geog 4a revision notes 1
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A2 GeographyUnit 4a
Revision Notes
Fieldwork Investigation
&
Geographical Skills
2. Ai!. "ocation#. $ethod%. Risk Assessent. 'ata (resentation
). Interpretation*. +val,ation
-. Averages--. $eas,res o/ 'ispersion
-2. Spearan0s Rank-!. 1hi S,ared
-4. $ann3hitney U
-#. Sapling $ethods-%. $aps with "ocated Sy5ols
-. Flow $aps-). 'esire "ines
-*. 1horopleth $aps2. Isoline $aps
2-. 'ot $aps22. (ie 1harts
2!. Radial 'iagras24. 'ispersion 'iagras
2#. 6riang,lar Graphs2%. 7ite 'iagras
2. "ogarithic Graphs2). GIS
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A
I$(8R6AN1+ 8F 69+8R:;3 Prior knowledge < needed a theory which
we wo,ld ,nderstand /ro prior st,dy in orderthat we co,ld ,nderstand the processes
involved= ake an ed,cated hypothesis to5egin & ake ed,cated concl,sions. 9ad
already st,died >radshaw.
3 Location < needed a theory which we co,ldinvestigate in a sa/e= accessi5le= availa5le
location
3 Risk assessment < soething we co,ldsa/ely test. >radshaw sa/e in ,pper co,rse
3 Equipment < a theory which wo,ld not needsophisticated?e@pensive instr,ents to test
3 Challenge & learning < one which wo,ldchallenge o,r skills & allow ,s to learn new
ones & new processes. >radshaw involvedinvestigating several dierent varia5les
TO INVETI!"TE #O$NTRE"%C"N!E IN "E OLLO$'
PECI(IC"LL) T"T "((ECTIN!#IC"R!E' IN LI!T O(
*R"#"$+ %O#EL (OR#O$NTRE"% C"N!E
Potential questions, iportance o/theory in choice o/ ai? reason /orchoice? iportance o/ location in
choice? relevance o/ a ethod?eval,ation o/ s,ccess in light o/ theai. R+AS8NS F8R 198I1+;
(from mark scheme )
3 -nowledge
3 Theor. < a5ility to test this. "ink withlocation
- Risk assessent
- S,ita5ility & availa5ility o/ location
- Availa5le equipment= time &resources
+BA"UA6I8N;
3 S,ccess o/ sapling method < acc,racyCrelia5ilityC validity < helped reach ai
3 Appropriateness o/ location /or reaching ai
3 Conclusions < relia5ility & validity. Statisticaltest res,lts; n,ll hypothesis accepted < goes
against theor. so ,st ,estion acc,racy &relia5ility. S,ggest iproveents &
developents in order to properly /,lDl ai.
3 I/ contradicts theory < wh.E
3 (ersonal geographical de/elopment steing /ro reaching ai
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"ocat onPotential questions, reasons/or choice? iportance o/ choicein relation to ai? relevance to
theory or ai? why appropriate.
R+AS8NS;
3 "ccessi0ilit. < /ootpath & >3roadnr. "ittle Stretton
3 a1et. < ,pper co,rse shallowest=narrowest= least /ast owing
3 T.pical ,pper co,rse s,ita5le /ortesting >radshaw. 6ypiDed ,pperco,rse= >radshaw 5ased on the
per/ect river. Needed ,pper co,rse to5e te@t5ook e.g. v3shaped valleysides= wo,ld then 5e a5le to test
>radshaw0s theory eectively.
