<metadata>
  <idinfo>
    <citation>
      <citeinfo>
        <origin>Schuyler R. BorgesMark R. SalvatoreLee F. StanishSarah N. PowerEric R. SokolJohn "Jeb" E. BarrettChristian J. Tai Udovicic</origin>
        <pubdate>2023-09-18</pubdate>
        <title>Distribution models of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019)</title>
        <!-- edition -->
        <geoform>tabular digitial data</geoform>
        <!-- serinfo -->
        <pubinfo>
          <pubplace>McMurdo Dry Valleys LTER</pubplace>
          <publish>McMurdo Dry Valleys LTER</publish>
        </pubinfo>
        <othercit>10.6073/pasta/de796f76bc4aa7cbff001733805adf72</othercit>
        <onlink>https://mcm.lternet.edu/content/distribution-models-microbial-mats-and-mosses-across-fryxell-basin-taylor-valley-antarctica</onlink>
        <!--lworkcit -->
      </citeinfo>
      <descript>
        <abstract>Long-term ecological field surveys from the McMurdo Dry Valleys Long Term Ecological Research program (MCM LTER) have documented the abundance and diversity of microbial mat types across ephemeral glacial meltwater streams in the McMurdo Dry Valleys region of Antarctica. However, field surveys are limited and are incapable of being performed across the entirety of streams within a field season. Therefore, we used remote sensing to examine the distribution of these diverse communities across streams in order to determine whether large scale distribution patterns are similar to those the MCM LTER has already thoroughly studied in situ. As part of our 2018-2019 field campaign, we established two to three 20 x 20 m plots within five different streams (Bowles Creek, McKnight Creek, a relict channel, Canada Stream, and Crescent Stream) in the Fryxell Basin of Taylor Valley. We performed point transect and quadrat field surveys of microbial mat and moss cover within each 20 x 20 m plot. We then used hyperspectral measurements of mat and moss collected in the field, previously archived in “Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019),” in linear spectral mixing models to determine mat and moss coverage in the same 20 x 20 m plots within an atmospherically corrected WorldView-2 satellite image from Dec. 12, 2018. We ground truthed our modeled mat and moss abundances with our field survey coverages and determined the limitations of our methods. We then modeled mat and moss coverage across Huey Creek and Von Guerard Stream to apply our methods to streams without ground truthing measurements. Our results demonstrate the spatial distribution of moss and black, orange, red, and green microbial mat across Fryxell Basin streams. Observations of mat and moss coverage at the basin-wide scale are similar to those seen in localized stream areas.</abstract>
        <supplinf>Funding for this work was provided by the National Science Foundation grants #OPP-1758224 and #OPP-1745053 to Mark Salvatore, a Graduate Research Fellowship award to Schuyler Borges, and&#160;#OPP-1637708 and #OPP-2224760 to the MCM LTER for assistance with data management.</supplinf>
      </descript>
      <timeperd>
        <timeinfo>
          <rngdates>
            <begdate>
              <caldate>2018-12-06</caldate>
            </begdate>
            <enddate>
              <caldate>2019-01-25</caldate>
            </enddate>
          </rngdates>
        </timeinfo>
        <current>ground condition</current>
      </timeperd>
      <status>
        <update>As needed</update>
      </status>
      <spdom>
        <descgeog>This is the Taylor Valley, a subjectively approximated contour by San Gil. We use this to denote the geographical extent of studies that encompass the whole Taylor Valley.According to Wiki contributors, the&#160;Taylor Valley&#160;is the southernmost of the three large&#160;Dry Valleys&#160;in the&#160;Transantarctic Mountains,&#160;Victoria Land, located west of&#160;McMurdo Sound. The valley extends from&#160;Taylor Glacier&#160;in the west to&#160;McMurdo Sound&#160;at&#160;Explorers Cove&#160;at the northwest head of&#160;New Harbour&#160;in the east and is about 29 kilometres (18&#160;mi) long. It was once occupied by the receding Taylor Glacier, from which it derives its name. Taylor Valley contains&#160;Lake Bonney&#160;in the west (inward), and&#160;Lake Fryxell&#160;in the east (coastward), and&#160;Lake Hoare,&#160;Lake Chad,&#160;Mummy Pond&#160;and&#160;Parera Pond&#160;close together between the two. Further east of Lake Bonney is&#160;Pearse Valley. Taylor Valley is separated from Wright Valley in the north by&#160;Asgard Range, and from&#160;Ferrar Glacier&#160;in the south by&#160;Kukri Hills.</descgeog>
        <bounding>
          <westbc>163.624877929690</westbc>
          <eastbc>161.707763671880</eastbc>
          <northbc>-77.519802097166</northbc>
          <southbc>-77.808487073526</southbc>
        </bounding>
      </spdom>
      <keywords>
        <themekt>LTER Core Areas</themekt>
        <themekey>primary production</themekey>
      </keywords>
      <accconst>None</accconst>
      <ptcontact>
        <cntinfo>&lt;cntperp&gt; &lt;cntper&gt;McMurdo Dry Valleys LTER Information Manager&lt;/cntper&gt; &lt;/cntperp&gt; &lt;cntemail&gt;im@mcmlter.org&lt;/cntemail&gt;</cntinfo>
      </ptcontact>
      <datacred>Name: Renée F. Brown Role: data manager</datacred>
      <dataqual>
        <logic>Not Applicable</logic>
        <complete>Not Applicable</complete>
        <lineage>
          <method>
            <methtype>Field and/or Lab Methods</methtype>
