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Exam 2

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Natural Resource Information Management
Ningning N. Kong
Study Guide
Natural Resources, information management, forestry
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This 232 page Study Guide was uploaded by Sierra on Wednesday March 9, 2016. The Study Guide belongs to FNR 210 at Purdue University taught by Ningning N. Kong in Spring 2016. Since its upload, it has received 67 views. For similar materials see Natural Resource Information Management in Agriculture and Forestry at Purdue University.

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Date Created: 03/09/16
FNR 21000, 2016, Week 1, Lecture 1 Nicole Kong  Assistant Professor, GIS Specialist Purdue University Libraries  Office: HAMP 2215E  496-9474   Office Hours by appointment FNR 21000, 2016, Week 1, Lecture2  Course Introduction  Basic Concept about GIS FNR 21000, 2016, Week 1, Lecture 3  Enable a natural resource professional using data to create information that helps improve the efficiency and quality of resource management.  Why? FNR 21000, 2016, Week 1, Lecture  How?  Course Goals: ◦ Define basic spatial data concepts (GIS), ◦ Create and use spatial and textual databases, ◦ Develop spatial analysis abilities, ◦ Use ArcGIS software to analyze and recommend possible solutions to natural resource problems. FNR 21000, 2016, Week 1, Lecture 5 Name Email Rec/Lab Section Mekala Sundaram T W R Margaret Hutton T W R Tyler Folk T R Ryan Schroeder T W Kimberly Ordonez W FNR 21000, 2016, Week 1, L6cture  Lecture – Monday 10:30-11:20, BRNG 2280  Recitation/Laboratory in PFEN 202 ◦ Tuesday, 2:30 - 3:20, 3:20 - 5:20, ◦ Wednesday, 2:30 - 3:20, 3:20 - 5:20, ◦ Thursday, 2:30 - 3:20, 3:20 - 5:20,  Help Session – Mondays, 5:00 – 6:00 PFEN 202 (starts Jan. 25) FNR 21000, 2016, Week 1, Lectur7  Price, Maribeth. 2013. Mastering ArcGIS. McGraw-Hill Education; 6 edition.  FNR 21000 Class notes, Blackboard  Learning ArcGIS 10, ERSI Virtual Campus Course  It is your responsibility to check each week for readings, activities and other assignments or requirements. FNR 21000, 2016, Week 1, Lecture 8 Items: # Points Total Final exam 1 100 100 10 or more quizzes (only top 10 10 10 100 scores will be used in final grade) Lab Practicum Quizzes 5 10 50 - Final 1 50 50 Laboratory Report 12 30 360 Semester Projects Part 1 – Database creation and 1 50 50 population Part 2 – Spatial Analysis 1 50 50 Class/Rec/Lab participation 100 100 TOTAL 860 FNR 21000, 2016, Week 1, Lecture 9 Grade Point Range GPA Value* A+ 860 – 834 4.0 A >834 – 800 4.0 A- >800 – 774 3.7 B+ >774 – 748 3.3 B >748 – 714 3.0 B- >714 – 688 2.7 C+ >688 – 662 2.3 C >662 – 628 2.0 C- >628 – 602 1.7 D+ >602 – 576 1.3 D >576 – 542 1.0 D- >542 – 516 0.7 F >516 0.0 * GPA values are set by University Policy FNR 21000, 2016, Week 1, Lecture 10  10 or more quizzes in lecture/recitation  10 points each, most will be online in Blackboard Learn.  5 lab quizzes will be included in grade  In general, you will not be allowed to make up quizzes.  First quiz will start from the second week. FNR 21000, 2016, Week 1, Lecture 11  All course information will be available on blackboard.  Use blackboard to submit lab assignment reports and lab quizzes. FNR 21000, 2016, Week 1, Lecture 12  Class Absences  Students with Accomodation (See me)  Classroom etiquette  Scholastic Dishonesty  Campus Emergency policy  Course Syllabus (Blackboard) ◦ FNR 21000, 2016, Week 1, Lecture13 FNR 21000, 2016, Week 1, Lecture 14  GIS – Geographic Information Systems A system designed to collect, manipulate, analyze, and output spatial information. Two important components – What and Where A third component – When FNR 21000, 2016, Week 1, Lecture15  When we refer to spatial information, we simply mean that the information is linked to a specific location.  By our definition, GIS can be carried out by hand, using only paper, pencil, and a ruler. FNR 21000, 2016, Week 1, Lecture 16  For practical purposes, we define GIS as: A computer-based system to aid in the collection, maintenance, storage, analysis, output, and distribution of spatial data and information.  GIS - an abstraction of reality used to communicate information and relationships… FNR 21000, 2016, Week 1, Lecture 17  Tools: Computer software/hardware  Data: with spatial/location component  Trained personnel: develop the database and carry out the data processing FNR 21000, 2016, Week 1, Lectur18  Resource depletion/degradation  Increased problem complexity  Demands by the body politics  Improved capabilities FNR 21000, 2016, Week 1, Lecture19 From Observations and Process Knowledge to Prediction andAction FNR 21000, 2016, Week 1, Lecture 20  Be aware #1: Computing intensive!  Be aware #2: Don’t need to be panic!  ArcGIS is a Windows-based desktop software developed by ESRI. ◦ ArcGIS 10.2.2 and extensions, ESRI, Inc.,  Laboratory exercises and data will be made available from the Blackboard, a ‘mapped drive’ or other websites. FNR 21000, 2016, Week 1, Lecture 21  Primary instructional lab: PFEN 202.  Other ITAP computer labs, such as HIKS 959, HAMP 3144, NLSN 1195 and MTHW 116.  