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SISTER: AVIRIS-NG L2B Fractional Cover 30 m V001

Documentation Revision Date: 2023-06-02

Dataset Version: 1

Summary

Generated by the Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) activity in support of the NASA Earth System Observatory's Surface Biology and Geology (SBG) mission, this dataset utilizes existing airborne and spaceborne sources to generate prototype data products spanning terrestrial ecosystems, inland and coastal aquatic ecosystems, hydrology, and geology. The objective of SISTER is to mature many of the workflows, algorithms, and data products envisioned for SBG, lay the groundwork to develop a robust cal/val network, and build a vigorous and expansive user community ahead of launch. This dataset contains experimental Level 2B fractional cover maps for water, vegetation, snow/ice, and soil at 30-m spatial resolution derived from data measured by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument during various campaigns (https://avirisng.jpl.nasa.gov/). For the purposes of SISTER, only a handful of scenes have been selected from these campaigns, with a temporal range between 2014-06-25 and 2022-08-19 and spatial coverage within the United States of America and Italy. AVIRIS-NG measures reflected radiance at 5-nanometer (nm) intervals in the visible to shortwave infrared spectral range between 380 and 2510 nm. The raw AVIRIS-NG data is first processed to L1B orthocorrected calibrated radiance by the Imaging Spectroscopy Group at Jet Propulsion Laboratory (JPL) and then ingested into the SISTER platform for further downstream analysis. This collection was derived from corrected surface reflectance using a spectral mixture analysis. Spectral unmixing was performed to derive per-pixel fractional cover estimates of soil, vegetation, water and snow/ice using a generic four end-member dataset. The output products are provided in GeoTIFF format with values expressed as percentages in the range 0-1.

For this dataset, there are 427 total files including 61 flight line files of fractional cover in cloud optimized GeoTIFF file format. Each flight line also contains experimental product generation traceability files in JSON file formats and a Product Generation Executable (PGE) log file.  A quicklook image is also available for each flight line.

Figure 1. Portion of quicklook image for fractional cover (soil, vegetation, water, snow) derived from the AVIRIS-NG sensor acquired on August 15 2022 over the Napper Lake area south of Churchill, Manitoba, Canada (approx. 58.321 lat, -93.360 lon). Source: SISTER_AVNG_L2B_FRCOV_20220815T202918_001.png

Citation

Townsend, P., M.M. Gierach, C. Ade, A.M. Chlus, H. Hua, O. Kwoun, M.J. Lucas, N. Malarout, D.F. Moroni, S. Neely, W. Olson-Duvall, J.K. Pon, S. Shah, and D. Yu. 2023. SISTER: AVIRIS-NG L2B Fractional Cover 30 m V001. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2167

Table of Contents

  1. Dataset Overview
  2. Data Characteristics
  3. Application and Derivation
  4. Quality Assessment
  5. Data Acquisition, Materials, and Methods
  6. Data Access
  7. References

Dataset Overview

This dataset contains experimental Level 2B fractional cover maps for water, vegetation, snow/ice, and soil at 30-m spatial resolution derived from data measured by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument during various campaigns (https://avirisng.jpl.nasa.gov/). For the purposes of SISTER, only a handful of scenes have been selected from these campaigns, with a temporal range between 2014-06-25 and 2022-08-19 and spatial coverage within the United States of America and Italy.

Project:  SISTER 

The Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) is a NASA project aimed at prototyping workflows and generating SBG-like data products in efforts to sustain and build the community to increase prospects for major scientific discovery post launch.

These data are associated with experimental products run by the SISTER Science Team as pre-launch modeling tools and data for algorithm development are investigated. The SISTER files for the Composite Release ID (CRID) 001 experimental run contain 19 separate collections (Table 1) that include four instruments and five data products (with the exception of the DESIS instrument). The output range for all sensors except DESIS is 400-2500 nm, while the DESIS output range is 400-990 nm. 

Table 1.  Summary of SISTER Sensors, Products, and Coding for all CRID 001 outputs available as separate datasets.

