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Unsupervised Classification of Higgins Beach and Vicinity Remote Sensing (GEO 205) Author: Stanley Max Final Project Using ERDAS Imagine 8.7 to Conduct an Unsupervised Classification of Higgins Beach and Vicinity

Remote Sensing (GEO 205)

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Remote Sensing (GEO 205). Final Project. Using ERDAS Imagine 8.7 to Conduct an Unsupervised Classification of Higgins Beach and Vicinity. Author: Stanley Max. Why Have I Chosen to Study This Area?. Several types of land-cover: Residential Wooded suburban River Marsh Beach Ocean - PowerPoint PPT Presentation

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Page 1: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Remote Sensing (GEO 205)

Author: Stanley Max

Final Project

Using ERDAS Imagine 8.7 to Conduct an Unsupervised Classification of

Higgins Beach and Vicinity

Page 2: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Why Have I Chosen to Study This Area?

• Several types of land-cover:ResidentialWooded suburbanRiverMarshBeachOcean

• My parcel of land

Page 3: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

• 6 km2 = 600 ha• My parcel shown in red

Page 4: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

• 6 digital orthophoto quarter quadrangles (DOQQs) from Maine Office of GIS

• Mosaicked with ERDAS Imagine 8.7• Unsupervised classification

13 classes with 13 iterations; 98% convergence

Completed all 13 iterations; 95.6% convergence

Page 5: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Let us view the classified image.

Page 6: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

• Classified image• Composed as a map• Saved as a TIFF• Converted to a JPEG• Exported into PowerPoint

• Poor color fidelity• Looks too blue• Actual classified image

resembles the original closely

Page 7: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

The following pie chart depicts all the classifications I

obtained using ERDAS:

Page 8: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

TreesShallow water; TreesDeep waterWater with sedimentGrass; Wet sandDry sandPavement; SandSand-soil combination

Class nameSand-soil combination2.5%

Pavement; Sand7.3%

Dry sand10.1%

Grass; Wet sand33.5% Water with sediment

15.5%

Deep water18.3%

Shallow water; Trees9.2%

Trees3.7%

Proportion of Territory Filled by Each Land-Cover Type

Total area = 600.210 ha

Page 9: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

TreesShallow water; TreesDeep waterWater with sedimentGrass; Wet sandDry sandPavement; SandSand-soil combination

Class nameSand-soil combination2.5%

Pavement; Sand7.3%

Dry sand10.1%

Grass; Wet sand33.5% Water with sediment

15.5%

Deep water18.3%

Shallow water; Trees9.2%

Trees3.7%

Proportion of Territory Filled by Each Land-Cover Type

Total area = 600.210 ha

We can see that grass, sand, and

water predominate — which makes

sense.

Page 10: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

I also ran a supervised classification.

Page 11: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Page 12: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Let us examine the pie chart depicting the supervised classifications I obtained

Page 13: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Deep waterShallow waterMarshPavementGrassRoofDry sandWet sand

Class nameWet sand1.9%Dry sand

1.3%

Roof42.7%

Grass16.1%

Pavement3.0%

Marsh13.0%

Shallow water4.0%

Deep water17.9%

Supervised ClassificationProportion of Territory Filled by Each Land-Cover Type

Total area = 600.210 ha

Page 14: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Deep waterShallow waterMarshPavementGrassRoofDry sandWet sand

Class nameWet sand1.9%Dry sand

1.3%

Roof42.7%

Grass16.1%

Pavement3.0%

Marsh13.0%

Shallow water4.0%

Deep water17.9%

Supervised ClassificationProportion of Territory Filled by Each Land-Cover Type

Total area = 600.210 ha

• Roof classification predominates!

• Marsh appears as a separate class.

Page 15: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

What Issues Have We Encountered in the Study?

• Excellent resolution of DOQQs (approximately 15 cm) makes classification analysis difficult

• Need non-visible bands• Tremendous computer power needed• Very slow to run• Even negative results have value

Page 16: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Angus the dog lying on the back porch. The photograph looks East by Southeast. In the immediate background the marsh is visible. Just behind

lies the Spurwink River, with Cape Elizabeth in the distance on the left.

Page 17: Remote Sensing (GEO 205)

Unsupervised Classification of Higgins Beach and Vicinity

Happy Holidays