The Student Edition ArcGIS 10.2 software access codes. This is a full ArcGIS software package that you may install on your computer (PC). The software will work for one year from the date of registration. FNR 21000, 2016, Week 1, Lecture 22  PFEN 202 ◦ PFEN 202 will usually be open by 7:30 am and closed at 10:30 pm M-F. ◦ PFEN 202 will NOT normally be on Saturday.  Check out other ITAP lab schedule. FNR 21000, 2016, Week 1, Lecture 23 FNR 21000, 2016, Week 1, Lecture 24  You have begun learning the ArcGIS software tools by working through the ESRI Virtual Campus web course - Learning ArcGIS Desktop, Module 1.  Week 2 you will be completing Modules 2 and 8. FNR 21000, 2016, Week 1, Lecture 25 Data Models and Georeference 1 Map .mxd file Document Data Frame Layer Feature 2  Basic component of a layer  Linked to one row in attribute table  Has a location, shape, and a symbol 3 Three types of GIS features:  Point feature: A point feature represents a single location. It defines a map object too small to show as a line or area feature. A special symbol or label usually depicts a point location.  Line feature: A line feature is a set of connected, ordered coordinates representing the linear shape of a map object that may be too narrow to display as an area, such as a road, or a feature with no width, such as a contour line.  Polygon feature: An polygon feature is a closed feature whose boundary encloses a homogenous area, such as a state, county, or census block. 4 Two data models are commonly used in GIS: Vector & Raster Organization 1 Point ID X Y Points 2 4 1 32.7 45.6 3 2 76.3 19.5 3 22.7 15.8 etc….. 1 6 C Line Begin End Lines A B ID Point Point 239 A 6 9 9 B 9 1 C 239 1 etc….. 12 13 Polygon 11 52 22 ID Lines Polygons A 11, 12, 52, 53, 53 54 41 B 52, 53, 9, 41, 54 9 22, 13 6  Points - ◦ Marker or point symbol, ◦ color, ◦ size and angle.  Lines – ◦ Line symbol, ◦ color, ◦ width  Polygon – ◦ Fill color and pattern, ◦ Outline width and color, ◦ background color 7  Not using attributes  Using Attributes 8  Names (city, county, buildings) – LABEL  Types and conditions ◦ Landuse (forest, water, urban, cropland)  How would you symbolize this? ◦ Ranking (1-5) of scenic view along a highway  How would you symbolize this? 9  Usually requires grouping the data for display using graduated colors or size or both  How many classes (groups) do you need?  How do you divide the data into groups? 10 Turn on the labels for your layer –  Based on attribute value  Parameters: ◦ Size ◦ Font ◦ Color ◦ Position 11  Shapefile  Coverage  Geodatabase Arc/In(coverage format) Versions 1-7 form 1980 -1999 Arc Macro Language (AML) ArcGI(geodatabase format) Versions 8.1-10.3 2000- Visual Basic Application ArcView(shapefile format) Versions 1-3 form 1994 -1999 Avenue script language 12  Coverage 13  Shapefile: includes a set of files with the same file name but different extensions. These files have to be saved in the same folder. An ESRI shapefile consists of three or more files (with extensions .shp, .shx, .dbf, .sbx and .sbn) 3 mandatory files: Main File (geography) <filename>.shp Database File (attributes) <filename>.dbf Index File (indexing) <filename>.shx 14  Geodatabase A collection of geographic datasets of various types held in a common place (database).  3 Types of geodatabase Personal GDB File GDB Enterprise GDB Microsoft Folder of Storage Format Access binary files DBMS Storage capacity 2 GB 1 TB Depends on per table* edition Supported OS Depends on Windows Any platform edition platform Single editor Single editor Multiple editors Number of users Multiple readers Multiple readers & readers Extend the Geodatabase level Dataset level transaction model Editing lock with Versions 15  Inside a Geodatabase 16 Two data models are commonly used in GIS: Vector & Raster  Elevation and Satellite imageries are two common raster data sources.  Raster image resolution: cell dimension Pros:  Conceptually simple & efficient  Well established processing and analysis algorithms Cons:  Rigid data structure  Linear features are not well represented 18  The Storage Space/Resolution Tradeoff Decreasing the Cell Size by one-half causes a Four-fold increase in the storage space required 19 20 Vegetation Classification Map Discrete data – unique value Digital Elevation Model Continuous data – Stretch or classify 21  Geodatabase  Raster dataset  ArcInfo GRID  TIFF  Many other formats 22 23  In ArcMap, you have two options to work with your map: ◦ Data View ◦ Layout View  Analysis: Data View  Map Production: Layout View 24  Title  North Arrow  Legend  Scale bar/text  Other text  Neatline 25  In ArcMap, a map document is saved as a *.mxd file.  A MXD file saves information about: ◦ Reference to different map layers ◦ Symbology, labels, map layout, etc.  A MXD file doesn’t save information of the layers themselves. 26 27 Where in this world are you? 28  How do we locate a point on the earth?  The most basic system is the spherical grid ◦ longitude (measures east- west), Meridians ◦ latitude (measures north - south), Parallels ◦ measured in degrees (DMS or DD) ◦ 3-D perspective 29 What is the shape and size of the earth? Complex Simple Earth’sActual Shape mathematical mathematical estimation of the estimation of earth’s shape earth’s shape 30 There are locally “best fit” ellipsoids geoid Ellipsoid B Ellipsoid A 31  Datum - Defines the surface (ex radius for a sphere, major axis and minor axis or inverse flattening for an ellipsoid) and the position of the surface relative to the center of the earth.  