I. Data Set Descriptors A. Title: Merryl Alber. 2019. Variation in Landsat 8-estimated land surface temperature with elevation from Spartina alterniflora marsh cross sections in the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) site and Virginia Coast Reserve (VCR) LTER sites for winter and summer observations spanning 2013-2018. Georgia Coastal Ecosystems LTER Data Catalog (data set MSH-GCE0-1904; http://gce-lter.marsci.uga.edu/public/app/dataset_details.asp?accession=MSH-GCE0-1904) B. Accession Number: MSH-GCE0-1904 C. Description 1. Originator(s): Name: Merryl Alber Address: Dept. of Marine Sciences University of Georgia Athens, Georgia 30602-3636 Country: USA Email: malber@uga.edu 2. Abstract: We estimated land surface temperature from top of atmosphere brightness temperature provided by Landsat 8's band 10 (a thermal band). We collected these measurements first for Spartina alterniflora dominated marsh near the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) eddy covariance flux tower. Measurements were collected from pixels along three east-west cross sections that spanned a marsh edge to interior gradient. We extracted Landsat 8 data for all available cloud-free low tide dates during August, September, January and February during the years 2013 to 2018 and associated these with marsh elevation information from a 1 m^2 Digital Elevation Model (DEM), created by Haldik et al 2013, also available from the GCE data catalog (http://dx.doi.org/10.6073/pasta/4c5187ef603f70cd0a77ece24ef0fed9). We rescaled the DEM to the coarser spatial resolution of Landsat 8 (30 x 30 m) where the rescaled elevation was the mean of the constituent DEM values. Ultimately, we used generalized additive models to relate land surface temperature to elevation, while accounting for variation from spatial proximity, transect and sample date. These models revealed that land surface temperature was negatively related to marsh elevation on the marsh platform. We then confirmed the generality of this pattern by rederiving these same relationships for three cross sections of Spartina alterniflora marsh at Virginia Coast Reserve (VCR) LTER for winter sampling dates only (data also included here). DEM data for VCR LTER are available at https://www.vcrlter.virginia.edu/gisdata/LIDAR/USGS2015/. We used custom R functions that can convert Landsat 8 top of atmosphere brightness temperature or top of atmosphere radiance from band 10 data to land surface temperature, which are available at https://github.com/jloconnell/convert_top_of_atmosphere_thermal_to_land_surface_temperature . Currently, a provisional land surface temperature product is available on earthexplorer.usgs.gov, which was not available at the time of this study. However the R functions and scripts hosted on O'Connell's github will allow end-users to repeat our calculations for any Landsat 8 pixel and will also provide the ability to customize the atmospheric correction algorithms and calibrate the resulting land surface temperature estimation to ground-truth information. 3. Study Type: Other Study 4. Study Themes: Marsh Ecology 5. LTER Core Areas: Other Site Research 6. Georeferences: geographic coordinates as data columns 7. Submission Date: Apr 16, 2019 D. Keywords: Climate Monitoring, cross-site research, digital elevation model, elevation, GCE, Georgia, Georgia Coastal Ecosystems, LTER, remote sensing, salt marshes, Sapelo Island, summer, temperature, USA, VCR, wetlands, winter II. Research Origin Descriptors A. Overall Project Description 1. Project Title: Georgia Coastal Ecosystems LTER Project III 2. Principal Investigators: Name: Merryl Alber Address: Dept. of Marine Sciences University of Georgia Athens, Georgia 30602-3636 Country: USA Email: malber@uga.edu 3. Funding Period: Nov 01, 2012 to Nov 01, 2018 4. Objectives: The research proposed for GCE-III is designed to address how variations in salinity and inundation, driven by climate change and anthropogenic factors, affect biotic and ecosystem responses at different spatial and temporal scales, and to predict the consequences of these changes for habitat provisioning and carbon (C) sequestration across the coastal landscape. 