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https://ntrs.nasa.gov/search.jsp?R=19810007378 2020-05-05T19:30:19+00:00Z

NAS, ATechnical Memorandum 82031

Interfaces Between Statistical AnalysisPackages and the ESRI GeographicInformation System

Edward Masuoka(OASA-TM-82U31) INTERFACES BETWEEN N81- 15893STATISTICAL ANALYSIS PACKAGES AND THE ESRIGEOGRAPHIC INFURMATION SYSTEM (NASA) 26 P

HC AU3/M? A01 CSC:L U5Il UnclesG3/32 13149

OCTOBER 1980,̂4', - .^ v^v

ti

JAN 1x$1" x Ri

., :. ^ NAsg ^ ^ NFUNational Aeronautics ai +d , ACc'. AC/,Space Administration sQom,Goddard Space Flight CenterGreenbelt, Maryland 20771

TM 8203

INTERFACES BETWEEN STATISTICAL ANALYSIS PACKAGES

AND THE ESRI GEOGRAPHIC INFORMATION SYSTEM

ELI ward

Nis,SA/Goddard Space Flight Centc.r

October 1980

GODDARD SPACE FLIGwr CENTERGreenbelt, Maryland

INTERFACES BETWEEN STATISTICAL ANALYSIS PACKAGES

AND THE ESRI GEOGRAPHIC INFORMATION SYSTEM

Edward Masuoka

NA'"A/Goddard Spice Flight Center

Abstract

The Environmental Systems Research Institute (ESRI) geographic information system (GIS)

in use at Goddard Space Flight Center provides users with the means of combining remote sens-

in¢ data with ancillary data (soils maps, geologic maps, topographic maps, etc.) and performing

qualitative analyses on the resulting multivariable data base. However, statistical techniques such

as multiple regression, analysis of variance and spatial autocorrelation analyses are not available

in the GIS. This paper describes interfaces between ESRI's GIS data files and real valued data

files written to facilitate statistical analysis and display of spatially referenced multivariable data.

An example of data analysis which utilized the GIS and the Statistical Analysis System (SAS) is

presented to illustrate the utility of combining the analytic capability of a statistical package

with the data management and display features of the GIS.

PRECEDING PAGE BLANK NOT FILMED

iii

CONTENTS

Page

Abstract .......................................... 6....... 0 ............ ,.. W

INTRODUCTION ........................................................... 1

DESCRIPTION OF INTERFACES . . . . . . . . .................................... . . 2

RUNNING SAS2GIS AND GIS2SAS ........ ............................. . .. . .. . 3

COMBINING THE GIS AND A STATISTICAL PACKAGE FOR DATA ANALYSIS .. - .. , . 3

REFERENCES ............................. .........................,... 7

APPENDIX 1 ........................................................... . ... Al-1

APPENDIX 2 ..................................... ........................... A2-1

APPENDIX3 ....................... . ...... ... ...................... . ........ A3-1

LIST OF TABLES

Table Page

1 Input Parameters for SAS2GIS . . . ................. . .. , .. , ... , . , . 5

2 Input Parameters for GIS2SAS . . . . . . . . ................................. 6

LIST OF FIGURES

Figure Page

1 Structure of an ESRI GIS Multivariable File (MVF) .... . ... . ....... . .... . . . . 8

2 Logical Units Required by SAS2GIS .. . ................................... 8

3 Logical Units Required by GIS2SAS ....... , . , , . . ... . . . . . . .. . .... 9

4 A Plot of Elevations in the Rio Grande Rift Study Area Produced

By the ESRI GIS....,. .................................................... 9

5 Bouguer Gravity Values from the Rio Grande Rift Study Area . .. . ............ . 10

6 Residuals from a Regression of Elevation and Bouguer Gravity , . , , , . , , , , . , 10

PRECEDING PAGE BLANK NOT FILMED

i

v

I---

I__ __ ____

INTERFACES BETWEEN STATISTICAL ANALYSIy PACKAGES

AND THE I SRI GEOGRAPHIC INFORMATION SYSTEM

INTRODUCTION

Automated geographic information systems provide a framework in which spatially referenced

data (maps and remote sensing imagery) may be manipulated, displayed and analyzed (Knapp,

1979). The utility of a geographic information system (GIS) lies in ita ability to create and anal-

yze a multivariable file derived from snaps and .images of a study area, Geographic information

systems have been used by land planners to select sites for campgrounds in Canadian national

parks (Arbour, 19880), by researchers at the National Cancer Institute to study patterns of mortal-

ity (Mason, 1980) and by geologists to examine relationships between petrologic and geophysical

information on the moon (Andre et al., 1977).

