IMPRS Summerschool 2018

IMPRS 2018 MPI BGC Jena, 3.9.2018

PD Dr. S. Hese (Friedrich-Schiller-University Jena, Department for Earth Observation, soeren.hese@uni-jena.de)

Introduction to image processing for Earth observation data analysis: – Landcover Classification and Multispectral Data Analysis using the ENVI/IDL Image Processing Environment

Data: Landsat TM5 subset (LS-TM5-02071993-SUBSET-UTM32.envi.hdr), 30 m spatial resolution, UTM 32, Datum:WGS84, BSQ file structure.

ENVI 5.4 Hands-On Exercises:

1. Software Environment Setup:
   1. ENVI working directory setup
   2. ENVI .hdr & external format import ()
   3. Linking displays within ENVI
   4. Window Management in ENVI Classic
2. Subsetting
   1. Data spectral sub-setting (deleting channel 6)
   2. Spatial sub-setting using ROI Tools
3. Header Data Analysis
   1. spectral properties,
   2. geocoding information,
   3. header information,
   4. band statistics & histograms,
   5. band scatterplots
   6. BSQ /BIL Setup
4. Data Preprocessing
   1. Orthocorrection & ATCOR (demo in PCI EASI/PACE)
   2. Contrast stretching / histogram modifications on display and with LUT
   3. Filtering with spatial filters, low pass, high pass, custom filter functions)
5. Texture filtering with Co-Occurrence masks
6. “Band Math” tool syntax (IDL) and NDVI calculation into a new floating point image file
7. Landcover classification
   1. Preparation and design of ROIs for supervised classification,
8. ROI management
9. Signature separabilit
10. Scatterplot visualisation
11. n-dimensional visualization

1. Maximum likelihood classification with ROIs
2. Calculation of area statistics from thematic classification results

Post-classification analysis – confusion matrix using ROI ground truth

IMPRS2018-ENVI54.zip