S
the Remote Sensing Data
ect
, Tokyo
Dr. S8 Tanaka, Mr. T. sugiura and Mr. Me Yoshimura
Remote Sens
Center, Tokyo,Japan
VII
1"
ects,
construction and
s
and
are now
using com-
color,
how to evaluate
1 engineering
1 evaroads and
2 ..
The
are such items as
and weather
is diff
are connected to
by
constructing
Moreover the
the
were
mos
of natural resources.
area, about 3 71
zuoka Pre-
s
from
roads refor
factors of the second class road.
Item 10.
Class
Tashiro
(H=700m)
Vehicle velocity for pranning
Velocity for
First
40
or
Second
30
or
30
20
Third
Item 15.
20
Curve radius
Radius (m)
Velocity
Fig. 1 Automatic drawing of forest roads researched by specifications of forest roads
planning (km/h)
40
60
40
30
30
20
15
20
12( 8)
Item 20.
Profile gradient
1: 25,000
Velocity
Profile
(%)
Vehicle velocity
20km/h
Road class
Second order
40
7
10
Profile gradient
10%
12m
30
8
12
20
9
14
Radius
Fig. 3 Planning factors
Fig. 2 Specification for construction of forest
road
3. System and Data Processing
Fig.4 shows the system flow chart used for
s study for
is
the cons
a forest road.
Existing Materials
Field Survey
Statistic Materials
Maps
Reports & Papers
Field Survey& Observation
Questi onai re
Intervi ew Survey
L__
Evaluation & Modelling
Formation of Mathematical
Matrix
Output of necessary Data
Numerical Formulation
Wei ght~d Factors
Classification
Studies of Environment
Specifications
Formation of Decision Table
Fig. 4
-
Remote Sensing
Aerial Photos
Monochro & Natural
Color Infrared, Mul ti band
Satetll i te Images
Ground Photos
-------------
Compilation of Data Map
Natural Data
Topgraph
Vegeta ti on etc.
Soci al
ng Data
T ransporta ti on
Compilation of AnalysisMap
Inclination
Direction of Unit Area
Sunshine Energy
Cutting / Banking
Fi eld Data of Vi si on
Stereo-Model etc.
In the f
stage,
approach are needed.
to be encountered in each
cleared and related and
at the same time be collected, such as
maps and reports. Adding to the conventional
photo images of remote sensing techniques from airplane and satellite also provide very useful information. But these data are
arranged in a certain fixed list and must
tabled in a
inventory
data.
Secondly
arranged program
processing
divided into
data
the
to the natural
mesh data. Files
first
of
to the number
the
into the details neces
for each relationship. For
obtained such as data on
unit area and sunshine
,etc. and the
files, which is called a master file,
of anlys
in proportion to percentages.
The
file can be
in analogue
a
the line
these drawings
the automatic drafter.
advantage
various kinds
stati
information
systematized master file
at the dame time select
that are equivalent to
environmental conditions.
stage, the necessary data are
with the mathematical matrix to satisfy certain
condition tables, called"
ion Tables"
Accordingly,
modelling work needs an
purpose for the
ects and for the formation
tables. Severe and descreet s
of
the
of each
a
zed process@
4. Processing System of
as
(1)
(2 )
(3 )
(4)
The outline of the process
lows :
Preparation of basic map
preparation of mesh data
preparation of data
Ie
Environmental evaluation
4-1 .. P
The
lected
Data
tem
is
0
of master
Ie )
of basic map
s amd data for analysis of the
1974 and 1975 and the results were
were
a
form of a topographic map, water flow map ( river system map),
landslide map. vegetation map. soil map and geology map. They
are shovln in the basic data of
first column in Fig" 5"
Basic Data
Primary Processing
Primary Evaluation
-
Map showing
number of Landslides
Map showing
area of Landsl ides
.
Secondary Evaluation
If''~~''--~-;------l-
of Ground
Pr\)(1uct.i
---} EvaluatIon
Ground EJ('vnliol1
Value Sheet of
Slope A n a l y s i s - Land Use
_ Soi 1_._.___
. __
Prohabi I i ty
Evaluation valW.' .Sheet:rf..
.~. --~----Danger Probabi I f.y by Land
Slide
.~=.v;luati~-;;Slope Analys;;----Vegetion
Value Sheet
Geology
of Fore,st
Protection
Eveluation Value Sheet of
Vegetation Protection
Natural Grade Classification
Vegetation Classification by
Elevation Range
Fig.5
Environment analysis by computer
E~pecially, the map showing the number of landslides \'lere
completed in 1974 using areial photos at a scale of 1/20,000 and
on the aerial photographs at a scale of 1/20,000 taken by the
Government Forest Agency, landslide areas occupying more than the
1 mm X 1 mm on the photos were interpreted.