There maybe infinite reference surfaces.  Nations or governing bodies can agree on points and surfaces as standard references. 32  Commonly Used:  North American Datum of 1927 (NAD 27)  NAD 83  World Geodetic System 84 (WGS 84)  We can transform positions from one datum to another via mathematical operations. 33 Geographic Projected Copyright © 2004–2008 ESRI. All rights Locations 34  Project a 3-D earth to a 2-D map. ◦ Linear units are most common ◦ 2-D perspective ◦ There are always projection errors. 35  A systematic rendering of locations on a 3-D spherical coordinate system (lat./long.) to a two- dimensional system.  Distortion introduced by projection: ◦ Shape ◦ Area ◦ Distance ◦ Direction 36  Simple - tangent to the globe at a point, parallel, or meridian, or  Secant - passing through the earth (multiple standard lines.  Standard line – line(s) (point) of tangency between the projection and the reference globe. ◦ No distortion at standard line. ◦ Distortion increases with distance from the standard line. 37 38 At national level:  Transverse Mercator  Lambert Conformal Conic  Albers Equal-Area Conic  Equidistant Conic 39 At state level:  State Plane Coordinate (SPC)  Universal Transverse Mercator (UTM)  Public Land Survey System (PLSS) ◦ Special Case –Historical ◦ Legally important – Deeds/ownership descriptions ◦ Is NOT a ‘projected’ coordinate System and cannot be Projected or Defined 40 41 42  Used in most of the Central and Western US  Established for inventory and transfer of property  Grid system ◦ 6 square mile Sections within ◦ Subdivide into 36 1-mile square sections ◦ Quarter, quarter-quarter sections 43  Define T ownship 44 45  SE1/4, SE1/4, NE1/4, sec. 13, T2S., R2W. 46  Used in many of the Eastern and Southeastern States.  Also used for land titles and transactions.  Example: "beginning with a corner at the intersection of two stone walls near an apple tree on the north side of Muddy Creek road one mile above the junction of Muddy and Indian Creeks, north for 150 rods to the end of the stone wall bordering the road, then northwest along a line to a large standing rock on the corner of the property now or formerly belonging to John Smith, thence west 150 rods to the corner of a barn near a large oak tree, thence south to Muddy Creek road, thence down the side of the creek road to the starting point." 47 Creating and Editing Vector File 1  To create a new shapefile: open ArcCatalog, right-click on a folder, click on New/Shapefile… in the drop down menu, enter the Name for the new shapefile, and then select the Feature type to be inserted. Optionally, you can also select the Spatial reference. 2  Scenarios: ◦ Digitize new data ◦ Modify existing data ◦ Delete features  ArcGIS allows you to edit data using editor toolbar.  You can edit vector data by ◦ Editing feature shapes ◦ Editing attribute value 3 Edit tool Edit vertices Editing Window Cut polygons ArcGIS edit tools can be used to create new features or to edit features existing in a dataset. To add the editor toolbar to a ArcMap document, click Tools/Customize. In the Customize wizard, click Toolbars/Editor. 4  Feature templates are how you add features to your file.  Feature template are used to define the types of objects that you create on a map and are comprised of these items: ◦ Name ◦ Symbol ◦ Default attribute value ◦ Default tool used to create the object 5  Open map document  Start an edit session (select workspace to edit)  Choose a feature template  Select the feature and display its sketch  Create new feature/edit feature  Save edits and stop editing 6  Editing applies to a single workspace (a geodatabase or a folder).  Try to edit your data in data view (not the layout view).  Edits are temporary until you save and apply them permanently to your data.  Just saving a map document does not save the edits. 7  Feature templates define all the information required to create a feature: the layer where a feature will be stored, the attributes a feature is created with, and the default tool used to create that feature.  A layer can have multiple templates associated with it, where each template has different default settings.  Anytime you create features on the map, you start with the Create Features window. 8 9  Snapping allows you to create features that connect to each other so that your edits are more accurate and have fewer errors. 10  Point  Line or Polygon 11 12  Quit the editing mode once you are done.  If you don’t save your edits when you quit, all the edits will be lost. 13  Table manipulation ◦ Each feature class has an associated table ◦ One row for each geographic feature Right- click 14  Records/rows and fields/columns  Column types can store numbers, text, dates  Unique column names Field Attribute Rows values (records) or Features 15  Unique identifier field for vector data – FID field in shapefile, or ObjectID field in geodatabase file.  Shape field: required geometry field – Polygon, Polyline, Point 16  Add Field  Field Calculator 17 18 19 Creating data for the Martell Forest & GeoRectifying 1  Martell Forest  Information you have at the start point: ◦ Reference layers Existing reference maps. ◦ Background maps Aerial photo, scanned map, etc.  What you need to do: ◦ Georectify the background maps ◦ Create & Digitize the information you know, and save into GIS. 2  Why? For maps without spatial reference information.  