3 Pro2imit. to Deld st,dies centre availa5ility o/ e,ipent
3 "/erage rain/all in Shropshire area3 Not aected 5y human acti/it. <nearest settleent 2k downstrea
3 8wned 5y the National Trust <legal perission
3 a1e terrain < st,dying 8S ap=co,ld see that it was not too steep
I$(8R6AN6 68 1988S+ A "81A6I8N9I19 (R8BI'+' 69+ 18N'I6I8NSF8R US 68 SAF+": & +FF+16IB+":
UN'+R6A7+ AN INB+S6IGA6I8N IN68
>RA'S9A0S 69+8R:
A((R8(RIA6+N+SS IS >AS+' U(8N98 +"" 69+ "81A6I8N +NA>"+'
US 68 1ARR: 8U6 69+ INB+S6IGA6I8NIN68 >RA'S9A0S $8'+"
R+"+BAN1+ 68 69+ 69+8R: 8R AI$ IS$+ASUR+' >: 9+69+R 69+
"81A6I8N (R8BI'+' 69+ 18N'I6I8NSN+1+SSAR: 68 1ARR: 8U6 69+
INB+S6IGA6I8N IN68 >RA'S9A IN
8R'+R 68 FU"FU" 8UR AI$A11URA6+": AN' SAF+":
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9ollow
(ositives
• Accessi5ility; /ootpath & >3road
• National 6r,st land < legalperission
• Nr. Field st,dies centre <
e,ipent & reso,rcese.g. previo,s data
• Upper co,rse < sa/e• 'istance /ro
downstrea village
2k. No h,aninter/erence
• 6ypiDed ,pper co,rse co,ld eectively & relia5lytest >radshaw0s theory as
is 5ased on Hper/ect0 river
Negatives
• 8nly 2k o/ ,pper co,rse< not representative o/whole river which is what>radshaw theorises < nots,ita5le /or theory=
concl,sions narrow• # inaccessi5le d,e tosteep sides & water/all
• 8nly very shallow• 8nly ,sed data /ro one
location < 5roader= oresigniDcant res,lts i/ hadchosen ore points either/,rther downstrea oralong ,pper co,rse o/siilar rivers
• Rocky o,tcrops aected
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$ethodJ
Potential questions, assess ,se/,lness? eval,ate s,ita5ility?eval,ate eectiveness? relevance to ai
(ositives o/ ethod
• Gathered data necessary to reachconcl,sion /or o,r ai & theoryeectively. Belocity distance?tie.'ischarge velocity @ c.s.a relevant to theory
• (rod,ced data which we co,ldeectively & s,ita5ly anip,late toreach concl,sions
• +asy to carry o,t in environent <ini, e,ipent & light tocarry in terrain easy to achieve
ai• +asily repeated /or acc,racy• S,ita5le intervals < eno,gh saple
points to cover river yet did notstretch reso,rces or tie
Negatives o/ ethod
• S,5Kect to h,an error in tiing=eas,ring 5oth # stretch &- intervalsJ < red,ceseectiveness & relevance to ai asinacc,rate so ,nrelia5le
• S,5Kect to nat,ral in,ences e.g.wind= de5ris= s,r/ace /riction <sae eect as a5ove
• $eas,red only s,r/ace velocity <channel velocity ore s,ita5le /orai & theory
•Re,ired 2 people in river < risk
• Unsophisticated= inacc,ratee,ipent < hydroprop? digital owetre ore eective= s,ita5le &relevant as ore acc,rate &relia5le
• 6oo shallow to 5e eective in areas
• G(S ore s,ita5le /or eas,ringinterval distances
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Risk AssessentPotential questions,descri5e & K,sti/y? eval,ate
• Need to ention steps 5e/ore & d,ring; – Pilot stud. < /ailiarise with haLards that ay coe
,p in Deld & prepare. $ake adK,stents to ethods to
red,ce potential risks. – Risk assessment grid 5e/ore 5e/ore so co,ld 5e
aware & prepare?/ailiarise with risks to avoidJ <involved ,s st,dying the 8S ap also 5eneDcial /oro,r awareness o/ the area & haLards within• hat we did to prepare e.g.
– packed spare clothes < in case o/ /all= stop hypertheria
– wore st,rdy /ootwear < red,ce risk o/ trips & slips
– wore waterproo/s < red,ces likelihood o/ hypertheria as stay dry
– Continuous monitoring d,ring e.g. weatherconditions? water levels? teperat,re? h,an risks.