5. Abstract: The Georgia Coastal Ecosystems (GCE) LTER is located along three adjacent sounds on the Atlantic coast and includes both intertidal marshes and estuaries. Long-term drivers of climate change, sea level rise and human alterations of the landscape will cause transitions in dominant habitat types (state changes) within the GCE domain by changing the amounts and patterns of water delivery across the landscape. These changes in water delivery can be conceptualized as presses and pulses in river inflow, local runoff, groundwater input, and tidal inundation, which will in turn manifest themselves as changes in salinity and inundation patterns in the domain. The research proposed for GCE-III is designed to address how variations in salinity and inundation, driven by climate change and anthropogenic factors, affect biotic and ecosystem responses at different spatial and temporal scales, and to predict the consequences of these changes for habitat provisioning and carbon (C) sequestration across the coastal landscape. The goals are to: 1) Track long-term changes in climate and human actions in the watershed and adjacent uplands, and evaluate the effects of these drivers on domain boundary conditions. 2) Describe temporal and spatial variability in physical, chemical, geological and biological, and to evaluate how they are affected by variations in river inflow and other boundary conditions. 3) Characterize the responses of three dominant habitats in the domain to pulses and presses in salinity and inundation. 4) Describe patterns of habitat provisioning and C sequestration and export in the GCE domain, and to evaluate how these might be affected by changes in salinity and inundation. These efforts will be synthesized into a synoptic understanding of both biotic and ecosystem responses to variations in salinity and inundation driven by climate change and human activities, which will be used to assess thresholds between habitats and the potential for state changes in the domain. 6. Funding Source: NSF OCE 1237140 B. Sub-project Description 1. Site Description a. Geographic Location: GCE_Flux -- GCE Flux Tower Marsh, Sapelo Island, Georgia VCR -- Virginia Coast Reserve LTER, Virginia, USA Coordinates: GCE_Flux -- NW: 081 17 19.06 W, 31 27 23.72 N NE: 081 16 21.23 W, 31 27 23.72 N SE: 081 16 21.23 W, 31 26 12.12 N SW: 081 17 19.06 W, 31 26 12.12 N VCR -- NW: 076 04 40.49 W, 37 55 10.38 N NE: 075 19 13.03 W, 37 55 10.38 N SE: 075 19 13.03 W, 37 03 51.43 N SW: 076 04 40.49 W, 37 03 51.43 N b. Physiographic Region: GCE_Flux -- Lower coastal plain VCR -- Holocene barrier island c. Landform Components: GCE_Flux -- Intertidal salt marsh bordering maritime forest VCR -- Barrier island d. Hydrographic Characteristics: GCE_Flux -- Site is along the Duplin River, and bounded by Barn Creek on the south and east, and is subject to 2-3m semi-diurnal tides VCR -- unspecified e. Topographic Attributes: GCE_Flux -- Flat, with elevations ranging from 0-3m above mean low tide VCR -- unspecified f. Geology, Lithology and Soils: GCE_Flux -- unspecified VCR -- unspecified g. Vegetation Communities: GCE_Flux -- Dominated by Spartina alterniflora VCR -- unspecified h. History of Land Use and Disturbance: none recorded i. Climate: Climate summary for Sapelo Island, Georgia, based on NWS data from 1980-2010: Daily-aggregated Values: Mean (sample standard deviation) mean air temperature: 20.09°C (7.28°C) minimum air temperature: 15.02°C (7.96°C) maximum air temperature: 24.82°C (6.98°C) total precipitation: 3.26mm (10.3mm) Yearly-aggregated Daily Values: Mean (sample standard deviation) total