Examples: ◦ Scanned maps – maps from books, historical maps, field scratch ◦ Aerial photos & Satellite images  Most of the raster datasets that you obtain from the government or commercial sources are already georeferenced, and they should be ready for you to use. 3  Georectification: the process of aligning geographic data to a known coordinate system so it can be viewed, queried, and analyzed with other geographic data.  This process creates additional information within the file itself or in supplementary accompanying files that specifies how GIS software should properly place and draw the data. 4 5  To convert your raster data into GIS, you need reference data that covers the same area as your target area.  Reference data is a layer with a known spatial reference.  All the transformations in the georeferencing are based on the assumption that the reference data is perfectly accurate. 6 7  In ArcMap, add the raster dataset that you want to align with your map.  Add control points that link your raster dataset positions to known positions in map coordinates.  Save the control points information when you are satisfied with the alignment.  Permanently transform the raster dataset. 8 9  Control points: Locations that can be accurately identified on the scanned map/aerial photo and in real-world coordinates on the reference data.  The control points are used to build a transformation that will shift the raster dataset from its existing location to the spatially correct location.  Link: The connection between one control point on the scanned map and the corresponding control point on the aligned target data. 10  Example: road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows.  Control point is better to be selected based on artificial land markers. 11  Points should be located evenly across the image (sometimes difficult in natural areas)  The first pair of points results in a shift in the image relative to the coordinate system.  The second pair results in a change in scale across the image  The 6third pair results in the production of affine transformation  Subsequent pairs produce RMS (Root Mean Square) error calculations 12 View Link T able 13  Transformation Transformation Technique Required Best fit links Shift (zero order Slides already georeferenced data to its When previously georeferenced data needs polynomial) correct location 1 to be placed in its correct location Affine (1st order Rotates, shifts, and scales a raster to fit its For simple data alterations that fit the raster polynomial) proper location on earth 3 to its proper location on earth; optimized for global accuracy Higher order 6 (2nd) For complex data alterations that fit the polynomial (2nd and Bends, curves, and wraps a raster to fit iOR 10 raster to its proper location on earth; proper location on earth (3rd) optimized for global accuracy, 3rd) First performs a polynomial transformation For complex raster data transformations for global accuracy, then adjusts the that fit the raster to its proper location on Adjust control points locally, ensuring both good3 earth; optimized for both global and local global and local fit accuracy Transforms the source control points When control points are known and/or Spline exactly to the target control points, 10 precisely registered; optimized for scanned ensuring local accuracy imagery Preserves the projective properties of 4 When lines need to remain straight but not Projective embedded objects parallel; optimized for oblique imagery 14  The number of links you need to create depends on the complexity of the transformation you plan to use to transform the raster dataset to map coordinates.  Adding more links will not necessarily yield a better registration.  You can achieve a better georeferencing result if you evaluate the links, eliminate ones that do not match, and define the most accurate transformation for your data. 15  You can save the control points information and use it later. 16  All the transformations you did in Step 1-3 are temporary.  You need to transform the scanned map permanently.  Convert the scanned map to match the reference map. 17  Measures the residual locational error between the true coordinates and the transformed coordinates. 18  Minimum number of links – transformation equation can fit perfectly.  However, using only the minimum number of control points is not recommended because you can overlook control point errors.  Placing more than the required number of links introduces the possibility of errors. These errors indicate how well the transformation was able to "fit" your link point in the image to the desired map location. 20 Creating a Spatial Database 1  Georectification converts raster dataset from one projected coordinate system to another. (F)  When georectifying an raster dataset, the more control points you have, the less RMSE you will get. (F)  When georectifying a scanned map, the control points should be better scattered across the map. (T)  Saving a map document can automatically save the edits in the map layers. (F) 2  Quizzes 3 – 30 pts  Lab Quizzes 2 – 20 pts  Lab Assignments 5 – 150 pts  Check your grade on Blackboard  If you decide to resubmit a lab assignment which is previously graded: ◦ Please let me know that you have resubmitted. ◦ If it is past due date, late submission policy is applied. 