What is Remote Sensing?

December 14th, 2007

Lillesand et al. (2004) define remote sensing as “the science and art of
obtaining information about an object … through the analysis of data acquired
by a device that is not in contact with the object.” This includes sensors that
measure gravitational, magnetic, or electric forces; sonic devices; and optical
and microwave imagers that sense electromagnetic radiation (EMR). Scripts
by Jack™ deal mostly with remotely-sensed EMR data from a variety of
multispectral (MS) systems.

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What are the Types of EMR Systems?

December 13th, 2007

• Active EMR Systems:

  • Radar (RAdio Detection And Ranging): Synthetic Aperture Radar(SAR) and InterFerometric SAR (IFSAR)
  • LIDAR (LIght Detection And Ranging)

• Passive EMR Systems:
o Non-imaging radiometers (a.k.a., spectrometers)
o Optical EMR imagers (some are imaging radiometers):

  • Single-band imagers, e.g., panchromatic (PAN)
  • Shortwave multispectral (MS) imagers: e.g., blue-light (BL), greenlight(GL), red-light (RL), near infrared (N), and middle infrared (M)systems.
  • Thermal infrared imagers
  • Hyperspectral imagers

Some Passive EMR Systems cover the whole earth more than once every
day, but at very coarse spatial resolution (250-m or worse). Other Passive
EMR Systems capture very high-resolution images (as good as 0.61-m) – but
not every day or even every month or year. Active EMR Systems on
spacecraft today include only single-band, single polarization combinations of
SAR systems.
Organized by spatial resolution, Four Basic Types of Passive EMR Systems
include:
• High Resolution: e.g., QuickBird, IKONOS & OrbView 3
• Medium Resolution: e.g., SPOT MS & IRS (Indian Remote Sensing
Satellite)
• Low Resolution: e.g., Landsat (MSS, TM, ETM+) & Terra ASTER
• Coarse Resolution: e.g., Terra & Aqua MODIS

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Is a Good Image Good Enough?

December 10th, 2007

Even the best looking natural color or color infrared images do not show the
full extent of the information that can be extracted from a MS image data set.
Making a “good-looking” image does not require highly-analytical operations.
But, producing accurate and consistent information always requires highly analytical
and precise, knowledge-based operations.
Many analysts rely exclusively on their brain and their eyes to “see”
information in spatial patterns and perceived colors. While manual photo
interpretation is an old and respectable art, this approach often leaves
significant information behind.

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