Lesson 10: Applied Image Analysis for the Urban Environment

In this lesson, you will learn how to applied image analysis for urban planning and management.

Content

• Multi-spectral Classification for Urban Land Use/Land Cover (LULC) Mapping

  • Unsupervised classification

  • Supervised classification

• Urban LULC Change Detection
• Urban Features Extraction techniques

Lesson Slides and Hands-on Notes

• Lesson slides in html format.

• Hands-on Exercise 10 in html format.

References

Articles

• Sandipta Das . Dasharatha P Angadi (2022) “Land use land cover change detection and monitoring of urban growth using remote sensing and GIS techniques: a micro-level study” GeoJournal, Vol. 87, pp. 2101–2123.

• Jane Ferah Gondwe, Sun Lin, Rodger Millar Munthali, “Analysis of Land Use and Land Cover Changes in Urban Areas Using Remote Sensing: Case of Blantyre City”, Discrete Dynamics in Nature and Society, vol. 2021, Article ID 8011565, 17 pages, 2021. https://doi.org/10.1155/2021/8011565

• Geymen, Abdurrahman ; Baz, Ibrahim (2007) Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area, Environmental Monitoring and Assessment, Vol.136 (1-3), p.449-459.

• Yin, Jie et. al. (2010) Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979–2009) in China, Environmental Monitoring and Assessment, Vol.177 (1-4), p.609-621.

• Praveen Kumar Mallupattu* and Jayarama Reddy Sreenivasula Reddy (2013) Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India, The Scientific World Journal (online)

• Ali Alzahrani and Awos Kanan (2022) “Machine Learning Approaches for Developing Land Cover Mapping” Applied Bionics and Biomechanics, Volume 2022, 8 pages.

QGIS Methods

• Landcover change detection using QGIS. Land use landcover change detection

• Step-by-Step: Land Cover Change Detection through Supervised Classification.

• Land Cover Classification using the Semi-Automatic Classification Plugin version 7

• Unsupervised Classification using the Semi-Automatic Classification Plugin version 7

• Random Forest Classification using the Semi-Automatic Classification Plugin for QGIS

• Image Conversion to Reflectance using the Semi-Automatic Classification Plugin version 7

• SCP Tips: Import ROIs from shapefile

• SCP Tips: ROI Pointer

• Object-based Image classification in QGIS || OBIA !! || A complete Tutorial

• Accuracy Assesment In Quantum GIS || A complete Tutorial

• Calculating Land surface temperature using Landsat 8 Imagery || QGIS Tutorial

QGIS Plugin

• Semi-Automatic Classification Plugin (SCP) for QGIS
• Orfeo toolbox Plugin for QGIS
• OTB Plugin installation
• dzetsaka: Classification tool supports Random Forest, KNN and SVM for supervised classification of multi-spectral satellite data.
• Neural Network MLPClassifier provides a supervised classification method for multi-band passive optical remote sensing data based on the Neural Network MLPClassifier by scikit-learn.
• GEOSYS Plugin
• PCA4CD - PCA for change detection
• buildseg: QGIS plugin for building extraction
• Terminus
• Tree Density Calculator
• RS&GIS