3  Demonstrate your GIS knowledge and skills without detailed instruction.  Part 1: Create spatial database (50pts) ◦ Due: March 11, noon  Part 2: Spatial analysis (50pts) ◦ Due: April 22, noon  Brainstorming from this week: select a location of interest, such as your home, a vacation spot, a park, hunting area etc.  Your spatial scope will be the County (or parts of Counties) that encompasses your area of interest. 4  Define the problem ◦ What is the question you are trying to answer?  Identify and acquire the data you need ◦ Where to get the data? ◦ What are data format? ◦ How to organize your data?  Data analysis ◦ Plan the analysis ◦ Prepare the data for analysis ◦ Execute the analysis  Examine and present the results 5  Management of a forested and reverting agricultural land 7 miles west of Campus.  What questions need to be answered to manage the property?  Define the criteria: ◦ What are the criteria and/or resource requirements such as habitat characteristics, legal constraints, policies, etc.  What types of data would support the above? 6  Coordinate system must be specified.  Accuracy of both attribute and spatial positions. (Sample resolution, detection, and area amounts assuming the minimum line on a map is 0.5mm) 7  Data is the most expensive part of GIS  Sources of existing digital data ◦ Public Domain ◦ Commercial  Creating new data ◦ Editing and enhancing existing databases ◦ Digitizing or scanning existing Hardcopy maps ◦ Field inventory of features including attribute and spatial data 8  Disadvantages of public data ◦ Free or cheap ◦ Scale and/or resolution ◦ May require “format” conversion  Advantages: availability of basic data such as ◦ roads ◦ streams, rivers ◦ elevation ◦ Wetlands ◦ landuse, etc. 9  Moderate to very expensive.  Sometimes, customized to fit your needs.  Coarse to fine scale. 10  Very expensive,  Fits your exact needs  GPS, field collection, remote sensing  Editing, adding to Public or Commercial Data 11  State Examples  National Examples ◦ Indiana ◦ Census 2012 Shapefiles:  Indiana Spatial Data Portal: ww/tiger/  Indiana Map: ◦ The National Map Seamless Server: ◦ Michigan GIS : /viewer/ l/?action=ext ◦ Soil data: ◦ WisconsinView Data Portal http://websoilsurvey.nrcs.usda.g Aerial Photography: ov/app/HomePage.htm 12  Starting the Hunt: Guide to mostly online free U.S. geospatial data:  Geodata Portal at Purdue:  Google Earth 13  About 5-year repeat cycle, first done in early 1990s  21 landcover classes, ◦ based on satellite images, ◦ 30 meter cell size, and ◦ other data 14  A georeferenced raster image of a scanned USGS map. (1:24,000 or 1:100,000 or 1:250,000)  Often delivered in a compressed GeoTIFF (.tif) format 15  Orthophotos ◦ Aerial photography which is corrected using digital elevation models to create map quality imagery. ◦ Best base map layer ◦ Raster data model  USGS Digital Orthophoto Quadrangles (DOQ)  National Agriculture Imagery Program (NAIP) ◦ Annual  IndianaMap Orthophotography (2013) 16 17 1 meter 6 inch 18  NED – National Elevation Dataset (in meters) ◦ 1 arc-second (30 meter grid) ◦ 1/3 arc-second (10 meter grid) 1 ◦ /9 arc-second (3 meter grid)  2013 IndianaMap Elevation and Surface Model 19  Natural Resource Conservation Service (NRCS)  Digital soil data sets at different scales and extents  National Soil Geography (NATSGO), national coverage, small scale.  State Soil Geographic (STATSGO) data intermediate scale and resolution. (1:250,000)  Soil Survey Geographic (SSURGO) data at a very large scale provides the most spatial and categorical detail. 20 Source: Indiana Soil Map: Search for isee app from Apple Store 21  Intended for use in management, not regulation; wetlands may be missing, or over defined.  Typical MMU’s (Minimum mapping unit) are between .5 and 2 hectares (vary by vegetation, source, region, etc.)  Wetland legal definitions often include not only surface water, but also characteristic vegetation or evidence on the surface or in the soils that indicates a period of saturation. 22  TIGER® comes from the acronym Topologically Integrated Geographic Encoding and Referencing  TIGER is the set of digital database developed at the Census Bureau to support its mapping needs for the Decennial Census and other Bureau programs 23  Line Features—roads, railroads, hydrography, and transportation and utility lines.  Boundary Features—statistical (e.g., census tracts and blocks); government (e.g., places and counties); and administrative (e.g., congressional and school districts).  Landmark Features—point (e.g., schools and churches); area (e.g., parks and cemeteries); and key geographic locations (e.g., apartment buildings and factories). 24  What is metadata? ◦ Data about data – information that describes other data ◦ Metadata is not just limited in GIS – e.g. labels on the photo, size of files on your disk, number of pages in a book  In order to use your downloaded files in an appropriate way, you need to find and read metadata information. ◦ Metadata in ArcGIS can be exported as xml file. ◦ In case metadata file is missing, you can find related information from your data source.  ArcGIS metadata can include spatial and attribute information, collection methods, access and use constraints, resolution, etc. about the data.  The default metadata style in ArcGIS is called the Item Description 25  In ArcGIS, you can access and edit metadata information from ArcCatalog.  