Studies of the effects of spatial resolution on extraction of geologic information are woefully lacking but spatial resolution effects can be examined as they influence two general categories: detection of spatial features per se; and the effects of IFOV on the definition of spectral signatures and on general mapping abilities

Abrams, M.

English

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EFFECTS OF SPATIAL RESOLUTIO_'T
Michael Abrams, JPL
I. Introduction
Studies of the effects of spatial resolution on extraction of geologic
information are woefully lacking. This writer was unable to find even a
single systematic, quantitative study bearing on this problem, though there
has been a never-ending hue and cry for better spatial resolution. Figures of
10-30 m are often mentioned, with little substantive evidence to support these
demands. However, pieces of various reports do have bearing on this subject,
and they will be discussed as appropriate.
Spatial resolution effects can be examined as they influence two general
categories: detection of spatial features per se; and the effects of IFOV on
the definition of spectral signatures and on general mapping abilities.
II. Detection of Spatial Features
Mapping of lineaments and curvilinear features from remote sensing images
has been one of the most widely pursued uses of these data. Lineaments can be
manifestations of faults, fractures, and joints which may be of geologic
significance. Or they may be caused by fortuitous topographic alignments or
by a wide range of culturally-related phenomena, such as roads, fence lines,
etc.
Lambert and others (1975) examined detectability of lineaments on Landsat
images (80 m resolution), Skylab SI90A photography ( 40 m resolution) and
Skylab SI90B photography (~20 m resolution) for the area of Alice Springs,
Australia, and compared these to faults shown on a 1:250,000 scale geological
map (Table I).
Table i. Number of faults identified
Source >10km <lOkm Total
Map 26 39 65
Landsat 48 26 74
SI90A 48 4 52
SI90B 72 71 143
Two to three times as many faults were identified from the 20 m data compared
to the 40 or 80 m data. Similar results have been reported by other investi-
gators •
The two features which are improved by better spatial resolution are:
i) detection of short lineaments, which may represent joint systems. Landsat
data at 80 m do not have the necessary resolution to detect any but the
grossest Joint patterns; 2) fine structure of large lineaments which have
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co,np!ex surface expression. Again, Landsat is inadequate for detectin_ these
features. The Landsat Follow-on Working Group (Billingsley and others, 1976)
concluded that the 30 m resolution of Landsat-D would provide a large improve-
ment in the ability to map lineaments.
Mapping of geomorphic features is another area where spatial resolution
is a critical factor. Billingsley and others (1976, p. 111-17) reported that
the threefold increase in resolution of Landsat-D compared to Landsats I, 2
and 3 would "significantly improve the capability to map glacial (individual
drumlins, isette lakes, eskers), fluvial (drainage boundaries, meanders,
terraces, fans), desert (dune types) and permafrost (pingoes, polygonal
ground) features, which • are marginally observable or below the limits of
detection on earlier Landsat imagery."
III. Definition of Spectral Signatures and Mapping Abilities
Measurement of spectral reflectance characteristics is accomplished at
widely varying scales, ranging from laboratory analyses of i cm 2 powders or
chips, to km size areas from orbital scanners. Conel (1982) examined the
effects of spatial resolution at three different IFOV's: 1 cm2, 200 cm2, and
225 m 2. Spectral reflectance curves for a variety of rock types in the 0.45
to 2.45 _m region are shown in Figures i and 2. Figure i depicts hemispher-
ical reflectance curves obtained in the laboratory for 1 cm 2 samples using a
Beckman UV 5240 Spectrophotometer. Figure 2 depicts: a) the upper and lower
range of Portable Field Reflectance Spectrometer (PFRS) in situ measure-
ments. These spectra are normalized bi-directional reflectance measurements
of a 200 cm 2 area on the ground; and b) image spectra from the NS-001 Thematic
Mapper Simulator. These data •were calibrated to reflectance using ground
control measurements; the IFOV of the instrument is about 15 m (225 m 2
area). The laboratory measurements display sharp, well-defined absorption
features characteristic of the samples" mineralogical composition. Cutler
unbleached (#i), for example, has bands at 0.9, 1.4, 1.9, 2.2 and 2.35 _m due
to the presence of ferric iron, water, water, kaolinite, and carbonate
respectively (confirmed by X-ray analyses). Besides the absorption features,
the general shapes of the curves and overall brightnesses provide diagnostic
information relating to composition.
Field acquired reflectance data for these same materials reveal several
effects of increasing the IFOV of the measurement. The most obvious effect is
the inclusion in the 200 cm 2 IFOV of a wider variety of materials than is
represented by a tiny laboratory sample. In addition to rock materials, such
materials as soil and vegetation contribute their spectral properties to the
measured spectrum. Only rarely do the two measuring systems observe the same
materials. A major effect is to reduce the intensity of absorption bands in
many cases. There is a fair similarity between the Beckman and PFRS spectra
for Wingate, bleached; Kayenta; and Upper Chinle Sandstone. Cutler Formation
PFRS represents samples of both bleached and unbleached Beckman samples; Moss
Back MBR, Chinle PFRS curves include the three types of Beckman Moss Back
samples. PFRS curves show absorption bands at 2.35, 2.2, 0.9, and 0.65 _m.
All of these features are seen in the Beckman curves, though not all are
