QScat and AMSR-E data sets?

26 End of FY2009 Plans