You can export metadata from ArcGIS as an XML file. 26 Projected Coordinate System Geographic Coordinate System Vector Raster 27  Geospatial information are usually organized as a geodatabae or folder structure. ◦ Both work as a collection of geographic datasets of various types held in a common place.  In this class, for the folder structure, we organize the information as: 28  Save your mxd file with relative pathnames so that your whole folder can be copied between places. 29  Tools available in ArcT oolBox search in ArcToolBox  Merge – mosaic  Clip – Extract by mask 30 GIS Models 1  Topics we learned in previous weeks: ◦ Symbol & Maps, GIS Data Models, Spatial Data Editing, Georectification, Creating Spatial Database Data & Display GIS Analysis 2  The process of using combinations of commands to answer questions about spatial phenomena.  Is a set of interacting, ordered map operations that act on raw data, to simulate a spatial decision- making process. 3  Cartographic models  Spatio-temporal models  Network models  Others 4  Application of spatial operations such as buffers, interpolation, reclassification, and overlay to solve problems ◦ Often temporally static (features represented at a fixed period of time) ◦ It may include a temporal component when it compares change through time (comparing vegetation in 1990 to vegetation in 2000) ◦ Input data/values don’t change during the model 5  Ranking sites by suitability for home construction using four criteria ◦ Slopes should not be too steep. Steep slopes may substantially increase costs or may preclude construction. ◦ A southern aspect is preferred, to enhance solar warming. ◦ Soils suitable for on-site septic systems are required. There is a range of soil types in the study area, with a range of suitable soils for septic system installation. ◦ Sites should be far enough from a main road to offer some privacy, but not so far as to be isolated. 6 7 8  Finding features by attributes/locations - Query  Spatial manipulation - Overlay, buffer, etc.  Terrain analysis  Raster modeling  Spatial interpolation  Many other spatial models, such as pattern detection, clustering, etc. 9  Refers to GIS operations that manage and analyze your GIS data.  In software – it includes tools that perform analysis and managing your spatial data.  A tour of geoprocessing ◦ Geoprocessing menu – demo ◦ ArcToolbox ◦ Search window ◦ Tool dialog box ◦ Results window ◦ Backbround processing 10  Query – week 8 (next week) ◦ Attribute based query ◦ Location based query  Simple spatial analysis – week 9 ◦ Buffer ◦ Overlay  Today’s lecture – prepare your attribute data for analysis 11  Fields – ◦ Unique identifier field for vector data – FID field in shapefile, or ObjectID field in geodatabase file. ◦ Shape field: required geometry field – Polygon, Polyline, Point 12 • Each field in the table has a “Type”. When creating new field in a vector attribute table, you can choose one of these types: • Integer: Short, long • Decimal: float, double • Text • Date • Blob • GUID • Check “Properties” for existing field type.  Sort field  Statistics  Summarize Generate new table to generalize attribute for selected fields.  Add field  Field calculator  Attribute T able (spatial) geospatial datasetins information about specific features in a 1 record for each feature  can have multiple fields  Stand Alone T able (non-spatial) A table that is independent of the geographic data in the map  The data may come from a Excel spreadsheet, field work, etc.  Need a OID (Object Identification numbers) field. Spatial vs. Non-Spatial data The connection between spatial and non-spatial data are made through databastables  T ables can be joined or related to each other by using a common field (column) Two methods to associate tables in ArcMap based on a common field Join appends the attributes from one onto the other ◦ Label or symbolize features using joined attributes Relate defines a relationship between two tables  Cardinality: how data relate to each other • 1 to 1 relationship - each record (row) in the destination table has a match in the source table • Many to 1 - each record in the destination has multiple matches in the source tables • 1 to Many - each record in the destination table match a single record in the source table One parcel One parcel Many parcels Many parcels has one owner has many owners have one owner have many owners or  Associate tables with common column key values ◦ Must be same data field types  Must know table relationships (cardinality) Additional Feature attribute table attribute table Example: Associating county attribute table with separate table of poverty estimates by county for WV  Common field  Records with the same value are matched  Some cleaning necessary Must remove dashes! Copyright – Kristen S. Kurland, Carnegie Mellon University Appends the attributes of two tables Assumes one-to-one or many-to-one cardinality County Attributes (before Join) WV_Poverty98 One-to-one County Attributes with joined poverty data (virtual table after Join)  Joining a table has a direction  Direction is important because it defines what the resulting data table might be used  There is a SOURCE table and a DESTINATION table  The source database represents the database that will be associated with another database (the data that will be joined)  The destination or target database is the data location where a source database will be associated (the data that will have something added)  The join item or join field is the common attribute between databases that will guide record or spatial entity matching  Joining in this way yields a table capable of being mapped; reversing the source and destination labels yields only a stand alone table.  