Introduction Analysis and applications of remote sensing imagery Instructor: Dr. Cheng-Chien LiuCheng-Chien Liu Department of Earth Sciences National Cheng Kung University Last updated: 15 June 2015 Chapter 0

Syllabus  Course name: Analysis and applications of remote sensing imagery  Credit: 3  Prerequisite: Graduate students Undergraduate students of the third or four year Introduction to remote sensing Digital image processing  Time: Tuesday 8:10 – 10:00 Wednesday 13:10 – 14:00 Place: Room 201, Building of Computer Center  Teaching Assistant: Conifer Chang

Objectives  Introduce students The fundamental concepts of Analysis and applications of remote sensing imagery The training in a commercial software (ENVI) of digital image processing  Students will learn The techniques of enhancement and quantification of digital imagery acquired by remote sensing  Students are expected Design and implement a practical project using techniques/knowledge learned from this course

Textbook  Remote sensing and image interpretation, 5th edition, T.M. Lillesand, R.W. Kiefer and J.W. Chipman. John Wiley & Sons, 2004 偉明代理（成大圖書部可代訂）  ENVI Tutorials, 2003 edition, Research System Inc, 2003.

References  Remote sensing, models, and methods for image processing, Robert A. Schowengerdt, second edition, San Diego, Academic Press,  Introductory Digital Image Processing: A Remote Sensing Perspective, John R. Jensen, second edition, Prentice Hall, 1995.

Schedule  Introduction  Reading images  Image rectification  Image restoration  Image enhancement  Image classification  Data merging  GIS integration  Hyperspectral image analysis

Some questions  Who am I?  Why are we here? You and I, …  Why exams? Acquire knowledge, …  Why taking lectures? Save time and efforts, …  Why Lab evaluation? Keep on the right track, …

Responses  Lecture notes on web  Three ways to be master of AARSI Practice  Strategy 10 min on-site test every week On-site (mid-term and final) exams Monitoring student’s progress and grade  On-line report everybody’s grade every week

Grade  Weekly on-site exams 60%  Term project 40% Base on at least one SCI paper A short essay

Office hours  Monday: 14:00 – 17:00  Wednesday: 15:00 – 17:00  Friday: TGIF party  Anytime if necessary

Some issues  Representative Textbook  Name, Student ID number, Department/Year, Cell phone number, address, (advisor’s name)  Introduce yourself Why take this course Background (computing) Research interests Accessible computer resources

Getting start with ENVI  Install ENVI Temporal license ######## EVALUATION LICENSE INFO ######## Product: ENVI+IDL 4.0 Expiration: 18-Mar-2005 Key: 761E504EA8774A ########### END LICENSE INFO ############ Demo CDs  Start ENVI  Data location Tutorial data location: C:\RSI\envidata FTP site: ftp.rsinc.comftp.rsinc.com  enviprog  Load a gray scale image

Getting start with ENVI (cont.)  Display Scroll window Image window Zoom window  Some helps Window Finder Display Information Resize Preference  Smooth  Style

Getting start with ENVI (cont.)  Mouse control Three-button mouse Symbol boxes  “+” box: left, middle, right button  “-” box: left, middle, right button  “ ” box: left, middle, right button The meta scroll window  Middle button Mouse button description Summary

Getting start with ENVI (cont.)  Main image display menu bar Profile Sharpening Auto placement off Preference Window style  Subset Spatial Spectral  On-line help

Getting start with ENVI (cont.)  ENVI configuration Preference Cache size setting Changing default directory  Closing files

Self Test  Setup your ENVI preference Data directory: (envidata directory) Output directory: (your personal directory) Display style: as next page  Open file  Enable cross-hair in zoom and image window

Batch mode ENVI  Why batch mode  Initiating batch mode envi, /restore_base_save_files envi_batch_init envi_select Envi_batch_exit  Online help class_doit, envi_doit Common keywords Example program

Batch mode ENVI (cont.)  Opening envi files in batch mode $ and & filename = envi_pickfile(title = 'open boulder data') help, filename envi_open_file,filename, r_fid=bldr_fid Envi_select, dims=bldr_dims, fid=bldr_fid2, pos=bldr_pos, title=‘select BoulderTM’ print, ‘dims =‘,bldr_dims & ‘pos = ‘, bldr_pos Try spatially and spectrally subset envi_file_mng, id = bldr_fid, /remove Open_ids = envi_get_file_ids() Print, open_ids

Batch mode ENVI (cont.)  Collecting info from the ENVI header file = envi_pickfile() envi_open_file, file, r_fid = fid_cup envi_file_query, fid_cup, ns=ns, nl=nl, nb=nb, data_type=dt, interleave=inter, fname=fname, sname=sname, bnames=bnames, wl=wavelengths, file_type=ft Nir_bands = where(wavelengths ge 2.20 and wavelengths lt 2.25, count) print, bnames[nir_bands] dims = [-1L, 0, ns-1, 0, nl-1] pos = nir_bands

Batch mode ENVI (cont.)  Reading the Cuprite AVIRIS data band193 = envi_get_data(fid=fid_cup, dims=dims, pos=pos[0]) help, band193 window, /free, xsize=ns, ysize=nl Tvscl, band193

Self Test  Write an IDL pro file to Open the file ‘bhtmref.img’ Locate the band between 0.6 and 0.7  m Show the band in a new window NDVI = (NIR – Red) / (NIR + Red), show the result of NDVI in a new window