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GraphJPotential questions, eval,ate eectiveness? eval,ate
alternatives? assess ,se/,lness? how did the ai or res,lts
in,ence(ositives o/ ethod• 1lear /isual representation o/
relationship 5etween 2 varia5les• +sp. with distance on @ a@is;
illustrati/e representation o/downstrea change in Ashes9ollow < ,se/,l & eective /ordrawing concl,sions to ai
• 'ata continuous < neededscatter graph
• 6he need to see relationship /orthese 2 varia5les to eet ai
in,enced choice• Allows /or line o1 0est 3t <
co,ld see needed statistical testas line hard to draw
• +ective at co,nicating ainin/o necessary to reach
conclusion /or ai• "nomalies easily identiDa5le 3
Negatives o/ ethod
• 1o,ld only copare the 4/aria0les
• Not statisticall. /eri1.ing <ay see correlation= 5,t needstatistical test to conDr
• For 5etter eectiveness= co,ld 5elocated to give preciseconcl,sions /or ai
• 1o,ld have copared 2 varia5leswith another e.g.depth?width?velocity on a
triangular graph
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RankPotential questions, how & why ,se/,l /or geog
,nderstanding? appropriateness /or data & ai? K,sti/y ,se
Appropriate;• Uses 56786 data sets
• 9ad 4 /aria0les which we wanted to statistically veri/y acorrelation /or
• Continuous data with a relationship
• 9elped to achie/e our aim; assess relationship 5etweendischarge & distance statistically
• Fact that it con3rmed null h.pothesis helped to de/elopgeog ,nderstanding as then had to ret,rn to data?aps?previo,sdata?data /ro other rivers to ,nderstand why we achieved thisres,lt t,rned o,t to 5e rocky o,tcrops < helped /,rther,nderstanding o/ e@ternal in,ences on river processes
• 9usti3a0le; - data sets= contin,o,s data= 2 correspondingvaria5les= gave ,s the res,lts needed to concl,de o,r
investigation & develop o,r concl,sions to ,nderstand why
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val,ationPotential questions, eval,ate s,ccess?,se/,lness /or geog ,nderstanding?eval,ate in light o/ its ai & theory?
investigation developent?,nderstanding theory? ,se o/ secondarydata to develop concl,sions? ,se/,lnesso/ concl,sion & iplicationsS,ccess;
• a1el. reached the ai o/ o,r investigation
• hile res,lts were ,ne@pected= co,ld e@plain
why ,sing secondar. data e.g. 8S aps &previo,s data
• 9elped to de/elop our geogunderstanding o/ river processes &e@ternal /actors e.g. rocky o,tcrops= whichaect the; now ,nderstand 5etter theprocesses aecting discharge= th,s have0etter understanding o1 geog theor.
• Location success1ul < sa/e= easy toinvestigate & access
• Res,lts ay 5e use1ul /or; the local
a,thority e.g. co,ncil in town planning i/want to e@pand "ittle StrettonC /arers to
Negatives & Iproveents;
• Onl. 4km o1 uppercourse; not representativeo/ whole river= does notparallel *radshaw as he
covered whole long3proDle
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= =$odePotential questions, ,se/,lness
/or certain data? appropriateness/or data sets? 5eneDts o/ ,se
$ean;
• 6he average o/ all val,es
6akes into acco,nt all data
val,es
Use/,l in akingeas,reents ore acc,rateas can take ean o/ repeats
• +asily distorted 5y very large?very sall val,es & anoalies
$edian;
• 6he iddle val,e
Bery 5ig & very sall val,es donot aect it < less aected 5y
anoalies than the ean Used in $ann3hitney U
statistical test
• 1an take a long tie to calc,late
• 'oes not acco,nt /or whole
spread o/ data• I/ gap is large 5etween soe
val,es e.g. * & 4#J 5,t sall5etween others e.g. - &!J= theacc,racy o/ the edian can 5e
skewed
$ode;
• 6he ost coon
1an also 5e ,sed with non3
n,erical data• 6here can 5e ore than -
• 6here ay not 5e a ode atall
•
'oes not acc,rately representdata or its s read
/ i i
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$eas,res o/ 'ispersionPotential questions,appropriateness o/ inter,artilerange & standard deviation /or
certain data? ,se/,lness o/ 5oth
Inter,artile Range;
• #i;erence 0etween
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Advantages
• Assesses statistical relationship5etween 2 varia5les.
•Can con3rm?re@ect nullh.pothesis < draw concl,sions &help geog ,nderstanding as= i/accept n,ll= ,st investigate/,rther to Dnd o,t why.
• Used alongside a scatter graph /orvis,al representation < SR11 gives
n,erical val,e to strength &direction o/ correlation.