present in any individual curve. The effect of increasing the IFOV is to
average and include a greater diversity of materials. In the PFRS curve for
Navajo Sandstone, the 2.2 _m band is not visible; the area sampled in the
field included some dry vegetation and soll which tend to mask this feature.
Increasing the resolution one step further is crudely shown by the
aircraft scanner image spectra on Figure 2. For most of the rock ty?es, the
Image spectra fall within the range of PFRS values. The Cutler formation
shows the effects of the inclusion of a significant vegetation component in
the spectral signature - albedo is depressed and falls below the range of PFRS
measurements, which excluded piEon-juniper prevalent on this rock type. Again
the same types of effects are seen going from the ground (20 cm 2) to aircraft
(225 m 2) as from laboratory (I cm 2) to the ground. More heterogeneous
materials are included in the field of view, contributing a mixture of spec- s
tral signatures to the reflectance measurements.
Mapping capability is probably the bottom line for remote sensing.
Landsat data with 80 m IFOV are usable to produce maps equivalent to 1:250,000
geological maps. Landsat-D resolution (30 m) is expected to allow mapping at
i:I00,000 scale (Billingsley and others, 1976). Systematic studies of reso-
lution for mapping are scarce. Vincent of GeoSpectra Corp. used 7.5 m IFOV
aircraft scanner data to produce spatial resolution simulations of different
IFOV°s. An area near Knoxville, Tennessee was overflown, and false color
infrared composites were produced. Figure 3 shows: (i) quick-look 7.5 m data,
(2)10 m, (3) 20 m, (4) 30 m, (5) 40m, and (6) 80 m simulations. It is
instructive to examine the appearance of small roads, houses, fields, and
treed areas as a function of spatial resolution. At I0 m they are all
visible. At 20 m, there is little loss of detail. At 30 m, small streets are
less clear, individual houses can no longer be resolved; fields and treed
areas are still distinct and boundaries between them are still detectable. At
40 m only the larger streets are detectable; houses are unrecogizable; field
boundaries are starting to break down, though some are visible. At 80 m,
individual fields are no longer detectable; only the largest roads and
building complexes are discernible.
Abrams and Brown (1982) compared Landsat data to high resolution aircraft
scanner data over the Silver Bell copper deposit in Arizona; the scanner data
were acquired at 12 m resolution, and were then degraded via computer proces-
sing to 20 m and 80 m resolution. Figure 4 shows the same strip of area for:
(i) 12 m scanner ratio composite data, (b) 30 m degradation, (c) 80 m degrada-
tion, (d) Landsat 80 m false color infrared composite, and (e) Landsat ratio
composite. At 12 m resolution, small drainages, cross-cutting dikes and roads
on the dump are visible. At 30 m these features are barely visible; and by
80 m, they are indistinguishable. The detail visible on the degraded 80 m
resolution aircraft scanner image is the same as on the Landsat image.
At about 1:125,000 scale, the 80 m data appears grainy, as the individual
pixels are about 0.5 mm in size. At 1:50,000 scale, the pixels are about
1.5 mm each, and the images start to become unusable due to the appearance of
grain due to the large pixel size.
The 30 m data at 1:50,000 scale is similar in appearance to the 80 m data
at 1:125,000 scale: the pixels are starting to be discernible. At higher
enlargements, no additional information is visible; the pixels merely get
larger.
This little exercise, perhaps provides some quantitative feel for the
useful scale of various resolutions; i.e., digital data can be displayed at a
sacle of 1500 X the IFOV in meters. With sophisticated image processing, this
can probably be increased by a factor of 2.
67
IV. Recommendations for Future _#ork•
It is obvious that there is a crying need for detailed, systematic
studies of effects of spatial resolution on information extraction. These
studies should be cond6cted over a wide variety of geological terrains, and
examine a range of problems. The field of geology encompasses many subdisci-
plines, each of which has its own requirements for the scale of information
necessary to address key problems. Global or continental tectonics needs data
at scales on the order of l:lOxl06. Geological mapping is done at various
scales, from 1:250,000 to 1:2,000. Resolution requirements are grossly dif-
ferent: 50-100 m may be adequate for small scale mapping; ~I m resolution for
detailed mapping. Therefore, the requirements are to a large extent problem
or site specific. Nevertheless, detailed studies of the effect of decreasing
resolution on information content should be done.
Similarly, the effects of resolution on spectral signatures should be
systematically studied. One experiment would be to examine a heterogeneous
area, measuring spectral reflectance at increasingly larger FOV's (Perhaps
using the PFRS in a helicopter). Characterizing the resulting mixed signa-
tures and developing satisfactory methods for estimating components would be
fruitful.
REFERENCES
Abrams, M., and Brown, D, 1982, "The Silver Bell Porphyry Copper Test Site
Report" in the Joint NASA/Geosat Test Case Stud_, JPL publication,
Pasadena, CA, in preparation.
Billingsley, F., Helton, M., O'Brien, V., 1976, "Landsat Follow-on: A Report
by the Application Survey Groups", JPL Technical Memorandum 33-803,
• Pasadena, CA.
Conel, J., 1982,"Lisbon Valley Uranium Test Site Report", in Joint NASA/Geosat
Test Case Stud_, JPL Report,Pasadena, CA, in preparation.
Lambert, B., Benson, C., et al., 1975, "A Study of the Usefulness of Skylab
EREP Data for Earth Resources Studies in Australia", NASA CR-144493,
Washington, D.C.


Effects of spatial resolution

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