4-2. Preparation of mesh data
To store each type of data in the computer, the test was
divided into square meshes consisting of one unit 450 m X 575 m
and each legend data of the basic map was read within each area
mesh and denoted by numbers.
(1) topographic map -minimum ground elevation reading 10 meters
at the center of one unit mesh.
(2) Geology map - from first to third rank in order of geological
calssification occupied in one unit mesh.
(3) Landslide frequency map - map showing number and area of
landslide.
(4) Vegetation map - from first to third rank in order of area
occupied in vegetation classification in one unit area.
(5) Soil map - from first to third rank inorder of area occupied
in soil calssifocatipn .
(6) Water flow map - density of mumber of valleys~ ( river
system map )
4-3 .. Formation of Data
Various basic map data can be input into the computer, each
file in a matrix-form, known as a unit data file. The drawing by
the line printer can be called a computer map as shown in the
following figures.
T~ere are inclination slope analysis map, slope direction
analysl~ map, valley density map, map showing number of landslide,
ve~eta~lon map, soil map and geology map. From this topographic
unlt flle, slope analysis, direction map and sunshine energy map
were outputted by the computer.
VII-"""II"-'''-'''
... ++XX ... •
~xxxx
•••• ·xx •• ++00000000' tA)'~ ~{I-H·
1
.. ··xxxx •• eeeexx •• xx •• ++OO&.O~ooxrYX.,,: , .... "'
•• ooeexx •••• 9<1eeeeee®0Q11100ee00' 'XX •••• '+~J'.{
.... 9<1geXX •• ++~nn~l!IJo0000000XX'Hl •• Hooce,v'
...... geee .. 00 •• XX •• ++llleooo' 'eexx •• n •.. , .,
•• ++ •• 1I!leeIl1lXX •• 00 •• ooeoooooeexxxx •• ++000000
XX •• ++' '~@II&eexxee •• ooueeeeegeeee .. ooU~0gf;
XXX X•••••••• ooooeexx •• ' 'eexx •••• ++!i!i~0U00ge •• 00++ .... xxeeee •• ooooe<>' ,
• • eexx ...... ++++' • XXXX •• !lCIJeeX x •• ++++XXXX •••• HOOOO •• ++xxxxee •• 00++00++
ooeexx •••• ++OOOOXX •• xx •• xxxxee •••• ++9<1eeoooooo •••• ++ooeexxeemlloooooOOO
•• eeee .... ++00 •• eeeeeexx •• ooeexx •••••••• lIlIIllnIlXx •• 00++ •• ee •• llIooooee ••
• .eee9OO .. oooo •••• ee0!1ee"@00UI!! •• eeee@@lIIle()1I4IIee .. 00 •• ++XX·•• ++00++ •• ++
XX •• 1I~nnoo •••••• ++n0~BnUUBe •• !lnnn&ee~nlin •••• +H,e •• 000000++++
XX •• HXX •• ++xx •• ++0000n@~neeee"001ll.nIll00Xx •• ee .. xx •• ee •• 000000++00
xx •• ooeexx •••• ++0000' '1lIlnXXeell~nl!lIeeeenxxeell~nIlllU •• XX •• 0000000000
•• XX •••••••• ++oooe~o •••• ' 'eeee(lj(!1I1111110()0000ee@0U .... ee •• ee .. oo++00' ' ••
lI!1egeeeeoo •• OOOOOOXX •••••• ++allIIIIIIOORli' • oolllllil •• eeeal!l!Il!llltlellllClOOOOOX X••
ooel'l~(!lIIeetflOOOQ •• eexx •• ++ ••• '''''IIIlOOXX •••• XX •• ee®!lllillooee .. oooooo ••••
IlUlineexx •• oan . . ++ XX •••••• ++lInueexxxxee"oOUlllueeeexx •• ++++XX ••
•• ' 'xxeexx •• 00 •••• ++xx •• ++++ooee' • XXXX •• eenllloeIIlOO· ·Il~eeef) .. ooooel) ..
• • eeeeIH!ee .. oo .... ++ •• HOOOOOO++XX •• xxee"(!I!~U'o~BliXXXX •• eallllllll ••••••••
XX •• I!ooooexx •••••• 00 •• 00oenCloooeeeeeeIlIlllUUlllfIlgQeeeeeeeexx •••••••• ++
• ••• XX • • &i!eeeexx •• " ++0000' , •••• Ht'HIGIlIIOO()Onu' '!llleem0neeee .. 000000
•••••••••• HlnIXX •• 0000 ...... ++0011111111110011 •••• XX .. ~Q!®!110@eel!II' ••• ++111
99xxeeee .. OOIllQlUIOOOO .... " ++OOOOOO!!Uloexx ••• , eexx •••• eeeeeeee ......