• Indicates statistical signiDcance o/a res,lt < r,les whether hasocc,rred 5y chance when ,sedwith ta5le o/ critical val,es soeval,ates an investigation
• Gives o5Kective data•
'isadvantages
• 'oes not show i/ there is a ca,sallink
• 6oo any tied ranks aect validityo/ test• S,5Kect to h,an error.
eQcientPotential questions, appropriateness /or certain data? ,se/,lness?
eval,ate ,se in a certain investigation
Appropriate /or data with -3! val,es with 2 varia5les which are 5elievedto 5e related.
For,late a n,ll hypothesis individ,ally rank val,es o/ each varia5le Dnd the dierence 5etween the 2 s,are the dierences s, the
val,es inp,t into the /or,la
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$ hit U
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$ann3hitney UPotential questions, coent on the res,lts? assess the ,se/,lness or
appropriateness /or a certain investigation• Used to show i/ there is a statistical dierence 5etween 2 sets o/
data e.g. there is no dierence 5etween the siLe o/ rocks in,pper co,rse & downstrea sites
• "ssesses i1 the di;erence 0etween 4 data sets occurred0. chance
• 'oes not e@plain why there is a dierence
• I/ yo, Dnd that the dierence co,ld have occ,rred 5y chance= itay ean that the saple siLe was too sall or that there
really is no statistically signiDcant dierence(rocess;
• 'evise a n,ll hypothesis e.g. there is no dierence 5etween the siLes o/ rock
,pstrea & downstrea• Rank all the val,es across 5oth sets one rank < not like Spearan0s rank
where each varia5le is given a dierent rankJ
• 6otal the ranks 5eneath each col,n
• 1alc,late U val,es /or 5oth ,sing the /or,la
• Use the sallest res,lt to Dnd the critical val,e /ro the critical val,es ta5le
• I/ it is lower than the critical val,e= n,ll hypothesis is reKected
S li $ th d
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Sapling $ethodsPotential questions, whichsapling ethod is ost appropriateor s,ita5le? ,se/,lness o/ saplingethods? eval,ate ,se o/ this
sapling ethod
Rando Sapling;
+ach ite in parent pop,lation hase,al chance o/ selection < avoids
5ias• Allocate each val,e a n,5er
,se rando n,5erta5le?cop,ter generator to select
saples
• Rando n,5ers can 5e ,sed tochoose a sapleM
- Fro a list e.g. electoral rolls < willalways achieve a ,sa5le val,e
- >y point sapling /ro a ap e.g.grid re/erences < ay lead to
selection o/ epty sites- >y line sapling < drawing a line
across a ap 5etween rando co3ordinates & choosing rando
points along it < this ay lead toselection o/ epty areas e.g.
Delds?roads so not the 5est
Systeatic;
Saves tie copared to rando
,st as eective at choosing ,n5iaseddata
• $ay lead to leaving o,t areas whichay 5e signiDcant to investigation
e.g. i/ going in - intervals 1an 5e ore acc,rate than rando <
avoids possi5ility o/ rando saplingselecting too any o/ the sae sites
$ay 5e a5le to avoid epty sitesStratiDed;
Use when have gro,ps o/ a known siLewithin the parent pop,lation e.g. no.Bictorian= 2th cent,ry & 2-st cent,ry
ho,ses in a town
Saple selected so each gro,p ise,ally & /airly represented
+ns,res /air representation
$ ith " t d S 5 l
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$aps with "ocated Sy5olsPotential questions, advantages & disadvantages? eval,ate
,se o/ this presentational techni,e? ,se/,lness?appropriateness? s,ita5ility
Potential use, siLe o/ de5ris along long proDle? environental,ality s,rveys(ositives
• (roportional 5ars easier todraw & ,nderstand than
circles. 1ircles oreeQcient & neater i/ thereis a large range
• 1lear representation o/located data < eans
ore when located < orein/o
• 1oparisons easily ade5etween areas
• Spatial patterns in
distri5,tion shown
Negatives
• 'o not show spread o/distri5,tion < need
choropleth?isoline• 1an o5sc,re parts o/ ap?
