Highway runoff stormwater management potential (HRSMP) site characterization using NASA public domain imagery.

Details

• Creators:
  Wilson, Frederick K. ; Owolabi, Oludare ; Willoughby, Arthur ; Whitney, III, James
• Corporate Creators:
  Morgan State University
• Corporate Contributors:
  Maryland. State Highway Administration. Office of Policy & Research ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Best practices
  • Field studies
  • Machine vision
  • Land use
  • Landsat satellites
  • Location
  • Remote sensing
  • Runoff
  • Spatial analysis
  • Vegetation
  More +
• Publication/ Report Number:
  MD-16-SHA/MSU/4-3
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States ; Maryland
• Edition:
  Final report
• Corporate Publisher:
  Maryland. State Highway Administration. Research Division
• Abstract:
  The focus of this research project was the development of geospatial technology (GST) methodology to ; characterize and evaluate highway runoff stormwater management potential (HRSMP) sites in order to ; reduce their impact on properties, save lives and cut operational costs. Reduction of Total Maximum Daily ; Load (TMDL), an important initiative of the SHA, could undoubtedly be achieved through the ; development and use of GST (remote sensing, geographic information system (GIS), and differential ; global positioning system (DGPS)). Field activities and groundtruthing were conducted at selected BMP ; sites to better understand their conditions and the land use/land cover (LULC) types currently present at ; these sites. Landsat images were assessed for quality-related issues including cloud cover and downloaded ; from USGS. Based on the outcome of the image assessment, 5 Landsat TM and 1 Landsat OLI_TIRS ; images which span from 1990 to 2015 were processed and analyzed using the Environment for Visualizing ; Images (ENVI) software. LULC and the normalized difference vegetation index (NDVI) images were ; created. Both LULC and NDVI values for the selected BMP sites, which were ranked by the SHA from I ; (Good) to IV (Failed), were extracted and analyzed to determine their relationship with the performances. ; The results from the LULC analyses suggested that vegetation was a major factor affecting the ; performance of the BMP facilities; poor and failed sites showed the excessive overgrowth of vegetation. ; Analysis of NDVI did not show definitive results, which might have been due to the relatively low spatial ; resolution of the TM images. Use of higher spatial resolution such as IKONOS multispectral images in the ; future could help resolve these inconsistencies.
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• Format:
  PDF
• Funding:
  MD-16-SHA/MSU/4-3
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/30961/dot_30961_DS1.pdf
• File Type:
  [PDF - 3.02 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:3aa620399c0de40d0d00f1629e2876d53ebf720dc23f859e8277feed64ebf993