The author has identified the following significant results. Computer processing techniques were applied to ERTS-1 computer-compatible tape (CCT) data acquired in August 1972 on the Ohio Power Company's coal mining operation in Muskingum County, Ohio.  Processing results succeeded in automatically classifying, with an accuracy greater than 90%: (1) stripped earth and major sources of erosion; (2) partially reclaimed areas and minor sources of erosion; (3) water with sedimentation; (4) water without sedimentation; and (5) vegetation. Computer-generated tables listing the area in acres and square kilometers were produced for each target category. Processing results also included geometrically corrected map overlays, one for each target category, drawn on a transparent material by a pen under computer control. Each target category is assigned a distinctive color on the overlay to facilitate interpretation. The overlays, drawn at a scale of 1:250,000 when placed over an AMS map of the same area, immediately provided map locations for each target. These mapping products were generated at a tenth of the cost of conventional mapping techniques

Pettyjohn, W. A.

Reed, L. E.

Rogers, R. H.

English

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AUTOMATED STRIP-MINE AND
RECLAMATION MAPPING FROM ER TS
Robert H. Rogers and Larry E. Reed
Be idix--Aerospace' Systems Division
Ann Arbor, Michigan 48107
(E74-10490) AUT OATED STRIP-INE AND
RECLAtATION MAPPING FRCM ERTS Special
Report (Bendix Corp.) 15 p HC $4.00
CSCL 081 Unclas
G3/13 00490
Wayne A. Pettyjohn
Ohio State University,
Columbus, Ohio
April 1974
Special Report
Prepared for
GODDARD SPACE FLIGHT CENTER
Greenbelt, Maryland ?0771
oux so7WIN
https://ntrs.nasa.gov/search.jsp?R=19740013901 2020-03-23T09:43:04+00:00Z
TECHNICAL REPORT STANDARD TITLE PAGE
1. Rprt N*. j2. Governmet Accession No. 3. Recipient's Cotalog No.
4. Title and Sobti 5. Report Date
Automated'Strip-Mine and Reclamation April 19 7 4
Mapping From ERTS. 6. Performing Orgonioation code
7. A.der(s) R.H. Rogers, L. E. Reed, 8. Performing Organixotion Report No
and Wayne A. Pettyjohn
9. Performing Orgonisetion Name and Address 10. Work Unit No.
Bendix Aerospace Systems Division
3300 Plymouth Road 11. Contract or Croa, No.
Ann Arb6r, Michigan 48107 NAS511762 MMC309
13. Type of Report and Period Covered
12. Sponsoring Agercy Neme and Address
NASA Goddard Space Flight Center Special Report
Greenbelt, Md. 20771 14. Sponsoring Agency Code
15. Supplemewtary Notes
16. Abstract Computer processing techniques were applied to ERTS com-
puter-compatible tape (CCT) data acquired in August 1972 on the
Ohio Power Company's Coal Mining Operation in Muskingum County,
Ohio. Processing results succeeded in automatically classifying,
with an accuracy greater than 90%: (1) stripped earth and major
sources of erosion, (2) partially reclaimed areas and minor sources
of erosion, (3) water with sedimentation, (4) water without sedimenta
tion, and (5) vegetation. Computer-generated tables listing the area
in acres and square kilometers were produced for each target cate-
gory. Processing results also included geometrically corrected map
overlays, one for each target category, drawn on a transparent ma-
terial by a pen under computer control. Each target category is as-
signed a distinctive color on the overlay to facilitate interpretation.
The overlays, drawn at a scale of 1:250, 000 when placed over an AM
map of the same area, immediately provided map locations for each
target. These mapping products were generated at a tenth of the cost
of conventional mapping techniques.
