Accessing NASA data NASA ORNL DAAC Distributed Active

Accessing NASA data NASA ORNL DAAC (Distributed Active Archiving Center) Oak Ridge National Laboratory http: //www. daac. ornl. gov/

NASA Observing Spacecraft for Earth System Research Moderate Resolution Imaging Spectroradiometer (MODIS)

How a Polar Orbiting Satellite orbits…

Haze Cloud Sunglint Data provided by NASA Goddard Space Flight Center. Image processed by Battelle using MODIS HDF Look.

MODIS Aerosol Optical Depth 25 June 2002 Data provided by NASA Goddard Space Flight Center. Image processed by Battelle using MODIS HDF Look.

The Earth Observing System (EOS) Program EOSDIS Archive • NASA’s Earth Observing System (EOS) Program – centerpiece of NASA’s Earth Science Directorate, largest component in the U. S. Climate Change Science Program – spaced-based observing system – ground-based field campaigns – objective is to enable quick and easy access to data about the earth • EOS Data and Information System (EOSDIS) – explicitly planned and funded by NASA to make maximum use of the data – data available at 8 Distributed Active Archive Centers (DAACs), organized by scientific discipline

EOSDIS Distributed Active Archive Centers EDC U. Colorado JPL Cryosphere Land Processes GSFC Upper Atmosphere, Global Biosphere, and Geophysics SEDAC Socio-economic Ocean Circulation And Air-sea Interaction U. Alaska Sea Ice and Polar Processes La. RC ORNL Biogeochemical Dynamics Atmospheric Processes

Data Center Earth System Science discipline ASF DAAC- Alaska Satellite Facility U. of Alaska Synthetic Aperture Radar (SAR), Sea Ice, Polar processes, Geophysics GES DAAC - GSFC Earth Sciences Goddard Space Flight Center Atmospheric Composition , Atmospheric dynamics, Global Precipitation, Ocean biology, Ocean dynamics, Solar irradiance GHRC – Global Hydrology Resource Center Nat’l Space Science & Technology Center Hydrologic cycle, Severe Weather Interactions, Lightning, Convection La. RC DAAC – Langley Research Center Radiation budget, clouds, Aerosols, Tropospheric Chemistry LP DAAC – Land processes EROS Data Center (USGS) Land Processes NSIDC DAAC- National Snow and Ice Data U. of Colorado Snow and ice, Cryosphere and climate ORNL DAACOak Ridge National Lab Biogeochemical dynamics, Ecological data, Environmental processes PO, DAAC – Physical Oceanography Jet Propulsion Lab (JPL) Oceanic Processes, Air-Sea interactions SEDAC – Socioeceonomic Data and Applications Center Columbia University Population, Sustainability, Geospatial data, Multilateral Environmental Agreements

Getting data from Data Centers • Directly from Data Centers websites – Center-unique search-and-order systems – Specialized data set tools • Viewing, subsetting, web GIS • EOS Data Gateway (EDG)- A NASA site where one can search across all the NASA data centers and also order (soon to be replaced by another system called ECHO). Has browse capability. http: //eos. nasa. gov/imswelcome • Global Change Master Directory – Allows one to search across all the NASA data centers plus many other data sites. Over 2, 400 providers. Points you to where to order. ( but is not the place to order. ) http: //gcmd. nasa. gov • Many of the data sets require special tools for image processing and analysis. These tools are provided by the data centers and are under continual development.

http: //ghrc. msfc. nasa. gov/ http: //datapool. nsstc. nasa. gov

Example of a data center search system - hydrology

EOS Data Gateway http: //eos. nasa. gov/imswelcome

http: //gcmd. nasa. gov/

ORNL DAAC ~ Distributed Active Archive Center http: //www. daac. ornl. gov/ • Mission: Support the needs of NASA’s Earth Science Enterprise (ESE) and Earth Observing System (EOS) Program by assembling, archiving, and distributing terrestrial biogeochemistry and ecosystem dynamics data • Sponsor: NASA – Martha Maiden - EOSDIS – Diane Wickland - Earth System Science – Carbon Cycle and Ecosystems • Is not responsible for satellite downloading. Does get satellite data from other NASA data centers… and then puts it in a format accessible to ecological field researchers.