III1Hlelllllllllloeoo' • ~CIlIII •••• ++"OOOOOOOO(lQlU' • EJexx •• ++xx •• ++Ql~~nu\iln •• 00
1!)IIIlIIlIee •• OO(H1XX XX•••• OOOOIlD~QO(lO(lQO •• ++ 1l0000X XXX•••• ++ ooeeeB@0seee •• 00
1110nneexx •• ++XXXX •• UmtlOOOOIllOOC;O •••• ++ •• xxeexxee .. 0000' '®nlleeee •• 00
III1UIIII~~ee •• 00' 'ee .. 00++1100' ' •• XX •• ++ •• Hee~aeeeexx •• ++++@~ul!l~eexx ••
IIIIH1I1XXxxe6xx •••• aUIIOOOOOO++O(lXXXX •••• ++++XX •• ~0I1XX •• ++++9gee'H)l'!mnee
(I(leeeee91!I!ee ...... ++++ 000000 .... ea •• ++OOOOXX •• ++X xes. '00++ •• i!l~lneeetll.
III' ·ee~I!~!lllnlllee •• OOOOQe()o" XX •• 00"00QQ' 'eexx •• ooxx •• ++00 •• XX •• 1I~@0n
XXXUfJI!IIXXlrX •• 6e .. 000000++ •• 00XX •••• ooooxxeexx ... ' " •• OOXX •• xx.. xx ••••
)(Xxx •• xxeeeeeexx •• H •• H •• ++!!I~eexx •••• '" .ooeexxxx •• ++ooee •• eexx •••• ++
eeeexx •• I!n~xx •• ++ •• ++00 •• Heeeeeexx •• ++++xuaxx •• ++IIIIIOOXXXX •••• ee •• 00
1l!lllllooee!l~X xeeeeooxx •• ++++00' • ooeeee •• ooooeex xee. - .. eex x •••••••••• ++111
1111 XXB 1111111 , • e91111111111111M1I .. 0000++ •• eellllleexx •• ++' • eelllllln()()' •• '" ++++000000' •
• • eexx •••• 69i!lI!i&llOe@UMoooe++++oonIlClxx •• ++ xx XXXX •• Heeee .. oooooeeonee
• • xxeooeeelllfllll)()XX •• n •• ++0000' • xxxxee .. ooeexx •• ' <oon •• noenUOOOODIII
xxxxnllllllllllntlOeeeexx •• ++ •• ++++ •• eeeelllllllllooxxee •••••••• ++ooooeelllllUQClOO
• ·ee~!Hf.lllllnlfllleeIlIHlexx •• ++0000 •• ++lIlfllXX •• • • XX •••• ++00 •• 00llfleeUUllllleeee
99I11I1BleelllllneGmIll1ll!0Uleeoo++ •••• H •• ee •• OOeeeellll!lllf •• ++oooo++eOIJ@liIIeeoo
111111110000++' '111(9II1(1(11111111111111111X ...... ++ •• ++11100Ilmxx •• • ... 00' • eooo++' • l I n ' •
lIllII'··III1 •••••• xx •• XX •• xxxx •••••••••• , • ++++ooeeeexx •• 1II1111111001lIllee++++IIRI!IIQ()
00 •• 00 •• ooooee •• ooooe9OOlll®nee .. oo'; 0000000' '1l1I&lInOO' • eo' • "0000' '1111: ..
Fig .. 7 Slope analysis map
Fig.6 Slope direction
analysis map
Fig. 6 shows slope direction
8 directions, gray tones
show, north the darkest and south the lightest. Westerly directions are shown lighter than easterly directions, since late
afternoon sun is a greater attribute than early morning sun for
most activity. The following shows the frequency distribution of
data in each direction.
Level Direction
10
north
2
••••••••• 1111111111111111
xxxxxxxxx ......... +++++++++ 000000000
••••••••• flunRnll
xxxxxxxxx ......... +++++++++ 000000000
northeast
3
.... 1.... lin? ....
xxxnxxxx .... 6 .... ++++7++++ OOOOROOOO
••••••••• nllUllin
xxxxxxxxx ......... +++++++++ 000000000
••••••••• InUlnll
xxxxxxxxx ......... +++++++++ 000000000
east
4
===:::::::::==============::::=======-==========================================================================:::-:::=.
219
307
116
171
85
171
southeast
5
south
6
Fig .. 8 Frequency of directions
southwest
7
west
8
northwest
9
Fig .. 7 shows slope analysis in 10 levels with a range of
9.33 e~ch level, X signal is the steepest,lower numbering shows
gentle and number 1 is the gentlest. Fig .. 9 shows frequency distribution of each level.
LEVELS
0In®~1J(!0@
0@elJ@1J0®~
(!1II1J03~~0(!