            <methdesc>During the 2018-2019 austral summer, field surveys were conducted across 20 x 20 m plots established in several streams across the Fryxell Basin of Taylor Valley, Antarctica. Two plots were established in Bowles Creek, McKnight Creek, and Crescent Stream. Three plots were established in Canada Stream and a relict channel, but only the first and third plot in the relict channel was surveyed because plot 2 was outside the channel. Plots were assigned before the field season based on areas with homogenous NDVI signatures. Field surveys involved point transect and quadrat coverage estimates. Point transect measurements were collected by establishing cardinal (N, E, S, W), and intercardinal (NE, NW, SE, SW) transects across the 20 x 20 m plots. Every 25 cm along all transects, surface types were categorized as “dry” and “exposed” or “inundated” and “black mat, orange mat, red mat, black/orange mat, black/orange/red mat, orange/red mat, moss, cobbles/pebbles, sand, or rock.” Results were then averaged across the 20 x 20 m plots as abundances. For quadrat surveying, 1 x 1 m quadrats were randomly generated in the Esri geographic information system software, ArcGIS, within the 20 x 20 m plots. Ten quadrats per 20 x 20 m plot were established for most stream plots. However, due to field logistics and time constraints, some plots only had 6, 8, or 9 quadrats surveyed. Once in the field, 20 x 20 m general plot overview descriptions were recorded (weather, flow conditions, vegetation coverage, any notable features or changes since previous visit), and then each 1 x 1 m quadrat was surveyed. Observations of mat or moss type (black mat, orange mat, red mat, green mat, sandy orange mat, black/orange mat, black/orange/red mat, black/red mat, orange/red mat, moss, moss with black mat on top, black mat with moss on top, black mat and moss with orange mat on top), coverage, water levels (dry, moist, saturated, inundated), and substrate type were recorded. All coverages were then averaged for each quadrat and applied to the entire 20 x 20 m plot (multiple by two if ten quadrats). Further methodological details can be found in&#160;Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019). For our remote sensing techniques, we first atmospherically corrected a WorldView-2 (WV2) image of Fryxell basin taken on Dec. 12, 2018 using the same methods as Salvatore et al. 2021. We then used multispectral data, found in “Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019),” as endmember spectra in linear spectral mixing models in the program, Davinci. Model outputs included averaged abundances of mat and moss within each 20 x 20 m plot and the measured and modeled WV2 spectrum of the 20 x 20 m plot. After merging all coverage datasets, averaged abundances of mat and moss within each 20 x 20 m plot were statistically compared with field survey abundances to determine how well our models were fitting measured&#160;in situ&#160;data (R2,&#160;p-value, RMSE, AIC, and reduced chi-squared were calculated from the results). Other modeled results of mat and moss abundances for entire stream channels were outputted as geotiffs, which were then uploaded to the Harris geospatial deep learning software, ENVI, for further analysis. In ENVI, the reassigned WV2 bands displayed the different coverages of moss and each mat type. Using the statistics tool, percent coverages of mat and moss were found for entire stream channels. Percent coverages were converted to areal coverages by dividing the percentages by the total area of the stream channels.&#160;</methdesc>
          </method>
          <procstep>
            <procdesc>During the 2018-2019 austral summer, field surveys were conducted across 20 x 20 m plots established in several streams across the Fryxell Basin of Taylor Valley, Antarctica. Two plots were established in Bowles Creek, McKnight Creek, and Crescent Stream. Three plots were established in Canada Stream and a relict channel, but only the first and third plot in the relict channel was surveyed because plot 2 was outside the channel. Plots were assigned before the field season based on areas with homogenous NDVI signatures. Field surveys involved point transect and quadrat coverage estimates. Point transect measurements were collected by establishing cardinal (N, E, S, W), and intercardinal (NE, NW, SE, SW) transects across the 20 x 20 m plots. Every 25 cm along all transects, surface types were categorized as “dry” and “exposed” or “inundated” and “black mat, orange mat, red mat, black/orange mat, black/orange/red mat, orange/red mat, moss, cobbles/pebbles, sand, or rock.” Results were then averaged across the 20 x 20 m plots as abundances. For quadrat surveying, 1 x 1 m quadrats were randomly generated in the Esri geographic information system software, ArcGIS, within the 20 x 20 m plots. Ten quadrats per 20 x 20 m plot were established for most stream plots. However, due to field logistics and time constraints, some plots only had 6, 8, or 9 quadrats surveyed. Once in the field, 20 x 20 m general plot overview descriptions were recorded (weather, flow conditions, vegetation coverage, any notable features or changes since previous visit), and then each 1 x 1 m quadrat was surveyed. Observations of mat or moss type (black mat, orange mat, red mat, green mat, sandy orange mat, black/orange mat, black/orange/red mat, black/red mat, orange/red mat, moss, moss with black mat on top, black mat with moss on top, black mat and moss with orange mat on top), coverage, water levels (dry, moist, saturated, inundated), and substrate type were recorded. All coverages were then averaged for each quadrat and applied to the entire 20 x 20 m plot (multiple by two if ten quadrats). Further methodological details can be found in&#160;Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019).For our remote sensing techniques, we first atmospherically corrected a WorldView-2 (WV2) image of Fryxell basin taken on Dec. 12, 2018 using the same methods as Salvatore et al. 2021. We