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Lecture 6

by: Sierra

Lecture 6 FNR 210


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Creating a Spatial Database
Natural Resource Information Management
Ningning N. Kong
Class Notes
Natural Resources, information management, forestry
25 ?




Popular in Natural Resource Information Management

Popular in Agriculture and Forestry

This 30 page Class Notes was uploaded by Sierra on Friday March 4, 2016. The Class Notes belongs to FNR 210 at Purdue University taught by Ningning N. Kong in Spring 2016. Since its upload, it has received 25 views. For similar materials see Natural Resource Information Management in Agriculture and Forestry at Purdue University.


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Date Created: 03/04/16
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


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