1II1II1l1l1II~0®0
'YMDOI.S
@1II1l1l~1l01l1l
f
REQU~~CY
lEVELS
5
•••••••••
• ............................... XXXYXXXXX 000000000 eeeeeeeee o()OOeOOCHl
........ " • ...
,YM80LS
9
10
========== ===== == ::== == =::::: :::::::::=::: ========== ==:::::::: == ========::: === ===:: ======--=::: :::=========== =::::::::::: ==:::::: ===:::::: :::::-:::::: ::-tit I I I It.
• • /I II /I I II /I II
.... 1.... • ... 2 . . . . . . . . :I . . . . ++++4++++ XXXX5X XX X 000060000 eeet17eeee
.... . . . . . . . . . .
t t t l I I I 0'
• 0 /I II /I . . . . . . .
1I~1I@0!l1l1'l0
+++-++++++ XX XYXX XY, X 000000000 ~ee OeOCHH;)eOO f)WtI)D€lE)®t3
oeoe~eoeo
-t-+++++++ .... XX X xx xxx x 000000000 eeeeeeeBB ooeeeeeoo
t1i!'llllly0IUI!I
=0®@@~~~0
. . . . . . . . . . . , .. , .. ' ......... ""'+-H++++ xxxxxxxxx 000000000 eeeeeeeee OO()()OOOOO 01111@111011011
:::::.::: =::: ===::: ::=::::: ==== =:::::::::;:;;:.: =:: ==:::: ==::: =======::::: === ==:::= :::=:::::-:::::::::== ==::::: == ==:;: =::: =::::;:::::::;::::: =-::: ==::::::::.:::::. ===:::: ::.::: == ::: - - -'PFOU~-'JCY
172
11:1
160
15"
178
Fig.9 Frequency
266
55
j
2
slope level
4-4. Correlation of Unit Data
The computer map file can be used for correlation analysis
of each unit data file.
The final purpose of environmental evaluation by computer is to determine the potentiality of land use
and forest protection which can be shown as primary evaluation
in the former figure of envirnmental anlysis by computer.
the following divided into three
They are explained
categories.
(1) Evaluation of danger probability of land slide by correlation
(2) Evaluation of
(3) Evaluation of
The evaluation of (1) can be
graphic slope, geology,
frequency which are considered
rence. The evaluation of (2)
and land use probability which have
file on soil, topography, slope
soil classification can be calss
dard of the soil product
tion grade which is
from the unit
e
topttribution of landsl
factors for landslide occurto ground productivity
done by using the data
and ground elevation. The
stanby
calss
elevaadding the
The evaluation of (3) was
, ground
elevation and sun
was classified by
the natural grade
Environmental
Agency of the Government.
In
of vegetation
distributed
several
on
, natural
grades of the ground
cons
scal distribution of ground
were decided. Moreover, sun shine
energy calculated from the
lination and direction of the unit
area on the inclination was the essential factor for evaluating
the ecological and practical engineering s
of the existing
field vegetation during construction and thus the evaluation of
forest protection and land use probability were completed in the
secondary evaluation process.
111\HV1IHHll IIHHI IHI1111 lLU3??HHll!! 1 P2i'1'IIH
;i~~i,~~~: :~~m~u,~~~~!I'~~~[~;~~~~~~;: ~~:~;'~~i
IfH Hf! III! 1111 YH HH 1 I HHHHI122 55 2 211 HHllL LH H! ! ? 2
! I II J I lLHHHH HH HH/," II HHII I 11111111 1111 I HH1 j ) 0
! 122 HI! I I HHI I HH 1111 I I HH I I HHHHHH 11 Hf!LLH H I I Ii f' IlH
11 112n21111 HHHHHHHHHHlll1HHHHHHHHLlllHIIII HH
LUIII D22 HHl II II III 1 11 ! l L11 Jill 11 HH I! HHHHHHH HHHHH I I HHH HHH II HH HHH HI!H HH
LL 1111111 j HHHHllHHlL 111111 Hill J t 1 HHHHII HHHHHHHHHHHHLLLLHHHHHHHHHHLLHHHH
LLI I L LI III HHHHHH2nu I fill fin \ 1 I 1Hil HHHH II HHHHllH HLlHH II HHH 'IHHHHHH HH II HIl nli
II HH II HH II HHH HII 1111 ! I LU 11 1 1111 HH HHHH HH HH II HHHHHHLlI II III HHIlH HNil H" 4 ! 1
1111221 IHHHHHIlHHLL 1111111111 HHHHHHHHHHHHLLHHHHHHHH 1122HH 1IIIIlHHHHH~flHIl
HH II 1122HHHKHHHHliHHH I! HHHH II HH 11I1 HHlll I! 1 lL! I LLHHHHHHHHLLHHII HHHHLLLL
HHII HHHHHHIIHHII 1 111221 IIIHHHH22LLlII! II! IHHlLHHLLHHHHI IHHHHHHHHHHHHHH
II HH 1 II ! KKK flHHL LI 12211111 11 ! HfI! I HH II HH II i 122 i I ! I HHHHLLlI HHHHHH HH HHHI! I !