17. Key Words (S l*cted by Alu~ i(s)) 18. Distribution Statement
ER TS, Strip MiningComputer
Processing
19. Security Clessif. (of this rport) 20. Security Clossif. (of this page) 21. No. of Pages 22. Price'
Unclassified Unclassified /s I Do
AUTOMATED STRIP-MINE AND RECLAMATION
MAPPING FROM ERTS
Robert H. Rogers and Larry E. Reed
Bendix Aerospace Systems Division, Ann Arbor, Michigan
Wayne A. Pettyjohn
Ohio State University, Department of Geology, Columbus, Ohio
ABSTRACT
Using computer processing techniques, it is possible to produce
geometrically-corrected maps of the coal strip mines in East-
Central Ohio by utilizing ERTS-1 CCTs. Several target cate-
gories can be drawn by a computer-controlled pen on film that
will accurately overlay a base map of any scale selected by the
operator. For each overlay, the computer can generate a table
that shows the area of each target category in square kilometers,
acres, or percent of total area.
INTRODUCTION
The area encompassed by this investigation includes five counties in eastern Ohio
that comprise nearly 3, 000 square miles. The counties; Muskingum, Coshocton,
Guernsey, Tuscarawas, and Belmont; have been disrupted by coal mining since the
early 1800s. Strip mining, which generally began before the 1920s, has been
practiced in all of them. The total area of stripping operations in each county was
quite large during the period from 1914 to 1947, but was insignificant when com-
pared to the area stripped from 1948 to the present time.
On-site examination of individual mines, and particularly older mines, is hindered
by (1) a lack of adequate mine map coverage; (2) deeply eroded, non-existent, or
blocked access roads; (3) lack of accurate or adequate records; (4) the great total
size of the stripped area; (5) strip mine reclamation planting along roads that ob-
scures adjacent barren land; and (6) dated aerial photographic coverage.
From the earliest days of mining until 1948, little thought was given to the detri-
mental effects of coal mining on the environment. However, reclamation techniques
required by 1948 legislation resulted in some grading and planting of trees and
forage on soil banks although, in some areas, the soil was too toxic for replanting.
In view of the stricter laws passed by the state legislature in 1973, reclamation
is proceeding, not only more rapidly, but rduch more effectively.
1
Various agencies within the Ohio state government collect certain types of coal-
mining data. There is, however, little or no coordination between agencies; auto-
matic data processing is non-existent; and various filing systems approach the
choatic. Consequently, reports available to the public are severely dated, com-
monly inaccurate, and difficult to acquire.
ENVIRONMENTAL EFFECTS OF STRIP MINING
In addition to large areas that are disrupted to such an extent that they are no longer
productive, strip-mining has caused severe ecologic effects. These include the
erosion of bare or sparsely vegetated spoil banks and the discharge of highly min-
eralized water. Sediment eroded from mined areas tends to fill streams and
reservoirs which, in turn, leads to flooding, decreased storage area, and the chok-
ing of vegetation. Water that discharges from spoil banks and underground mines
generally has a low pH and is highly mineralized.
MAJOR TARGET AREA
Although several specific areas have been examined, a very large mine in South-
eastern Muskingum County, owned and operated by the Ohio Power Company, was
chosen for detailed examination. The mine, although very irregular, is nearly
14 km (9 miles) long and as much as 8 km (5 miles) wide (see Figure 1).
Mining and reclamation at this mine is proceeding at a very rapid rate. Air photo-
graphs indicate that there was no stripping in the area in 1950. By 1965, however,
about 1. 6 x 107 square meters (4, 000 acres) had been disrupted and, by 1971, strip
mining had devastated close to 4. 5 x 107 square meters (11, 000 acres) in a single
mining area (see Figure 1). A similar pattern occurred in several other Ohio
counties.
Because of the more stringent 1972 Ohio strip-mine bill, reclamation now proceeds,in many areas, at the same rate as the mining. In fact, grading equipment may be
operating just behind the giant mining machinery.
Aerial photographs of the Northern part of the Ohio Power Company area were
taken in May of 1972. The area was examined in the course of field work in June
of 1973. In several parts of the mine, there is no comparison between the land-
scapes that appear on the 1972 photography and the condition that existed only 13
months later (see Figure 2). Many of the strip mine lakes had been filled, graded,
and planted as a part of the reclamation program.
