Geographic Information Systems
Geographic Information Systems CSS 4200
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Date Created: 09/26/15
088 4200 Geographic Information Systems Lecture 1 Course Objectives and Resources Instructor Background Historical Perspective Conceptual Framework Course Objectives Increase awareness of GIS science and technology Provide opportunities to process analyze and visualize spatial data and information using commerciallyavailable GIS software Generate enthusiasm and interest in using GIS for meeting environmental assessment needs Gain appreciation for the complexities of spatial data manipulation and analysis at varying scales of space and time Instructors Steve DeGIoria Professor of Resource Inventory amp Analysis Department of Crop and Soil Sciences SabineVerena Jauss Graduate Teaching Assistant Graduate Field of Soil and Crop Sciences Adam Ganser Graduate Teaching Assistant Graduate Field of Landscape Architecture Course Resources Textbook Lecture Material Laboratory Facilities Exercises and Problem Sets Internet Instructors Grading and Assignments Laboratory exercises 40 Quizzes 10 Prelim 2 and Final exams 40 Class participation 10 Course Web Page ltwwwcsscorneed ucourses420css4200htmgt Lecture overview Schedule Readings Exercises Lab overview Project Mapping Agroecologica Zones in N YS 1 Soil characteristics Terrain derivatives 2 3 Climate parameters 4 Land useland cover conditions Academic Courses in GIS at Cornell Fall 2008 CRP 5250 Introductory Methods of Planning Analysis CRP 6070 GIS Applications Workshop C88 4200 Geographic Information Systems 088 6600 Remote Sensing Fundamentals also CEE 6100 Spring 2009 CEE 6150 Digital Image Processing CRP 4080 Introduction to Geographic Information Systems GIS also CRP 5080 C88 4110 Environmental Information Science also CEE 4110 C88 4650 Global Positioning System C88 6200 Spatial Modeling and Analysis 088 6210 Applications of SpaceTime Statistics DSOC 3140 Spatial Thinking GIS and Related Methods SBA KCM Other courses not listed for Fall 2008 or Spring 2009 CRP 40805080 Introduction to Geographic Information Systems GIS DSOC 5605600 Analytical Mapping and Spatial Modeling DSOC 7197190 Logistic Regression and Spatial Linear Regression LA 494 GIS for Landscape Architecture NTRES 6700 Spatial Statistics last edited by Keith Jenkins on Aug 08 2008 httpsconfluencecornelleduxIIM BQ Mann Library Workshops httpmannlibcornelleduinstructionworkshops Background Horticulture Field Crops Fruit Production Background Agriculfur al and Nafur al Resource Invenfor y Western Africa New York USA India 197039 198039s 199039s 200039s Geographic Information Systems Understanding the term and process is important A reasonable understanding can come simply from breaking down the acronym Look at the idea of a system as modified by the words information and geographic Concept of GIS System group of connected items and activities that interact for a common purpose output Information representation of attributes or events or objects or using known symbolism and known relationships Information system set of processes executed on data to produce information useful for decisionmaking or advancing knowledge data gt information gt knowledge gtgt Geographic refers to location proximity or spatial distribution appropriately georeferenced pr39ocesses agor39i rhms equa rions var iablespar39ame rer39s DATA GIS ver ifica rion geor39efer39enced da ra layers caibr a rion r39ea riona da rabase vaida rion modeing scenarios simua rion visuaiza rion Tools mm zgam m f Emma sz Ci 531111 Resource Inventory amp Geospatial