precipitation (1980-2010): 1124mm (266mm) 2. Experimental or Sampling Design a. Design Characteristics: We used Landsat 8 to estimate land surface temperature patterns on the marsh platform. We limited this analysis to dry conditions because we were interested in evaluating marsh surface temperature, which is obscured during flooded conditions. We then identified 10 winter (Jan, Feb) and 11 summer (Aug, Sept) scenes of GCE-LTER for downstream analysis. Following this, we repeated these analytical steps for the VCR LTER site, for 6 winter (Jan, Feb) scenes. The horizontal datum is NAD83 (lat/long unprojected coordinates), while the vertical datum is NAVD88. b. Permanent Plots: 45 sample pixels total along three east-west transects spanning a marsh edge to interior gradient in Spartina alterniflora marsh c. Data Collection Duration and Frequency: Land surface temperature and elevation for every available cloud-free, low-tide observation during summer (August, September) and winter (January and February) date from Landsat 8 spanning 2013 to 2018 for pixels sampled by our three east-west cross sections. Beginning of Observations: Aug 01, 2013 End of Observations: Oct 01, 2018 3. Research Methods a. Field and Laboratory Methods: Method 1: Landsat 8 data acquisition and pre-processing -- We acquired Landsat 8 surface reflectance and top of atmosphere brightness temperature for our study areas from Google Earth Engine. These same data can also be retrieved from earthexplorer.usgs.gov in the Landsat "Analysis Ready Data" category. One can retrieve either top of atmosphere brightness temperature or top of atmosphere radiance to repeat these steps because the scripts provided on github eventually back-calculate brightness temperature into radiance. We preprocessed the Landsat imagery we acquired, which has 30 X 30 m pixels, to obtain cloud-free low-tide observations for all available Landsat 8 scenes at the time of this study (2013 through 2018).We first used the Landsat 8's pixel quality flag in the "pixel_qa" band from the Landsat 8 surface reflectance product to filter out cloudy pixels. Next, we identified low-tide scenes through the combined use of the "GCESapelo" PhenoCam, which photographs our study area every half hour and was used to estimate the degree of marsh flooding during the hours that Landsat passed over the site (see O’Connell & Alber, 2016). We combined this with information from the GCE flux tower creek water height sensor, which was used to filter out scenes where creek water height was greater than the height of the marsh platform. To estimate the height of the marsh platform, we used digital elevation model (DEM) data, which we rescaled to the spatial resolution of Landsat. DEM data were either Hladik et al.'s (2013) data, available at http://dx.doi.org/10.6073/pasta/4c5187ef603f70cd0a77ece24ef0fed9, or DEM data from VCR LTER, available at https://www.vcrlter.virginia.edu/gisdata/LIDAR/USGS2015/). Thus, we ensured we only analyzed low-tide cloud-free land surface temperature data. Method 2: Calculate land surface temperature from top of atmosphere thermal band data -- We estimated land surface temperature based on band 10 top of atmosphere brightness temperature (wavelength mid-point at 10.9 µm), as provided in the Landsat 8 surface reflectance product (landsat.usgs.gov/landsat-8). We did not use Band 11, also a thermal band, because noise from stray light makes correcting this band to surface temperature difficult (Cook et al., 2014). We converted band 10 to land surface temperature with a radiative transfer equation that corrected for atmospheric conditions (Barsi et al. 2003, 2005; Yu et al. 2014). Custom R functions for retrieving atmospheric correction parameters from Barsi et al.'s NASA web tool and calculating land surface temperature are provided at https://github.com/jloconnell/convert_top_of_atmosphere_thermal_to_land_surface_tempe