Object Based Image Analysis: Introduction to eCognition
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eCognition, developed by Trimble, is a geospatial software specializing in Object-Based Image Analysis (OBIA). It allows automated image analysis through rule-based classification, integrating seamlessly with GIS platforms. The software finds applications in environmental monitoring, forestry, agriculture, and disaster management, excelling in extracting information from high-resolution imagery. With customizable workflows, users can adapt the software to specific analysis requirements. eCognition supports various remote sensing data types, including multispectral and hyperspectral imagery, LiDAR, and radar data. Trimble's acquisition enhances its geospatial portfolio, providing comprehensive solutions for professionals in the field.
Object Based Image Analysis: Introduction to eCognition
- 1. KATHMANDU UNIVERSITY 2023 Object Based Image Analysis: Introduction to eCognition Lab-Assignment 7 Submitted To: Upama Koju Prepared By: Bikram Rawat ME-Geoinformatics 9869621034,9803329579 rawotbikram222@gmail.com
- 2. Lab-Assignment 7 2 LAB OBJECTIVES 2 Explain the difference between the capabilities of a pixel based classifier vs. an object based classifier. 3 Be familiar with some of the more common algorithms used in eCognition software. 1 Understand how rule sets work in eCognition software
- 3. Lab-Assignment 7 3 eCognition, developed by Trimble, is a geospatial software specializing in Object-Based Image Analysis (OBIA). It allows automated image analysis through rule-based classification, integrating seamlessly with GIS platforms. The software finds applications in environmental monitoring, forestry, agriculture, and disaster management, excelling in extracting information from high-resolution imagery. With customizable workflows, users can adapt the software to specific analysis requirements. eCognition supports various remote sensing data types, including multispectral and hyperspectral imagery, LiDAR, and radar data. Trimble's acquisition enhances its geospatial portfolio, providing comprehensive solutions for professionals in the field. INTRODUCTION TO ECOGNITION
- 4. Lab-Assignment 7 4 INTRODUCTION TO ECOGNITION CONTD... Customized rulesets Utilize the Python integration and combine image interpretation like object creation and classification with rulesets to define the required output. Quality and robustness Obtain robust and quality automation by combining the best of object-based image analysis and AI technologies Extracting information Quickly generate analytics and extract new geospatial information for use in GIS or to create specialized applications Scaled processing Drastically reduce processing time with server batch processing to accelerate the transformation of data to information. Source: https://geospatial.trimble.com/en/products/software/trimble -ecognition
- 5. Lab-Assignment 7 5 Step 1 BODY-METHODOLOGY Setting up eCognition Setup installation >> copying patch file in c drive >> Setting licensing path>>Rule Set
- 6. Lab-Assignment 7 6 Step 2 Step 3 BODY-METHODOLOGY Opening project CONTD....... Develop Rule set view
- 7. Lab-Assignment 7 7 Step 4 Step 5 BODY-METHODOLOGY Observing edit window CONTD....... Executing Reset
- 8. Lab-Assignment 7 8 Step 6 Step 7 BODY-METHODOLOGY Observing edit window/segmentation CONTD....... changing scale parameter
- 9. Lab-Assignment 7 9 Step 8 Step 9 BODY-METHODOLOGY Spectral Differencing (merging) CONTD....... Classification, observing pixel value
- 10. Lab-Assignment 7 10 BODY-METHODOLOGY CONTD....... What does the process step in Beach do? What element of image interpretation is this utilizing? Could you do this with a pixel based classifier like ERDAS Imagine’s unsupervised classifier? identification: recognition of certain target. A simple example is to identify vegetation types, soil types, rock types and water bodies. The higher the spatial/spectral resolution of an image, the more detail we can derive from the image. Yes we could do but it will be difficult as depend upon resolution of image.
- 11. Lab-Assignment 7 11 Classify St. Paul Campus Area of Interest BODY-METHODOLOGY CONTD....... Four band imagery is multispectral, which means that it is collected from several parts of the electromagnetic spectrum. The spectrum is the entire range of light radiation, from gamma rays to radio waves, including Xrays, microwaves, and visible light. Four band imagery, when delivered to a customer, typically contains red, green, blue, and near infrared bands. Only three bands can be viewed at one time in most software applications in use at present
- 12. Lab-Assignment 7 12 Step A Step B BODY-METHODOLOGY CONTD....... Edit Image Layer Mixing Modification window FSA PDF LINK
- 13. Lab-Assignment 7 13 Step C BODY-METHODOLOGY CONTD....... Edit Image Layer Mixing after naming layer
- 14. Lab-Assignment 7 14 Step D BODY-METHODOLOGY CONTD....... Setting up classes My final screen looked like this and I could not understand below 17 step. I thinkwe had to create new class new rule as in this report and section 7- page no 33 +, I want confirmation mam https://openjicareport.jica.go.jp/pdf/12150314_03.pdf