Analysis Framework 39 and EnVirolImental gt and Environmental lnformatlon NEEdS Framework Data Process Models v Spatial Database Design and Development 1 User Interactions Data Accession Data Queries and Services 4 Encoding and 4 D Transformation Quality Control amp Calibration v Spatial Modeling and Analysis Evaluation and Assessment v Data Visualization and Documentation F v v v Information Transfer Environmentai Technology amp Exchange Poiicy 8 Decision Evaluation and Support Adoption v Physical Land Conditions in Schuyler County New York 1943 J and 39 MW 11 mm I mu m 11 WW W SEaxexmaqe 11 mm mm W 7 o 7 UPdaAeVa ues A Example Land Suitability Analysis Ag Census Digital NASS Elevation Model Land suitability rules and Current Land 30quot type yied Usel Land Cover drainage predictions fertility etc Maps amp tables of area suitable for each land use Pommal ReedCanary mama or 250 I 251 m w 7 sn Experiential Learning eg Global Positioning System for Resource Inventory 1w Mummers a 15 5a ma Mummers Pvedicted Arsenic Concanrrarron rgIL n 57 um Mummers Wquot f wx In Prediction Standard Errors Mean Arsenic Concentration ngL 7 n Inn xrrrrmrm Productlon Di Groundwaurr Irrigated Bore Rlca tonnes 1600 um V High ighled Upazila Have Mean Groundwater Arsenic Concenlralions IL Groundwaler Irrigated Born Rice Production ramas 1mm Unrehame Eshmanes rzxcrmeur Geographic Information Science Generally refers to the research issues and gaps in knowledge related to generating analyzing manipulating and using geographic information Provide theoretical and organizational framework or context for applying the technology Developing new knowledge about geographic information and its principles To avoid confusion generally termed GlScience GlScience therefore not a substitute for GIS The Physical World Define ProTocols 1 Decide and Ac l Collect and Edh Spa rial Darla E1 Analyze A Summary Course Resources GIS Background Reading Assignment Laboratory Sessions 1 September T E R in the Lower Mekong River Basin i 3 c I E R Populations exposed to Flood RISK 1 Fewmhan mama 39 vouaz mm zoouwoousu 4000 mall 72 r v No linkquoty iclivl pedlimzian i332 Numberof children per pediatrician ESRI GIScom Influenza spread Harvard Magazine Pre 911 we lransrwsswn Post 911 Internet f aai a 1 39 ammu wommuu m m dummmuu r I palms lt3 mm hupd M 255 Munuc pm m I re 39339 mgammnn Remote Sensing Technology NASA F0795quot Projec In eractive MaP FORCST Project h 17 mdcdpmwcl Mhmmw mumM mm a YHHQRUHOKL CVWWQW HHUHIVYMEA HR HHN51mgIKA Hg v Emu Mme mm StandAlone Networked Networked GIS GIS GIS Local Global Arthur J Lembo Jr Spatial Analysis and Manipulation The distinguishing characteristic of GIS Ideas have long been recognized and considered but there were many practical limitations Spatial is the novel part of the term Has to do with location usually on earth The idea of where Spatial analysis is a routine process for us Spatial Analysisove ay Network Analysis Cartographic Output Visualization Arthur J Lembo Jr Modeling Fundamental Principles of Spatial Analysis L Caldwell DEANS my Location in space 9 m mm C 393 Spatial elements or objects fiat WWW C al Spatial relationships such as nquot j Number 7 L ses Bragg Distance proximity orientation Arrangement pattern distribution Association correlation Go beyond analysis to integration synthesis Geographic Information is Increasingly Available and lnterrelated General education Higher education Business Internal organization Special interest groups National agencies Local government agencies The public GIS History H0W3rd FiSheri Ian McHarg Roger Tomlinson Jack Dangermond SYMAP