Presentation is loading. Please wait.

Presentation is loading. Please wait.

Stennis Space Center Phenological Parameters Estimation Tool Presented by Jerry Gasser Lockheed Martin Mission Services John C. Stennis Space Center USDA.

Similar presentations


Presentation on theme: "Stennis Space Center Phenological Parameters Estimation Tool Presented by Jerry Gasser Lockheed Martin Mission Services John C. Stennis Space Center USDA."— Presentation transcript:

1 Stennis Space Center Phenological Parameters Estimation Tool Presented by Jerry Gasser Lockheed Martin Mission Services John C. Stennis Space Center USDA Forest Service, Asheville, NC September 6-7, 2007

2 Phenological Parameters Estimation Tool Stennis Space Center 2National Aeronautics and Space Administration Phenological Parameters Estimation Tool Background –Phenology is the study of observable key plant and animal life- cycle phenomenology that are influenced by temporal, seasonal changes in environmental conditions— especially those parameters driven by weather and climate (e.g., temperature and precipitation) Objective –Employ the Phenological Parameters Estimation Tool (PPET) to assess the potential of MODIS-based phenological data for characterizing and monitoring vegetation health conditions

3 Phenological Parameters Estimation Tool Stennis Space Center 3National Aeronautics and Space Administration Project Details Approach –Apply multitemporal MODIS data to generate a 250 meters vegetation phenology geospatial data base for the CONUS (conterminous United States) Use filtered NDVI (Normalized Difference Vegetation Index) time series data derived from MODIS (Moderate Resolution Imaging Spectroradiometer) products to calculate phenological parameters on an annual basis Compute parameters over each growing season and derive a set of baseline parameters for each pixel location –Compute phenological parameters for a specific season (or other relevant time frame) and compare the parameters to the baseline data to determine whether disturbances can be detected Goal –Develop or contribute to a forest threat monitoring system that applies PPET data products in order to identify and track emerging forest health problems

4 Phenological Parameters Estimation Tool Stennis Space Center 4National Aeronautics and Space Administration Data Processing Flow Raw MODIS data (from Aqua and Terra satellites) is processed by the TSPT (Time Series Product Tool) to generate filtered time series data The PPET uses TSPT output to generate phenological parameters for each region Data tiles are mosaicked into a CONUS image using ERDAS IMAGINE ® Mosaics of data products are then reprojected to the desired map projection using ERDAS IMAGINE

5 Phenological Parameters Estimation Tool Stennis Space Center 5National Aeronautics and Space Administration PPET Processing Overview For each pixel within an image tile: Extract time series data Identify growing seasons within each year Locate specific points within the growing season; for example: –Beginning –End –Peak Calculate data value and day of year for growing season points of interest Compute integrals, cumulative integrals, and running maximum NDVI over growing season Scale data and store in output ENVI BSQ (Band Sequential) files

6 Phenological Parameters Estimation Tool Stennis Space Center 6National Aeronautics and Space Administration Phenological Parameter Definition Left Min Right Min Start Season End Season Left 80 % Right 80 % Peak Season Center Growing Season

7 Phenological Parameters Estimation Tool Stennis Space Center 7National Aeronautics and Space Administration Phenological Parameter Calculations Using NDVI Data The parameters are calculated as follows: –Base Value = (Left Season Min + Right Season Min) / 2 –Amplitude = Season Peak NDVI – Base Value –Season Start = Left Season Min + (0.2 * Amplitude) –Season End = Right Season Min + (0.2 * Amplitude) –Left 80% Point = Left Season Min + (0.8 * Amplitude) –Right 80% Point = Right Season Min + (0.8 * Amplitude) –Season Length = Season End - Season Start –Small Season Integral = Integral of Season – Base Value –Large Integral = Integral of Season –Cumulative Integral = Integral at each point in time series Day of year parameters are found by locating the corresponding NDVI value within the filtered data

8 Phenological Parameters Estimation Tool Stennis Space Center 8National Aeronautics and Space Administration PPET Phenological Parameters The following parameters that correspond to phenological transitions are included in the PPET phenological parameters product: –NDVI and Day of Left Season Minimum –NDVI and Day of Right Season Minimum –NDVI and Day at Start of Season –NDVI and Day at End of Season –NDVI and Day of Left 80% Point of Season –NDVI and Day of Right 80% Point of Season –NDVI and Day of Season Peak –Small Season Integral –Large Season Integral –Cumulative Integral –Running Maximum NDVI Parameters are stored as 16-bit integers NDVI values are scaled by 1000

9 Phenological Parameters Estimation Tool Stennis Space Center 9National Aeronautics and Space Administration PPET Software Modifications Transitioned from GUI (graphical user interface) based system to batch processing mode –Required because of data volume and processing times for MODIS data files Performance Enhancements –Eliminate curve fitting to smooth data (already done via TSPT) –Exclude water pixels (via NDVI thresholding technique) –Optimize code for large datasets Investigated several processing techniques