then used multispectral data, found in “Spectral and biological characteristics of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019),” as endmember spectra in linear spectral mixing models in the program, Davinci. Model outputs included averaged abundances of mat and moss within each 20 x 20 m plot and the measured and modeled WV2 spectrum of the 20 x 20 m plot. After merging all coverage datasets, averaged abundances of mat and moss within each 20 x 20 m plot were statistically compared with field survey abundances to determine how well our models were fitting measured&#160;in situ&#160;data (R2,&#160;p-value, RMSE, AIC, and reduced chi-squared were calculated from the results). Other modeled results of mat and moss abundances for entire stream channels were outputted as geotiffs, which were then uploaded to the Harris geospatial deep learning software, ENVI, for further analysis. In ENVI, the reassigned WV2 bands displayed the different coverages of moss and each mat type. Using the statistics tool, percent coverages of mat and moss were found for entire stream channels. Percent coverages were converted to areal coverages by dividing the percentages by the total area of the stream channels.&#160;</procdesc>
            <procdate>unknown</procdate>
          </procstep>
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            <enttypd>Total areal and percent coverage for models.</enttypd>
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            <attrlabl>Dataset code</attrlabl>
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              <udom>Unique model identifier that corresponds with the name of the model and field survey measurements being compared.</udom>
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            <attrdef>Name of the stream associated with the model.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Name of the stream associated with the model.</udom>
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          <attr>
            <attrlabl>Model number</attrlabl>
            <attrdef>Model run identifier.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Model run identifier.</udom>
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          <attr>
            <attrlabl>Sample type</attrlabl>
            <attrdef>Sample type (i.e., microbial mat type by color, moss, soil).</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Sample type (i.e., microbial mat type by color, moss, soil).</udom>
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          </attr>
          <attr>
            <attrlabl>Moisture content</attrlabl>
            <attrdef>Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total).</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total).</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Areal coverage</attrlabl>
            <attrdef>Areal coverage of mat and/or moss for the associated model and stream.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <rdom>
                <attrunit>meterSquared</attrunit>
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            <attrlabl>Percent coverage</attrlabl>
            <attrdef>Percent coverage of mat and/or moss for the associated model and stream.</attrdef>
            <attrdefs>The data provider</attrdefs>
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            <attrlabl>Dataset code</attrlabl>
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              <udom>Unique model identifier that corresponds with the name of the model and field survey measurements being compared.</udom>
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              <udom>Name of the stream associated with the field measurement or model.</udom>
            </attrdomv>
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          <attr>
            <attrlabl>Plot ID</attrlabl>
            <attrdef>Plot identifier within the stream where the field measurement was taken. See methods for further details.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Plot identifier within the stream where the field measurement was taken. See methods for further details.</udom>
            </attrdomv>
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            <attrlabl>Data type</attrlabl>
            <attrdef>Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details.</udom>
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            <attrlabl>Model number</attrlabl>
            <attrdef>Model run identifier.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Model run identifier.</udom>
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            <attrlabl>Sample type</attrlabl>
            <attrdef>Sample type (i.e., microbial mat type by color, moss, soil).</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Sample type (i.e., microbial mat type by color, moss, soil).</udom>
            </attrdomv>
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            <attrlabl>Moisture content</attrlabl>
            <attrdef>Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total).</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Sample coverage type, roughly corresponding with moisture content (i.e., dry, inundated, wet, total).</udom>
            </attrdomv>
          </attr>
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            <attrlabl>Percent coverage</attrlabl>
            <attrdef>Percent coverage of mat and/or moss for the associated stream, plot number, and data type.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <rdom>
                <attrunit>percent</attrunit>