Design With Canandian ESRI founded Harvard Lab Started Nature Geographic Information System Implemented in 1971 Arthur J Lembo Jr GIS History Harvard Laboratory GIS Functions ODYSSEY POLYVRT CALFORM Topology Polygon Overlay Landsat Bureau of Census DIME file GIS Education Harvard Oneonta Buffalo Zurich GIS Pioneers Dana Tomlin Nick Chrisman Tom Peuker Scott Morehouse Denis White Arthur J Lembo Jr Vector GIS ARCl NFO Strings Maplnfo AutoCAD GIS History Computational Global Geometry Positioning Rubbersheeting System Polygon Overlay SPOT Edge Matching Network Analysis Arthur J Lembo Jr GIS History Workstation Migration to PC Closed to Open GIS ArcView Integration of MS Tools ARCINFO Maplnfo 00 Programming System 9 Microstation ActiveX GDS AutoDesk Adoption within IT MGE GeoVision Arthur J Lembo Jr GIS History Data Warehousing Internet Field Data Collection Wireless Technology Smart Objects GIS Evolution Societal GIS Enterprise GIS Data AccessData Publishing NetworkCooperation Projects Data Management CartographyAnalysis Arthur J Lembo Jr What is a GIS A system for capturing storing checking manipulating analysing and displaying data which are spatially referenced to the earth DOE 1987 Any manual or computerbased set of procedures used to store and manipulate geographically referenced data Aronoff 1989 A database system in which most of the data are spatially indexed and upon which a set of procedures operated in order to answer queries about spatial entities in the database Smith 1987 A system with advanced geomodeling capabilities Koshkariov et al 1986 Are these definitions helpful Some More Ideas Distinction ofGlS Anatomical approach are the following components required Computer resources hardware software network Data People Procedures Disciplinary knowled e amp experience Another approach IS 0 list common features leaVIng room for unique approaches Contributing disciplines Why is GIS Important Becoming nearly ubiquitous Environmental analysis Engineering design Business geographics Social services Government Some examples from ESRI book Getting Started with GIS The S in GIS System or Science Overtime the availability understanding and applications of geographic information systems have matured The widespread use of this information systems technology has helped to converge numerous interrelated disciplines Many issues and gaps in knowledge also emerged Consequently a new term has emerged geographic information science Conclusions GIS has come a long way in a short time GIS can be useful in almost any field You will probably use it It is important to understand it 088 4200 Geographic Information Systems Lecture 12 Continuous Fields Surface Analysis Bolstad Chap 11 What is a Surface Continuous entity Infinite number of points Must use a subset of points in practice Interpolate at least to some level Often synonymous with elevation terrain surface Base Data Raster Most obvious choice Representing spatially varying continuous entities abrupt gradual Vector Triangular Irregular Network TIN Continuous values at vertices of triangles Surface Operations Profile Terrain derivatives Slope gradient Slope azimuth deg aspect dir Slope curvature Terrain ruggedness surface roughness Topographic indices Surface water flow watersheds Flow direction Flow accumulation Line of sight viewshed Illumination shaded relief CutFill volume Flythroughs drapes Bilinear Interpolation distance weighted average Wha r is the value of Zn 2b z z3 zwdI 2b 14 46 1429 326 c 5 Zu Zz rth Z I 4 65029 516 c 5 ig431 1 Bolstad 2W zb 2 zbwz zour 326 516 3 2622 41 T 5 Measure change along linear features Evaluating