Inmap 2005 elevation datasets
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INMAP 2005 Elevation Datasets. Anna Radue University Information Technology Services (UITS) Indiana University. INMAP05 Elevation Data. Created from 2005 Indiana orthophotography imagery collected in March & April, 2005 65,670 DEM ERDAS *.img files (~200 GB) 34,161 stple images

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INMAP 2005 Elevation Datasets

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Inmap 2005 elevation datasets

INMAP 2005 Elevation Datasets

Anna Radue

University Information Technology Services (UITS)

Indiana University

http://gis.iu.edu [email protected]


Inmap05 elevation data

INMAP05 Elevation Data

  • Created from 2005 Indiana orthophotography imagery collected in March & April, 2005

  • 65,670 DEM ERDAS *.img files (~200 GB)

    • 34,161 stple images

    • 31,509 stplw images

  • 800 x 800 pixel *.img images

  • 2.78 MB *.img file and 0.3 MB *.rrd

http://gis.iu.edu [email protected]


Dem and dsm image properties

DEM and DSM Image Properties

  • Cell size (X,Y): 5 feet, 5 feet(4,000 ft x 4,000 ft)

  • Source Type:

    • Continuous

    • 32 bit floating point

    • Uses 4bytes/pixel for storage

    • Supports decimals

  • Elevation Units: Feet

http://gis.iu.edu [email protected]


Accuracy

Accuracy

  • Horizontal

    • Better than 5 feet at 95% conf level for 1 FT counties

    • Better than 2.5 feet at 95% conf level for 6 inch counties

  • Vertical

    • Compiled to meet 6 foot vertical accuracy at 95% conf level

    • Suitable for automated compilation of 10ft contours

http://gis.iu.edu [email protected]


2 ft contours

2 Ft Contours

  • Higher accuracy contours can be produced but only with additional ground control points, re-triangulation of the datasets, and stereo-compilation of breaklines as required.

  • Dearborn County and City of Bloomington have purchased

http://gis.iu.edu [email protected]


Digital surface models dem

Digital Surface Models (DEM)

http://gis.iu.edu [email protected]


Digital surface models dsm

Digital Surface Models (DSM)

http://gis.iu.edu [email protected]


32bit floating data

32bit Floating Data

  • Challenge to load to ArcSDE geodatabase raster dataset

  • Required using ArcSDE 9.2 sderaster

  • Tried loading using Python scripting, but memory leaks with ArcGIS 9.1; loading failed after loading ~200 images

http://gis.iu.edu [email protected]


Arcsde raster dataset

ArcSDE Raster Dataset

  • Valuable to load images to raster dataset as any misaligned or corrupt images found.

  • Sderaster command

    • loads only TIFF or BSQ files

    • Exported *.img files to Geotiff format

    • Loaded with command line using LZ77 (lossless) compression

    • Could visualize entire state

    • Geotiff files available for download from ISDP

http://gis.iu.edu [email protected]


Dem index

DEM Index

http://gis.iu.edu [email protected]


Dem stpl raster datasets

DEM STPL Raster Datasets

http://gis.iu.edu [email protected]


Dsm stpl raster datasets

DSM STPL Raster Datasets

http://gis.iu.edu [email protected]


Challenge create single statewide dataset

ChallengeCreate Single Statewide Dataset

  • Mosaic stpl *.img images by county

  • Reproject to UTM

    • Cell size ?

    • Resampling method?

    • Subset to remove invalid DNs and no data areas

  • Load Data to ArcSDE raster dataset

  • Archive county mosaics on ISDP

http://gis.iu.edu [email protected]


Cell size

Cell Size

  • STPL imagery 5 ft (1.524m) pixels

  • UTM selected 1.5 meters to most closely approximate spatial resolution of original imagery

  • Changing to 1 meter pixels would more than double the size of the imagery

http://gis.iu.edu [email protected]


Determining pixel size

1m 1m 1m

5ft

5ft

1m

5ft

1m

5ft

1m

Determining Pixel Size

1.5m

1.5m

1.5m

1.5m

32 bit floating data stores 4 bytes/pixel

4 pixels/image * 4 bytes/pixel = 16 bytes/image

9 pixels/image * 4 bytes/pixel = 36 bytes/image

36/16 = 2.25

http://gis.iu.edu [email protected]


