geog 4a revision notes 1

8/15/2019 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


14/28

$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


15/28

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 $


17/28

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


18/28

'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 $


19/28

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 [email protected]. pop,lation o/

( e arts


22/28

( 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


23/28

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


24/28

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


25/28

' 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


26/28

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


27/28

"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


28/28

<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

geog 4a revision notes 1

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