the nature and quality of transmission corridors Assessing landscape transitions t y see the corresponding i r I i h h I h l t I mouse over the 616 Slope Gradient Change in elevation rise over the run Calculated in percent or degrees Generally calculated using a 3x3 moving window 8 neighboring cell elevations subtracted from center cell and divided by distance Use average or highest Slope Gradient Other methods of calculation 4 neighboring cells rook s case 3rel order finite difference Percent to degrees tan391 slope100 slope gradient in degrees radians to degrees conversion r39Ise Slope as per39cen r run 100 AB 100 Slope as degrees l Tan391AB B To conver39T from per39cen r slope To degr39ees apply formula eg 3 how many degrees AB 100 3 Then AB 3100 003 Tan391003 172 degrees for39 Z0 dZdx 49 4020 045 dZdy 45 4820 o15 slope aTan 0452 015392 105 253 llels eleva rion values kernel for dZdx kernel for dZdy Z2 ZS 42 45 4o 44 Z7 0 dZdx Z5 Z4 2c dZdy Z2 z12c dZdx 49 4020 045 dZdy 45 4820 015l slope c1 rc1n045 2O152O395 253 3rd order fini re difference eleva rion values kernel for dZdx kernel for dZdy z1 Z2 Z3 Z1 Z2 23 42 45 1 i Lt 4o 44 2 26 Z7 1 2 dZdx dZdx Zs39 Z1 2Z 539 Z4ZS39 Z139 26 2Zz 39 Z7Zs 39 Z38C dZdx dzdy 4742 4752 2 49 40 2 45 48 52 44 80 42 44 80 039 O16 2 2 05 o slope amno39 O16 229 rmi um 1mg Kg 63mg UESAUQNP Hm lzema l 353 mmr mg ammo ma m wa tic lm mm ff mimg s 1mr m y xqmag gdl m mam 3331 maimg m m 4 at azimuth 7 angle t E gammammn gt i310 xgismmmemmm r I Folded Aspect Used in calculating heat load Aspect is folded such that it runs from O to 180 and back down Highest value set to the aspect that receives the most solar energy Northern hemisphere example FA 180 aspect 45 180 Southwest 180 Northeast 0 Slope Curvature Z1 22 23 Z4 20 Z5 26 z7 ZB ngh 2 3 upwardly cumex Law 27 upwert y concave DZ4Z52Zo62 EZZZ72ZOCZ Fzszlz 284c2 925 z42c HZZZ7ZC plan curva rure 2DH2E62FGH 52 H2 profile curvufure 2 D52 EH2 FGH 62 H2 Runoff and Watersheds Runoff measures downhill flow of water Watershed the area of land that accumulates and transmits precipitation input to a water body In theory any water that falls in a given watershed will end up in that watershed s water body or evaporated or transpired Watersheds Fill depressions sinks Calculate flow direction for each cell Calculate flow accumulation Delineate watershed Flow steepest drop from cell to 8 neighbors lfoell is lowerthan all neighbors flow is 335333 defined into cell lfdecent is the sameto 7 all neighbors enlarge neighborhood 5 ow direcnon Elm alinu Flow Direction Flow Accumula ion Flow accumulation can be used to create a stream network The accumulated ow is based I upon the number of cells owing into each cell Output cells with a flow accumulation of 0 are local topographic highs Used to identify ridge lines or 39des dials a watershed dIVI Assumes that all precipitation is runoff and there Is no interception eva otranspiration or loss to groun water Flaw accumulall39un High 7505 Due on mimg D a Um mg L 3 Hquot f Mk r r gm J A WE rw rquot x 7 9 A x f z 21 v r or 5 1 N s 11 y 2 ix sz1W h1altci A quotIQ IVIJ1IU WW mm mum gm p u n A r5 39339 Ar rd quot N n 7 57 4 as r 5 531325 1 4 918 4 r szusgwan nmpag grmg fmm uMhM mm mm 1333 a quotfquot 394quot 7 quot 5 JL CWWHM A U Uum imssimm a s31 m l 1 lm E W Qiivsa w fm mm mm Q Wm surface normalri d IrecTIon incidence angle 6 is equal To cos391 cosz coss sinz sins cosao a where z is The solar zeniTh angle Direct Beam Re ectance ao is The solar azimuTh angle s is The surface normal slope angle a is The surface normal azimuTh angle MPH i W mg alti irtu ij W W Q39igmtf