Computer-generated spatial and statistical comparisons of critical land resource data derived from conventional sources, RB-57 photographs, and ERTS images, for an eastern Wisconsin test site, suggest that certain critical land resource data can be mapped from ERTS images on a statewide basis. This paper presents one of the biotic resources, wetlands, as an example of the use of ERTS imagery to inventory land resources

Clapp, J. L.

Kiefer, R. W.

Mccarthy, M. M.

Niemann, B. J., Jr.

English

NASA Technical Reports Server

Paper L 16 
THE USE OF ERTS-1 DATA FOR THE INVENTORY OF CRITICAL LAND 
RESOURCES FOR REGIONAL LAND USE PLANNING 
J. L. Clapp, R. W. Kiefer, M. M. McCarthy and B. J. Niemann, Jr., The University 
of Wisconsin 1, Madison, Wisconsin 
ABSTRACT 
Computer-generated spatial and statistical comparisons 
of critical land resource data derived from conventional 
sources, RB-57 photographs, and ERTS images, for an eastern 
Wisconsin test site, suggest that certain critical land 
resource data can be mapped from ERTS images on a statewide 
basis. 
"wetlands", as an example of the use of ERTS imagery to 
inventory land resources. 
This paper presents one of the biotic resources, 
1. INTRODUCTION 
The ERTS-1 project members at the University of Wisconsin-Madison 
are investigating the application and use of ERTS imagery as a data source 
for regional and state resource planning. 
being evaluated and examined to determine the potential for the detection 
and monitoring of these resources from satellite and high altitude 
platforms. Resources being evaluated for detection include major biotic 
communities, landform configurations, land and resource areas altered by 
man-induced activities (e.g., fanning, extraction, urbanization, and power 
plant construction) and the monitoring of land activity changes. This 
paper presents one of the biotic resources, "wetlands", as an example of 
the use of ERTS imagery to inventory land resources. The inventory of 
wetlands is especially important because the Governor's Wisconsin Land 
Resources Committee has concluded that "wetlands" are a critical resource, 
and yet, as of this date, state and regional planners do not know, in a 
quantitative sense, the location or extent of the State's wetland resources. 
A variety of resources are 
2. WETLANDS INVENTORY 
To determine the effectiveness of the ERTS sensors for resource 
lEnvironmenta1 Monitoring and Data Acquisition Group, Institute for 
Environmental Studies; Environmental Awareness Center, Department of 
Landscape Architecture; and Department of Civil and Environmental 
Engineering. 
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https://ntrs.nasa.gov/search.jsp?R=19730019579 2020-03-17T08:49:11+00:00Z
detection and inventory, a sample site in eastern Wisconsin is being 
utilized. 
1, is part of a larger (10,000 square kilometer) test site generally 
located between Green Bay and Milwaukee, Wisconsin. 
swamp" in the 10,000 cell, computer-based REMAP I (Regional Environmental 
Mapping and Analysis Process) data bank can be used as a measure of "wet- 
lands" distribution in the study area. 
to assist the Wisconsin Department of Transportation locate a corridor 
for Interstate 57 and is serving as a comparison basis for the ERTS-1 
investigation. 
by such biotic communities as those dominated by grasses, sedges, emergent 
aquatics, dogwoods, shrub-willows, and alders. Such communities are 
variously called bogs, wet meadows, marshes, or swamps. 
This 10 x 30 kilometer "Sheboygan Test Site", shown in Figure 
The variable "open 
The REMAP I data bank was developed 
"Open Swamp" can be defined as areas of wetlands occupied 
Figure 6 is a computer-processed spatial comparison which presents 
quantitative information about the occurrence of "open swamp" in the 
Sheboygan Test Site, as derived from 3 different sources: (A) ERTS-1 
multispectral imagery; (B) RB-57 high altitude color infrared photography; 
and (C) the REMAP I data bank. Each cell shown in this sample site is 
one square kilometer in size, referenced according to the UTM system. 
The density of the symbol printed in each cell shows the percentage of 
that cell occupied by "open swamp" (blank = 0%; "." = 1-9%; "," = 10-19%; 
etc.). Beneath each 300 square kilometer area shown on Figure 6 is given 
the total acres of the variable "open swamp" as determined from each of 
the three data sources. Numbers of occurrence and numbers of acres for 
each of the three types of data source (A, B and C) are presented for 
each level of occurrence. 