Pyramid resampling methods

Pyramid Resampling Methods

  • Nearest Neighbor

    • Does not create new values

    • Categorical data – landuse

    • Can be used on continuous data but the results can be blocky

  • Bilinear Interpolaton

    • Creates new values

    • Used for elevation data

  • Cubic Convolution

    • Good for smoothing continuous data

    • Computationaly intensive

http://gis.iu.edu [email protected]


Results from resampling

Results from Resampling

Gray Valid DN

Red No Data (0 DN)

Green Invalid DNs

Result bilinear interpolation

http://gis.iu.edu [email protected]


Subsetting

Subsetting

  • Difficult for border counties, required multiple subsets

  • Important to subset to create images which align with raster dataset grid

  • Use coordinates for whole pixel values

http://gis.iu.edu [email protected]


County dem mosaics utm stpl

County DEM MosaicsUTM & STPL

  • Large files 1-3 GB

  • Stateplane

    • IMAGINE, tiled

    • No NoData pixels

  • UTM

    • Striped, GeoTIFF

    • Border Counties have NoData (0)

http://gis.iu.edu [email protected]


Tiff format 6 0 spcs

TIFF Format 6.0 Spcs

Tiled 64x64 pixels

Striped - default

http://gis.iu.edu [email protected]


Tiff tile format

TIFF Tile Format

  • Image is broken in square tiles (64x64 pixel), each tile is loaded separately into memory and can be accessed independently of other tiles

  • All tiles in an image are the same size (4096 pixels/tile)

  • Border tiles are padded to the tile boundaries

  • If image is 800 pixels wide, then the image is stored as 13 tiles wide - 32 pixels are added for padding to fill rightmost column of tiles 800/64 = 12.5 832/64 = 13

  • Good viewers do not display pixels used for padding

  • Method used by ERDAS IMAGINE for .img files

  • Good for high-resolution, large images

  • Applications can access imagery more efficiently

  • Better compression with this format

  • ArcGIS 9.1 & 9.2 support, earlier versions do not

  • Other software may not support?

http://gis.iu.edu [email protected]


Setting tiff output format

Setting TIFF Output Format

http://gis.iu.edu [email protected]


Image information erdas imagine inmap 2005 dem img tiled format

Image Information ERDAS IMAGINEINMAP 2005 DEM.img – Tiled Format

64 pixel x 64 pixel tiles

13 tiles/image

http://gis.iu.edu [email protected]


Striped geotiff created from tiled dem img

Striped Geotiff created from tiled DEM.img

Stripe format

800 pixels x 8 pixelstrip

100 stripes/image

http://gis.iu.edu [email protected]


Size of striped and tiled images

Size of Striped and Tiled Images

*IMG (tiled) format (800x800 pixels): 2,782,240 bytes

TIF (stripe) format (800x800 pixels): 2,561,691 bytes

800x800 4bytes/pixel : 2,560,000 bytes/image

IMG (tiled) format (832x832 pixels): 2,785,163 bytes

TIF (stripe) format (832x832 pixels): 2,777,675 bytes

TIF (tiled) format (832x832 pixels): 2,773,747 bytes

832x832 4bytes/pixel: 2,768,896 bytes/image

* Format of INMAP05 DEM Imagine files

http://gis.iu.edu [email protected]


Tiff format summary

TIFF Format - Summary

  • IMAGINE file format is tiled

  • Default output TIFF format for ERDAS IMAGINE is striped unless preferences changed

  • Tiled image has padding if rows and columns not divisible by 64 – increases image size without adding information

  • Tiled Tiff – compresses better with Winzip than striped image

    • Clark County DEM

      • Striped: 2.007 GB

      • Tiled: 1.759 GB

http://gis.iu.edu [email protected]


Acknowledgements

Acknowledgements

  • ArcSDE/Oracle ConsultantMannion Geosystems, LLC

  • Data Management Support, UITS

    • Michael Halla, Manager

    • Stephanie Snider

  • Research and Technical Services, UITS

  • Digital Storage Services Group, UITS

http://gis.iu.edu [email protected]


Uitsgis@indiana edu

[email protected]

Access data

http://gis.iu.edu


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