HH II IllLLL11 LLHHHH II I I LUll! LLlI221111 1 12211 HHHHHHHHHH II HH lLLLLll 1HKKH
IIII! I HHHHHHHHHHHHHH 111122LLllHHHHHHHI 1 II! 122HHIILlHHHHI I HHLLHHI 12211 LL
HHHHLLlI HHHHL 1I III LUIUII tIl I HH 11 HHHH 11111111 HH 11 HHHHHHHHHHHHH HH Hil Ii 11
HHHHHHLLHHHHHHLLHHHHLL IIHHLLLL 1111 LLHHLLlIHHHHHHII HHII HHII HHHHHHHHHHLL
HHHH4"22LLlIHH22LLHHIIHHLL 11 HHHHI1221 1 II LLHHLLlIHHHKIiHHHHHHHLLLLHHHHHH
HH II ! III HHHHHHHHHHHH I ! 111I HH 111111 LUIIIIII I HHII HHHH I ! HHHHHHHH II HH I I HH
1111I II t HHIIHHII HHHHHHHHLLHHI ILL! i IILLHHHHHHHHIIIIIIHHHHHHHHHHHHHHHHHH
HHHHHHHHHHHHHHHHII LUIII HHHHHHHHHHlLHH IIHHHHHHHHLL22! III HHHHHHHHHHHHHH
HHHHHHHHI! HHHHII HHHHHHHHIIIIHHHHHHHHHH22 1 I HHI12211?2LLLLHHHHHHHHHHH~HH
HHHHHHHHLLHH IIHHHHLLLL1IHH II HHI ! 1111 HH221 IHHIIII HHII LLHHIIII HHHH~HLLHH
HHHHHHHHHHI IIIHHII 1 IIIIIHHHH22LLlIIILU~11I11I11111! 11 HHHHLlHHHHHHI I HH
II HHHHHHHHHHLLLlHHLL HH II HHHH II LLLL22HH! I LLLlII HHII HHHHI I HH llLLHHHHHHHH
HHHHHHHHHHHHIILL221 1 HHHHHHHH11 HHHHHHHHHH2211 HHHHIIHHHHIIII 1 IHHHHHHHHHH
HHHHHHHHHHlL11 HHHHflHHHHH221 1 II HHHHII HHIIIIHHHHHHLLHHHH IIIIHHHH~{HHHHHHH
HHHHI! II LLHHI II I HH'14HHHHHHHHIII1 1 IllHHHHIILl1lHHHHI! IILL II HHHflHHHHHHHH
.. 4 HH 111111 HHl!l! HK IIH HHHHHHHH LL1IIIHHHHHHHH II II HHHHHHHHH HHriHHHH II HHHHHH
22HHIII! HHlLLLHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHI I IIHHHHI! HHHHlll! HHHH
HHHHIII 1HHHHHHII HH4HHHHHLL11 HHHHHHHHHHII HHHHHHHHLLlI HHII HHHHHHHHHHHHHH
3311llHHHliHHHH II HHHHHHHHLLHHHHHHHH22HHIIII HHHHLL11 HHHHHHI 1LLHHHHHHHHHH
H~HHHHHHHHHH I 1 II HHHHHHHHI 1 HHHHHIiHH! IHH II HHHHHHIIHHHHHHHHHHHHHHHHHHHHHH
HK 111I HHHHHH III t HHHH IIII! I 1 1 I! HHHHHHLL22HHHHHHHH IIHHHHHHHHHHHHHHHHHHHH
LL I I HHHHHHHHHHHHHHH'ILlHHHHII HHHHHHHHHHIIIILL<lHHHIILLHHHHHHHHHHHHHHHHHH
HHHHI III LlHHHHHHflHHHHllHHl1 LUlll LLHHHHHHIILLHHHHLLHHHHHHI I HHHHHHHHHHHH
LL HH I I LLHHHHH HHHHHHH HH II HHHH LLHH 11 HHHHHH II HHHHLLHHHHHHHHHHHHHH HHHHHHHH
II HHHHHHHHHHHHHHHHHHHH! II 1HH! IHHHHHHHHHHHHHHHHHHHHHHLLLLHH!IIIHHHHHHHH
HHHHHHHHHH II HH I! HH 1111 HH HHLl HHHH HHLLHH II LLHHHHHHHHHHHHHHHH III I HHH HH HHH
I I HHHHHHHHHH HHHH HHHHHHHH 1 I HH HHHHHHHHHHHHHHHHHHHHHHLLHHH HHHLLHHHHH HHHHH
II I II IHHHHHHHHHHHHHHHHLlIIHHHHHHHHII HHI! HHHHHHHHHHII HHI I LLHHHHHHI !HHHH
HH IIlLllllll111 ! HHHHLL111111 HHHHHHHHHHHHHHHHLLHHHHII HHHHHHHHII HHHHHHHH
HHHHHHI 1 III! 11 LL22HHHHHHHHII HHHHHHHHHHHHlLHHHHHHHHHHHHHHHHLl.1! LLHHHHHH
++t t . . . . . . . .
