GEOG-4045 Environmental Remote Sensing Larry Kiage & Naresh K. Sonti Evaluation of land loss and or gain in the Indus River delta using Landsat Enhanced Thematic Mapper GEOG-4045 Environmental Remote Sensing Project Presentation By Larry Kiage & Naresh K. Sonti Spring 2003

Contents Introduction Problem Statement Methodology Results Conclusion Research Question Methodology Classification Change detection Principal Component Analysis Results Conclusion

Introduction East coast of Pakistan 200 kms out of 900 kms of coastline. 100 million people. Human intervention endangers future of the delta. (Up to 78% of Indus water is diverted for irrigation and damming).

Statement of the Problem This study is geared towards conducting land cover/use change detection in the Indus River delta, coastal Pakistan, using the Enhanced Thematic Mapper images of the delta acquired on a temporal scale of 8 years (1992 and 2000) with a view of establishing whether there has any land gain or loss in the delta and to infer into the possible causes of the changes in land cover.

Research Questions What changes have occurred in the delta between 1992 and 2000 in terms of land loss/gain? What changes have occurred in vegetation? Which areas have experienced most change? Which spectral bands are most appropriate for the change detection? What are the likely causes of these changes?

Methodology Sub setting Classify Change detection PCA Unsupervised Matrix Analysis PCA Plate 1(a): Indus River Delta (Path: 152, Row:043, Scene ID: LT5152043009211810, acquisition date: April 27, 1992) Plate 1(a): Indus River Delta (Path: 152, Row:043, Scene ID: LE7152043000006850, acquisition date: March 8, 2000)

Methodology Subsets Plate 2 (a): Subset of Indus River Delta (1992) used for change detection Plate 2 (b): Subset of Indus River Delta (2000) used for change detection

Methodology … Choice of ETM Bands. Band 4 & 5 were selected: determining vegetation types and delineating land and water surfaces.

Methodology … Major considerations in choice of image Cloud free (less than 10% cloud cover). Same season To limit sun angle differences and azimuth. Images acquired for the March/April period water level in the river is optimum. June – September : Flood season December – February: Dry season

Methodology … Approaches adopted for Change detection First Approach: Classifying band 5 (1992 & 2000) into 2 classes (Land and water). Unsupervised classification (20 classes) Supervised classification (2 classes: Land and Water GIS Analysis (Matrix Method).

Approach 1 1992 2000

Results Dominant changes Land/water interface Water (unchanged) Land gain Land loss Land (unchanged)

Results … Results of Matrix Analysis showing Land loss/gain between 1992 and 2000. No. of Pixels 1992 2000 Sq Miles Hectares Change 238649 water 74.84 19384.27 Water (no change) 29204 land 9.15 2372.095 Land gain 72601 22.76 5897.016 Land loss 708122 222.07 57517.21 Land (no change)

Methodology … Second Approach: Classifying band 4 (1992 & 2000) into general vegetation, land and water classes. Lack of Reference data. Change detection.

Results … 10% change 20% change

Principal Component Analysis Multispectral image data analysis is the presence of extensive interband correlation, i.e., images generated by digital data from various wavelength bands often appear similar and convey essentially the same information. Principal component analysis (transformation) reduces such redundancy in multispectral data. When applied as a preprocessing procedure to Unsupervised classification, this transformation increases the computational efficiency of the classification process.

PCA Component 2 Component 3 Component 4 Component 5 Original PCA Image Component 6 Component 7 PCA Component # Value 1 2720.657 2 230.4535 3 65.25159 4 40.50979 5 14.85401 6 8.26669 7 3.106021

Principal Component Analysis Value Percentage 1 2720.657 88.24 2 230.4535 7.47 3 65.25159 2.11 4 40.50979 1.31 5 14.85401 0.48 6 8.26669 0.26 7 3.106021 0.10

Conclusions Significant changes in land cover occurred during the 8-year period from 1992 to 2000. The most affected land areas are those that border the ocean and along tidal channels which were lost during the period under review.

Conclusions… The areas under water cover gained significantly and this has been interpreted as to be a result of reduction in water and subsequent sediment discharge of the Indus River. Because of human intervention in the natural delta building processes of the Indus, its future looks bleak.

Conclusions… Continued reduction in mangrove vegetation will not only deprive land protection from river and tide erosion but will be catastrophic to the biodiversity the many marine fauna that use the mangrove habitats as spawning and nursery grounds.

Thank you!