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Global, zonal and focal operations, map algebra
Task: compute summaries, use map algebra to analyze, modify and derive new maps, and explain difference between operations on
discrete and continuous data
1.Compute area and zonal statistics us in g r . repor t
Landuse 96_28m res=12 landuse96_28m res=30
These results are relevant because both outputs have within .01% of land use but the cell counts are very different.
2 Zonal Statistics Elevation_streets Avg_elevation_zipcode Mode-landuse_zipcode
3. Land use is spread
between four
categories of seven and
primarily in the 2nd and
3rd category
Lu_divers lu_divers report
This area does not appear to be very diverse but I would need to further evaluate the data to find if this is because of how
the data is categorized or due to lack of diversity in the actual land use classification.
MEA 582, Assignment4
Geospatial Analysis
Global, zonal focal operations,
map algebra
Due: Tues, Feb 8th
2011
Brenda McLuskie
Student ID: bhmclusk
704 708-4880
4. Using
neighborhood
operator,
How would
neighborhood size
influence results?
Elev_srtm_30m Elev_srtm_30m_sm5
The size (5) determines how many cells are used to average the each cell value. Using a higher value allows
for greater smoothing of the data because more cells are used in the average.
5. Patch multiple
layers into a single
raster maps
Composite map,
contains:
Major roads,
facility
Lakes
elevation
Custom colors
6. Map algebra
Ndvi1 Ndvi2
Integer Floating Point
Floating point
values require
special handling
because of the
decimal point.
Division of integers
creates truncated
integers where
division of float
values creates
accurate float values
7.SRTM and NED
elevation differences
Original ned Original srtm Difference Difference with
color change
This gives the data range for the custom color table.
Is the srtm mostly higher or lower than elev_ned?
The srtm elevation is higher in range and mean. I used Univar because it shows the statistical differences. I
would use the images if I wanted to know geographical area differences.
Strm Map with legend and streets
Strm_ned_difference Strm_ned_difference no nulls
8.Working with if
commands creating maps
of urban areas
These two maps are the same because the If commands are different methods to do the same thing..
r.mapcalc "urban1_30m=if(landclass96==1,1,0) + if(landclass96==2,2,0)"
creates a output where values or 1 is changed to 1 and values on 2 are changed to 2 and if the values are not 1 or 2
then are changed to 0
r.mapcalc "urban2_30m=if(landclass96==1 || landclass96==2,landclass96,0)"
d.rast urban2_30m
creates an output where values of 1 and 2 are left as their original values all other values are changed to 0
9. Land class 96 where
lakes are /1000
10. Landclass 96 where
where LULC codes are
>1(not nulls)
11. Masks Elevation with mask Elevation without mask
r.mask urban maskcats=55 g.remove rast=MASK
12. Elevation
3d_tilt_plane
13. Create subsets Ortho elevation elevation with mask ortho with mask
14. r-stats by zipcode
for land use
r.stats
The high developed zip code is the
27603 but 59% of the zipcodes are
no_data so accuracy is a concern.
15. Working with
relative coordinates
Elev_srtm_30
Elev_srtm_30_smooth
Elev_strm_30m Elev_strm_30m_smooth
Appro ach
I used Grass ins t ruc t ions to co mplete these ta sks .
Resu l t s
Th e r esu l t s are that modi fi cat ion to ras t er d ata u s in g masks , IF s t a t ement s and method o f d at a management may al t er your
resu l t s . Nul l s in the d at a must a l so be consid ered .
Discuss ion and Con clusio n
In the end i t i s impor tan t t o no t on ly cons ider the graphical ou tpu t bu t a l so kn ow your d at a . The impor t ance o f
unders t anding the d ata t yp e and e f fects o f methodo logy can skew output and r esu l t in poor deci s ion making.