2
Examination of several water quality parameters in lakes, reservoirs, and streams
throughout the region indicates a wide range in concentration, both in space and
time (see Figure 2). Furthermore, the quality cannot be readily predicted from
one area to another or, for that matter, from one impoundment to the next in the
same mine. Consequently, a detailed regional analysis of water quality character-
istics cannot be adequately accomplished without a monumental budget.
ERTS-1 DATA PROCESSING
Local, state, and federal agencies must have repetitive coverage of mining areas
and the capability for rapidly evaluating each situation. They also must be able to
quickly determine areas of mining reclamation and progress or viability of re-
planted vegetation, at least on an annual basis. This, presently, cannot economi-
cally be done by ground teams, and aerial photographs rapidly become outdated.
In response to the urgent need for a faster and more economical means of generat-
ing strip mine and reclamation maps, this study is evaluating the suitability of
using ERTS computer compatible tape (CCT) for automatic mapping. The procedure
uses computer target "spectral recognition" techniques as a basis for classification.
To implement these techniques, a computer is provided with a number of sam-
ples of ERTS measurements (training sets) for each target category of interest.
Once the numerical descriptions which define the spectral characteristics of each
target category are determined, the operator executes the "canonical analysis"
program. The program derives, for each target category being sought, a set of
"canonical coefficients". In the decision processing phase, the coefficients are
used by the computer to form a linear combination of the ERTS measurements to
produce a "canonical variable" whose amplitude is associated with the probability
of an ERTS measurement being from the target sought. A set of canonical co-
efficients are derived for each target category of interest.
In decision processing, the probability of an ERTS measurement arising from each
one of the different target categories of interest is computed for each ERTS spatial
resolution element, and a decision based on these computations is reached. If all
probabilities are below a threshold level specified by the operator, the computer is
permitted to decide that the target viewed is unknown (an unclassified category).
Before producing decision data on a large amount of ERTS data, a number of tests
are applied to evaluate the computer's capability of performing the desired target
classification. The tests include generating scatter diagrams, generating classi-
fication accuracy tables, and viewing the results of processed data on a TV mon-
itor. In the test site, the classification accuracy was greater than 95% (see Table 1).
3
Table 1. Classification Accuracy Table
CLASSIFICATION TABLE 12-OCT-73 10:11:59
REJECTION LEVEL = 0. 100000 PER CENT
TNG PER CENT CLASSIFIED AS GROUP
SET 0 1 2 3 4 5
1 0.000 97.872 0.000 2. 128 0.000 0.000
2 0.000 1. 587 98.413 0.000 0.000 0.000
3 0.000 4.545 0.000 95.455 0.000 0.000
4 0.000 0.000 0.000 0.000 100.000 0.000
5 0.000 0.000 0.000 0.000 0.000 100.000
PROGRAM RUN TIME = 00:00:21
Designation Target
1 Stripped earth
2 Water with sedimentation
3 Partially reclaimed earth
4 Vegetation
5 Water without sedimentation
DECISION DATA PRODUCTS
Decision products developed for this investigation, using the 21 August 1972 ERTS-1
CCTs, include a printout table showing the area covered by each target category,
decision imagery, and decision map overlays. The target classifications include
stripped earth and major areas of erosion, partially reclaimed earth and minor
areas of erosion, vegetation, deep (clear) water, shallow (turbid) water, and
unclassified areas. Decision imagery, although not geometrically-correct, is
produced rapidly and provides an immediate view of the processed scene.
Decision-map overlays are geometrically-corrected and will directly overlay
a UTM map coordinate system at any scale selected by the operator.
4
The canonical coefficients defining each of the five categories was applied to pro-
cess that portion of the CCTs covering the Ohio Power Company's surface mining
operation. The first step in the decision processing resulted in a new or processed
CCT, which contains a code for each spatial element designating it as one of the
categories. From this processing, Table 2 was generated, showing the area cover-
age of each category in terms of percent of total area processed, square kilometers,
and acres.
