This module is designed to provide students with a working knowledge of advanced digital image processing techniques on a range of satellite images. Comprehensive review of the history, concepts, principles, analysis, and applications of remote sensing are presented and illustrated. Applications of remote sensing in real world problems are presented. Remote sensing data from a suite of sensors/platforms, including, advanced very high resolution radiometer (AVHRR), LANDSAT multispectral scanner (MSS)/thematic mapper (TM and EMT+), systeme’ pour I ‘observation de la terre (SPOT), IKONOS, and moderate resolution imaging spectroradiomater (MODIS) will be used. In addition RADAR remote sensing, thermal remote sensing, lidar and hyper spectral data processing will be covered. The module has an equal emphasis on the (1) physics of remote sensing (2) digital image processing of remote sensing data (3) application of remote sensing. Students will carry out an independent project that will take them through a condensed, yet complete research experience of identifying a science problem/equation, designing a research protocol, carrying out meaningful analysis and effectively addressing the equation at hand. Students will learn about the large archive of available geosciences digital data sets; will acquire a proficiency in combining and managing disparate data sets, and increased competence in computational skills required for digital analysis and visualization of data. This module focuses on various satellites image classification methods that can be used for thematic information extraction as well as digital change detection methods for measuring land use/ land cover change. The module includes computer exercises in advanced classification methods (e.g., fuzzy and decision tree classification), radiometric normalization, and change detection using leading satellite image processing software packages including Erdas imagine and IDRISI Kilimanjaro.
- Teacher: Vanum Govindu