LL •••• t '+++~ ..............~+9BeeeeeG~';OO
•••••••••• LL •••• ··~+++.... XYeeeee~FyYYCeOO
•••••• lLLL •••••• _++++++....rX9'WeX X++++++B6ee
LLLLLL . . "" ..... ++++++-H-+"'XXXX)(~ )(y-4-+++++X XOOIII
LLLLLL ......... ~...............-+ ....... XX+++++... -+.·:++eeoo.!
LLLL •••••• _ _ ++++HH++++++++++-H-++++++999i-ln!
LL. ••••• ~++++HH->+++++->............ #·+++e'II'nl!
• ••••••••••••• LLLLLlLltLLl •••••••• ++++-_HH++++'-+++++#++"+Y. XtH*\%G
•••••••••• lLLUUL! U lLL •••••• ' '++++++++-++++HH~_+""'HHle%AOO
• ••••• LlLlLLl LLULLL n •••••• _++-+++++·+++++HH++++++++++"'#X XeOOeeAOO
•• LLlLLLLLlll LlLLl •••••• • ''''~+~-I-+HH~+++++++-+ooeooooe:(l
lLLLLllllLLLLLLL ....................++ ......+++++++++-++_....~++XyeeeetH*\~
LLLLU.LLLLLL .... e .... '" '~++++++++++++++++++'" 0' '++~++eeeeeeee\" '4-10
0 ....
.. II
LLLLLl.LLLJ.o· .... ·.tf~+1 I I I I I I I I I
LLLLLL .... " .. o' '~+111111111111
LLLL ........ '"
LL ..... " "
e
............ III . . . . . •
It . . . . . . . "
t 1111~ ........ " ...
III
'I++-++++xxeeeeeee&++++
I .. " .. e • • • o' f+++++++~~eeeeerx++++
I++++++++ ...+++++++++++t 1I . . . . . . . . . . . . . . . . . . . f t++++++++XXOO&geaatt+~
.++++++++++++......................................... '++++++++XXeeOOGe99X '/. ........... ++~
.... ++0+++. I ' . . . . . . . . . . . 0 .... LlLL ......... ,,~+++++yXXXeeeeeeeexX+++-4-+4-4-+
c •• ':" t" a .... II.".LLLLLLLLc .... ' lI~+++xxeeee&e&ea&eS+*,:+-"'++++-+-"
LL •••••••••' ••••••••• lLlLLLLLlL •••• • '++++++++YXeeeeoooooofH!++++++++++++
• ••••••••••'. L LlLLLLlLLL l LLllLl •••• ++++++++x xeeeeeeooooooH++++++Y X++++
LL •••• LLLLLLLLLLLLLLLLLLLlLL •• ' '++++++XXXXeeOOOO9999&OOG++++++JO ... + ...ee
LLLllLLLLLLLLllLlLlLlLLlLL •••• ' ·_xxxxooeeooooeeee~+++++++xx+ .... -+eEl
LLlLLLLLlLLlLLLLlULLlLL •••• _XXXXooeeoooooo&OO&&&++++ ....++XX++++GG++
LLLLlLLLLLLLLLLLLllL •••••• ++_xxooooeaeseseseeeaxr++++++XXU++++++++
lLlLLllLLLLLlLlL •••••••• _
.... x x x Xooooooooeeoo ge " " I I , I I XX .......... HH..+ .....