Table 2. Area Table
ERTS PROCESSOR 15-OCT-73 09:01:32
ERTS SCENE 10 - 1029-15361
DATE OF SCENE - 21 AUG 72
CENTER OF SCENE - N39-25/W081-00
SUN COORDINATES - EL53 DEGREES
AZ130 DEGREES
SPACECRAFT HEADING - 191 DEGREES
TAPE NUMBER - 1
STARTING SCAN LINE = 450
ENDING SCAN LINE = 950
PERCENT
CATEGORY OF TOTAL ACRES SQ. KM.
UNCLASSIFIED 4.47 20293. 15 82. 12
STRIPPED EARTH 0.74 3343. 62 13. 53
DIRTY WATER 0.80 3610.80 14.61
RECLAIMED EARTH 3.95 17928.80 72. 55
VEGETATION 89. 67 406771.91 1646. 13
CLEAN WATER 0.38 1704.79 6.90
TOTALS 100.00 453653.06 1835.84
PROGRAM RUN TIME = 00:23:23
5
Notable, on the list of categories shown, are the two water and two disturbed-
earth categories. Water without sediment includes deep or clear water such as
that found in reservoirs; water with sediment represents shallow or murky water,
characteristic of shallow rivers and strip-mine-associated lakes. The two dis-
turbed earth categories, stripped earth and partial reclamation, need little explan-
ation except for some definition of partial reclamation. Partially reclaimed land
may represent areas where reclamation, either natural or man-made, is proceed-
ing very slowly, and usually less than 40% of the area is covered with vegetation.
It also may represent recently mined areas where there has been a significant
amount of spoil-bank grading, as well as planted sites where the vegetation may
cover 0 to 100% of the area.
Table 2 also shows that stripped earth makes up 0. 74% of the total area processed
or 13. 53 x 106 square meters (3, 344 acres). It can readily be seen that this type
of data product could be especially valuable when a quantitative measure for new
stripping is needed, to determine progress of reclamation, and to measure changes
brought about by surface mining.
The tape produced for decision processing was also used to generate 70-mm imagery
wherein each image shows only a specified category at a scale of 1:1, 000, 000. This
imagery is geometrically (spatially) identical to the data on the decision CCT and on
the CCT provided by NASA from which it was produced. Since the tape if from bulk
processing, some geometrical errors exist and are carried over into the decision
imagery. Also, the CCT data provided from the NASA bulk processing is not cor-
rected for earth rotation; consequently, the decision imagery will not directly over-
lay a UTM map coordinate system.
A method of recording all computer classifications, each represented by a different
color, onto a single image, was also evaluated. To accomplish this, three images,
representing the three primary colors (red, green, and blue) and containing all
target classes in shades of gray, are produced. Using an additive color process,
a composite image, in which each target class is assigned a distinctive color, is
created. An example of this process, showing a large portion (about 1.8 x 109
square meters or 700 square miles) of Muskingum County and the Ohio Power
Company's operations in that area, is shown in Figure 3.
To produce data that will directly relate to a map, a method for correcting the
decision CCT for earth rotation and other geometric errors was developed. A
second CCT, with these geometric corrections applied in a format suitable for
driving a Gerber plotter, was recorded. This tape, when played back on the com-
puter, causes a geometrically-corrected map of each target category to be drawn
on film at a scale specified to the computer by the investigator. The pen drawings
were used to produce color-coded overlays for an AMS series map of the same scale.
6
Figures 4 through 7 are photographs of computer-produced transparent maps, from
the Gerber plotter, that overlay a 1:250, 000 scale AMS map. The two water classi-
fications are shown in Figure 4, stripped earth is shown in Figure 5, partially
reclaimed land in shown in Figure 6, and a composite of all the classifications is
shown in Figure 7. The overlay technique was found to be particularly useful for
updating base maps and, more importantly, for detecting and identifying changes;
i. e., change detection between the base maps and ERTS-1 data.