rature. These scripts will allow users to estimate land surface temperature for pixels in any Landsat 8 scene. USGS now provides a provisional land surface temperature data product on earthexplorer.usgs.gov that was not available at the time of this study. However, these scripts still may be useful to end-users who wish to customize the atmospheric correction procedure and calibrate the land surface temperature estimate to the ground-truth data of their choosing. b. Protocols: Method 1: none Method 2: none c. Instrumentation: Method 1: Landsat 8 surface spectral reflectance and top of atmosphere brightness temperature Method 2: none d. Taxonomy and Systematics: Method 1: not applicable Method 2: not applicable e. Speclies List: f. Permit History: Method 1: not applicable Method 2: not applicable 4. Project Personnel a. Personnel: 1: Merryl Alber 2: Jessica O'Connell b. Affiliations: 1: University of Georgia, Athens, Georgia 2: University of Georgia, Athens, Georgia III. Data Set Status and Accessibility A. Status 1. Latest Update: 24-Apr-2019 2. Latest Archive Date: 24-Apr-2019 3. Latest Metadata Update: 24-Apr-2019 4. Data Verification Status: New Submission B. Accessibility 1. Storage Location and Medium: Stored at not specified on media: not specified 2. Contact Person: Name: Wade M. Sheldon, Jr. Address: Department of Marine Sciences University of Georgia Athens, Georgia 30602-3636 Country: USA Email: sheldon@uga.edu 3. Copyright Restrictions: not specified 4. Restrictions: This information is licensed under a Creative Commons Attribution 4.0 International License (see: https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) has an ethical obligation to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. a. Release Date: Affiliates: Apr 16, 2019, Public: May 30, 2019 b. Citation: Data provided by the Georgia Coastal Ecosystems Long Term Ecological Research Project, supported by funds from NSF OCE 1237140 (data set MSH-GCE0-1904) c. Disclaimer: not specified 5. Costs: not specified IV. Data Structural Descriptors A. Data Set File 1. File Name: MSH-GCE0-1904_1_0.CSV 2. Size: 1207 records 3. File Format: ASCII text (comma-separated value format) 3a. Delimiters: single comma 4. Header Information: 5 lines of ASCII text 5. Alphanumeric Attributes: 6. Quality Control Flag Codes: Q = questionable value, I = invalid value, E = estimated value 7. Authentication Procedures: 8. Calculations: 9. Processing History: Software version: GCE Data Toolbox Version 3.9.9 (07-Jan-2019) Data structure version: GCE Data Structure 1.1 (29-Mar-2001) Original data file processed: landsat.txt (1207 records) Data processing history: 23-Apr-2019: new GCE Data Structure 1.1 created ('newstruct') 23-Apr-2019: 1207 rows imported from ASCII data file 'landsat.txt' ('imp_ascii') 23-Apr-2019: 13 metadata fields in file header parsed ('parse_header') 23-Apr-2019: data structure validated ('gce_valid') 23-Apr-2019: Q/C flagging criteria applied, 'flags' field updated ('dataflag') 23-Apr-2019: automatically assigned study date metadata descriptors based on the range of date values in date/time columns (add_studydates) 23-Apr-2019: Precision of column lat changed from 8 to 5; Precision of column long changed from 8 to 5; Precision of column proportion_vegetation changed from 9 to 4; Precision of column emissivity changed from 9 to 3; Precision of column b10_radiance_toa changed from 9 to 4; Precision of column land_surface_temperature changed from 8 to ('ui_editor') 23-Apr-2019: updated 1 metadata fields in the Dataset sections ('addmeta') 23-Apr-2019: imported Dataset, Project, Site, Study, Status, Supplement metadata descriptors from the GCE Metabase ('imp_gcemetadata') 23-Apr-2019: updated 57 metadata fields in the Dataset, Project, Site, Status, Study, Supplement sections ('addmeta') 23-Apr-2019: Q/C Criteria of column point changed from 