Why? Define relationship between two tables Tables remain independent Additional cardinality choices ◦ One-to-many ◦ Discovers any related rows 2) Open related table 1) Make selection Example: Relate WV county attributes to table of coal production statistics for 1986 - 1998 One linked to Many table violates the rule of joining  Join and relate brings spatial and non-spatial tables together in a temporary manner that doesn’t alter the original structures of the tables involved.  When two databases are joined, the visual affect is as if the databases are physically joined (they appear as one database)  When two databases are related, no physical link appears to exist yet records selected in one of the databases (either through attribute or spatial queries) will also selected in the linked database Q1: You are creating a table field to record the length of stream reaches (meters) with one decimal points (105.3 meters), which field type(s) could you use? A. Short integer – Numbers from -32,768 to 32,768, no decimal places B. Long integer - Numbers from -2,147,483,648 to 2,147,483,648, no decimal -308 308 C. Double – Approx. -2.2*E to 1.8*E with or without decimal -38 38 D. Float – Approx. -3.4*E to 1.2*E with or without decimal E. C and D 1 Q2: To change a feature file's coordinate system from one type to another, you would use the _____________ tool. A. Define Projection - For files with unknown projection information B. Project -Change projection from one to another C. ArcCatalog - “Project” tool is available in ArcToolbox D. A and B 2 Q3: You can change the information included in attribute table with the following operations, EXCEPT________: - A new field is added to the table: changed A. Add field B. Edit attribute table -Occurs in the edit session, attribute value is changed C. Join table - Brings two tables together in a temporary manner D. Use field calculator -Calculate the new attribute value for selected fields: changed 3  Join Many-to-1 1-to-1 Join Result: A visual effect -> 4  Relate 1-to-Many This relationship can only be reflected in “Selection” 5 Q4. When joining tables in ArcGIS, the common field in the two tables can have different data type as long as the recodes share the same values. A. True B. False Common Fields: • Same value • Same field type • Could have different field name 6 Q5. You cannot use join tables in ArcGIS, if the two tables have _______ relationship. A. one-to-one B. one-to-many C. many-to-one One-to-many 7 Query 8  Query: Asking and answering questions about data  Two basic methods: ◦ Selection by attribute (Attribute Queries) ◦ Selection by location (Spatial Queries)  Or you can combine these two types of queries together. 9 10  Manual selection of one feature  Manual selection of many features  Selecting ALL features  Selecting NO features (Clear)  Selecting features based on some criteria  Selecting features from a previous selection set 12 Create a box by clicking and holding the select tool 13 14  Select features based on one or more criteria  Performed on attribute data  Using ◦ Logical operators ◦ Boolean Connectors 15  = equal to  < less than  > greater than  => equal to or greater than  <= less than or equal to  <> not equal  Attribute  Relational operator  Threshold value  Query  How many polygons (i.e. stands of vegetation) are of Type ‘C’ in the vegetation shapefile?  Attribute (field): Veg_Type  Relational operator: =  Threshold value: C  Query: “Veg_Type” = ‘C’  Answer: ? 18 19 FNR 21000, Week 7, 20  You can combine attribute query criteria using Boolean Connector:  Boolean Connector: ◦ AND Intersection of two or more sets ◦ OR Union of two sets ◦ XOR Union – Not the intersection (not both, just one or the other) ◦ NOT Complement of a set 21 22 1. AAND B ? A. R2 B. R3 C. R4 2. A OR B ? A. R2, R3 B. R4,R1 C. R2, R3, R4 3. A NOT B ? A. R2 B. R3 C. R4 4. NOT (A OR B) ? A. R1 B. R2 C. R3 1. AAND B = R4 2. A OR B = R2, R3, R4 3. A NOT B = R2 4. NOT (A OR B) = R1  If you aren’t completely sure of the spelling or arrangement of what you are selecting for, you can use the “LIKE” operator and the wildcard ‘%”  For example, if you are selecting for someone’s address on ‘Marsteller Street’ but you don’t know if it’s Marsteller St. or Street in the database and selecting the unique button for the “ADDRESS” attribute would return too many entries  Selection: “ADDRESS” LIKE ‘Marsteller %’ 25  Spatial querying uses the location information that is integral to GIS.  Sample questions: ◦ What streams are within ½ mile of the Northern Spotted Owl nests? ◦ What are the stands adjacent to class 2 streams? ◦ How many stands (and acres) are more than 100 meters from a road? 26 27  intersect – The features in the input layer(s) will be selected if they intersect a feature in the selection layer.  