10 Phenological Parameters Estimation Tool Stennis Space Center 10National Aeronautics and Space Administration PPET Processing Techniques Pest Phenology Method –Identify the year’s time period when a specific type of pest-induced disturbance usually occurs –Compute specific phenological parameters from data for that time period Cumulative Method –Identify growing seasons for each year (assumes one per year) –Compute phenological parameters for each season –Compute cumulative integrals and a running maximum NDVI for the entire year Seasonal Method –Identify growing seasons for each year (assumes one per year) –Compute phenological parameters for each season Pest phenology and cumulative approaches have potential to monitor vegetation health in near-real time

11 Phenological Parameters Estimation Tool Stennis Space Center 11National Aeronautics and Space Administration Pest Phenology Demonstration Products Pest: Gypsy Moth Area: Mid-Appalachian Highlands Time Period: June 10 to July 27 of each year Primary Phenological Parameter: Maximum NDVI or NDMI (Normalized Difference Moisture Index) during specified time period Input MODIS products used: –MOD02 NDVI and NDMI –MOD09 NDVI –MCD43A NDVI (2000–2002) Temporal composite statistical products: Min, Max, Mean, Median value per pixel across specified time frame This work will be discussed in a follow on presentation

12 Phenological Parameters Estimation Tool Stennis Space Center 12National Aeronautics and Space Administration Cumulative Products Area: Mid-Appalachian Highlands Time Period: June 10 to July 27 of each year Primary Phenological Parameters: Maximum NDVI and Large Integral Input MODIS products used: –MOD13 NDVI Temporal composite statistical products: Min, Max, Mean, Median value per pixel across specified time frame Products generated: –MOD13 Running Max NDVI on July 27 –July 27–June 10 Delta Integral

13 Phenological Parameters Estimation Tool Stennis Space Center 13National Aeronautics and Space Administration MOD13 Pest Phenology and Cumulative Products – Views of 2001 Gypsy Moth Defoliation Cumulative Delta Integral NDVI 2001 Defoliation – Red Tones Cumulative Max NDVI 2001 Defoliation – Red Tones Maximum NDVI 2001 Defoliation – Red Tones

14 Phenological Parameters Estimation Tool Stennis Space Center 14National Aeronautics and Space Administration Seasonal Products Area: Conterminous United States (CONUS) Time Period: 2000–2006 Phenological Parameters: 16 individual parameters, 23 cumulative integral values, and 23 maximum NDVI values Input MODIS products used: –MOD13 NDVI Products generated: –MOD13 Maximum NDVI –MOD13 Small Integral of NDVI –Beginning and end of season –80% points of season

15 Phenological Parameters Estimation Tool Stennis Space Center 15National Aeronautics and Space Administration MODIS Tiles for CONUS Coverage

16 Phenological Parameters Estimation Tool Stennis Space Center 16National Aeronautics and Space Administration MOD13 2003 Max NDVI (250 m) 0.0049.995

17 Stennis Space Center 1.04313.874 MOD13 2003 Small Integral (250 m)

18 Phenological Parameters Estimation Tool Stennis Space Center 18National Aeronautics and Space Administration MOD13 H11V05 2003 Phenological Parameters Season 20% Value Left.779.197 Season 20% Value Right.843.213

19 Phenological Parameters Estimation Tool Stennis Space Center 19National Aeronautics and Space Administration Season 80% Value Left.985.205 Season 80% Value Right.940.228 MOD13 H11V05 2003 Phenological Parameters

20 Phenological Parameters Estimation Tool Stennis Space Center 20National Aeronautics and Space Administration MOD13 CONUS Data Storage Requirements MOD13 Products (250 m) –14 Tiles (4800 x 4800 pixels) –7 Years of data (2000–2006) –Aqua and Terra TSPT Output Files –Intermediate products at each step of processing Cloud removal, Outlier removal, Filtering, Stacking Phenological Parameter Output files –18 parameters per file (scaled to 16-bit integers) Storage –MOD13 Data: 2.0 Terabytes –TSPT Output: 1.6 Terabytes –Phenological Parameters: 273 Gigabytes –Total: Approximately 4 Terabytes

21 Phenological Parameters Estimation Tool Stennis Space Center 21National Aeronautics and Space Administration MOD13 CONUS Data Processing Requirements Eight-processor server –16 Gigabytes of RAM –2.66 GHz processors –Process 7 tiles per run TSPT Code –30 hours per tile Phenological Parameters code –14 hours per tile ERDAS IMAGINE Mosaic/Reprojection –3 hours per year per parameter Process CONUS data for 7 years in less than one week