Sensor Product Sensor_Level_Product
AVIRIS Next Generation Resampled Surface Reflectance and Uncertainty AVCL_L2A_RSRFL
Corrected Surface Reflectance AVCL_L2A_CORFL
Fractional Cover AVCL_L2B_FRCOV
Vegetative Biochemical Traits AVCL_L2B_VEGBIOCHEM
Snow Grain Size AVCL_L2B_SNOWGRAIN
AVIRIS Next Gen Resampled Surface Reflectance and Uncertainty AVNG_L2A_RSRFL
Corrected Surface Reflectance AVNG_L2A_CORFL
Fractional Cover AVNG_L2B_FRCOV
Vegetative Biochemical Traits AVNG_L2B_VEGBIOCHEM
Snow Grain Size AVNG_L2B_SNOWGRAIN
DESIS Resampled Surface Reflectance and Uncertainty DESIS_L2A_RSRFL
Corrected Surface Reflectance DESIS_L2A_CORFL
Fractional Cover DESIS_L2B_FRCOV
Vegetative Biochemical Traits DESIS_L2B_VEGBIOCHEM
PRISMA Resampled Surface Reflectance and Uncertainty PRISMA_L2A_RSRFL
Corrected Surface Reflectance PRISMA_L2A_CORFL
Fractional Cover PRISMA_L2B_FRCOV
Vegetative Biochemical Traits PRISMA_L2B_VEGBIOCHEM
Snow Grain Size PRISMA_L2B_SNOWGRAIN

Related Datasets:

See SISTER datasets with the Composite Release ID (CRID) version 001 (filter e.g.: V001)

Townsend, P., M.M. Gierach, P.G. Brodrick, A.M. Chlus, H. Hua, O. Kwoun, M.J. Lucas, N. Malarout, D.F. Moroni, S. Neely, W. Olson-Duvall, J.K. Pon, S. Shah, and D. Yu. 2023. SISTER: Composite Release ID (CRID) Product Generation Files, 2023. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2231

  • SISTER_CRID_001.json - SISTER Composite Release ID (CRID) file contains details of repositories and versions used for this V001 run.

Data Characteristics

Spatial Coverage: Selected scenes/flight lines across the globe

Spatial Resolution: 30 m

Temporal Resolution: One-time estimates

Temporal Coverage: 2014-06-25 and 2022-08-19

Site Boundaries: Latitude and longitude are given in decimal degrees.

Site Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude
AVIRIS-NG Flight Lines  -146.4636 12.4918 69.2948 34.3760

 Data File Information

There are 428 total files including 61 flight lines of fractional cover in GeoTIFF format with an associated quicklook image as well as processing product generation information for experimental reproducibility. For the 61 flight lines, there are seven files per flight line.

File naming convention: 
SISTER_<instrument>_<processing_level>_<product>_<flight_id>_<ver>.<ext>, where 

  • <instrument> = the spectroscopy instrument that provided input radiance (Table 3)
  • <processing_level> = the NASA Earthdata Data Processing Level
  • <product> = the SISTER Project data product (Table 2)
  • <flight_id> = flight line identifier, <YYMMDD>T<HHMMSS>, encoding the date and time by year (YY), month (MM), day (DD), and the UTC hour, minute, and second for the start of flight. 
  • <ver> = the SISTER processing version, also known as the CRID"
  • <ext> = file extension 

Example file name:

  • SISTER_AVNG_L2B_FRCOV_20110513T175417_001.tif

GeoTIFF bands and variables

There are four bands in the GeoTIFF files:

  • Band 1: Proportion of fractional cover of soil; variable name: soil_area_fraction
  • Band 2: Proportion of fractional cover of vegetation; variable name: vegetation_area_fraction
  • Band 3: Proportion of fractional cover of water; variable name: water_area_fraction
  • Band 4: Proportion of fractional cover of snow; variable name: snow_area_fraction

Table 2. The outputs of the L2B fractional cover PGE use the following naming convention and produce the following data products. The naming convention for these files follow the same pattern as described above. The no data value in the files is -9999.