get too crowded• $ay not 5e clear as to
precise location
• 6oo any on one ap hard to interpret
• 'anger o/ erelycoparing graphs & notlooking at characteristics
o/ areas to e@plain reasons
F $
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F ow $aps
Strengths
•Strong vis,al ipression o/ 5othvol,e o/ oveent & direction
eaknesses
• (arts o/ the ap ay 5eo5sc,red?crowded diQc,lt to
interpret
Potential questions, eval,ate ,se/,lness= s,ita5ility=eectiveness or appropriateness o/ this techni,e
Potential use, igration /ro dierent +U co,ntries? trade links
5etween co,ntries
' i "i
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'esire "inesPotential questions, eval,ate ,se/,lness orappropriateness o/ this techni,e? eectiveness? s,ita5ility
Potential use, areas /ro which people travel to ,se aservice e.g. s,perarket? oveent o/ +U igration
Strengths
• Bis,al ipression o/ oveent /ro areas to a
point• +asy to interpret• $ay present any pieces o/ data /or dierent
destinations < any varia5les so very ,se/,l
eaknesses• 6oo any lines con/,sing• (roportional thickness does not show act,al data• 'o not show ro,te?ca,ses o/ oveent
• Generalise the oveent
t $
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orop et $apsPotential questions, eval,ate the eectiveness= appropriateness=s,ita5ility or ,se/,lness o/ this techni,e
Potential uses, votes e.g. presidential election? GN( per co,ntry?
levels o/ e@tree poverty per co,ntry or region o/ a co,ntry(ositives
• Bis,al representation o/data
•1an easily identi/ypatterns & cl,sters
• Anoalies can 5eidentiDed i/ cells are anade,ate siLe
•1an show relationships i/placed on top o/ another
• 1an 5e co5ined withlocated?proportionalgraphs to show ore data
•Gro,pings are e@i5le toaccoodate data spread
Negatives
• Iprecise < larger cells lack o/ precisionC too
any sall cells hard tointerpret• A5r,pt changes < sharp
delineation < no gradientshown
•I/ ,sing raw data= shadingay 5e in,enced 5y siLeo/ area?pop,lation within
• 1an hide anoalies within• 8ne varia5le only•
Ine@act < not the act,aldata
Iso ne $aps
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Iso ne $apsPotential questions, eval,ate eectiveness= appropriateness= s,ita5ility or
,se/,lness o/ this techni,e
Potential use, teperat,re? atospheric press,re? gradient e.g. conto,r lines
oin points o/ the sae val,e to show gradient
Strengths
•Show ore grad,alchange thanchoropleths < avoida5r,pt change
• 1an clearly see
5o,ndaries• Show gradients
eaknesses
•Uns,ita5le /or showingdiscontin,o,s data
• Shading ay iplye,al val,e 5etweenlines
• I/ drawing interpolatedlines at e,alintervals e.g. -=-#= 2J= ay 5e
/orced to draw5etween lines
'ot $aps
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'ot $apsPotential questions, eval,ate ,se/,lness= eectiveness=
s,ita5ility or appropriateness o/ this techni,e
Potential uses, pop,lation o/ a city?co,ntry?region
Strengths
• Show spatialdistri5,tion ,sing dots
o/ e,al siLes• (recise• Show density• 1an show change=
ows & cl,stering• As located according
to distri5,tion= notevenly= can seeanoalies
• $ore realistic than
eaknesses
• 8nly ,se raw data• 'iQc,lt to co,nt large
n,5ers < can res,ltin s,dge whichshows no variation
• Needs a lot o/ in/o• 6edio,s to constr,ct• 1an0t show part
Dg,res• 1an 5e hard to plot i/
location is not D@ede.g. pop,lation o/
( e arts
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( e artsPotential questions, eval,ate s,ita5ility= eectiveness=
appropriateness= ,se/,lness o/ this techni,e
Potential use, ,se o/ services in a town? Page contri5,tion o/
dierent ind,stries to econoy
Strengths
• 1lear vis,alrepresentation o/data
• Shows Page totalsso can easilycopare
• 1ircle siLe can also5e adeproportional to total,antity to copare
eaknesses
• $ay not shown,erical data
• 1an get crowdedwith too anydivisions
• 1atagoric data only
Radial 'iagras
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Radial 'iagrasPotential questions, eval,ate ,se/,lness= appropriateness= s,ita5ility o/
this techni,e
Potential use, environental ,ality s,rvey i/ ,sing as a radial 5ar chart