22 Phenological Parameters Estimation Tool Stennis Space Center 22National Aeronautics and Space Administration Product Comparison Overview MODIS MOD12Q2 ProductPPET Phenological Parameters Input DataEVI (MOD43)NDVI (MOD13) Spatial Resolution1 km250 m Number of times produced per year 2 (hemispheric growing season differences) 1 (Northern hemisphere) CoverageGlobalCONUS Number of output parameters 8 per season16 per season Number of Seasons21 Method of transition determination Piecewise sigmoidal functions fit to EVI data Direct estimation from TSPT processed NDVI data

23 Phenological Parameters Estimation Tool Stennis Space Center 23National Aeronautics and Space Administration Product Parameter Equivalency MODIS MOD12Q2 ProductPPET Phenological Parameters —NDVI and Day of Left Season Minimum Day of onset greeness increaseDay at Start of Season —NDVI at Start of Season EVI and Day of onset greeness maximumNDVI and Day of Left 80% point of Season Day of onset greeness decreaseDay of Right 80% point of Season —NDVI at Right 80% point of Season EVI and Day of onset greeness minimumNDVI and Day at End of Season —NDVI and Day of Right Season Minimum —NDVI and Day of Season Peak EVI AreaLarge Season Integral —Small Season Integral Dynamics Quality Control—

24 Phenological Parameters Estimation Tool Stennis Space Center 24National Aeronautics and Space Administration 2003 MOD12 Land Cover Dynamics: EVI Area 2003 MOD13 PPET Computed Phenological Parameter: Large Integral Value Note Cloud Mask Artifacts 2003 H11V05 Phenological Parameter Comparison

25 Phenological Parameters Estimation Tool Stennis Space Center 25National Aeronautics and Space Administration Summary PPET code has been updated to handle large-scale processing of CONUS data Processing resources are available to generate phenological data in a timely fashion Preliminary data products need further validation and refinement Pest Phenology and Cumulative methods show promise for near-real-time vegetation health monitoring

26 Phenological Parameters Estimation Tool Stennis Space Center 26National Aeronautics and Space Administration Deliverables TSPT and PPET source code and executable files –MATLAB source code –PC based executable files Software documentation MOD13 CONUS phenological parameters –Determine optimal data format and projection

27 Phenological Parameters Estimation Tool Stennis Space Center 27National Aeronautics and Space Administration Next Steps Package initial software and data products for delivery Tweak TSPT and PPET software settings to fine tune processing and generation of phenological parameters Handle bad data values Integrate PPET code into TSPT –Incorporate code as another TSPT module –Develop GUI for software Determine data distribution mechanism for user access Develop “Nowcast” Monitoring System –Implement cumulative method for CONUS –Establish Alert conditions Incorporate ancillary datasets into processing stream Investigate use of MOD02 data products to generate CONUS data Support multiple growing seasons per year

28 Participation in this work by Lockheed Martin Corporation was supported by NASA at the John C. Stennis Space Center, Mississippi, under Task Order NNS04AB54T.

29 Stennis Space Center Backup Slides

30 Phenological Parameters Estimation Tool Stennis Space Center 30National Aeronautics and Space Administration MODIS MOD12Q2 Product Provides global estimates of timing of vegetation phenology Produced twice per year –First period July through June –Second period January through December Produced with 1-km2 spatial resolution Uses EVI (Enhanced Vegetation Index) from the MODIS Nadir BRDF (Bidirectional Reflectance Distribution Function)-adjusted reflectance in the MOD43B4 product

31 Phenological Parameters Estimation Tool Stennis Space Center 31National Aeronautics and Space Administration MODIS MOD12Q2 Parameters The following parameters that correspond to phenological transitions are included in the output MODIS Land Cover Dynamics Product: –Day of onset of greenness increase –Day of onset of greenness maximum –Day of onset of greenness decrease –Day of onset of greenness minimum –EVI at onset of greenness maximum –EVI at onset of greenness minimum –EVI area –Dynamics Quality Control Day parameters are found by differentiating the curvature of sigmoidal functions fit to the EVI data The EVI is calculated from the fit sigmoidal functions

32 Phenological Parameters Estimation Tool Stennis Space Center 32National Aeronautics and Space Administration Phenology Monitoring System PhenMon provides CONUS estimates of GSI (Growing Season Index) Produced on a daily basis Produced with 8-km 2 spatial resolution Derived from AVHRR (Advanced Very High Resolution Radiometer) data

33 Phenological Parameters Estimation Tool Stennis Space Center 33National Aeronautics and Space Administration Product Comparison Overview PhenMon GSI ProductPPET Phenological Parameters Input DataNDVI (AVHRR)NDVI (MOD13) Spatial Resolution8 km250 m Number of times produced per year Daily1 (Northern hemisphere) CoverageCONUS Number of output parameters 116 Method of transition determination N/ADirect estimation from TSPT processed NDVI data


Download ppt "Stennis Space Center Phenological Parameters Estimation Tool Presented by Jerry Gasser Lockheed Martin Mission Services John C. Stennis Space Center USDA."

Similar presentations


Ads by Google