1. Digital Image Processing
Geography KHU Jinmu Choi
In Situ Data Collection
Remote Sensing Data Collection
Adv. & Limit. Of Remote Sensing
Remote Sensing Process
Sensor Resolution
Image Analysis Perspectives
Next…
Remote Sensing

2. Text Book
Modified from Jensen, (2011)’s Notes
Remote Sensing

3. Digital Image Processing
Data Collection
Data Quality Assessment
Image Display
Image Corrections
Image Enhancement
Image Classification
Accuracy Assessment
(source: Jensen, 2011)
Remote Sensing

4. 1. In Situ Data Collection
Scientists formulate hypotheses -> Gathering Data -> Calculating Statistics -> Attempt to accept or reject them
Data collection may be directly in the field, often referred to as in situ or in-place data collection.
Time-consuming, expensive, and inaccurate process.
Remote Sensing

5. Problems with In Situ Data Collection
Method-produced error. Such error can be introduced by:
sampling design does not capture the spatial variability of the phenomena under investigation;
improper operation of in situ measurement instruments; or
uncalibrated in situ measurement instruments.
Remote Sensing

6. Ground Reference Information
in situ data
ground truth data
in situ ground reference data,
in situ ground reference data also contains error.
Remote Sensing

7. Remote Sensing Definition
ASPRS, Formal definition of photogrammetry and remote sensing (Colwell, 1997):
“the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from noncontact sensor systems”.
Remote Sensing

8. 2. Remote Sensing Data Collection
RS instrument collects information about an object or phenomenon
Within the instantaneous-field-of-view (IFOV) of the sensor system
Without being in direct physical contact
Sensor on airplane or satellite platform
(source: Jensen, 2011)
Remote Sensing

9. RS Systems Analog Camera Digital Camera Pushbroom Whiskbroom
Hyperspectral Array
Remote Sensing
(source: Jensen, 2011)

10. Relationship of the GISciences
(source: Jensen, 2011)
Remote Sensing

11. 3. Advantages of RS
Passive remote sensing does not disturb the object or area of interest.
Systematic data collection can remove the sampling bias introduced in some in situ investigations (a 9  9 in. frame of aerial photography)
Remote sensing can provide fundamental biophysical information, (location, elevation, depth, biomass, temperature, moisture etc.)
Remote Sensing

12. Applications of Remote Sensing
RS data can be critical to the successful modeling of numerous natural and cultural process
Water-supply estimation
Eutrophication studies
Nonpoint source pollution
Land-use conversion at the urban fringe
Water-demand estimation
Population estimation
Remote Sensing

13. Limitations of Remote Sensing
Remote sensing is not a panacea; some spatial, spectral, and temporal information that is efficient and economical.
Human method-produced error may be introduced as the remote sensing instrument and mission parameters are specified
Uncalibrated RS instruments result in uncalibrated RS data.
Remote sensor data may be expensive to collect and analyze.
Remote Sensing

14. 4. Remote Sensing Process
(source: Jensen, 2011)
Remote Sensing

15. Remote Sensing Data Collection
L: electromagnetic radiance, L (watts m- 2 sr-1; watts per meter squared per steradian) within the IFOV
where,
= wavelength (spectral response measured in various bands or at specific frequencies).
sx,y,z = x, y, z location of the picture element and its size (x, y)
(source: Jensen, 2011)
Remote Sensing

16. Remote Sensing Data Collection
(source: Jensen, 2011)
t = temporal information, i.e., how often data are collected
= set of angles that describe the geometric relationships among the radiation source (e.g., the Sun), the terrain target of interest (e.g., a corn field), and the sensor
P = polarization of back-scattered energy
W = radiometric resolution (precision) at which the data (e.g., reflected, emitted, or back- scattered radiation) are recorded
Remote Sensing

17. 5. Remote Sensor Resolution
Spatial: the size of the field-of-view, e.g., 10  10 m.
Spectral: the number and size of spectral regions (or frequencies) the sensor records data in, e.g. blue, green, red, near-infrared, thermal infrared.
Temporal: how often the sensor acquires data, e.g., every 30 days.
Radiometric: sensitivity of detectors to small difference in electromagnetic energy.
Remote Sensing

18. Temporal Resolution Remote Sensor Data Acquisition June 1, 2011
July 3, 2011
16 days
(source: Jensen, 2011)
Remote Sensing

19. Radiometric Resolution
7-bit
( )
8-bit
( )
9-bit
( )
10-bit
( )
(source: Jensen, 2011)
Remote Sensing

20. 6. Image Analysis Task
Optimum results are often achieved using a synergistic combination of both visual and digital image processing.
(source: Jensen, 2011)
Remote Sensing

21. Earth Resource Analysis Perspective
Digital image processing is used for many applications:
Weapon guidance systems (e.g., the cruise missile),
Medical image analysis (e.g., x-raying a broken arm),
Nondestructive evaluation of machinery and products (e.g., on an assembly line), and
Analysis of Earth resources.
Earth Resource Analysis may be useful for modeling:
1) the global carbon cycle, 2) biology and biochemistry of ecosystems, 3) aspects of the global water and energy cycle, 4) climate variability and prediction, 5) atmospheric chemistry, 6) characteristics of the solid Earth, 7) population estimation, and monitoring land-use change and natural hazards.
Remote Sensing

22. Next Lab2: Introduction to the Remote Sensing Process
Lecture 2: Remote Sensing Data Collection
Chapter 2
Source:
Jensen and Jensen, 2011, Introductory Digital Image Processing, 4th ed, Prentice Hall.
Remote Sensing