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Course
Outline: Schedule, Topics and Readings
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No.
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Date
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Topic
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Assigned
Reading
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Supplemental
Reading
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Concepts
of Quantitative Remote Sensing
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1
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9/5
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Course
Introduction
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2
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9/7
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Overview
of quantitative remote sensing
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Jensen,
chap 1
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Campbell,
chap 1
Lillesand,
Kieffer & Chipman, chap 1
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3
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9/10
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Rationale
and concepts of biophysical-quantitative remote sensing
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Swain
& Davis, chap 1;
Rationale
and concepts (MacDonald - handout)
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Folder
#1 -- Biophysical Remote Sensing
(Jensen)
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4
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9/12
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Physics
and assumptions in remote sensing data acquisition and analysis
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Folder
#2 -- Physics Concepts of Optical and Radar Reflectance Signatures
(Gerstl);
Assumptions
Implicit in Remote Sensing (Duggin
& Robinove)
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Energy-Matter
Interactions, Measurements and Sensor Systems
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5
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9/14
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Radiation
and radiation sources
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Campbell, chap 2;
Swain & Davis, pages 21-51
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Slater,
chap 3
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6
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9/17
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Biophysics
of reflected radiation of vegetation, soils and water
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Swain
& Davis, pages 231-251;
Folder
#3 -- Spectral Properties of Plants (Gates)
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Folder
#3-- Physical and Physiological Basis for Reflectance of Radiation from
Vegetation (Knipling)
Folder
#4 --Reflectance Properties of Soils (Baumgardner et al.)
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7
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9/19
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No
class today
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8
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9/21
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No
class today
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9
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9/24
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Sensor
systems and signals
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Jensen,
chap 2
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Swain
& Davis, chap 2
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No.
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Date
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Topic
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Assigned
Reading
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Supplemental
Reading
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10
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9/26
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What’s
in a pixel?
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Folder
#6 -- The Pixel: a snare and a delusion (Fisher)
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Folder
#6 -- Synergy in Remote Sensing – what’s in a
pixel? (Cracknell)
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11
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9/28
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Radiation
modeling; Applications of canopy reflectance modeling
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Folder
#5 -- Calculation of Directional Reflectance of a Vegetation Canopy
(Suits)
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Folder
#5 -- Light Scattering by Leaf Layers.... The SAIL Model (Verhoef)
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12
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10/1
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Landscape
radiation characteristics
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Folder
#7 -- The Factor of Scale (Woodcock & Strahler)
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Folder
#7 -- On the Nature of Models (Strahler, Woodcock & Smith)
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13
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10/3
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Sources
and characteristics of remote sensing data
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Jensen,
chap 2. Also see, http://homepage.mac.com/alexandreleroux/arsist/
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Richards,
chap 1
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14
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10/5
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Influence
of the atmosphere and illumination conditions
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Asrar,
chap 9
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Folder
#8 -- Atmospheric Effects on Remote Sensing of Surface Reflectance
(Kaufman)
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15
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10/8
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Exam
I
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Digital
Image Processing and Classification
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16
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10/10
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No
class today – MN GIS Conference
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17
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10/12
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ERDAS
Imagine demonstration
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18
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10/15
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Image
rectification and registration
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Jensen,
pages 124-135
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19
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10/17
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Radiometric
calibration
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Jensen,
pages 107-123
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20
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10/19
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Image
enhancement
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Jensen,
pages 139-171
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21
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10/22
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Image
Transformations, Vegetation Indices
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Jensen,
pages 139-171
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No.
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Date
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Topic
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Assigned
Reading
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Supplemental
Reading
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22
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10/24
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Fundamentals
of pattern recognition; Initial statistics extraction
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Jensen,
chaps 1 and 4
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Richards,
chap 3
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23
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10/26
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Supervised
classification
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Jensen,
pages 197-230
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Richards,
pages 181-194
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24
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10/29
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Clustering;
Unsupervised classification
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Jensen,
pages 231-239
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Richards,
chap 9
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25
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10/31
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Classification,
cont.
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26
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11/2
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Rectification,
clustering, and classification with Imagine (demonstration)
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27
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11/5
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Image
classification methods: Putting it all together
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Upper
Midwest Gap Analysis Program Image Processing Protocol, http://www.umesc.usgs.gov/documents/misc/umgap/98-g001.pdf
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28
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11/7
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Temporal
information and analysis
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GeoCarto_paper_FINAL-2.pdf
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Folder
#9 -- Use of Landsat-derived profile features for classification
(Badhwar)
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29
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11/9
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Change
detection
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Jensen,
chap 12;
Coppin
et al., Digital change detection methods in ecosystem monitoring: a
review. Int. J. Remote Sens. 25(9):1565-1596.
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Folder
#10 -- Processing of Multitemporal Imagery to Optimize Extraction of
Change Features (Coppin & Bauer)
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30
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11/12
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Use
of spatial information in classification
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Jensen,
pages 322-327
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Folder
#11 -- Textural Features for Image Classification (Haralick et al.);
Classification...by Extraction and Classification of Homogeneous
Objects (Kettig & Landgrebe)
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No.
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Date
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Topic
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Assigned
Reading
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Supplemental
Reading
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31
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11/14
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Other
approaches to image classification
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Jensen,
pages 389-392 and chap 10
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32
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11/16
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Evaluation
of classification results
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Jensen, pages 247-250;
Folder #12 -- Accuracy Assessment... (Janssen
& van der Wel)
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Folder
#12 -- Selecting and Interpreting Measures of Thematic Accuracy (Stehman)
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33
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11/19
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Exam
II
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34
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11/21
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Land
cover classification and change detection: a Minnesota case study
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Land
cover classification and change analysis of the Twin Cities (Minnesota)
Metropolitan
Area by multitemporal Landsat remote sensing,
TCMA_change_detection--RSE_paper-3.pdf
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35
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11/26
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Estimation
and mapping of continuous variables
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Estimation,
mapping and change analysis of impervious surface area by Landsat
remote sensing, Minnesota Impervious -- Pecora16 paper.pdf
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36
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11/28
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Student
presentations
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37
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11/30
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Student
presentations
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38
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12/3
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Student
presentations
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39
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12/5
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Student
presentations
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36
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12/7
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37
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12/10
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Perspectives
on future sensing and analysis systems
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Earth
Observing System; see, http://eospso.gsfc.nasa.gov/
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40
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12/12
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Comparison
and discussion of image classification project results
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