'x<1='I';x>19='I';x<1='Q';x>19='Q'' to 'x<1='I';x>40='I';x<1='Q';x>37='Q''; Q/C Criteria of column pixel_elevation changed from 'x<0.5='Q';x>0.9='Q'' to 'x<0.0='Q';x>0.9='Q' ('ui_editor') 23-Apr-2019: Q/C flagging criteria applied for column(s) point and pixel_elevation, 'flags' field updated ('dataflag') 24-Apr-2019: Q/C Criteria of column pixel_elevation changed from 'x<0.0='Q';x>0.9='Q'' to 'x<-0.1='Q';x>0.9='Q''; Q/C Criteria of column ndvi changed from 'x<0='I';x>1='I';x<0.001='Q';x>0.5='Q'' to 'x<0='I';x>1='I';x<0.001='Q';x>0.75='Q' ('ui_editor') 24-Apr-2019: Q/C flagging criteria applied for column(s) pixel_elevation and ndvi, 'flags' field updated ('dataflag') 24-Apr-2019: updated 1 metadata fields in the Dataset sections ('addmeta') 24-Apr-2019: imported Dataset, Project, Site, Study, Status, Supplement metadata descriptors from the GCE Metabase ('imp_gcemetadata') 24-Apr-2019: updated 57 metadata fields in the Dataset, Project, Site, Status, Study, Supplement sections ('addmeta') 24-Apr-2019: manually edited data set metadata ('ui_editmetadata') 24-Apr-2019: updated 6 metadata fields in the Data sections ('addmeta') 24-Apr-2019: updated 15 metadata fields in the Status, Data sections to reflect attribute metadata ('updatecols') 24-Apr-2019: parsed and formatted metadata ('listmeta') B. Variable Information 1. Variable Name: column 1. date column 2. site column 3. cross_section column 4. point column 5. pixel_elevation column 6. lat column 7. long column 8. b1 column 9. b2 column 10. b3 column 11. b4 column 12. b5 column 13. b6 column 14. b7 column 15. b10 column 16. ndvi column 17. Iu column 18. Id column 19. trans column 20. proportion_vegetation column 21. emissivity column 22. b10_radiance_toa column 23. land_surface_temperature 2. Variable Definition: column 1. date column 2. site id column 3. cross section id column 4. cross section location id column 5. Mean pixel elevation relative to NAVD88 estimated as the pixel mean from Hladik et al.’s (2013) digital elevation model (DEM) column 6. latitude column 7. longitude column 8. Landsat 8 band 1 surface reflectance column 9. Landsat 8 band 2 surface reflectance column 10. Landsat 8 band 3 surface reflectance column 11. Landsat 8 band 4 surface reflectance column 12. Landsat 8 band 5 surface reflectance column 13. Landsat 8 band 6 surface reflectance column 14. Landsat 8 band 7 surface reflectance column 15. Landsat 8 band 10 thermal band top of atmosphere brightness temperature column 16. Normalized Difference Vegetation Index column 17. Atmospheric Correction Parameter: Effective bandpass upwelling radiance column 18. Atmospheric Correction Parameter: Effective bandpass downwelling radiance column 19. Atmospheric Correction Parameter: Band average atmospheric transmission column 20. Proportion of vegetation in the pixel, calculated from NDVI column 21. emissivity of the surface land cover, estimated from ASTER band 13 column 22. Landsat 8 band 10 thermal band top of atmosphere spectral radiance column 23. Landsat 8 land surface temperature from the band 10 thermal data 3. Units of Measurement: column 1. yyyy-mm-dd column 2. none column 3. none column 4. none column 5. meters column 6. decimal degrees column 7. decimal degrees column 8. none column 9. none column 10. none column 11. none column 12. none column 13. none column 14. none column 15. Kelvin column 16. none column 17. W/m^2/sr/um column 18. W/m^2/sr/um column 19. none column 20. none column 21. none column 22. W/m^2/sr/um column 23. Celsius 4. Data Type a. Storage Type: column 1. string column 2. string column 3. string column 4. integer column 5. floating-point column 6. floating-point column 7. floating-point column 8. floating-point column 9. floating-point column 10. floating-point column 11. floating-point column 12. floating-point column 13. floating-point column 14. floating-point column 15. floating-point column 16. floating-point column 17. floating-point column 18. floating-point column 19. floating-point column 20. floating-point column 21. floating-point column 22. floating-point column 23. floating-point b. Variable Codes: site: gce = Georgia Coastal Ecosystems LTER, vcr = Virginia Coast Reserve LTER c. Numeric Range: column 1. (none) column 2. (none) column 3. (none) column 4. 