Second Test

Question 1

storing vector features

Answer 1

a multipart feature may contain several separate pieces

Question 2

spaghetti models

Answer 2

simple vector data formats; each state is stored as individual polygons; adjacent boundaries are stored twice; it is a robust model because of its simplicity

Question 3

topological models

Answer 3

test whether features are adjacent, connect, overlap, or intersect; can find data errors such as overlapping states, or a county boundary that falls outside the state; states information on how features

Question 4

types of data used in ArcGis

Answer 4

shapefiles, coverages, geodatabases

Question 5

shapefiles

Answer 5

vector feature classes developed for early version of Arcview to ArcGis; stored in a spaghetti data format that has a simple structure; care must be taken when copying or renaming shape files outside of ArcGis

Question 6

coverages

Answer 6

vector data format developed for ArcInfo and is oldest of data formats. not read by ArcGis Pro; must be converted to a shape file or geodatabase in ArcMap; composed of multiple feature classes

Question 7

geodatabases

Answer 7

recommend model for stating spatial information for ArcGis;

Question 8

4 types of geodatabases

Answer 8

personal, file, mobile, and enterprise

Question 9

personal geodatabase

Answer 9

original format but not recognized by ArcGis Pro stored in a Microsoft access database format; for single users or small workgroups; 2GB limitation on feature classes

Question 10

file geodatabase

Answer 10

stored as files in a geodatabase folder; for single users or small workgroups; platform independent

Question 11

mobile geodatabase

Answer 11

newest format available with latest version of ArcGis Pro; use open source database for storage and is optimized for mobile devices

Question 12

enterprise geodatabases

Answer 12

stored in a commercial relational database management system (DBMS) such as oracle or SQL server; designed for multiple users and large workgroups; supports multiuser editing, versioned editing

Question 13

queries

Answer 13

used to extract data using an expression based on an attribute field

Question 14

clip

Answer 14

extracts features within a bounding polygon from another feature class

Question 15

erase

Answer 15

extracts the features outside of a bounding polygon from another feature class

Question 16

merging

Answer 16

combines all feature from two or more data sets into a single new feature class; used to combine adjacent feature classes; works when data in attribute table identical; if they don’t match merge rules must be set up to combine the table data in a logical and ideal way

Question 17

pixels or cells

Answer 17

each pixel contain one numeric value; dimensions of a pixel is the resolution and they are in the units of the stored coordinate; value represents some property of the pixel area

Question 18

raster resolution

Answer 18

x and y dimensions of each pixel define the resolution of a raster; precision of a raster is limited by the resolution storage requirements increase by the square of resolution

Question 19

storing raster values

Answer 19

one binary digit is called a bit which corresponds to a single 0 or 1; bits are grouped into sets of 8 called a byte can store a number from 0 to 255

Question 20

pixel depth

Answer 20

number of bits or bytes used for each pixel

Question 21

value raster

Answer 21

DEM or land use raster stores a value representing an object or quantity, like elevation or rainfall; used for analysis

Question 22

picture raster

Answer 22

stores arbitrary color values that have no direct relation to quantity or attribute; used as background pictures or for land use analysis

Question 23

continuous rasters

Answer 23

store numeric values that can be measured anywhere such as elevation, temp, or precipitation; imagery type of continuous raster that stores brightness

Question 24

single band picture rasters

Answer 24

binary rasters results in black and white image (black = 0 white =1) grayscale raster creates a grayscale image ranging from black(0) through intermediate gray tones to white (255); colormap may be saved with a single band raster and serves as a look up table to find corresponding RGB color values

Question 25

multi band raster

Answer 25

RGB values are stored in 3 serpent raster layers and then displayed together as a composited band; 1=red; band 2 = green; band 3 = blue; satellite images this is often reverses

Question 26

vector data

Answer 26

each individual point has an x-y coordinate value which may be used in the trigonometric equation to convert from one projected coordinate system to another, it is very precise

Question 27

raster data

Answer 27

is projected new shape results that requires new cells be constructed, often with a change in size as a result, new numerical values have to be stored in each cell according to on elf several rules

Question 28

projecting rasters

Answer 28

can be converted form cone coordinate system to another by projecting cell centers are converted to the new system, does not preserve original rectilinear spacing of cell grid, so a new cell size must be specified resampling must occur

Question 29

resampling

Answer 29

during recifitifcation a new cell size is specified for the output grid; cell centers change location and cells may have gaps or overlaps; new cell centers rarely align with old cell centers, and must be resampled to fit the new grid

Question 30

resampling methods

Answer 30

nearest neighbor resampling; bilinear resampling and cubic convolution

Question 31

nearest neighbor resampling

Answer 31

grabs the value form old cell that falls at the center of the new cell; preserves the orginianl value and should always be used with categorical data (discrete raster) or when original data values need to be preserved fastest method

Question 32

bilinear resampling

Answer 32

calculates a new value from the four cells that fall closest to the center of new cell. it uses a distance weighted algorithm based on old cell centers. best used with continuous data such as elevation

Question 33

cubic convolution resampling

Answer 33

calculates a new value form 16 cells that fall closest to the center of new cells. uses a distance weighted lagrotihm based on the old cell centers. best used with continuous data such as elevation. most time consuming method

Question 34

digital elevation model (common continuous raster type) DEM

Answer 34

has cells or pixels each of which contains a single elevation. regular spaced array of elevation values

Question 35

indexed color raster (contains color map)

Answer 35

scanned versions of standard USGS topographic maps; stores a single band of integers that represent specific RGB combinatinons found don USGS maps

Question 36

raster pyramids

Answer 36

helpful when individual raster cells are too small to display when full image is shown; used to speed display of rasters; create successive lower resolution copies; built once used many times; increases size of file by about 50%

Question 37

slicing

Answer 37

divide range of values into 356 classes, or bins to create histogram

Question 38

stretching image improves appearance after..

Answer 38

after slicing, stretching enhances display by removing the less common values at the tails (extreme) of histogram