are within a distance of – The features in the input layer(s) will be selected if they are within a specified distance of a feature in the selection layer. When you choose this option the buffer distance field at the bottom of the dialog becomes automatically enabled so you can specify the distance.  contain - The features in the input layer(s) will be selected if they contain a feature in the selection layer.  completely contain - The features in the input layer(s) will be selected if they completely contain a feature in the selection layer. The selection layer must be a polygon layer.  contain (Clementini) – This is the same as Contain unless the source feature is entirely on the boundary of the target feature, with no part of the source feature inside the target feature. In this case, using the Contain Clementini operator would not select the target feature, whereas the Contain operator would. New in 9.3.  are within - The features in the input layer(s) will be selected if they are contained by a feature in the selection layer. The selection layer must be a polygon layer.  are completely within - The features in the input layer(s) will be selected if they are completely within or contained by a feature in the selection layer. The selection layer must be a polygon layer or there must be a buffer around point and line features.  are within (Clementini) - This is the same as Are Within unless the Target feature is entirely on the boundary of the Source feature, with no part of the Target feature inside the Source feature. In this case, using the Are Within Clementini operator would not select the target feature, whereas the Are Within operator would. New in 9.3.  are identical to - The features in the input layer(s) will be selected if they are identical (in geometry) to a feature in the selection layer.  touch the boundary of - The features in the input layer(s) will be selected if they have a boundary that touches a feature in the selection layer. The input layer(s) and the selection layer must be lines or polygons.  share a line segment with - The features in the input layer(s) will be selected if they share a line segment with a feature in the selection layer. The input layer(s) and the selection layer must be lines or polygons.  are crossed by the outline of - The features in the input layer(s) will be selected if they are crossed by the outline of a feature in the selection layer. The input layer(s) and the selection layer must be lines or polygons.  have their centroid in - The features in the input layer(s) will be selected if their center falls within a feature in the selection layer. 28  What are the stands adjacent to Class 2 streams? 29  New set  Add to set  Select from set  Complement 30  Export Data: ◦ Extracts the selected features to a new feature class ◦ Creates a new file ◦ The source file is not changed 31  Many ArcGIS operations are based on the selected dataset.  Examples: ◦ Field calculator ◦ Selection by location – the source data ◦ Field statistics 32  Displaying a subset of features in a layer 33 Original file is not Generate a changed. It is just a new file of the display in ArcGIS. subset. Query by Attribute Definition Query Export Data 34  Query, Definition Query, Export Data ◦ Highlight (select) the interested feature(s) from your data ◦ Only display the interested feature(s) from your data ◦ Create a new file for interested feature(s) 1 Buffer & Overlay 2  Overlay  Clip  Dissolve  Buffer 3  One of the most basic questions asked of a GIS is “what’s on top of what?” ◦ What forest types are within the ecoregion? ◦ What land use is in my study area? ◦ What fish species are within the streams in our county? Overlay helps you to answer those questions. 4  Overlay is a combination of different data layers  Spatial and attribute data is combined during overlay  A new data layer is created  Requires that data layers use a common coordinate system 5 6 In general, there are two major types of overlay operations:  Union Includes all data from both layers. New polygons are formed by the combinations of the layers.  Intersect Combines the spatial data from both layers but only for the common area. Data from both layers are combined. 7 8 Vegetation Type Logging roads 9  This approach is often used to find locations that are suitable for a particular use or are susceptible to some risk. 10  Clip – cut out a piece of one vector/raster dataset using one or more of the features in another layer as a cookie cutter. 11  You can also use line or point to clip your data: 12  Clip feature defines the output geometry  Attribute value from the input feature will be copied to the output data * Pay attention to those attributes with geometry information, such as area  Neither the Clip feature’s attributes or geographic (spatial data) are included in the output layer 13 14  New polygon or attribute class that is defined by the distance from a point, line or area.  Point  Line  Polygon 15 16 17 18 19  Calculates the distance from (to) a feature 20 21  Dissolve – aggregate features based on specific attributes. 22  Dissolve fields Features with the same value combinations for the specified fields will be aggregated (dissolved) into a single feature.  Multipart features Dissolve may result in multipart features being created. A multipart feature is a single feature that contains noncontiguous elements and is represented in the attribute table as one record.


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