LL LL LlllLl Ll LL ....................... H xreeeeeeoooooo x x-+-+++++++++ xr XX+++++"HHX X
LLlllLLLLL.'" .' .... + ................. xxxxee~eeeee "
" ' " I , , 'XXXX~++++HH+"
LllLlLLLLL." .'.' '++++++xnxxx~XX++++"-H"""+++XXXXXX+++'''''+YXf{H­
lLLllLLL'••• ,._XXXXXX~OOXXXX++++++++++++XXXXXY++++++XX+""+HH
LLlLlL .... _rxxxxxxxooeexxxxxx II II "II"I'XXXXXX_++++XX++++++HH
LLLL .... _ _ Xxvxxnxooooxxxx+++' I I I I '"
"XXXXXXXX++_XXXX++++++++
Ll .... ++++++++XXXxYXXXOOOOXYXX .... , I I " " " " '++XXXXXX-XXXX++++-HH
I , , 'XXXXOOXXXX............... • ·.+++++++++XXXXXX++++XYXX·+....,....,.~ ... HH
•• ' ·-..............+XXXXXXXXXX++++++· • ++H-++.... XXX XXXXX .........XXXX ............+,>+ .... HHHH
, ......................._ x x x x x x x X++++++' • +<+H:++'" XXXXXXXX++++++ X X_ _ ++++++++HH_
" " " " III 'XXXXXXXX++++++' '_++++XXXXXXXX++++XXXX_HHHHHH""
••• ' - r x x x - ' '++++++++_XXXXXXXX++++XXXXXX++++++++HIHlHHH ••••
~++++++++++'" '++++++++XXXXXXXX++++XXXXXX III I I I I t 1111 . . . . . . . . t II
I I I I I I I J I I I I I I I I I I ' I , I++++++++XXXX XXX X XX ..... YXXX&e++++++++++++ .. " .. "" ...... ........
++ I I I II I I I I I I I I 1" •• ++++++XXXXXXXXXXXXXXXXGe&OXX++++++++ .. " ............... .....
...++++++++++' ' •••• -++++XXX xx XXXXXX xx x x XOOOOXX ...... XX++++ •••• LLLL •••• ++++
+++++.........++ •••••• ++-++++XXXYX XXXXYXXY xx XOOOOGG++++++++ •••• lLLL •••• ++++++
++~. 0 . . . . . . ' ~++++XXXXXXXXy'xxxxx&eeeeaeexX++++++ ...... LL ......... t.++++++o
_
•••• LL •• ++++XXXXXXXXXXXXXX~OOXX++++++ •• llLL •••••• • '+++++-<-XX
.... ' "'1'" ,
Fig.IO Land slide frequency
Geolog
distribution
distribution
Fig.IO and fig.ll show the graphical
of basic map
data like in fig. 6 and 7. These are called the computer mapping
which can be used for the total evaluation, the others are vally
density map,vegitation and soil map. The evaluations mentioned
in 4-3,are analized by combining the basic map data using computer. The basic map data are important for the integrated environmental evaluation to dicide the weight value.
The followings are the graphical distribution of the basic
map data that were used for weighing of evaluation.
-Vegetation Remarks01
"-<> 02
.. ···.04
""... A05
A - d 06
Coniferous Forest
Planted Forest
Decidious Broad Leaved Forest
Mixed forest
Alpine plant
IJ-Q 07 Grassland
08 Treeless land & Bareland
0- •••011 Sttlement
.-.12 Miscellaneous
10-41
h
-Land Slide
Number Remarks--
o
••• '
0-0
400
I
2
3
4
Q-(j
5
..····.6-10
J(--.l(
<1_
300
"
0
;;..--:
~
0
150
z
<Ii
;::
...c::
U')
<Ii
100
::2
100
50
,.....~~ ..... )o-.Lt\jt\:lNt\:IN
WU1-..:)(J:> ..... WU1-..:)<O .... WU1-..:)(J:>
I
00000000000000
00000000000000
I
I
I
I
I
I
I
I
I
I
,
I
I
I
~""""""""'''''''NNNl\,jN
WU1-..:)(J:> ..... WU1-..:)(J:> .... WU1-..:)(J:>
00000000000000
00000000000000
Altitude(m)
Fig.12 Relationship of altitude
and vegetation specimen
Fig.13 Relationship of slope
and landslide occurrence
Fig.25 Altitude vegetation
Fig. 26 Land slide-slope
600
500
400
300
200
-Geology Remarks0--01 Upper Turbidite
....... 2 Upper Shale & Sand Stone
n - { J 3 Andesitic Tuffbrettia
11---44 Middle Shale & Sand Stone
x-x 5 Lower Turbidite
: : ; 6 ~ower Shale & Sand stone
8 Lowest Shale
0
Z
..c:
U')
- Vegetation Remarks-
150
\
<Ii
:E
100
50
......... 01
"--<> 02
of-",: 04
,,-.~\ 05
,,_.-Q 06
.... .., 07
0 •• -..., 08
Coniferous Forest
P J anted Forest
Decidi ous Broad Leaved Forest
Mixed Forest
A Ipi fie Plant
Grassland
Treeless land & Bareland
\
~~,-
o1 2
3 4 5 6 7 8 9 10
Land Slide Number
Land Slide Number
F~g
Relationship of ve~etation
.. 14 Relationship of geology Fig .. 15
species and landsll de
species and landslide
VII ... 468
5. Environmental
of
As explained
the relationship of
prepared
article, mesh maps and
of natural
and
5
4
:)
2
40---70
30----40
70<
30>
6
8
1
4, 5
8, 6
7
Weight
Slope
C%)
Vegetation
Geology
Fil .. 1 6
1
1
0
2, 3, 7
9 --12
5
4
Sup erPosi'
t10 n of evalua't10n of dange r probabl'Iity by land slIde
Slope grade
Landslide frequency
Number of mesh
Landslide outbreak ",."Ih"hilitu
*
Landslide outbreak probability = Landslide frequency/number of mesh
F
.. 17 Landslide frequency & landslide outbreak probability
Geology grade
2
3
4
5
6
7
8
Landslide frequency
Number of mesh
Landslide outbreak probability
.. 18
Landslide frequency & landslide outbreak probability
Vegetation grade
Landslide frequency
Number of mesh
Landslide outbreak probability
Fig .. 19
Landslide frequency & vegetation
In these figures, the evaluation value ( ranks
1 to 5 ) is
regulated by each statistic
distribution data. For example,
deciding the evaluation value of landslide occurrence probabi
,
the cause factors of landslides such as slope,
, vegetation
etc. are surveyed statistically as
sed
the former
es.