The Environmental Systems Research Institute (ESRI) GIS provides the user with a tool for

creating multivariable files from digitized map data and digital remote sensing data. A GIS multi-

variable file may be thought of as a cube made up of data cells. The horizontal axes of the cube

correspond to geographic location, Along the vertical axes are the different variables in the multi-

variable file, Thus, each column of cells in the cube has a unique geographic location and each

layer of cells in the cube corresponds to a unique thematic map variable, such as soil type, vege-

tation, type or topographic elevations (see Figure 1). Analyses which can be performed on the

multivariable files include. slope and aispect calculations, proximity analyses and the creation of

qualitative models based on user supplied weights (ESRI staff, 1979). However, statistical analy-

ses, such as multiple regression, analysis of variance and spatial auto correla tion analysis can not

be performed within the GIS. Further, since observations in a GIS multivariable file are stored

as sixteen bit integers, real values and integers outside the range t32,768 can not be manipulated

by the GIS.

The inability to perform statistical analyses on GIS multivariable files, precludes the develop-

ment of powerful quantitative models for resource exploration or land use planning with :a the

GIS package. However, statistical packages, suelf as SAS, provide tools for performing a

range of

statistical analyses front the computation or simple descriptive statistics to complex multivariate

techniques (Helwig and Council, 1979).

To provide a means of performing statistical analyses on variables in CIS flies and to allow

the results of these analyses to be merged with CIS multivariable files, Interfaces between the

ESR1 CIS and real valued data riles were created,

DESCRIPTION OF INTERFACES

SAS21 GIS is as computer program which converts gridded real valued data into the single

variable rile (SVF) format used by the ESRI geographic information system. The data file of

real values that is to be converted to all integer SVF must be sorted so that for a SVF file it rows by

in columns, the irml value for cell (I, j) in the SVF will correspond to entry (i*m+j) in the real val-

ued data rile. The conversion is accomplished by a linear transformation, y=ax+b, which maps a

real valued variable X into an integer variable Y, Tile program provides the user with two op-

tions for converting the data into integer format. First, the user may supply tile a and b terms

of Y=ax+b. Second the user may specify a range for the transformed data. The original data will

be mapped into this range using the linear transformation and the transformed data will be

checked to insure that the conversion did not truncate tile values more than a user specified

amount. After the transformed data have been written to a disk file, an additional record is

added to the file which contains the as and b terms that were used to make tile transformation.

This record is not read by any CIS software but may be used by the interface GISI-SAS to con-

vert the SVF file to a real valued data file.

GIS2SAS is a computer program which transforms integer data in ESRI's SVF format into

real valued data with row column references. The formula used to convert integer data to real.

valued data is x=(y-b)/a, where x is a real value, y is sin integer and a and b are consWnts. The

user li;js two options for converting integers to real values. First, the user may specify a and b

t 1

terms for the transformation. This is required if.the SVF rile was not created by SAS2GIS.

Second, if no a and b valor- were provided by the user the program will use the a and b values

in the lust record written by SAS2GIS when the file was created. Program output consists of a

real valued data rile in a format specified by the user.

RUNNING SAS2GIS AND GIS2SAS

SAS2GIS and GIS2SAS are interactive computer programs written in FORTRAN JV. At

Goddard Space Flight Center they run itt the foreground on an IBM 360/91 and an IBM 360/75,

Listings of these programs appear in Appendix 1, The clists Miles which contain TSO commands

and subcommands) used to set up and run the interfaces are presented in Appendix 1, To run

a program the user types the program's name, SAS CrIS or GIS2SAS, followed by T ("input file-

name") and 0 ("output filename"). For example if the user types,

SAS2GIS I(BOTANY,DATA) O(GISMATA)

the program SAS2GIS will be run to create an SVF file GIS,DATA from a real valued data f le

BOTANY.DATA,

When the programs are running in the foreground they will prompt the user for two lines of

input, The first line contains parameters used to make the transformations and the second line is

the format of the real valued data file, Tables l and 2 summarize the input parameters for these

interfaces.

