Thomas Schneider

Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Munessa-Shashemene Landscape of the Ethiopian Highlands

The objective of this study was to analyze land use/land cover (LULC) changes in the landscape of Munessa-Shashemene area of the Ethiopian highlands over a period of 39 years (1973–2012). Satellite images of Landsat MSS (1973), TM (1986), ETM+ (2000), and RapidEye (2012) were used. All images were classified using object-based image classification technique. Accuracy assessments were conducted for each reference year. Change analysis was carried out using post classification comparison in GIS. Nine LULCs were successfully captured with overall accuracies ranging from 85.7% to 93.2% and Kappa statistic of 0.822 to 0.924. The classification result revealed that grasslands (42.3%), natural forests (21%), and woodlands (11.4%) were dominant LULC types in 1973. In 2012, croplands (48.5%) were the major LULC types followed by others. The change result shows that a rapid reduction in woodland cover of 81.8%, 52.3%, and 36.1% occurred between the first (1973–1986), second (1986–2000), and third (2000–2012) study periods, respectively. Similarly, natural forests cover decreased by 26.1% during the first, 21.1% during the second, and 24.4% during the third periods. Grasslands also declined by 11.9, 17.5, and 21.1% during the three periods, respectively. On the contrary, croplands increased in all three periods by 131, 31.5, and 22.7%, respectively. Analysis of the 39-year change matrix revealed that about 60% of the land showed changes in LULC. Changes were also common along the slope gradient and agro-ecological zones with varying proportions. Further study is suggested to investigate detailed drivers and consequences of changes.

Changes of ecosystem service values in response to land use/land cover dynamics in Munessa–Shashemene landscape of the Ethiopian highlands

Land use/land cover (LULC) dynamics alter ecosystem services values (ESVs), yet quantitative evaluations of changes in ESVs are seldom attempted. Using Munessa-Shashemene landscape of the Ethiopian highlands as an example, we showed estimate of changes in ESVs in response to LULC dynamics over the past four decades (1973-2012). Estimation and change analyses of ESVs were conducted, mainly, by employing GIS using LULC datasets of the year 1973, 1986, 2000 and 2012 with their corresponding global value coefficients developed earlier and our own modified conservative value coefficients for the studied landscape. The results between periods revealed a decrease of total ESVs from US

Object-orientated image analysis for the semi-automatic detection of dead trees following a spruce bark beetle (Ips typographus) outbreak

130.5 million in 1973, to US

Drivers of land use/land cover changes in Munessa-Shashemene landscape of the south-central highlands of Ethiopia

118.5, 114.8 and 111.1 million in 1986, 2000 and 2012, respectively. While using global value coefficients, the total ESVs declined from US

Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data

164.6 million in 1973, to US

Collecting in situ remote sensing reflectances of submersed macrophytes to build up a spectral library for lake monitoring

135.8, 127.2 and 118.7 million in 1986, 2000 and 2012, respectively. The results from the analyses of changes in the four decades revealed a total loss of ESVs ranging from US

Parameter Determination by RapidEye and TerraSAR-X Data: A Step Toward a Remote Sensing Based Inventory, Monitoring and Fast Reaction System on Forest Enterprise Level

19.3 million when using our own modified value coefficients to US

Scenario modelling of land use/land cover changes in Munessa-Shashemene landscape of the Ethiopian highlands

45.9 million when employing global value coefficients. Changes have also occurred in values of individual ecosystem service functions, such as erosion control, nutrient cycling, climate regulation and water treatment, which were among the highest contributors of the total ESVs. However, the value of food production service function consistently increased during the study periods although not drastically. All in all, it must be considered a minimum estimate of ESV changes due to uncertainties in the value coefficients used in this study. We conclude that the decline of ESVs reflected the effects of ecological degradation in the studied landscape and suggest further studies to explore future options and formulate intervention strategies.

Multispectral Remote Sensing of Invasive Aquatic Plants Using RapidEye

The survey and continuing inventory in the Bavarian Forest National Park of deadwood areas resulting from a spruce bark beetle calamity are being performed by means of visual evaluation of colour infrared aerial photographs. With the aid of the object-oriented image analysis software eCognition, it was possible to develop a partially automated method for this purpose. In order to verify the classification results, a test area was classified, and the results compared with those obtained by the previously used method. In addition, the classification results from two consecutive years were compared, and accuracy assessment methods were used to scrutinize the results. Classification in the deadwood areas yielded a total classification accuracy of 91.5%. In regard to objectivity and degree of detail, the newly developed method is significantly superior to the former method, which is based on visual interpretation with a stereo workstation. One problem, however, was the insufficient spatial accuracy of the respective orthophotos. Because of this, it was not possible to detect changes over the course of specified time intervals. Therefore, a practical application of this method would require that the orthophotos from various dates or times be precisely spatially assigned. This requirement can be achieved with the production of new orthophotos.

Exploring Digital Surface Models from Nine Different Sensors for Forest Monitoring and Change Detection

Understanding drivers of changes in land use/land cover (LULC) is essential for modeling future dynamics or development of management strategies to ameliorate or prevent further decline of natural resources. In this study, an attempt has been made to identify the main drivers behind the LULC changes that had occurred in the past four decades in Munessa-Shashemene landscape of the south-central highlands of Ethiopia. The datasets required for the study were generated through both primary and secondary sources. Combination of techniques, including descriptive statistics, GIS-based processing, and regression analyses were employed for data analyses. Changes triggered by the interplay of more than 12 drivers were identified related to social, economic, environmental, policy/institutional, and technological factors. Specifically, population growth, expansion of cultivated lands and settlements, livestock ranching, cutting of woody species for fuelwood, and charcoal making were the top six important drivers of LULC change as viewed by the local people and confirmed by quantitative analyses. Differences in respondents’ perceptions related to environmental (i.e., location specific) and socioeconomic determinants (e.g., age and literacy) about drivers were statically significant (Pxa0=xa00.001). LULC changes were also determined by distances to major drivers (e.g., the further a pixel is from the road, the less likelihood of changes) as shown by the landscape level analyses. Further studies are suggested targeting these drivers to explore the consequences and future options and formulate intervention strategies for sustainable development in the studied landscape and elsewhere with similar geographic settings.