Detecting natural succession on abandoned agricultural land in the

war-affected northeast Bosnia-Herzegovina using Landsat TM

imagery

Msc thesis under the supervision of: prof. Jacek Kozak

The aim of this study is to identify the magnitude of landscape change that occurred due to several impacts of the war on agricultural land in Bosnia-Herzegovina. Main question of this research is to find places where significant natural succession

process occurred. • Subregion of Bosnia and

Herzegovina was chosen because, this place was the focus of intense fighting, ethnic cleansing and therefore underwent a substantial depopulation. Moreover, it contains minefields. The land use of this area was predominantly agricultural where natural succession is the most expected.

• The study is also an attempt to use remote sensing data in research when fieldwork is too dangerous because of civil conflicts.

The study was carried out using two Landsat TM images

from June 1991 and July 2011

• Especially advantageous and interesting is possibility to conduct research in places where work in field is dangerous or difficult.

• Knowledge about natural succession process is important in environmental management and for this reason this topic is considered as relevant.

This study gives insight for expedience of using various change detection techniques for evaluation environmental changes.

• For this purpose qualitative and quantitative description environmental changes are necessary. Post-classification comparison was used as qualitative method and NDVI differencing as quantitative.

• Additionally changes were evaluated in dependency on elevation and distance from Srebrenica.

• Shuttle Radar Topography Mission (SRTM) elevation data were used to analyze changes in land cover in dependency on elevation

• For qualitative changes description supervised classification was conducted.

• In case of this study landscape heterogeneity poses a problem which results in high spectral variation within the same land-cover class. Supervised classification was chosen as a good method to reduce this problem. Maximum Likelihood Classification (MLC) was used as a classification algorithm.

• Visually and statistical classification accuracy assessment based on a sample of points was performed. Overall accuracy and overall kappa coefficient were calculated.

• High resolution images available in Google Earth were used for accuracy assessment purposes.

• To assess land cover changes in a quantitative way, NDVI differencing was used. This method was chosen because it emphasizes differences in the spectral response of different classes. NDVI differences were then analyzed separately for land cover classes identified at 1991 image.

• The image of 1991 was classified with a supervised approach into three classes ‘Settlements and agriculture’, ‘Water’ and ‘Forest’. To calculate NDVI characteristics for various areas, zonal mean function available in Erdas Imagine was used. Zones were the three delineated land cover classes.

• Additionally calculations were carried out separately for the Bosnian and Serbian parts of the study area. SRTM data were used to recognize variations of land cover changes expressed with NDVI differencing in dependency on elevation.

• Changes of NDVI were described in dependency on distance from Srebrenica. To calculate NDVI characteristics for various areas, zonal mean function was applied. Zones were classes of distance and classes of elevation.

Results• The overall land use classification accuracy for image

from 1991 is 92%. Result of classification is significantly better than random (at the 95 percent confidence level).

• Because the aim of this work was to identify natural succession and to assess the impact of the war (through depopulation or landmines) on agricultural land, the most important was selecting places with significant changes in vegetation. For this qualitative change detection purpose, results of supervised classification was performed for both Landsat scenes.

Post-classification differencing: crosstabulation of

classification results from 1991 and 2011.

To support the research hypothesis on land abandonment and

succession on agricultural land, NDVI for the pre-and post-war imagery was calculated. This provides a directly comparable measure of vegetation changes.

The analysis was focused only on agricultural areas, with an assumption that forests and water bodies had stable NDVI over time and were not affected by the war. The higher NDVI values reflect the higher amount of vegetation in abandoned agricultural land.

NDVI values from both sets of scenes were differenced and combined into a single map of NDVI differences for the

“Settlements and agriculture”

• Both positive changes (increase of NDVI) and negative changes (decrease of NDVI) were observed in ‘settlements and agriculture’ class,.

• The most significant positive NDVI changes were observed in Srebrenica region and also in cities Banovici and Zivinice. Quantitative analysis confirmed thesis that vegetation cover increased in abandoned agricultural land of study area.

• Moreover, NDVI differences increased also in the ‘Forest’ class in area around Srebrenica. This pattern in the ‘Settlements and agriculture’ class further confirms that there was a significant land abandonment around Srebrenica, with more intense natural succession than elsewhere in the study area.

• No significant variation of NDVI differences were observed in dependency on elevation, in the ‘Settlements and agriculture’ class. Mean NDVI differences in this class for all study area very similar to values obtained for particular elevation ranges. Similar patterns were observed in the ‘Forest’ class.

Key research findings and conclusions

• Comparison of independently classified images confirms thesis that amount of vegetation increased over the analyzed 20 years period. The greatest amount of vegetation growing on abandoned agricultural land was found in the Srebrenica region.

• Ethnic cleansing, re-settlement actions and danger caused by minefields were likely a major factor in process of ecological succession.

• Bosnian War have had significant influence on land use pattern. In case of this study, the war has not put land use systems toward intensification trajectories but allowed landscapes to ‘rewild’, and gave opportunities for conservation.

• It is difficult to forecast how long-lasting land use changes will be. The vegetation cover probably would increase in region of Srebrenica but the future of minefields remains open. Evidence from other areas suggests that farmland abandonment may persist for a long time.

• Both post-classification comparison and vegetation index differencing (NDVI differencing) were found as useful in analyzing natural succession. Qualitative analysis in post-classification comparison may be used as a complementary methods to quantitative approach such as vegetation index differencing (NDVI differencing).