Study Guide for First Midterm
Geography 418/518, Fundamentals of Remote Sensing
Winter, 2007

Note: materials below are guide to what was covered in lectures and text book.  You must also review materials on web-based readings, which are not included in review list below.

NOTE: Andrew will be available on Tuesday, Feb 13  from 11-noon in his office if you have questions)

The first midterm covers lectures through week 5 (through geometric corrections), the labs through week 4 (general process questions, not which software command to use questions), and the following readings: 3rd edition - 1, 2, 4, 6 (skim) 9 and 10.5-10.6;  4th edition: Chap 1,2,4, 6 (skim), 10 and 11.5-11.6.

As you study for the midterm, you should focus first on lecture notes and the text book - the majority of questions come from these sources.   Pay particular attention to diagrams in the book and online readings.  You should understand and be able to explain the concepts presented in the labs (how data are stored as numbers, how different bands can be displayed in "false" colors, the nature of raster data).  Do not worry, however, about remembering details about the software (e.g., different ways to zoom in on the image). Finally, do complete the on-line readings.  I may have questions from the on-line NASA tutorials on the test.  Remember that I have not summarized the on-line materials below in the study guide - you will have to do this yourself.

The following is a list of points that you should put particular emphasis into studying.  Although I try to make the list as comprehensive as possible, there may be a question or two on the test that this list doesn't cover.  By in large, however, if you have a good grasp on the definitions, facts, concepts and skills below, you will do well on the test. 

I. Introduction to Remote Sensing

• Definition of R.S.

• Potential advantages/disadvantages of using R.S.

  • Speed

  • Document processes/features that cannot be detected otherwise

  • Cost

  • Accuracy

  • Permanent record

  • Reproducible record

  • Analytical capability (quantitative analysis)

• Decision to use or not to use R.S. dependent on:

  • What you want to detect

  • When you want to detect it

  • Where you want to see it

  • Logistical constraints

II  Brief History of Remote Sensing (see on-linereadings)

• Early developments

  • ~350 B.C., Aristotle and camera obscura

  • 1839, Daguerre an Niepce create the Daguerrotype

  • 1903, the Wright brothers and first airplane

• Importance of World War I and World War II

  • Technological advances

  • Training of large numbers of photo interpreters

  • Development of rockets

• The Space Age

  • Development of new platforms (rockets and satellites)

  • Development of new sensors (digital and multispectral)

  • Development of computers

  • Still a very young and developing science

III The Remote Sensing System

• Energy Sources

  • passive

  • active

  • the electromagnetic spectrum

• Energy Movement through the Atmosphere and at the Earth's Surface

  • Absorption

  • Scattering

  • Reflection

  • Transmission

  • Fluorescence (in the book)

• Sensor Systems and Platforms

• Data Handling Systems

• Data User

IV.  The Electromagnetic Spectrum

• Wavelengths associated with:

  • ultraviolet light

  • visible light (blue, green, and red)

  • photographic infrared (IR)

  • near IR

  • shortwave IR

  • midrange IR

  • thermal IR

  • radar

• Range and intensity of wavelengths

  • emitted from the sun

  • emitted from the earth

  • be able to draw a diagram showing the two key points above, with wavelengths and names of different ranges of energy

• Radiation laws (general concepts, not the equations)

  • Wien's Law

  • Stefan-Boltzman Law

• Concept and application of additive colors (e.g., how we generate the colors we see on a computer screen with mixtures of red, blue, green).

