1. APPLIED REMOTE SENSING TECHNOLOGY TO ANALYZE THE LAND COVER/LAND USE CHANGE AT TISZA LAKEBy
Yudhi Gunawan * and Tamás János **
* Department of Land Use and Region Development
** Department of Water and Environmental Management
UNIVERSITY OF DEBRECEN

2. CONTENTS STUDY AREA ENVIRONMENTAL ISSUES MATERIALS AND METHOD
INTRODUCTION
STUDY AREA
ENVIRONMENTAL ISSUES
MATERIALS AND METHOD
RESULTS AND DISCUSSION
CONCLUSIONS AND SUGGESTIONS

3. INTRODUCTION OBJECTIVE
to study the land cover change and fluctuation of the environmental conditions at the Tisza Lake and surrounding area using satellite imagery

4. Figure 1. Tisza Lake as the study area
Tisza Lake is an artificial lake that was formed by the construction of the Water Power Station of Kisköre, located in the northern part of Hungary at 20º26’ to 20º52’ E and 47º43’ to 47º25’ N (UTM/WGS 84)
Figure 1. Tisza Lake as the study area

5. ENVIRONMENTAL ISSUES
After the collapse of the command economy and industrial structures, because of the change of energy source to nuclear power, the rising need of natural protection and the increasing purposes of tourism, the objectives of this lake have grown and therefore there are urgent demands for appropriate strategies to avoid contradiction among purposes.

6. MATERIALS AND METHOD Landsat TM5, 08-07-1987 Landsat ETM7, 20-08-2000
Orthophoto
Topography Map
CLC100

7. Unsupervised Classification
METHODOLOGY
Preprocessing
- Image rectification and co-registration
- Making subset
Unsupervised Classification
- Using ISODATA method
- Applied to 7 LC/LU classes based on CLC100
Classification Comparison
- Using accuracy assessment with > 250 points

8. Figure 2. Model maker to perform change detection
METHODOLOGY
Figure 2. Model maker to perform change detection
Change Detection
- Multi-date composite
image method
- Image differencing
technique for modeling
Investigation of the Changes

9. RESULTS AND DISCUSSION
Image Rectification and Restoration
- Landsat TM, The RMSE is 13 m
Figure 3 : Control point errors for Landsat TM co-registration
- Landsat ETM, The RMSE 14 m
Figure 4 : Control point errors for Landsat ETM co-registration

10. RESULTS AND DISCUSSION
Classification
Figure 5: Unsupervised classification of Landsat TM

11. RESULTS AND DISCUSSION
Figure 6: Unsupervised classification of Landsat ETM

12. RESULTS AND DISCUSSION
Classification Comparison
Figure 7: Location of the 256 random sampling points shown in
the Landsat ETM viewer (left) and CLC100 viewer (right)

13. RESULTS AND DISCUSSION
Table 1. Error Matrix Resulting from Classifying Training Set Pixels at Landsat TM

14. RESULTS AND DISCUSSION
Table 2. Error Matrix Resulting from Classifying Training Set Pixels at Landsat ETM

15. RESULTS AND DISCUSSION
The overall accuracy of TM (26%) and ETM (38%) indicates a fairly low agreement with the reference CLC100 classification;
- Paper based interpretation was applied in CLC100, Hungary and then it was transformed to digital form by scanning (Maucha, 2004)
Assessing 2 levels of LC/LU categories CLC100 was not representative enough
- The gap over 3 or 10 years

16. RESULTS AND DISCUSSION
Table 3. Kappa Index of Landsat ETM unsupervised classification

17. RESULTS AND DISCUSSION
Table 4. Kappa Index of Landsat TM unsupervised classification

18. RESULTS AND DISCUSSION
It might be because of the big change in land management and land reform in agricultural area. (Márkus, et al (2003) reported that in the 1990s, parallel with the political changes, the transformation of Hungarian agriculture also began, the need of conservation area and the expansion of urbanization.

19. RESULTS AND DISCUSSION
Change Detection
Table 5. The summary matrix of the change detection between Landsat TM 1987 and Landsat ETM 2000

20. RESULTS AND DISCUSSION
- Water-body (15%)
relatively big drought during the 1990’s and then when the normal precipitation returned, most of the wetlands were covered back by water
Wetlands
- Forested Area (13%)
due to the new environmental protection policy in Hungary

21. RESULTS AND DISCUSSION
Except Water body
Forest (26%), Wetlands (14%)
Since the Hungarian agricultural production exceeds the limits of the EU regulations, the less fertile soils are reannexed to natural conservation or the process of forestation has started
Arable land
Settlements;19% (Recreational Area, Closed Garden)

22. RESULTS AND DISCUSSION
Misinterpretation on Settlements
The mixed pixels
Environmental analysis
For the moment it could not be carried out due to time limitation, missing data or difficulties to obtain data of total suspended solids, heavy metals, sediment quality, etc related to land cover change.

23. CONCLUSION AND SUGGESTION
The accuracy assessment was fairly low;
- Other classification method should be applied for instance Supervised Classification
The mixed pixels have to be overcome by applying Spectral Mixture Analysis and Fuzzy classification
Increase the natural protection area (e.g wetlands, forest)
The CLC100 is not representative enough;
- Therefore further study has to be done using CLC50 that has been updated to the geographic condition of Hungary
The environmental analysis has not been carried out as planned but further research is still going on

24. KÖSZÖNÖM A FIGYELMET !