The information derived from ERTS imagery was interpreted from two 
different dates examined concurrently - 14 September 1972 and 13 December 
1972. 
data bank area with the 10 x 30 kilometer Sheboygan Test Site outlined. 
Figures 4 and 5 show examples of ERTS imagery from 9 August 1972 and 
13 December 1972 for this test site. 
the images produced by Band 5 were found to present the most information 
for this particular variable for the dates data were available. 
Figure 3 shows an ERTS image (9 August 1972) of most of the REMAP I 
In examining the four MSS bands, 
Information from the RB-57 photographs was interpreted from color 
infrared positive transparencies taken in September 1971 (September has 
been found to be a superior time for photo interpretation of many vege- 
tktional communities in this region). 
for the test site is shown as Figure 2. 
An example of RB-57 photography 
"Open swamp" as it exists in the ZlEMAP I data bank was obtained from 
two sources: (1) Borgner land cover survey maps, and (2) interpretation 
of small-scale panchromatic aerial photographs. 
represent the most complete inventory of vegetational resources for the 
entire state of Wisconsin. 
1930's in which species types and communities identification were made. 
The Borgner studies 
They were ground studies done during the 
1008 
While some areas of the state have been studied more recently (e.g., 
Menominee County), no other data source exists for the state as a whole. 
The Borgner studies were supplemented with interpretations from black and 
white aerial photographs in an attempt to update the Borgner maps. 
Figure 6 illustrates certain differences in the spatial distribution 
of the variable "open swamp" as derived from the three data sources. The 
most conspicuous difference is in the total numbers of acres of open swamp 
accounted for as interpreted from each data source: 2673 acres from ERTS 
1; 2248 acres from RB-57; and 5002 acres in REMAP I data bank. From pre- 
liminary investigations (ground studies and re-check of interpretations) , 
it is our conclusion that the ERTS and RB-57 derived data are a closer 
approximation of the location and extent of the wetland resource in the 
test site than the data now stored in the REMAP I data bank. The RENAP I 
data represent the best existing data as derived from conventional data 
sources. These REMAP I data are less valid than ERTS and R3-57 data for 
two reasons: (1) many areas that were wetland communities in the 1930's 
when the Borgner maps were compiled have disappeared, and (2) the data 
sources used were conducive to generating errors. These errors exist in 
both the original Borgner studies (now generally recognized by Wisconsin 
ecologists as being of limited value) and in extraction and classification 
errors when using small-scale panchromatic photographs as a data source 
for interpretation. 
wetlands and account for the larger total number of acres of "wetlands" 
stored in the REMAP I data bank, 
during interpretations from ERTS-1 or RB-57 data because: (1) the data 
were of recent vintage (1971-72), and (2) the interpreters were able to 
differentiate well between lowland forest and open swamp. In the case of 
interpretations from RB-57 color infrared photographs (September 1971), 
community distinctions were possible because many plants were entering 
dormancy. In the case of interpretations from ERTS images, these dis- 
tinctions were possible by means of an examination of two dates of imagery 
(September and December). 
Many lowland forest areas were incorrectly coded as 
Such classification errors were =made 
In comparing the ERTS-derived data with the RB-57-derived data, both 
the spatial results and the numerical quantities are as expected. 
appears that certain small wetland areas (e.g., less than 10X of a cell) 
can be recognized on RB-57 photographs but cannot be identified on the 
ERTS images due to resolution limitations. 
characteristics appear to influence an interpreter into perceiving higher 
percentile levels (percents of cell classified as open swamp) on ERTS 
images than on RB-57 photographs. 
It 
Resolution and edge definition 
It is important to note that the delineating of wetlands, their 
extent and degree of occurrence, is only the first step in a resource 
inventory. Eventually, questions of wetland diversity, wetland quality, 
amount of biotic habitat, and similar concerns must be quantified. Many 
of these questions can be approached with RB-57 photographic data. ERTS 
data offer the advantage of sequentiality and can also exist in a number 
