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SISTER: DESIS L2A Corrected Surface Reflectance 30 m V001

Documentation Revision Date: 2023-06-05

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 2A topographic and glint corrected surface reflectances at 30-m spatial resolution derived from data measured by the DLR Earth Sensing Imaging Spectrometer (DESIS) instrument (https://www.dlr.de/eoc/desktopdefault.aspx/tabid-13614). For the purposes of SISTER, only a handful of scenes have been selected from this mission, with a temporal range between 2021-08-20 and 2019-02-04 and a spatial coverage that is global in scale. DESIS samples spectra over the visible and near-infrared wavelength range from 400 to 1000 nm with a unique spectral resolution of 2.5 nm. The raw DESIS data is first processed to L1B orthocorrected calibrated radiance by the German Aerospace Center (DLR) and then ingested into the SISTER platform for further downstream analysis. This collection was derived from resampled surface reflectance and observation geometry using a combination of topographic and glint correction algorithms. Topographic correction was performed using the Sun-Canopy-Sensor+C algorithm (Soenen et al., 2005) and glint correction was performed using the method of Gao and Li (2021). Because of the narrow field of view and off-nadir viewing the BRDF correction algorithm was not applied. The output products are provided in ENVI format with values expressed as percentages in the range 0-1.

For this dataset, there are 64 total files including eight scenes files of reflectance in ENVI binary and header pairs as well as experimental product generation traceability files in JSON file formats, and a quicklook image for each flight line. 

Figure 1. Quicklook image for topographic glint corrected surface reflectance from the DESIS sensor acquired on June 18 2022 over Nye County, Nevada, south of Duckwater, NV and north of the Desert National Wildlife Range (approx. 38.408 lat, -115.691 lon). Source: SISTER_DESIS_L2A_CORFL_20220618T211059_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: DESIS L2A Corrected Surface Reflectance 30 m V001. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2165

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 2A topographic and glint corrected surface reflectances at 30-m spatial resolution derived from data measured by the DLR Earth Sens­ing Imag­ing Spec­trom­e­ter (DESIS) instrument (https://www.dlr.de/eoc/desktopdefault.aspx/tabid-13614). For the purposes of SISTER, only a handful of scenes have been selected from this mission, with a temporal range between 2021-08-20 and 2019-02-04 and a spatial coverage that is global in scale.

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-Classic 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-NG 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

Spectral Resolution: 10 nm

Temporal Resolution: One-time estimates

Temporal Coverage: 2019-02-04 to 2022-06-18

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

Site Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude
DESIS Lines  -158.1085 152.3013 46.3992 -23.7926

Data File Information

There are 65 total files including eight scenes with files of reflectance for each scene (eight files per scene) in ENVI binary and header pairs.There is also an associated quicklook image of reflectance as well as processing product generation information for experimental reproducibility.

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_DESIS_L2A_CORFL_20130612T191820_001.bin
  • SISTER_DESIS_L2A_CORFL_20130612T190221_001.hdr

The ENVI header (.hdr) (https://www.l3harrisgeospatial.com/docs/enviheaderfiles.html) for each ENVI holds metadata for the binary data file, including: 

  • number of samples (columns), lines (rows), and bands 
  • band information: wavelength and fwhm
  • data type (4 = Float32, 5=Float64), interleave type, and byte order 
  • map info: projection and datum, coordinates for x y reference points, pixel size, and map units 
  • file metadata: sensor type, start and end acquistion time, and bounding box

The dataset also includes a quicklook image (png) for each flight line and data file run identifiers in JSON file format (Table 1) used for data product traceability for each experimental run.

Table 2. The outputs of the L2A corrected reflectance PGE.

Product description Units Example filename
Corrected reflectance datacube % SISTER_DESIS_L2A_CORFL_20130612T191820_001.bin
Corrected reflectance header file - SISTER_DESIS_L2A_CORFL_20130612T190221_001.hdr
Metadata including sensor, start and end time, description, bounding box, product, and processing level - SISTER_DESIS_L2A_CORFL_20130612T190221_001.met.json
Quicklook image - SISTER_DESIS_L2A_CORFL_20130612T190221_001.png
PGE runconfig: defines inputs for the dataset's runs (one file per flight line) - SISTER_DESIS_L2A_CORFL_20130612T190221_001.runconfig.json
PGE log (one file per flight line) - SISTER_DESIS_L2A_CORFL_20130612T190221_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_DESIS_L2A_CORFL_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_DESIS_L2A_CORFL_20110513T175417_001.dataset.json

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

Instrument Instrument full name
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

A subset of flightlines collected over terrestrial and aquatic targets were compared to in-situ spectra using mean absolute error (MAE), spectral angle (SA), and root mean squared error (RMSE). Two PRISMA and two DESIS flightlines were compared to RadCalNet measurements from the Gobabeb and Railroad Valley sites. Seven AVIRIS-NG flights collected for the SHIFT campaign were compared to concurrent Ramses TriOS remote sensing reflectance measurements taken off the coast of Santa Barbara, CA, USA. RadCalNet spectra range from 400- 2500 nm and Ramses TriOS from 400-800 nm. All comparisons showed acceptable agreement between field and image spectra (average terrestrial - MAE: 0.02; SA: 0.99, RMSE:0.02 and aquatic - MAE:0.01; SA:0.95; RMSE:0.01). Statistics and visualizations indicated that corrected reflectance products had slightly better agreement than resampled reflectance products over water targets. DESIS measurements had the largest differences for wavelengths less than 500 nm, while PRISMA had the greatest differences for wavelengths less than 500 nm and between 2000-2250 nm. AVIRIS-NG generally showed a greater difference between field and image spectra as wavelength increased.

Data Acquisition, Materials, and Methods

The datasets in this collection were collected by DESIS, a spaceborne imaging spectrometer installed onboard the International Space Station and operated by the German Space Agency (DRL). DESIS measures radiance at 3-nanometer (nm) intervals in the visi+E2ble to near infrared spectral range between 400 and 1000 nm at 30-m spatial resolution. The DESIS scenes included in this collection are globally distributed and primarily consist of aquatic targets and locations with in situ validation datasets, namely RadCalnet sites (Bouvet et al., 2019). Image datasets were downloaded from the DLR EOWEB GeoPortal and 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 converted to radiance using provided band gains and offsets and per-pixel sensor and solar geometries were generated using acquisition metadata. A digital elevation model (DEM) covering the extent of the image was then generated from the global Copernicus DEM ('https://copernicus-dem-30m.s3.amazonaws.com/'). 

DESIS radiance datasets were then 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 and glint correction algorithms were applied to each image. Topographic correction was performed using the Sun-Canopy-Sensor+C algorithm (Soenen et al., 2005), and glint correction was performed using the method of Gao and Li (2021).

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: DESIS L2A Corrected Surface Reflectance 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

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