At this time, analyses of the accuracy of classifications have been confined largely
to analyses of classification tables generated from data from the training areas.
To be truly objective in analyzing accuracy, the final output products must also be
evaluated with other areas not used in the computer training process. This was
accomplished by comparing classification results with available maps, ground-
survey data, and aerial photographs.
Figure 8 is a mosiac of the Ohio Power Company's strip-mine operation, generated
from photographs acquired by the NASA C-130 aircraft on 7 September 1973. By
comparing Figures 7 and 8, it is evident that the target categories are classified
correctly in nearly all cases. Especially noticeable is the accuracy with which
small lakes, a product of the mining operation, were classified.
A direct comparison between aerial photography and the stripped earth decision
image plot of a part of the mine is shown in Figure 9. This illustration shows, not
only that there is close agreement between the two techniques, but also that there
have been some significant changes in mining areas between 21 August 1972 and
7 September 1973.
Thus far, this investigation has demonstrated the feasibility of using ERTS-1 CCTs
for mapping and monitoring strip mining. The technique is rapid, accurate, and
very inexpensive when compared to standard methods using aerial photographs and
ground teams.
7
11798A-1 11798A-2 3
8 \
Area stripped before
ptember 1965. Pond
Area stripped between Stripped
2 September 1965 and '
12 October 1971.
12
0 1 2 3 4 5 6 7 8
Scale in Kilometers
S .. I i Site
0 1 2 3 4 5
Scale in Miles 1. Pond, nonexistent
2. Pond, pH-9.7, conductance-750
3. Lake, nonexistent
4. Lake, nonexistent
5. Lake, nonexistent
6. Pond, pH-9.3, conductance-580
7. Lake, pH-8.9, conductance-600
8. Pond, pH-3.1, conductance-1900
9. Stream, pH-8.2, conductance-775
12. Stream, pH-8.5, conductance-700
Base from May 9, 1972 air photograph
Field check on August 9, 1973
Figure 1. Strip-Mined Area in Figure 2. Water Quality and Reclama-
Muskingum County tion Data in the Northeastern Part of
the Ohio Power Company Mine
Classifications:
Red - Stripped Earth and Major Lt. Blue - Shallow Water or Water
Sources of Erosion with Sedimentation
Yellow - Partially Reclaimed Earth Blue - Deep Water or Water
and Minor Sources of Erosion without Sedimentation
Green - Vegetation Black - Unclassified
Figure 3. Decision Imagery Representing a Large Part of the
Study Area Based on the 21 August 1972 ERTS-1 CCT
9
Figure 4. Overlay of Both Computer-
Generated Water Categories on a
1:250, 000 Scale Base Map
Figure 5. Overlay of Computer-
Generated Stripped Earth Category
on a 1:250, 000 Scale Base Map
Figure 6. Overlay of Computer-
Generated Partially Reclaimed
Category on a 1:250, 000 Scale Base Map
10
Figure 7 Color-Coded Overlays Generated by Computer
from ERTS Data Acquired 21 August 1972
Red: Stripped Earth; Yellow: Partially Reclaimed Earth
Dark Blue: Water without Sedimentation; Light Blue: Water
with Sedimentation (1:250, 000 Scale Base Map)
11
9A
Sk N
i~~ ~~ --....
PO
C9
Figure 8. Aerial Photo-Mosaic of Southeastern Muskingum County, Ohio,
and the Ohio Power Company Strip Mine
12I
Figure 8. Aerial Photo-Mosaic of Southeastern Muskingum County, Ohio,
and the Ohio Power Company Strip Mine
12
Figure 9 Stripped Earth Category (Red) Generated from
21 August 1972 ERTS Tape Overlaying
Aerial Photograph Acquired on
7 September 1973
13


Automated strip-mine and reclamation mapping from ERTS

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