Should the user wish to convert these interfaces to run in a batch environment, he must

make two modifications. First, the clists must be replaced by JCL statements which assign disk

files for input and output to logical units S and 10, as shown in Figures 2 and 3. Second, the

write statements which prompt the user for input should be removed,

COMBINING THE GCS AND A STATISTICAL PACKAGE FOR DATA ANALYSTS

Some preliminary results in an analysis of gravity and elevation data from the Rio Grande

rift are presented here to illustrate the utility of combining a package of statistical analysis

3

iprograms, SAS, with the PSV I geographic information system (CIS). The objective of this study

was to remove the relationship between Bouguer gravity and topographic relief which. was present

in a data set of elevation and gravity observations compiled by Keller and Conrad at the Univers-

ity of Texas.

Tlie gravitational field measured at a given point on the, earth's surface include, effects unre-

lated to geology, These effects are due to: variations In the distance between the earth's center

and the station where the gravity field was measured and the contribution of local topography to

the observed gravity (grant and West, 1965). Once corrections for these effects have been ap-

plied to the data, the resulting values are termed Bouguer gravity data and reflect the contribu-

tion of underlying geologic structures.

At present there is no agreement can the best Method for computing Bouguer gravity from

the observed gravity which Is measured at a station. However, Nettleton (1940) has suggested

that when the corrections to reduce observed gravity to Bouguer gravity are properly applied, the

correlation between station elevation and Bouguer gravity should be low. A striking similarity

between the Bouguer gravity and station elevation was first observed in three dimensional plots

of these two data types produced by the GIS. In order to determine the degree of correlation

between the gridded elevation data from the rift (Figure 4) and gridded Bouguer data (Figure 5),

the statistical analysis package SAS76 was used to compute a Pearson product moment correla-

tion coefficient. The correlation between Bouguer gravity and elevation was high, —0.903, and a

linear regression was computed to remove the variation in Bouguer gravity due to elevation. The

residuals from the regression provide a better estimate of Bouguer gravity because the effect of

station elevation has been removed. A plot of these residuals, Figure 6, reveals regions of high

positive residuals in the North—west and South-east corners of the Rio Grande study area. This

suggests that there are regional variations in rock density in the study area and that individual

Bouguer gravity corrections should be calculated for each region.

4

In this analysis the Statistical Analysis Syst6n (SAS) and the h SR1. CIS proved useful tools

fot examining the ntationship between variables in a spatially referenced multivariable database.

With these interfaces the researcher can utilize the extensive data base mwnagement and

graphics +apabillties of the GIS to complement existing software In the analysis of real valued

multivariate data,

Table IInput Parameters for SAS2GIS

Parameter Column Format Function

First Input Line

ROW 1-5 15 Number of rows in the SVF which will be createdfrom the input data file,

COLUMN 6-105 Number of columns in SVF.

A 11-15 FS-0 Multiplicative term in y=ax+b, used to map real xinto integer y ,

B 16-20 F5.0 Additive t erm in y=ax+b, if A and B are omittedNEWMIX and NEWMAX must be specified.

MIN 26-30 F5.0 Minimum value of input data default: value cal-culated by the program..

MAX 26-30 F5.0 Maximum value of input data default: value cal-culated by program.

NEWMIN 31-37 15 New minimum value after transformation tointegers,

NEWMAX 38-44 15 New maximum value after transformation tointegers.

TOLER 45-49 F5.0 User specified tolerance for truncation resultingfrom conversion of real values to integer format.

MISVAL 50-55 F6.0 Value indicating missing observations in the data.

NEWVAL 56-61 F6,0 Value which will be assigned to missing observa-tions in the SVF file, default: 0.

Second Input Line

FMT 1-80 80A1 User supplied input format for data in real dataset.

S

Table 2Input Parameters for CIS2SAS

Parameter Column Format Function

First Line of Input

A I-6 F6,0 Divisor in xa(Y-b)/a used to transform Integervalues Into real values default, use lust value inlast record cf SVF file.

