ArcGIS did well in organization of the complex and gigantic data in GIS. First the data models are divided into vector model, raster model and triangulated irregular network model to present data in different condition of real world and requirement of analysis. The formats of feature data include shapefiles, coverages and geodatabases.
Metadata consists of properties and documentation. It has 3 parts: description, spatial, and attributes. “Description” contains the information of keywords, status of the data, publication information, data storage and access information, and details about the document. “Spatial” let us know the coordinate system used in the document, the bounding coordinates, and the spatial data description. “Attributes” includes the type of object, number of records, and attribute types in the table.
The steps for a GIS project include: identifying the objectives, creating a project database, data analysis, and results presentation. The project database creation is a critical and time-consuming part of the project, which is a three-step process: designing the database, automating and gathering data for the database, and managing the database. Designing includes identifying the spatial data required by the analysis, determining the required feature attributes, setting the study area boundary, and choosing the coordinate system. Automating the data involves digitizing or converting data form other systems and formats into a usable format as well as verifying the data and correcting errors. Managing the database involves verifying coordinate systems and joining adjacent layers. The completeness and accuracy of the data in the analysis determines the accuracy of the results.
Essay 2:
The most significant things I learned in this Lab were how to define and manipulate various data formats in the new ArcGIS data model. I also learned how different GIS formats are constructed, used and projected within an ARC 8x geodatabase. I gained knowledge about the new ESRI geodatabase model and how it differs from previous GIS data models.
Previously
my GIS experience has largely been in an Arcview environment. Although I’ve made several attempts to work
in the geodatabase world, job demands and data limited to shapefile format made
the attempt to learn this new format somewhat difficult. This lab’s structured approach to defining
shapefile, coverage and geodatabase data models clarified differences in file
structures of the three types, and how they might be better managed on
screen. The lab also was quite helpful
in defining how ‘layers’ are merely on-screen pointers or placeholders for data
files stored elsewhere.
I
am particularly impressed with how the new geodatabase relational model allows
much greater interaction with underlying data files than does the older,
hierarchical or ‘flat file’ shapefile storage model. Clearly this allows data stored and in today’s relational
databases to be more effectively joined, queried and managed in geodatabase
feature classes. Similarities in object
modeling and behavior between contemporary relational databases such as Oracle,
Sybase and others and the ESRI geodatabase became quite apparent. I also was impressed with ArcGIS improved
capability for managing and displaying raster and vector data together. In arcview I found that working with raster
data was somewhat limited, particularly with the ability to view and modify the
behavior and properties of images. This
process seems to be greatly enhanced in ArcGIS. I look forward to learning more about raster manipulation,
particularly in regards to GIS
applications in remote sensing.
Regarding
the manipulation of data, I finally learned how tics and topology are used to
relate and delineate feature data contained in adjacent tiles. Probably more significantly for effective
manipulation of ArcGIS was the description of how annotation is different from
labeling, and how annotation is stored with geographic coordinates to maintain
position and scale relative to other features displayed in the GIS.