Computer Processing of LANDSAT Digital Data and Sensor Interface Development for Use in New England Reservoir Management.

Abstract

A preliminary analysis of Landsat digital data using the NASA GISS computer algorithms for an 11 February scene of the upper St. John River Basin, Maine, showed that the total radiance of pixels contained in three snow courses varied from 5.34 to 7.74 mW/sq. cm sr for a water equivalent of approximately 24.1 cm (9.5 in.) of water. This correlation between radiance values and water equivalent of the snowpack still needs to be tested. A multispectral signature was developed with an accuracy of 75% for a wetlands category in the Merrimack River estuary. Low-water reservoir and flood water stages were mapped from grayscale printouts of MSS band 7 for 27 October 1972 and 7 July 1973, respectively, for the Franklin Falls reservoir area, New Hampshire. Two snow pillow transducer systems for measuring the water equivalent of the snowpack in northern Maine were interfaced and field tested. Temperature data from the surface to a depth of 30 m (100 ft) were transmitted through the Landsat DCS. Also, a tensiometer/transducer system to measure moisture tension and soil volumetric moisture content was successfully interfaced to the Landsat DCS.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1978
Accession Number
ADA055762

Entities

People

  • Carolyn J. Merry
  • Harlan L. Mckim

Organizations

  • Cold Regions Research and Engineering Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • California
  • Cold Regions
  • Computer Programs
  • Detectors
  • Digital Data
  • Drainage Basins
  • Flood Control
  • Floods
  • Forests
  • Geography
  • Literature Surveys
  • Measurement
  • New England
  • New Hampshire
  • Remote Sensing
  • Water Resources

Readers

  • Atmospheric Remote Sensing.
  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.