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            <attrdef>Plot identifier within the stream where the field measurement was taken. See methods for further details.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Plot identifier within the stream where the field measurement was taken. See methods for further details.</udom>
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            <attrlabl>Data type</attrlabl>
            <attrdef>Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details.</attrdef>
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              <udom>Data type, either field measurement (i.e., point transect or quadrat) or model. See methods for further details.</udom>
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            <attrdef>Wavelength of reflectance corresponding with bands from the WorldView-2 satellite: 0.427 um, 0.482 um, 0.546 um, 0.608 um, 0.659 um, 0.724 um, 0.831 um, and 0.908 um.</attrdef>
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              <udom>Reflectance values (unitless) associated with each band and measurement/model.</udom>
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            <attrlabl>Dataset code</attrlabl>
            <attrdef>Internal dataset code.</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Internal dataset code.</udom>
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          <attr>
            <attrlabl>Model ID</attrlabl>
            <attrdef>Unique model identifier that corresponds with the name of the model and field survey measurements being compared.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Unique model identifier that corresponds with the name of the model and field survey measurements being compared.</udom>
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            <attrlabl>Stream name</attrlabl>
            <attrdef>Name of the stream associated with the field measurement or model.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Name of the stream associated with the field measurement or model.</udom>
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          <attr>
            <attrlabl>Plot ID</attrlabl>
            <attrdef>Plot identifier within the stream where the field measurement was taken. See methods for further details.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Plot identifier within the stream where the field measurement was taken. See methods for further details.</udom>
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          <attr>
            <attrlabl>Field survey type</attrlabl>
            <attrdef>Type of field measurement (i.e., point transect or quadrat).</attrdef>
            <attrdefs>The data provider</attrdefs>
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              <udom>Type of field measurement (i.e., point transect or quadrat).</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Model number</attrlabl>
            <attrdef>Model run identifier.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Model run identifier.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Regression slope</attrlabl>
            <attrdef>Regression slope calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Regression slope calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Regression intercept</attrlabl>
            <attrdef>Regression intercept calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Regression intercept calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Regression R2</attrlabl>
            <attrdef>Regression R2 value calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Regression R2 value calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Regression p-value</attrlabl>
            <attrdef>Regression p-value calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Regression p-value calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Root mean square error</attrlabl>
            <attrdef>Regression root mean square error (RMSE) calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Regression root mean square error (RMSE) calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Akaike Information Criterion</attrlabl>
            <attrdef>Akaike Information Criterion (AIC) value calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Akaike Information Criterion (AIC) value calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
          <attr>
            <attrlabl>Reduced chi squared</attrlabl>
            <attrdef>Reduced chi-squared value calculated between the modeled and measured abundances of mat and moss.</attrdef>
            <attrdefs>The data provider</attrdefs>
            <attrdomv>
              <udom>Reduced chi-squared value calculated between the modeled and measured abundances of mat and moss.</udom>
            </attrdomv>
          </attr>
        </detailed>
      </eainfo>
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              <cntorg>McMurdo Dry Valleys LTER</cntorg>
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            <enttypd>Davinci and python scripts specific to the manuscript associated with this data package, detailing the linear unmixing model methods used to retrieve data from the “mvmspectra” and “mvmpctcov” files. This zip file also includes the multispectral data in their original format for the python script.</enttypd>
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        <metd>2023-09-18</metd>
        <metrd>2023-09-18</metrd>
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        <metstdn>Biological Data Profile of the Content Standards for Digital Geospatial Metadata devised by the Federal Geographic Data Committee.</metstdn>
        <metstdv>Drupal Ecological information Management Systems, version D7, Biological Data Profile module</metstdv>
      </metainfo>
    </citation>
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