B 7-12 F6«0 b term in x=(y -b)/a used to transform integervalues into real vsaues default., use second valuein last record of SVF file,

Second line of Input

NCOL 1-3 13 # columns in output file,

Third Line of Input

FMT 1-50 80AI User supplied output format for real vaWieddata, set.

REFERENCES

1. Andre C. M. Blelefeld, E. Elinson L Sodorhlom I Adler, and .1

surface chemistry-. a new imaging technique." Science 197 , 986-989,

2, Arbour, J. 14., 1 1980, "Tito use of a biophysical (ecological) data base for park planning,"

Proceedings of the International symposium on cartography and computing; applications In

health and environment, vol. 1, p. 515-523,

3. Environmental Systems Research Institute staff, 1979, ESRI geographic information soft-

ware descriptions, 79 p.

4. Grant, F. and G. West, 1965, Interpretation theory in applied geophysics, McGraw-Hill, New

York, 584 pp.

5. Helwig, J, T. and K. A. 0ioV,cil, 1979, SAS user's guide. SAS Institute, 494 p,

G. Knapp, E., 1978, "Landsat and ancillary data inputs to an automated geographic information

system.- Applications for urbanized area delineation." CSC T.R.-78 5019, 82 p.

7. Mason, T,, 1980, "A mechanism for selecting communities at high risk for cancer." Proceed-

ings of the international symposium on cartography and computing: applications in health

and environment, vn.l. 1, p. 216-321.

8, Nettleton, L., 1940, Geophysical prospecting for oil, McGraw-Hill, New York.

7

SOILSGEOLOGYTOPOGRAPHYLANDSAT SAND 1

% SLOPEAWECT

Figure 1. Structure of an CSR1 GIS MultivuriableFile (MVF)

UNIT STRUCTURE COMMENT5 CARD USER CONTROL, CARDS6 PRINTER JOB LISTING8 CARD REAL VALUED DATA FILE

10 SVF INTEGER SINGLE VARIABLE FILE

Figure '. Logical Units Required by SASLGIS

9

r

UNIT STRUCTURE COMMENT5 CARD USER CONTROL CARDSE PRINTER JOB LISTING8 SVF INTEGER SINGLE VARIABLE FILE

10 CARD REAL VALUED DATA FILE

Figure 3, logical Units Required by GIS"SAS

Figure 4. A Plot of Elevations in the Rio Grande Rift Study Area Produced by the ESRI GIS

9

it

Figure 5, Bouguer Gravity Values from the Rio Grande Rift Study Area

Figure 6. Residuals from a Regression of Elevation and Bouguer Gravity

10

APPr-NbIX I

I'I' OGRANt LISTINGS OF THE INTERACTIV8 INTERFACES BETWEEN REAL

VALUED DATA SETS AND THE- ESRI CEOGRAPHIC INFORMATION SYSTEM

A. SAS: GIS PROGRAM LISTING

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ELSF WRITS AN 1• ..401 '15SSAGE AND 5T?U

WRITE(o i l) ^ ,n ^ r I p ,S ! ^

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1

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ERUGaAMUH: nDWAPn IASICKA

DATE: AUGUST 1 # 1979

THIS PEOGRAM TRI IISFORIS 1313 71L33 IN INTPN'IFn*2IiTC ThE QRIuTNAL FSAL VAL'IF1 IA'r l IN 3 ST'SPR:

1. tiEADS 1,10W COLUN IN F C33A7."ICK FRCM PECO q r I

2. ; r i A IN S F G V. IT"Z T 13 'I' 71"AL VtNLU%S ITS"IN-A I I N aA m.9 r o "Ri i T 1 01 : .11 A "A I NT % G n." "A ) / A

J. 431TES TH"7. 91AL nVr l TO A VILE WITH AUSER SUrFLIE9 F r P'l A'r

VARIADLE F tj 'N c T 10 1. 1

CAIA STOTIVS PEAL !A^-",AFUWCUL .9 1 111 ES I CT lc^9 AND COLU4"s

TN Tli'' T.lV r IT FILEsuw or imis ri ENTA AND k-lis rILF.CUL UMN C()VIMNS 11 CATA S "JIS TILL'AB STOr-ES '"' Zll"wll TPA ISFORM PARA'4SSLJPE SLUE C rL1 11 r.,'An P uricrioN q,;"-n