1 to 37 column 5. -0.03119 to 0.86373 column 6. 31.4382 to 37.4199 column 7. -81.291 to -75.8217 column 8. 0.0096 to 0.0697 column 9. 0.0107 to 0.0712 column 10. 0.0158 to 0.0762 column 11. 0.0087 to 0.0769 column 12. 0.0357 to 0.146 column 13. 0.0175 to 0.1455 column 14. 0.0085 to 0.1126 column 15. 276.1 to 301.6 column 16. 0.096139 to 0.61942 column 17. 0.18 to 4.88 column 18. 0.31 to 7.07 column 19. 0.4 to 0.97 column 20. 4.0159e-07 to 1 column 21. 0.969 to 0.985 column 22. 6.5294 to 9.8265 column 23. 4.3241 to 37.0366 d. Missing Value Code: 5. Data Format a. Column Type: column 1. text column 2. text column 3. text column 4. numerical column 5. numerical column 6. numerical column 7. numerical column 8. numerical column 9. numerical column 10. numerical column 11. numerical column 12. numerical column 13. numerical column 14. numerical column 15. numerical column 16. numerical column 17. numerical column 18. numerical column 19. numerical column 20. numerical column 21. numerical column 22. numerical column 23. numerical b. Number of Columns: 23 c. Decimal Places: column 1. 0 column 2. 0 column 3. 0 column 4. 0 column 5. 5 column 6. 5 column 7. 5 column 8. 4 column 9. 4 column 10. 4 column 11. 4 column 12. 4 column 13. 4 column 14. 4 column 15. 1 column 16. 4 column 17. 2 column 18. 2 column 19. 2 column 20. 4 column 21. 3 column 22. 4 column 23. 1 6. Logical Variable Type: column 1. datetime (none) column 2. coded value (none) column 3. free text (none) column 4. ordinal (discrete) column 5. data (continuous) column 6. geographic coordinate (continuous) column 7. geographic coordinate (continuous) column 8. data (continuous) column 9. data (continuous) column 10. data (continuous) column 11. data (continuous) column 12. data (continuous) column 13. data (continuous) column 14. data (continuous) column 15. data (continuous) column 16. data (continuous) column 17. data (continuous) column 18. data (continuous) column 19. data (continuous) column 20. data (continuous) column 21. data (continuous) column 22. data (continuous) column 23. data (continuous) 7. Flagging Criteria: column 1. none column 2. none column 3. none column 4. x<1="I";x>40="I";x<1="Q";x>37="Q" column 5. x<-0.1="Q";x>0.9="Q" column 6. x<-90="I";x>90="I";x<31="Q";x>38="Q" column 7. x<-180="I";x>180="I";x<-82="Q";x>-75="Q" column 8. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 9. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 10. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 11. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 12. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 13. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 14. x<0="I";x>1="I";x<0.001="Q";x>0.5="Q" column 15. x<0="I";x>325="I";x<273.15="Q";x>313.15="Q" column 16. x<0="I";x>1="I";x<0.001="Q";x>0.75="Q" column 17. x<0="I";x>10="I" column 18. x<0="I";x>10="I" column 19. x<0="I";x>1="I";x<0="Q";x>1="Q" column 20. x<0="I";x>1="I";x<0="Q";x>1="Q" column 21. x<0="I";x>1="I";x<0.95="Q";x>1="Q" column 22. x<0="I";x>100="I";x<5="Q";x>10="Q" column 23. x<-10="I";x>50="I";x<0="Q";x>40="Q" C. Data Anomalies: V. Supplemental Descriptors A. Data Acquisition 1. Data Forms: 2. Form Location: 3. Data Entry Validation: B. Quality Assurance/Quality Control Procedures: C. Supplemental Materials: D. Computer Programs: E. Archival Practices: F. Publications: not specified G. History of Data Set Usage 1. Data Request History: not specified 2. Data Set Update History: none 3. Review History: none 4. Questions and Comments from Users: none