to copareJ? orientation o/ cir,es? ann,al teperat,re cycle$ay show in/o like a 5ar chart
$ay show orientation < e.g. like a copass
$ay show contin,o,s cycles < e.g. ann,al teperat,re cycle
Strengths
• 1an show direction=orientation= distanceand contin,o,s cycles
• Bis,al representationo/ data
eaknesses
• 1an 5e diQc,lt to read• S,ita5le /or only
certain data i.e. thatwhich has directiona5o,t a point or whichinvolves a cycle
• $ay only show general
trends= not very
6r ang, ar rap s
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6r ang, ar rap sPotential questions, eval,ates,ita5ility= eectiveness= ,se/,lness=appropriateness o/ this techni,e
Potential use, eployent str,ct,resdivided into tertiary= secondary &priary
Strengths
• Bis,al representation o/relationship 5etween !varia5les
•Pages are plotted <especially easy tocopare & contrast
• 'isplay relatively largeao,nt o/ data
• 1an see cl,stering
eaknesses
• Raw data ,st 5e t,rnedinto Pages
• Not any investigations
/eat,re ! varia5les• 1an 5e diQc,lt to
interpret= esp. i/ a lot o/data is plotted
' spers on ' agras
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' spers on ' agrasPotential questions, eval,ate s,ita5ility= appropriateness=
,se/,lness or eectiveness o/ this techni,e
Potential use, discharge along the long proDle o/ a river
Strengths
• Bis,al representation o/spread & range. 1anidenti/y cl,stering
• (rel,de to statistical testse.g standard deviation
• 1an plot ean= edian=ode= inter,artile range toanip,late data & showspread a5o,t theseaverages
•+na5les coparison o/spread o/ data /ro
eaknesses
• :o, can0t see relationshipsor draw concl,sions as doesnot show correlation like ascatter graph
7 te ' agras
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7 te ' agrasPotential questions, eval,ate eectiveness= appropriateness=
s,ita5ility or ,se/,lness o/ this techni,e
Potential use, distri5,tion o/ plant species along a transect o/
a sand d,ne Show presence?a5sence o/ species along a transect
6hickness shows no.?Page o/ each species at a point
6hickness 5alanced e,ally 5elow & a5ove a line
Strengths
• Raw data or Pages• Bis,al representation o/
change & progression
along a transect• 1an identi/y Lones• 1an draw concl,sions /ro
vis,al distri5,tion• 'raw correlations < soe
ay show ca,salrelationships
eaknesses
• "iited to transect lines• 8nly s,ita5le /or very
speciDc data with speciDc
p,rpose• 6oo any kites diQc,ltto read & interpret
"ogarithic Graphs
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"ogarithic GraphsPotential questions, eval,ateeectiveness= s,ita5ility= ,se/,lnessor appropriateness o/ this techni,e
Potential use, pop,lation graphs
Used with very large ranges orwhen an arithetic graphwo,ld prod,ce a para5olicrelationship rather than a
straight lineStrengths
• "ots o/ data? data with a largerange can 5e plotted
• Saller val,es are given greaterpriority d,e to nat,re o/ logarithicscale -3-
• 1an 5e sei3logarithic or 5otha@es can 5e logarithic
• Baria5les o/ very dierent siLes can5e plotted on the sae graph e.g.pop,lation & tie
• Show progression & can drawcoparisons /ro dierent so,rcese.g. pop,lation o/ dierentcontinents
• 1an show previo,sly ,nseen
patterns e.g. log graphs showincrease in world pop,lation to 5e
eaknesses
• 1annot start /ro • $ay ake soe relationships
appear dierent as para5olicc,rves on a noral graph 5ecoestraight on log graphs
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<Systes
Potential questions, advantages & disadvantages? ,ses o/?,se/,lness? eectiveness
Potential uses, ,sed /or p,5lic services e.g. re/,se collection=a5,lance services= s,perarket delivery services 3 show data
a5o,t location & area characteristics. !OO!LE E"RT B 0este2ample
$erge cartography= statistical analysis= and data5ase technology.
Strengths
• A5ility to show lots o/in/o= layered= on one
ap• In/o can 5e linkedtogether to identi/yspatial patterns?s,pport analysis o/
data
eaknesses
• Re,ire e@pensiveso/tware
•1oplicated < ayre,ire training increating & ,se
• 6oo any layers diQc,lt to interpret
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