iamfgg39hm r kg E ILK Iquot quotvquot 7 quotgt5 9 r w 7E r V agg mg yen w W H FWEQ W mm 0 Wm unn r39cam a 2313 0 Irz o H fear WW 4me m t mmmw WEE am E CSS 4200 Geographic Information Systems Lecture 9 Data types and classification Lab Exercise 4 preview Classifying Features Classification is a means of grouping entities into categories or sets of values with unifying attributes Classification Requirements Relevant does it make sense Comprehensive does it include all the data Repeatable can we recreate it Achievable given technology can we develop it Discrete can we separate the classes Measurement Values All of the data that are used in GIS can be categorized as Nominal Ordinal Interval Ratio Without a proper understanding of the measurement values it is easy to misapply the data to specific GIS processes Bolstad p 31 ArcGIS Desktop Help Measurement Levels Nominal Data STATSGO Soils in the Variables that describe Fmgei Lakeg Reglon feature with no assumption of t or ering Nominal data are described as qualitative and categorical These values are qualities not quantities with no relation to a fixed point or a linear scale Examples include vegetation type city name soil series Measurement Levels Ordinal Data Ordinal data determine position 39 e39 ch place ranking In These measurements do not establish magnitude or relative prop39o ions Examples Soils can be Considered poorly dra39 moderatelywell drained or we39lldrain Elevation can b eclassi e d into zones 0 2 or high 3 Potential Frost Action for the Fin ion srnseo Solis Low MODERM39E men Measurement Levels Interval and Ratio Data Interval and ratio data are useful for both ordering and quantifying differences between categories Interval data do not have n absolute zero starting point as do ratio data Ratio data measure magnitude of entities usually using real floating point numbers They are derived relative to a fixed zero point on a linear scale Examples Area length weight elevation slope gradient depth temperature STATSGO Soils in the F ger Lakes Region quotA Mlmmum Slaps Value 1 3 Data Classification Equal Area Total area of the polygons in each class is the approximately the same Equal Interval Divides the range of attribute values into equal sized categories Natural Breaks Finds groupings and patterns inherent in data Quantile Each class contains the same number of features or values May not be suitable for population counts because some areas have larger populations Standard Deviations Class breaks above and below the mean at intervals of either 14 12 1 2 standard deviations Bolstad p 332339 ArcGIS Desktop Help Equal interval classification 01711 1 171273422 3422 5133 frequency 1000 2000 3000 5000 popula iion frequency 70 Equalarea classification i o 902 i 903 1223 1224 5133 B 6 4 2 o 0 1000 2000 3000 population 5000 frequency Natural breaks classificafion o 1130 1130 2156 2156 5133 1000 2000 population 3000 5000 Discrete v Continuous Data Discrete Data Discrete data or categorical data represent objects These objects usually belong to a class category or group egsoi series land use type political party A categorical object has known and definable boundaries An integer value is normally associated with each cell in a discrete raster dataset Most integer raster datasets can have a table that contains additional attribute information Discrete data are best represented by ordinal or nominal values From ArcGIS Desktop Help Discrete v Continuous Data Continuous Data A continuous raster dataset or surface can be represented by a raster with floatingpoint numerical values referred to as a floatingpoint raster dataset