10, rr .1.4 ,;-. 0rj n ZAIA DATAI All I k ra v.\,T"?Svps o p L'IN7AR TRANSPOn4

9Tn!i-.- ,3 I i0l; U TUE TBAN5iopqED*rATA

FAT 11SvI SIP2-tIll P CIMAT FOR rzvALVALIF1 IAV1 3E.T'

r%EAI*4 DATA (150L, A P (2 FLC I)EI TNMRINTEG O H*2 liCoCC k) 115WLCCxTCAL*l BUHH h")

ti ECU IVALt, NCE (Ad (i) ^-,L E) mi vi R) , (nu FF cr i) -m- (1)

C r^EAC USER SUPPLIED (',U'7r-U'r AID DAIALIrTUSc

ilt'P.1 T E (a 4)NrQ7N,*',AT(ldJ

U f *11510 1 M0.L d 41.'JL 'Lr E 'Vi le") In iA"Kt VIR

A 1-6

.1IH (DEFAULT: IF 24H10, n RO'RA! %ILL U.Q "4 LAS" Pr-CORD, Of SVF)IH A of

•Rr A r. 5LGEE#INT,R

WPITE4 2)2 FORMA W PLEASE 1 1.1?f)T COL INS C OR CITPUT DATA SET: (13)

DEFAIJLr: IF ;EliC,, PROGriAl W MILL USE # CO MNS IN SVF l )REAC(5,6 N,CCLfCFPAT ^i q, IT F (E, 81

P. FORMAT ( PLEASE IZ0UT FCRIAT FOR .0"A' VALUE!) n ATA SrT'.'0 // life,' -EI FA(JLT: LAST 1.1ECCRD OF SV 71 411EL JE HSEDo

(8OA1)

, FA V (9 f 1 ) FMTFORMAT(d0ill)

CG qBAC A,d) .C u C o !u 4S 14C COVIVIS)4"',1 '311*5 7ILFc

FEAC g) LOWCCLFCW=r. ),(:CL(l)CCl0 N=BCwCCL(2)

3WRITF^b 3) ACWotXL,9!NFCRFA

J M10/11U # Jl'.%JT-j- , c m22,T5/lX10 'COlUMNS= # j T22?I5)

GT V I

". A rllN v (SLOOI AE N E74. 0 . C A. .1 1 t4 c" 1-10

C SPACE PAST TRAi4SFCl.!En rATAc

DO

30 1=1,RCwC 30 CALLFBACC (IROW, COL".'1'4 , 9)

C FEAR AaD ZCHO VAbA ll"47"'ll "IS t]S-r r) *T(7 0+"W14^1NAL REAL IIATAC

0PFAE

8) -)1'ITE SLcPE INTvlV5 Ili 1 SLCP"j='Fo IR 'q 11 ,110 0 , T 19,F8. 3/1 X X10 I I.NTE VZ SFr1T=' 117 21 r 9-3)

C CHFCF E06 U Eli SPECITIH.C

Cc, 50 1=1"'oIF (Ftl l ^ l) 81'IK) - 33C 'rC61

50 CcNTINUCC NCNE FCOND USE LAST ESURn Cr 5V?C

rxEAcQl,.E,No=99) FAI

Ccc r p A N F r y v : h E U n"r A V ITO 0.- T G3 I A '94 VA !J 73 5c A HCW isl A 7XIEc

IF tNCk;L . EQ^ V) 0) NCL;L=CCtt'lNSEA (^L 6Cm Ln (11 10 i = 1, Rew

Al-7

h

CALF READS ( lkow CUL'13W,R)C t^ 10 J= 1 -CLU M Ir

o DATA (J) (IIICW (J)— xvT^11) /SLOP"C %RITE ThE REAL VAL gP D nATA FILLC

14 CALL WklI TEC (DAlA j NC'CL, v MT, 1D)WRITE n, 1t)

12 FORMW (/1110o'++++ S r1CCESSF TJL CONV 11. 5ION TO 11.7-AL V L qT D FILE *#+*'

9 9 E. RTT1( e, 1001OO FORMAT j1,iU 1t1 **+*+' F ATAL PRROR:

NO "CR`SAT S?PCIFTFC'.