ORNL DAAC: Roles in EOS Four primary data management roles, supporting: 1. Field Campaigns • 6 -9 year intensive study of a region: • Amazon (LBA) • Canada (BOREAS) • Southern Africa (SAFARI 2000) 3. Regional and Global Studies* • Climate • Soils • Vegetation • Hydroclimatology 2. Validation of Remote Sensing In-situ Products Observations Remote Sensing BOREAS LBA LAI/f. PAR NPP LBA S 2 K ? LAI/f. PAR NPP S 2 K 4. Model Code* • Benchmark Models • IBIS, BIOME-BGC, LSM • Manuscript Models • PNe. T, Century, Biome-BGC

ORNL DAAC data sets & renewable energy? • Regional & global data relevant to hydropower – Climate collections - Several global climate data sets. Climate data include measured and modeled values for variables such as temperature, precipitation, humidity, radiation, wind velocity, and cloud cover – Hydroclimatology collections - data on streamflow and climatology. The data were collected with a range of frequencies (daily and monthly) and are from meteorological and streamflow discharge stations in the U. S. – River discharge - The Global River Discharge (Riv. DIS) data set contains monthly discharge measurements for 1018 stations located throughout the world. The period of record varies widely from station to station, with a mean of 21. 5 years.

ORNL DAAC data sets & renewable energy? • Regional & global data relevant to bioenergy – Climate collections - Several global climate data sets. Climate data include measured and modeled values for variables such as temperature, precipitation, humidity, radiation, wind velocity, and cloud cover – Soil Collection - data on the physical and chemical properties of soils, including soil carbon and nitrogen, soil waterholding capacity, soil respiration, and soil texture. The data are gridded at spatial scales ranging from regional to global. – Vegetation Collections - Gridded data on vegetation from regional to continental scales. Information about vegetation data archived at the ORNL DAAC is available on the Leaf Area Index Web page. The DAAC also offers data from the Net Primary Productivity Database, which contains biomass and NPP estimates.

MODIS ASCII Subsets: Remote Sensing Products for Field Sites Bob Cook, Steve Margle, Susan Holladay, and Suresh Kumar ORNL DAAC Oak Ridge National Laboratory Distributed Active Archive Center Oak Ridge, Tennessee, USA

MODIS ASCII Subsets (Coll. 4) q Subsets of Terra and Aqua MODIS Land Products for 280 sites worldwide (field sites or flux towers) in ASCII format q 7 km x 7 km centered on flux tower or field sites q Two annual products, four 8 -day products, two 16 -day products, and calculated albedo, from 2000 to present MODIS Products Surface Reflectance Surface Temperature Land Cover NDVI / EVI LAI / f. PAR Net Photosynthesis Annual NPP Albedo (calc) Reflectance – BRDF Adjusted

Getting MODIS Data from the ORNL DAAC

* Images from USGS Global Visualization Viewer http: //glovis. usgs. gov/ Dec 02 Jan 03 Feb 02 Mar 02 Apr 02 Location from Google maps Greenup (Above images) – Matches with time series Also 2001, seems to be a special case – Scope for further analysis NDVI Time series for cropland in Michigan

Multiple paths to access data • FTP – most popular method • Picklists – Site, investigator, land cover class, network • Web. GIS – Site location plus background layers • Geo. TIFF file picklist – with Web. GIS • Google Earth – MODIS Subset metadata file that opens in Google Earth application

Using Google Earth to Access Subsets

Using Google Earth to Access Subsets LAI at Lost Creek NDVI at Lost Creek Pixel Values Mean Value of Pixels Percent of Pixels that meet QC Criteria

Beginning to compile site data for comparison NDVI Albedo (Visible) Pixel Values Mean Value of Pixels Percent of Pixels that meet QC Criteria

Acquisition and Processing of MODIS Tiles: Tool for North America LP DAAC MODIS Data Pool ORNL DAAC Automatic FTP pull from Data Pool Inventory HDF Tiles MODIS Reprojection Tool: Conversion to Binary Temporary Inventory ORNL Code: Conversion to ASCII tiles (per SDS) 1200 x 1200 km Files for User Interface Computer Resources Dedicated Server 10 TB RAID storage (capacity through 2009 for 1. 5 TB/y) SDS = Science Data Set

User Interface • User selects center coordinates or site, areal extent, and period of interest • Processing of time series (selection of tiles, mosaicking, generating time series data file and graphs) takes 10 to 60 minutes for most products (depends on area, time period, and product) • URL with graphs and pointers to data files is emailed to user

Time Series Example Center Pixel Mean Value of Pixels Percent of Pixels that meet QC Criteria EVI Southern California

Land Cover Visualization

Time Series Example Center Pixel Mean Value of Pixels Percent of Pixels that meet QC Criteria Mean (std dev) for pixels with same land cover as the center pixel (20 of 49 pixels) Center pixel = Woody Savannas