Examples of continuous surfaces are elevation slope aspect slope gradient the radiation levels from a nuclear plant etc Floatingpoint raster datasets usually do not have an attribute table associated with them because most if not all cell values are unique and the nature of continuous data excludes other associated attributes Continuous data are best represented by ratio and interval values From ArcGIS Desktop Help RasterS m Mmmmensmm aways a ce um mm 1 a quot WWMWWMW mm A mm a Magma mWmmsemmmm m r maiauhcn mmmmgvc edanca on precxpmzhon and cummum quotNMWWW RasKevs nave rm mmgmwmam spam you can Us39amung E mmwwwu mu canmmaxe m y mummmmns lmmma s aw Wwvvnmhavkxwfu mmun a mm H n Nymmmmu a mm n he lop Row and mm mamas begm w Hms evs mm nave Nagprumue cm can x mm Mm aquot whona39 almbnls lama wmuh vacu39 s mm are mum cm vmue You mm m cuslnm Mama he mmnme um r m WWW 6mm m mm m mm m mmmmmm 51mm wmmmwmw wmuqemwk m a wmmmmmm wnnmmzm mmwsmmmw xmmmwmmWWW Warm mm mm WWW umwwnm u w W WM 5quot Wm ESP L Modehng Our Wo d 1 0 1 2 3 4 5 Miles 088 4200 Geographic Information Systems Lecture 34 Coordinate Systems Geodesy Datums Projections Basic Definitions Map a representation of reality depicted on a spherical or planar surface showing relative size position and arrangements of various features using a given scale projection and coordinate system Coordinate System set of xyz values defining the location and relationship of spatial data on a spherical geographic geodetic or planar projected Cartesian grid Mapphoto scale ratio of distance on the mapphoto to the corresponding distance on the ground surface Largescale mapphoto smallsurface area depicted surface features depicted in fine detail large ratio eg 112000 scale Smallscale mapphoto large surface area depicted features depicted in coarse detail small ration eg 15000000 scale Azimuth horizontal direction of a line measured clockwise on a reference plane 0360 fonNard back Aspect cardinal direction from reference point Bearing direction of a line measured as an acute angle lt90 from a reference meridian NS expressed in the form N45W Azimuth S15E Azimuth Basic Definitions Ellipsoid mathematical model ofthe shape ofthe Earth that is approximately the shape of a attened sphere formed by rotating an ellipse oblate spheroid and de ned by semimajor axis semiminor axis and flattening factor Spheroid mathematical model of the shape ofthe Earth based on the equation ofa sphere Geoid mathematical model ofthe shape ofthe Earth based on a gravitational equi potential surface used for specifying terrain heights Datum reference surface de ned by an ellipsoidwith spherical coordinates and an origin horizontal and vertical Projection a systematic rendering of locations from the curved Earth surface 3D onto a at surface 2D True area shape distance or direction are compromised Developable surface a geometric shape onto which Earth surface locations are projected eg plane cone cylinder Relevant Scale Equations Scale 1sf Representative Fraction RF unitless ratio sf Scale Factor Map Scale 1sf Map Distance md Corresponding Ground Distance cgd Photo Scale 1sf Photo Distance pd Corresponding Ground Distance cgd Photo Scale 1sf Camera Focal Length f Altitude of Photograph above terrain h Spherical coordinates eqU Y quotquotquotorlgin 0000 A longitude W 8 3 5 nor rh Pole N710 E8401 7 N52039w 0 52 S zu39 w35a 0quot 172039 35quot soufh Po39e 15N 35N 45N 60N 55 105 155 205 255 305 355 405 455 505 555 605 1o 11 12 13 14 UTM Zone MN MW Conrdinafes are Eastings E rela i n and a Norfhing N relative to The Equator 397800 m 4922900 m Cenfral meridian a1 W117 zone is