BY USER AhD &C FOn Mll C4 SV ***+*^STOP 2r.-ND

CcCC * THIS SUBEC U11NE REaC$ A SV F P0.11AT FILEC + '^C *t**#*****#*****+*******#*# ►**ix#*^*#***#********.***C

SUBROUTINE TEADC(IRCWvCCL"U NoLU`i-A.T)INTEGE°R*4 COLUMNINTEG E R*2 1-hOW (COLW4 l)REACALUNIT)IhOwRETU NEND

CC

C •C * THIS SUBROUTIN E "4RTTFS THS 17, AL V AL ► f EC DATAC wlTd A USER S ECIFIEC ?ORIAT **CC *s^*****+*h***##**z**#y*******^******^***i****C

SUERCUTINi 6RIIEC(DATI,CCLnM'1,£ IT, VISIT)INTE;GFa*4 COLUMNREAL*4 DATA (COLUMN,FIT ( q)IRITF jL7h17,Fm)UA,41r ET11RNVND

A.1-8

AP'CNb1Y 2

CLISTS

A. CL.IST FOR SAS2GIS

FROG O INFILE (REAL.DATA) OUTFILE (SAS.GIS)CALLOC DA (&INFILE,) F(FT08F000ALLOC DA (&OUTFILE.) N SP (10, 1) TR U (GIS)CALLOC DA (&OUTFILE.) F (FT10F001)DO SAS2SVF LIB (PROG.LOAD)

S. CLIST FOR GIS2SAS

PROG O INFILE (SAS.GrIS) OUTFILE (REAL.DATA)CALLOC DA (&INFILE.) F (FT08F001)CALLOC DA (&OUTFILE.) N SP (1.0, 10) TR U (FORT)CALLOC DA (&OUTFILE.) F (Fr 10F001)ALLOC DA (*) F (FT05F001)ALLOC DA (*) F (FT06F001)DO SVF2SAS LIB (PROG.LOAD)

A2-1

APPENDIX 3

AN EXAMPLE OF THE OUTPUT FROM THE INTERACTIVE

PROGRAMS, SAS2GIS AND GfS2SAS. PROGRAM OUTPUT IS IN

UPPERCASE AND USER INPUT IS IN LOWERCASE LETTERS,

A. EXAMPLE OF RUNNING SAS2GIS

sas2gis infile (realdata) outfile (elev2,svf)

INPUT: ROW COLUMN A B MIN MAX NEW_MIN NEW—MAXTOLERANCE MISS—VAL NEW —VAL USING.(215, 2175.0, 2175.0, 2F7.0, F5.0, 2F6.0)

.... 5, o. 10, o. 15..,20.,.25 ... 30 . . . 35 ... 40 ... 4$ ... 50 ... 55 ... 60

36 48 1 0.

ROWS = 36COLUMNS= 48SLOPE= 1.000INTERSEPT 0.0

PLEASE INPUT FORMAT OF REAL VALUED DATA(I Of8.0)

+4-+ SUCCESSFUL C014VERSION TO ESRI SVF FILE 1

1H00021 STOP ICONDITION CODE = 01

B, EXAMPLE OF RUNNING GIS2SAS

gis2sas infile (elev.svf) outfile (realdata)PLEASE INPUT A (F5.0) B (F5.0) TERMS WHICH WILL BE USED TO MAKETHE TRANSFORMATION

(DEFAULT: IF ZERO, PROGRAM WILL USE LAST RECORD OF SVF)

A B........ I +

1. 0.

PLEASE INPUT # OF COLUMNS FOR OUTPUT DATA SET: (13)DEFAULT: IF ZERO, PROGRAM WILL USE # COLUMNS IN SVF

PLEASE INPUT FORMAT FOR REAL VALUED DATA SET, (80A0DEFAULT: LAST RECORD OF SVF WILL BE USED(10f8.0)

A3-1

ROWS a 36COLUMNS 48SLOPE- 1.000INTERSEPT - 0.0

++++ SUCCESSFUL CONVERSION TO REAL VALUED FILE i i 1+

IH000 2 1 STOP IICONDITION CODE - Al

A3-2