Data Download Options

Importing ASCII Grid Data into GIS/Image processing software Table of Contents Importing data into: • Arc. GIS 9. x • ENVI • Arc. View 3. x • GRASS Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Importing the ASCII Grid data into Arc. GIS 9. x Go to Table of Contents Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Example File : GRID. MOD 13 A 2. asc MODIS ASCII Subsets: Data Visualization [MOD 13 A 2] Terra Vegetation Indices (NDVI, EVI) USA, Walker Branch Watershed, Oak Ridge, Tennessee Centered on Latitude [35. 958767] Longitude [-84. 287433] 7 Kilometers [7 Pixels] Wide and 7 Kilometers [7 Pixels] High Requested Time Span November 2005 to November 2005 For a PRJ file, access http: //daac. ornl. gov/cgi-bin/MODIS/GR_common/modis. prj For a prj. adf file, access http: //daac. ornl. gov/cgi-bin/MODIS/GR_common/prj. adf MODIS HDF Tile MOD 13 A 2. A 2005305. h 11 v 05. 004. 2005325075111. hdf -----START Scientific Data Set (Band): 1_km_16_days_NDVI, MODIS Date: A 2005305 (Nov. 1, 2005)----ncols 7 nrows 7 xllcorner -7589988. 98 yllcorner 3995608. 83 cellsize 926. 62543305583381 nodata_value -9999999 5579 5846 5940 5769 5566 5869 5776 6173 5722 5876 5912 5920 5882 5632 5844 5812 5972 5904 5154 4966 5282 5786 5765 5822 5695 5739 5817 5992 5609 5094 4333 5790 5763 5793 5863 5602 5499 5844 5811 5210 5436 5728 4749 5674 5419 2617 4012 5607 5219 -----END Scientific Data Set (Band): 1_km_16_days_NDVI, MODIS Date: A 2005305 (Nov. 1, 2005)----MODIS HDF Tile MOD 13 A 2. A 2005321. h 11 v 05. 004. 2005342022515. hdf -----START Scientific Data Set (Band): 1_km_16_days_NDVI, MODIS Date: A 2005321 (Nov. 17, 2005)----ncols 7 nrows 7 xllcorner -7589988. 98 yllcorner 3995608. 83 cellsize 926. 62543305583381 nodata_value -9999999 5279 5480 5584 5226 5248 5275 5781 5508 5517 5383 5347 5281 5051 5634 5554 5571 5511 4825 4557 5344 5635 5375 5293 5432 5298 5562 5581 5386 4646 4660 5279 5446 5480 5393 5396 5118 5750 5563 4825 5260 5587 4774 5425 5047 3500 4174 5187 4955 -----END Scientific Data Set (Band): 1_km_16_days_NDVI, MODIS Date: A 2005321 (Nov. 17, 2005)----- Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 1 Copy contents between “-----START Scientific Data Set (Band)…………. . ” And “-----END Scientific Data Set (Band)……………. . . ” Into a separate file. If there are more than one START-END entries, copy contents within each of the START-END statements into individual files like: File GRID_MOD 13 A 2_A 2005305 _1_km_16_days_NDVI. asc from example file GRID. MOD 13 A 2. asc ncols 7 nrows 7 xllcorner -7589988. 98 yllcorner 3995608. 83 cellsize 926. 62543305583381 nodata_value -9999999 5579 5846 5940 5769 5566 5869 5776 6173 5722 5876 5912 5920 5882 5632 5844 5812 5972 5904 5154 4966 5282 5786 5765 5822 5695 5739 5817 5992 5609 5094 4333 5790 5763 5793 5863 5602 5499 5844 5811 5210 5436 5728 4749 5674 5419 2617 4012 5607 5219 Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 2 Importing the individual file GRID_MOD 13 A 2_A 2005305 _1_km_16_days_NDVI. asc into Arc. GIS : Using Arc. Toolbox from ESRI’s Arc. GIS 9. x software Select: Conversion Tools To Raster ASCII to Raster Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 3 Provide path to ASCII file (GRID_MOD 13 A 2_A 2005305 _1_km_16_days_NDVI. asc ) and Output Raster (MD 13 A 205305) Click OK Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 4 After converting to Raster the output raster (MD 13 A 205305) would automatically load into Arc. Map Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 5 Export this file (MD 13 A 205305) into Arc. GIS GRID Right Click on the file to Export Provide output filename (e. g. md 13 a 2053051) and format Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 6 Setting up the projection Download file prj. adf from http: //daac. ornl. gov/cgi-bin/MODIS/GR_common/prj. adf copy the prj. adf file into the GRID file directory (md 13 a 2053051) created in the previous step Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC

Step 7 Load the GRID file in Arc. Map – Make sure that the projection is defined on the dataset Final output md 13 a 2053051 with projection set, overlaid with the MODIS site locations If the projection isn't defined, use the following file to define the projection. Download file modis. prj from http: //daac. ornl. gov/cgi-bin/MODIS/GR_common/modis. prj Copy this file into <ESRI installation Folder>Coordinate SystemsProjected Coordinate SystemsWorldSphere-based and manually set the projection for the file Prepared by Suresh Kumar on March 10 th 2006, ORNL DAAC