wide Zane boundaries 0 W120D and W1147 Origin N O of the Equator E 0 at 5001000 meters wesf of the central meridian UTM Zone 52 SouTh N 0000000 at me Equarur 0 mm wesf of m 00 m2 Mvm Manama Coordinates are mung E rehm39v central meridian at E129 zonz 4r s 5quot w4d2 an k E1 x w zone boundaries of E126 d 32 2 2 Ellipsoud 1 Yvo 2 1 r2 semiminor axis equa ror r I semimajor axis flah enin PH factor f T 1 pole Vor rhomefr39ic 6 g 0 ifi heigh r H x e mvsol d Zv h gee mg d geoidal height hHN ellipsoidal heighf orfhomefric heigln geoidal heighf Map Projections A Working Manual By jOHN P SNYDER LES GEOLOGICAL SURVEY PROFESSIONAL PAPER 1395 ellipsoid map K Developable j Surface Cylindrical Conic a 2w M 4 kn Cylinder ellipsoid Infersec Ion cemul merldlurl Transversa Mercator Map from quotdevelopedquot cylinder cenfml meridian Lamber39T Conformal Conic Cone elipsoid infarsec rio Map from paralleis quotdevelopedquot cone standard m m m mm mm t MAWquot n M 1 er m mm mm mm v M mm 7mm mm mm an n m w m u w Fm M 1 7mm mmww Cums wwuunn m MalMm pmum m m e Amenu mlluglwud m Vnaw nummmwmwrmemum mm m m mnmw Emma mm mum 5mm 1mmva mm m zr m mm 1 wrm s muwm nukh wmmw W 8 3 5 nor rh Pole N710 E8401 7 N52039w 0 52 S zu39 w35a 0quot 172039 35quot soufh Po39e DD from DMS DD D M O 53600 e g DMS 32 4539 28quot DD 32 4560 283600 32 075 00077778 327577778 DMS from DD D in reger pum M integer of decimal pur r x 60 S 2nd decimal x 60 e9 DD 2493547 D 24 M integer of 093547 x 60 in reger of 561282 2 56 S 2 2nd decimal x 60 01282 60 7692 so DMS is 24 5639 7692quot Gram Clr cle Drs39h39mce arsdzr m poms gruv m 1H m 5mm mam ma my 9 mm geographc m dumm 03 1 Um qreuf c rel dlsmncz from pclm A W pmm B 5 given by the farmum 4 a 05 d z r 2 5n7xmx 7kyg cus74usg swimw a Mm L a 0m s rm an mm m m Sur ng or m Eum mm A Iu s m formu n may m ug d fa mu m mum mm nusad by a prngcw an hgmm m painla m xnmplz mumquot Ursirm and mm ah when using um Zane 2N aardlnmes mun GFBOT circle distance mum nngxlude cf Ursmz um wag unguud vf Mm um 114 215944 37 9231 409551111 36 57361 d 637B 2 srquotsmz 11421e944 109 5511mm ccs37 9E4mmlt3 573m ltm 37 QAasta 573m2 412 906 km Ervd distance UTM Zone 12N coordinam 6nd roommates nf Ursme Umh 217529 84z05572 a Mum um 52523 2 4270405 9 dg Lm 7 x3 m 7 may 217529a r 526239 22 may 437030592 All 300 km 0394 to or u 294 New larg ummg 63732064m Clark1366 63731370m wesa4 Inverse amp Forward dxsmrhon 1 412305 453300 UTM Zone 11N 1 i 9 N relative to The Equator 29 E 397800 m N 4922900 m Cenfral rnnzridian a is 6 wi a Zone boundaries at w120 O N O of the Equator E 0 at 5001000 meters wesf of 39d n the central merl 1a UTM Zone 52 SouTh N 0000000 at me Equarur 0 mm wesf of m 00 m2 Mvm Manama Coordinates are mung E rehm39v central meridian at E129 zonz 4r s 5quot w4d2 an k E1 x w zone boundaries of E126 d 32 PRINCIPAL MENDsz OF THE FEDERAL SYSTEM K 0F RECTANGULAR SURVEYS X 7 y A quotmax h emx 57 7 i 7m 39 r 39 V g 5 V 7 7 v A Shading Showsthe area governed by each r 39 Dnncipalmendwan and base ine L V 39 39 w l m 1 I SECTIONAUZED TOWNSHIP Raw sz mw WE RZE R35 TEN DIAGRAM SHOWING DESKSNATION OF TOWNSHIPS AND RANGES TYPICAL FRACTVDNAL LAND DWISIONS u NW A sec 343151135 5th PM 2 NEVA SW74 Sec 34 T1s RSE am PM 3 SW 5V2 SW A Sec 341157RV3E 6m RM 4 NEVA NW ASE14 Sec 34 Y1SR3E am P M 5 WVz S u SEW Sec34T s H3E6th PM 5v PM 7 57 NEVA SEW Sec 1 35 6 a NEW NEm NEVA Sec 5A T1SFLBE6th PM L QUARTEHED SECTION m 22 Fracxmna ana dlvxs mns in he USPLS and their Iega desmmmns 125o USGS Map Quadrangles 123 124000 scale 76 x 75 1100000 scale 30 x 1 38 1250000 scale 1 x 2 37
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