Product description Units Example filename
Proportion of fractional cover of soil, vegetation, water, snow - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.tif
Metadata including sensor, start and end time, description, bounding box, product, and processing level -
SISTER_AVNG_L2B_FRCOV_20110513T175417_001.met.json
 
Quicklook image - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.png
PGE runconfig: defines inputs for the dataset's runs (one file per flight line) - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.runconfig.json
PGE log (one file per flight line) - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.log
PGE context: supports data product traceability by providing provenance details, arguments, and runtime settings used during the run of the Product Generation Executable (PGE) on the SISTER platform. - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.context.json
 
Dataset file version (e.g. {"version": "v1.0"}) used internally by SISTER to track product versions.  Note that this is not the same as the CRID. - SISTER_AVNG_L2B_FRCOV_20110513T175417_001.dataset.json
 

Table 3. Possible SISTER Project Instruments available in the v001 dataset

Instrument Instrument fullname
AVCL  AVIRIS Classic
AVNG AVIRIS Next Generation
DESIS DLR Earth Sensing Imaging Spectrometer
PRISMA PRecursore IperSpettrale della Missione Applicativa

Application and Derivation

The 2018 National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space.” identified Surface Biology and Geology (SBG) as a Designated Observable (DO) with the following observing priorities:

* Terrestrial vegetation physiology, functional traits, and health
* Inland and coastal aquatic ecosystems physiology, functional traits, and health
* Snow and ice accumulation, melting, and albedo
* Active surface changes (eruptions, landslides, evolving landscapes, hazard risks)
* Effects of changing land use on surface energy, water, momentum, and C fluxes
* Managing agriculture, natural habitats, water use/quality, and urban development

To accomplish these priorities, the DO requires the combined use of visible to shortwave infrared (VSWIR) imaging spectroscopy and multispectral or hyperspectral thermal infrared (TIR) imagery acquired globally with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. 

This approach presents some interesting challenges. Due to the high spatial and spectral resolution, SBG is expected to generate roughly 90 TB of data products per day. In addition, the number of existing community algorithms for processing this data is large and needs to be evaluated, and there is no particular consensus yet on standard file formats for hyperspectral data.

To help address a subset of these challenges the SBG Algorithms Working Group was formed to review and evaluate the algorithms applicable to the SBG DO. Also, the SISTER activity was created to prototype workflows and generate SBG-like data products

This collection is one of several that include the first experimental data products produced by SISTER with the objective of generating SBG-like VSWIR imagery with 30-m spatial resolution and 10-nm spectral resolution. The scenes in the various SISTER collections include examples from the terrestrial, aquatic, snow/ice, and geologic domains, as well as from validation sites. The main purpose of this data is to provide the scientific community with prototype data products from the SBG workflow in order to get early feedback on things like useability, file formats, and metadata.

Quality Assessment

These products are still considered experimental, and no quality assessment procededure was conducted for this collection.

Data Acquisition, Materials, and Methods

The datasets in this collection were collected by the AVIRIS Next Generation (AVIRIS-NG) imaging spectrometer as part of various flight campaigns in the United States and Italy over vegetation, aquatic and snow targets, including ABOVE, SHIFT and AVIRIS-Europe. AVIRIS-NG measures radiance at 5-nanometer (nm) intervals in the visible to shortwave infrared spectral range between 380 and 2510 nm. The raw AVIRIS-NG data was processed to orthocorrected calibrated radiance by the Imaging Spectroscopy Group at Jet Propulsion Laboratory (JPL) and then ingested into the SISTER platform for further downstream processing (Figure 2).

process flow

Figure 2. Workflow diagram of the SISTER 001 production run (Click on image to view full-resolution version).

First, images were spatially downsampled to 30-meter resolution and processed to surface reflectance using an optimal estimation atmospheric correction algorithm, ISOFIT (Thompson et al., 2018) with an open-source neural-network-based emulator for modelling radiative transfer (Brodrick et al., 2021). Next, spectral resampling to a 10-nm sampling interval was performed in a two-step calculation. Bands were first aggregated and averaged to the closest resolution to the target interval then a piecewise cubic interpolator was used to interpolate the spectra to the target wavelength spacing. 

Following spectral resampling a combination of topographic, bidirectional reflectance distribution function (BRDF) and glint correction algorithms were applied to each image. Topographic correction was performed using the Sun-Canopy-Sensor+C algorithm (Soenen et al., 2005), BRDF correction was performed using the FlexBRDF algorithm (Queally et al., 2022) and glint correction was performed using the method of Gao and Li (2021). 

