Item talk:Q58169
From geokb
{
"USGS Publications Warehouse": { "schema": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "USGS Numbered Series", "name": "Delineation of marsh types and marsh-type change in coastal Louisiana for 2007 and 2013", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "sir20175044", "url": "https://pubs.usgs.gov/publication/sir20175044" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70187550 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.3133/sir20175044", "url": "https://doi.org/10.3133/sir20175044" } ], "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Scientific Investigations Report" } ], "datePublished": "2017", "dateModified": "2017-05-30", "abstract": "The Bureau of Ocean Energy Management researchers often require detailed information regarding emergent marsh vegetation types (such as fresh, intermediate, brackish, and saline) for modeling habitat capacities and mitigation. In response, the U.S. Geological Survey in cooperation with the Bureau of Ocean Energy Management produced a detailed change classification of emergent marsh vegetation types in coastal Louisiana from 2007 and 2013. This study incorporates two existing vegetation surveys and independent variables such as Landsat Thematic Mapper multispectral satellite imagery, high-resolution airborne imagery from 2007 and 2013, bare-earth digital elevation models based on airborne light detection and ranging, alternative contemporary land-cover classifications, and other spatially explicit variables. An image classification based on image objects was created from 2007 and 2013 National Agriculture Imagery Program color-infrared aerial photography. The final products consisted of two 10-meter raster datasets. Each image object from the 2007 and 2013 spatial datasets was assigned a vegetation classification by using a simple majority filter. In addition to those spatial datasets, we also conducted a change analysis between the datasets to produce a 10-meter change raster product. This analysis identified how much change has taken place and where change has occurred. The spatial data products show dynamic areas where marsh loss is occurring or where marsh type is changing. 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