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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Cynthia S. Loftin</dc:contributor>
  <dc:contributor>Steven A. Sader</dc:contributor>
  <dc:creator>Ian M. McCullough</dc:creator>
  <dc:date>2012</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30&amp;nbsp;m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16&amp;nbsp;days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500&amp;nbsp;m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May&amp;ndash;September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (&lt;/span&gt;&lt;i&gt;R&lt;/i&gt;&lt;span&gt;&amp;sup2;&amp;nbsp;=&amp;nbsp;0.72&amp;ndash;0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes &amp;ge;&amp;nbsp;8&amp;nbsp;ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1016/j.rse.2012.05.018</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Elsevier</dc:publisher>
  <dc:title>High-frequency remote monitoring of large lakes with MODIS 500 m imagery</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>