Fig .. 21 Evaluation
Fig 2 0
to
Evaluation value sheet of danger probability by land slide
I-:-~::;;;~I
I
4. Fairly High
3 Medium
2 Fairly High
t§:j§
2 Fairly Law
3 Medium
1 Law
4 Fairly Law
D
-n.em'\I·ks~·
5 High
I
I
value sheet of ground productivity
5Law
Fig.20,Fig.2l and Fig.22 show the
result of correlation analysis of
basic unit file shown at article
4-4.
From these data, the four
selected roads, the correlation
values are calculated as shown in
Ftg. 23 and 24. These were calculated for the total length of each
route and total meshes which the
preliminary routes expect to pass.
There if one unit evaluation value
which is closely related to the
cost of construction and a little
different from the total evaluation value.
Fig.22
From the final grade of integrated
evaluation, per unit mesh and per one
kilometer, C route is the best followed
by A route. From the evaluation value
sheet of land use probability and forest
protection, the best is C route followed
by D route ..
Evaluation value sheet of vegetation protection
-Remarks1 High
2 Fairly
3 Medium
4 Fairly Law
5 Law
VU ... 470
To clarify the loca1 character to generalize this system
the evaluation value sheet of land use probability and forest
protection were drawn by automatic drafter. These are shown in
Fig.25 and 26. The final route selection from anlysis of computer
data considering the natural environmental conditions was decided
as C route ..
6 .. Conclusion
The pattern classification by computer has played an important role for environmental evaluation of civil engineering projects ad shown in this paper. But there are various problems which
must be solved if this method is to be applicable systematically
through the final ~tage of construction using the multispectral
data.
Since only a fundamental solution for evaluation study by
pattern classidivation for evaluating the effect of civil engineering projects has been given, we must perform more research in order
to find integrated techniques in considering economical and easily
applicable conditions.
Route
A
B
!
....----
Evaluation value of ground
productivity
Evaluation valuf of danger
probaoility by land slide
Simbol
---I
E"I",ti"
Value for
Vegetation
Danger
Forest
Protection
Protection
Probability
A
Total
Fig .. 23
-Remarks..
&
Evaluation value of ground
Evaluation value of danger
by land slide
High
High
(Eva. 1-2) (Eva. 1-2)
High
Law
(Eva. 1-2) (Eva. 3-5)
- - I--'
B
Law
(Eva.3-5)
Law
(Eva. 3-5)
C
0
D
High
(Eva. 1-2)'
Law
(Eva. 3-5)
q__~_~.,--.2 km
Route
/AIBICID
Evaluation value of ground
productivity
1246122612251246
Fig .. 25
Evaluation value sheet. of foresy protection
Evaluation value of vegetationl 1581 1351 1261 132
protectIOn
Total
Fig .. 24 Evaluation
,
I
404/ 361/ 351 1 373
value of ground productivity
Evaluation value of vegetation protection
Value Evaluation .
Va Iue of
(,round
I
j)a ngfl'
Land Use [) d .. f) I I
Probabil i ty 1'0 uctlVl ty ro la Ii Ili.\
A
H~La;--'
(Eva. 4-5) (Eva. 4-5)
Law
t---_ _-+--_B_-l(Eva.
Law
1-3) (Eva. 4-5)
1-3)
9~,
_, _L_,.2,Jm
Fig .. 26 ;.50
Evalation value sheet of land probability
Acknowledgements : The author is very indebted to Mr .. Kawasaki,
Mr . Ando, PASCO Co. Ltd. and want to thank to Mr. Shimazoe & Mr.
Ando, the former students of Hosei University, Oshima Seminar.
1... 471