of formats. 
1009 
As previously mentioned, we are investigating a variety of resources 
to determine the potential for the detection and monitoring of these 
resources from satellite and high altitude platforms. Initially, 15 
resource types have been mapped for the Sheboygan Test Site and another 
300 square kilometer test site near Green Bay. 
spatial printouts, such as shown in Figure 6, have been prepared for these 
15 resource types. 
have been especially promising. 
Computer calculations and 
They show (for the Sheboygan Test Site): 
The results obtained for "Forest" and "Agriculture" 
Total Acres Total Acres Total Acres 
(A) ERTS (B) RB-57 (C) RENAP 1 
Forest 11 , 992 
Agriculture 45,352 
14,507 
44,830 
12 , 599 
48 , 894 
3. SUMMARY 
Effective regional and state land resource planning are dependent 
upon relevant information which presently may not exist, except in 
inaccurate or archaic forms. Also critical, for use by state and regional 
planners, is resource information at varying scales, including land 
resource information for citizen educational purposes, large area planning 
(e.g. , power plant sites) , public facility planning (e.g. , controlled 
access highways), and information for legislation and control of land 
resources. As presented in this paper, the detection, inventory and 
monitoring of wetland resources appears feasi'ble for the scales of 
planning just described, except for legal control (which requires accurate 
property description). 
ERTS-interpreted information in the case of wetland resources was more 
descriptive and accurate than the current statewide information sources. 
For the detection of the wetland resources as overall patterns, the EkTS 
images appear comparable to RB-57 photographs as a data source. 
With the coming advent of statewide planning systems, such as New 
Importantly, it was shown in this paper that 
York's LUNR and Minnesota's MLIS, plus the need to inventory specific 
resources, the extent of applicability and usefulness of satellite sensors 
will be tested. Definitions and data resolution levels of resource infor- 
mation are being established by planning and governmental agencies. 
the State of Wisconsin, for example, the State is implementing a Critical 
Resource Information Program (CRIP) aimed at establishing definitions, 
units of measurement, inventory, and monitoring of critical land resources 
for planning and legislative purposes. 
and monitor land resources during the coming decade is obvious and the 
extent of applicability of ERTS satellite sensors will be of utmost 
interest to members responsible for and interested in the land resource 
planning and decision processes. 
In 
The desire and need to inventory 
1010 
FIGURE 1 FIGURE 2 
U.S,G.S. TOPOGRAPHIC W RB-57 PHOTO, 4 June 1972 
10x30 km SHEBOYGAN TEST SITE Hasselblad, b/w red band 
101 1 
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FIGURE 3 - ERTS BAND 5 (BISS-red), A u g u s t  9, 1972 
GREEN BAY-MILWAUKEE REGION 
1012 
IGURE 4 
BAND 5 (MSS-red) 
9 August 1972 
IGURE 5 
ERTS BAND 5 (MSS-red) 
13 December 1972 
1013 
E Q T S - 1  I N V E S T I G A T I O N :  CONTRACT & NAS '5-21754 
FNVIRON.  H Q N I T O Q I N G  AN0 A C O U I S I T I O N  GROUP 
I N S T I T U T E  FOR ENVIRONHENTAL STUDIES 4 4 UTM 
U N I V E R S I T Y  O F  U I T C O N S I N  - HAOISON 1 1 
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SYFBOYGPN TEST S I T E  0 n 
VARIABLE 2 1  OPEN SWAMP U 0 
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ERTS 9 8 5 7  REMAP I 
TOT. ACRES 2 6 7 2 - 5 Y  2 2 4 7 . 7 0  500 1 . 7 5  
LEVELS 1 2 3 4 5 6 7 8 9 10 ...., . r 9 9 e  +++++ cuoon EBWR t t w ~  x x x x x  uaoam mamma mmamm 
SYYROLS .. .. . .. * *  +++++ coono eeeee x x x x x  mucin maaaa mmmBa .. .. v *  * +++++ ooooo eeme t x t * *  x x x x x  aunan mmmmm a~ama 
RANGE ( X 1  1-9 1 0 - 1 9  2 0 - 2 9  3 0 - 3 9  40-49 50-59 60-69 7 0 - 7 9  8 0 - 8 9  90-99 
A 10 1 3 4 3 0 4 3 1 0 
OCCUR 9 11 8 4 4 1 2 0 2 0 1 
C 2 9  1 2  6 7 4 3 4 2 3 0 
A 2 2 2 .  3 7 .  2 2 2 0  346. 3 5 1 0  0. 6 7 9 0  5980  7 1 7 ,  0. 
A C Q E S  9 2 2 s .  7sa.  2 9 6 .  3 4 6 .  iii, 29s. no 370. 0 -  2450 
c 689. 5 5 3 .  435, 6 7 2 .  4 9 4 .  430. 674, 390.  659. u, 
FIG. 6 WETLANDS (REMAP I VARIABm "OPEN SWAMF'") 
ERTS and RB-57 INTERPRETATIONS E REMAP I DATA BANK 
1014 
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The use of ERTS-1 data for the inventory of critical land resources for regional land use planning

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