Fractional cover maps were generated from the corrected reflectance datasets using a spectral mixture analysis (Keshava and Mustard 2002). Spectral unmixing was performed using a generic four endmember dataset to derive fractional cover estimates of soil, vegetation, water and snow/ice. To minimize the impact of intraclass brightness variability on unmixing results a brightness normalization was applied.

For all datasets in the SISTER 001 processing version (also known as the CRID), workflow components, versions, and links to source code are summarized in Table 4 as provided in the SISTER_CRID_001.json dataset file.

Table 4. Key SISTER workflow components, versions, and links to source code used for V001 production (Townsend et al., 2023).

software version url
maap-api-nasa 2.0 https://gitlab.com/geospec/maap-api-nasa/-/tags/2.0
sister-preprocess 2.0.0 https://github.com/EnSpec/sister-preprocess/releases/tag/2.0.0
sister-isofit 2.0.0 https://gitlab.com/geospec/sister-isofit/-/releases/2.0.0
sister-resample 2.0.1 https://github.com/EnSpec/sister-resample/releases/tag/2.0.1
sister-reflect_correct 2.0.0 https://github.com/EnSpec/sister-reflect_correct/releases/tag/2.0.0
sister-fractional-cover 1.0.0 https://gitlab.com/geospec/sister-fractional-cover/-/releases/1.0.0
sister-algorithm_router 1.0.0 https://github.com/EnSpec/sister-algorithm_router/releases/tag/1.0.0
sister-trait_estimate 1.0.0 https://github.com/EnSpec/sister-trait_estimate/releases/tag/1.0.0
sister-grainsize 1.0.0 https://github.com/EnSpec/sister-grainsize/releases/tag/1.0.0

Data Access

These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

SISTER: AVIRIS-NG L2B Fractional Cover 30 m V001

Contact for Data Center Access Information:

References

Brodrick, P.G., D.R. Thompson, J.E. Fahlen, M.L. Eastwood, C.M. Sarture, S.R. Lundeen, W. Olson-Duvall, N. Carmon, and R.O. Green. Generalized radiative transfer emulation for imaging spectroscopy reflectance retrievals, Remote Sensing of Environment, Volume 261, 2021, 112476, ISSN 0034-4257. https://doi.org/10.1016/j.rse.2021.112476

Gao, B.C., and R.R. Li. 2021. Correction of Sunglint Effects in High Spatial Resolution Hyperspectral Imagery Using SWIR or NIR Bands and Taking Account of Spectral Variation of Refractive Index of Water. Advances in Environmental and Engineering Research, 2(3), 1-15. https://doi.org/10.21926/aeer.2103017

Keshava, N., and J.F. Mustard. 2002. Spectral unmixing. IEEE signal processing magazine, 19(1), 44-57. https://doi.org/10.1109/79.974727

Queally, N., Z. Ye, T. Zheng, A. Chlus, F. Schneider, R.P. Pavlick, and P.A. Townsend. 2022. FlexBRDF: A Flexible BRDF Correction for Grouped Processing of Airborne Imaging Spectroscopy Flightlines. Journal of Geophysical Research: Biogeosciences, 127(1), e2021JG006622. https://doi.org/10.1029/2021JG006622

Soenen, S.A., D.R. Peddle, and C.A. Coburn. 2005. SCS+ C: A modified sun-canopy-sensor topographic correction in forested terrain.IEEE Transactions on geoscience and remote sensing, 43(9), 2148-2159. https://doi.org/10.1109/TGRS.2005.852480

Thompson, D.R., V. Natraj, R.O. Green, M.C. Helmlinger, B.C. Gao, and M.L. Eastwood. 2018. Optimal estimation for imaging spectrometer atmospheric correction. Remote Sensing of Environment 216, 355-373. https://doi.org/10.1016/j.rse.2018.07.003

Townsend, P., M.M. Gierach, P.G. Brodrick, A.M. Chlus, H. Hua, O. Kwoun, M.J. Lucas, N. Malarout, D.F. Moroni, S. Neely, W. Olson-Duvall, J.K. Pon, S. Shah, and D. Yu. 2023. SISTER: Composite Release ID (CRID) Product Generation Files, 2023. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2231