V. Energy Interactions in the Atmosphere

• Scattering ( for the scattering types below be able to describe which wavelengths are affected and how to avoid that type of scattering)

  • Rayleigh

    • role in controlling sky color and sunsets

    • how this can affect contrast on a clear day image

  • Mie

  • Nonselective 

• Absorption

  • Atmospheric windows

  • Key gases controlling absorption

• Transmission

• Reflectance

  • specular

  • intermediate

  • diffuse

  • how variations in reflectance allow us to distinguish different features

VI.  Multispectral Sensing Systems

• Framing Systems (classic cameras)

  • Concept

  • Advantages (similar to human eye, easier to interpret)

  • Disadvantages (multiples lens, tough to register, historically film-based and not digital) 

• Analog to Digital Systems (A to D)

  • Concept: multispectral scanner with cross track scanning (whisk broom)

  • Advantages (wide field of view, broad spatial coverage, more frequent coverage, one sensor per band)

  • Disadvantages

    • short dwell time

    • historically a lower spectral resolution

    • more geometric distortion

      • tangential-scale distortion

      • resolution cell size variations

      • one dimensional relief displacement

      • flight parameter distortions

• Charge Coupled Device (CCD) Systems

  • Concept: multispectral scanner with along track (push broom) scanning

  • Advantages (longer dwell time, historically better spatial resolution and higher spectral resolution, less geometric distortion) 

  • Disadvantages (less spatial coverage, more sensors and calibration issues, less frequent coverage, unable to cover wavelengths longer than mid-IR)

• Table of Relative Advantages/Disadvantages

• Resolution

  • Spatial (the ability to resolve objects of a given size)

    • Controls

      • target variables (contrast, shape, size, spacing, number, background uniformity)

      • system variables (IFOV, scan speed, instrumentation)

      • operating conditions (atmospheric scattering, absorption) 

    • Advantages of fine spatial resolution (more spatial detail)

    • Disadvantages of fine spatial resolution relative to coarse resolution imagery (assuming same image "footprint")

      • more data storage required

      • shorter dwell time leads to

        • weaker signal per pixel 

        • lower spectral resolution

      • finer resolution images cover a smaller area

      • because a smaller area is covered, the return interval to get to that area is much longer (assuming satellite imagery) - i.e., poorer frequency of coverage

  • Temporal (repeat interval)

    • Controls

      • Velocity of platform

      • Image footprint (i.e., area covered in one image)

    • Advantages of more frequent coverage

      • ability to avoid cloud cover

      • closer to real time monitoring

    • Disadvantages of more frequent coverage

      • usually required greater footprint, which means coarser resolution

  • Spectral (the ability to detect variations within a given bandwidth) 

    • Controls

      • dwell time (longer dwell = more energy = more ability to resolve spectra)

      • spatial resolution (bigger area = more energy = better resolving capability)

      • image brightness

      • instrumentation (signal to noise ratio) 

    • Advantages of finer spectral resolution - enhances ability to differential objects with small variations in spectral signal

    • Disadvantage: more data storage if many narrow spectral ranges (i.e. hyperspectral) 

  • Radiometric (in multispectral system, the smallest variation in reflectance that is recorded)

    • Largely controlled by signal to noise ratio

    • Advantage of finer radiometric resolution: ability to detect subtle differences between objects

    • Disadvantage: finer resolution requires more data storage

• Landsat, SPOT. IKONOS, AVHRR (examples of the concepts above - see Chapter 6)

  • Orbits and rationale

    • near polar

    • sun synchronous

    • crossover timing and rationale

  • Systems

  • Relative spatial resolutions:

  • Relative temporal resolutions

  • Relative spectral resolutions

VII.  Data Restoration/Image Preprocessing

• Image Rectifications (geometric corrections) 

  • Sources of distortion/error

    • Systematic (be able to give some examples)

    • Non-systematic (be able to give examples)

  • Techniques for adjusting pixel locations

    • Mathematical corrections for systematic errors

      • models for earth rotation, scanner characteristics

      • camera focal adjustments

    • Approaches for  systematic/nonsystematic error

      • polynomial approaches

        • use of ground control points

        • how different order polynomials

        •  use of root mean square (RMS) error for evaluation

      • triangulation/rubber sheeting approaches (requires same input as polynomial approaches)

      • orthorectification techniques (requires DEM)

      • reasons for choosing one of three approaches for rectifying image

  • Techniques for assigning pixel values to the new locations

    • Nearest neighbor sampling

    • Bilinear interpolation

    • Cubic convolution

    • Advantages/disadvantages of each approach

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