Evaluation of a Cloud Detection Technique Using Spatial and Radiometric Thresholds for Near Infrared Satellite Imagery

Abstract

Knowledge of cloud location in near infrared (NIR) imagery is of interest to the meteorological community given the wavelengths greater spatial resolution compared to longwave infrared and its potential nighttime applications. This method consists of an algorithm that can be employed by multiple instrument platforms. It analyzes changes between satellite image radiances and a seasonal synthetic background radiance image. The NIR sensor bands of the Sentinel-2 Multispectral Instrument (MSI) and Suomi National Polar-Orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments are used to evaluate the performance of a monochromatic change detection technique designed to locate areas of cloud cover. VIIRS imagery is examined for its higher temporal resolution compared to MSI; whereas, MSI imagery is examined for its greater spatial resolution. Background images are constructed either manually or algorithmically using a first-guess image. Observed and background images are differenced based on user-defined radiance, size, and shape thresholds. Pixels that meet these thresholds in the first algorithm are flagged as cloud cover. Output is compared to operational cloud masks that rely on multispectral techniques. Findings indicate that the developed algorithm identifies cloud cover above the specified size threshold well, but optically thin clouds and fresh snow still present limitations.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 22, 2018
Accession Number
AD1056252

Entities

People

  • William J. Graff

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Bodies Of Water
  • California
  • Change Detection
  • Chi Square Test
  • Cirrus Clouds
  • Cloud Cover
  • Detection
  • Detectors
  • Engineering
  • Geography
  • Graphical User Interface
  • Grids
  • Information Science
  • Light Sources
  • Meteorology
  • Operating Systems
  • Pattern Recognition
  • Remote Sensing
  • Satellite Imaging
  • United States
  • Urban Areas

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Space