School of Water ResourcesIndian Institute of Technology

Kharagpur

Seminar on,

Digital Change Detection

TechniquesUnder the Guidance Under the Guidance of,of,Prof. M. D.

Behera Presented by,

Mr. Santosh Navnath Borate

Roll No. 08WM6002

Date 6-3-2009

IntroductionDigital Change Detection

What is Digital Change Detection ?

Why it is required?

General Steps Used to Conduct Digital Change Detection Using Remote Sensor Data

1. State the Change Detection Problem Define the study areaSpecify frequency of change detection Identify classes from appropriate land cover classification

system

2. Consideration of Significant factors When Performing Change Detection

Remote sensing system considerations - Temporal Resolution - Spatial Resolution and Look Angle

- Spectral Resolution- Radiometric Resolution

Environment Considerations - Atmospheric condition - Soil Moisture condition - Phenological cycle characteristics - Tidal stage

3. Conduct image processing of remote sensor data to

extract upland wetland informationAcquire appropriate change detection data Preprocess the multiple-date remotely sensed data Select Appropriate Change Detection AlgorithmPerform change detection using GIS algorithms

4. Conduct Quality Assurance and Control Program

Assess spatial data qualityAssess statistical accuracy

5. Distribute ResultsDigital productsAnalog (hardcopy) products

Selecting the Appropriate Change Detection Algorithm1. Change Detection Using Write Function

Memory Insertion2. Multi-date Composite Image Change Detection3. Image Algebra Change Detection 4. Post-classification Comparison Change

Detection5. Multi-date Change Detection Using A Binary

Mask Applied to Date 2 6. Multi-date Change Detection Using Ancillary

Data Source as Date 17. Manual, On-screen Digitization of Change

1. Change Detection Using Write Function Memory Insertion

It is possible to insert individual bands of remotely sensed data into specific write function memory banks (red, green, and/or blue) in the digital image processing system

2. Multi-date Composite Image Change Detection

3. Image Algebra Change Detection (Band Differencing)

It is possible to simply identify the amount of change between two images by image differencing

Dijk = BVijk(1) - BVijk(2) + c

4. Post-classification Comparison Change Detection

This is the most commonly used quantitative method of change detection

- It requires rectification and classification

- images are compared on pixel by pixel basis

5. Multi-date Change Detection Using A Binary Mask Applied to Date 2

- very effective method

- Date1 –base image

- Date 2- earlier image or later

image

- spectral change image is then

recorded in to binary mask file

6. Multi-date Change Detection Using Ancillary Data Source as Date 1

-Exist land cover data

-Prepare NWI maps

7. Manual, On-screen Digitization of Change

Fig-Sullivans Island before Hurricane Hugo 1988

-Buildings with no damage

-Buildings partially damage

-Buildings with completely damage

-Buildings that were moved

-Areas of beach erosion due to Hurricane Hugo

• This article finds the Remote Sensor System and environment variables that must be considered in RS Change Detection Techniques

• One time inventory of natural resources is often limited value but due to several techniques of change provides series of inventories which provide information on sources at risk.

• Change information is becoming more important in local, regional, global environment monitoring

Summary

16

Phenological Cycle CharacteristicsVegetation Phenology

Fig 2 Landsat Thematic Mapper scenes of the Fort Moultrie quadrangle near Charleston, SC obtained on November 11, 1982 and December 19, 1988.

Fig-Demonstrate the post-classification comparison change detection method, consider the Kittredge (40 river miles inland from Charleston, S. C.) and Fort Moultrie,

Fig- land cover change classes summarized in the change matrix

Fig- Spectral Change Mask File Fig-Change Classes derived from Analysis