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The achievement and monitoring of a good environmental status on continental shelf seas requires
the use of acoustic remote sensing techniques due to their range. The interpretation of acoustic signals
for the identification of benthic communities, however, is still in its infancy. In this thesis, the results
of two field campaigns conducted in a sandy environment off the shore of Sylt Island (North Sea)
utilizing ship- and lander-based acoustic and optical remote sensing techniques are discussed. The
objective of the thesis is a better knowledge of the impact of the polychaete Lanice conchilega on
physical seafloor properties, especially roughness at a cm to mm scale, which is relevant for
understanding acoustic scatter. The results show a clear impact of L. conchilega on roughness even in
sparse populations of less than 2% coverage. However, these sparsely populated areas could not be
reliably identified with acoustic data; a denser population of L. conchilega provided a clearer signal for
the acoustic remote sensing methods. The results are promising regarding the broader use of acoustic
remote sensing techniques for environmental monitoring in selected habitats, although the
determination of minimum population thresholds that can be identified will require further studies.
All-embracing human activities have transformed one-third to one-half of the Earth’s land surface. There is a strong correlation of human well-being with ecosystem function, including poverty alleviation programs as well as enhancements of the health sector. To assess and evaluate the progress and outcome of initiatives stringent periodic observation is necessary. The presented approach combines the strengths of remote sensing and GIS analysis with social research applications. The Bach Ma National Park as an area under investigation was designated as protected area in 1991 and extended in 2008. The national park is uninhabited, but in the surrounding buffer zones approximately 62000 to 79000 people live in rural areas and in mostly impoverished conditions. The comprehensive nature conservation efforts of the Vietnamese Government during the last two decades has led to growing forest coverage of both plantation and natural forests. Nevertheless, the decreasing biodiversity and ongoing illegal logging and hunting activities in the national park are seen as major threats to conservation initiatives in the future. The remote sensing component consists of an analysis of a time series of Landsat images with seven steps ranging from 1973 to 2010. The resulting land cover analysis had 13 different classes. The accuracy assessment revealed an overall accuracy ranging from 84 to 90%. The basis for the second monitoring component was the Landsat images. A total of 25 different landscape metrics on the landscape, class, and patch level were calculated by FRAGSTATS. The third monitoring component is itself divided into two parts. This part consists of a qualitative social research study with 26 expert interviews. The second part consists of 61 standardized questionnaires and an evaluation by SPSS. The assessment reveals a more or less stable forest cover, but with a considerable degradation process during the last four decades. Urban areas outside of the national park have increased in size considerably. For dense and medium forest patches an increasing fragmentation and isolation of patches was observed. Patches of natural forests and habitats of thousands of species have declined dramatically, a trend that is related to a decreasing core area characterised by its undisturbed conditions. The Landsat images and landscape metrics reveal the major differences between the national park and surrounding areas. Despite extensive alterations near the border, remaining forest patches in the national park are still bigger and less fragmented. Nevertheless, the third monitoring component revealed undiscovered changes in the forest beyond the possibilities of used images and metrics. It includes illegal logging and hunting activities. Non-timber forest products are similar to faunistic species collected for both the subsistence of the local residents and associated markets as important sources of income. Based on this bisection, local residents as well as certain strangers are responsible for the activities in the forest. The plan of national park management is to intensify existing monitoring and patrolling in the forest to limit the exploitation and impact in relevant zones. Furthermore, the importance of a network of protected areas has attracted increasing attention. The assessment of the questionnaires reveals that deforestation and also reforestation were the key aspects of historical land cover change. Additionally, for the local residents the conversion of forests into arable land as income alternative is of major importance. Capacity development is not only one priority of the Bach Ma management but also of the international community for all of Vietnam. The tourism industry, one of the most promising opportunities of recent years, stands to support both national park management as well as the local residents. For local residents the extraction of non-timber forest products is an essential portion of the income. The current pilot policy 126/QD-TTg in the extension zone of the national park and research on an appropriate sharing mechanism is of the utmost importance. The established and presented monitoring components are cost-effective and can be used to regularly assess the land cover change of a protected area. They can be implemented together or individually into existing monitoring schemes. A smart combination of pre-existing datasets is necessary to overcome the inconsequential amount of money for monitoring procedures. Supplemented by socio-economic monitoring and the demands as well as impacts of human activity need to be integrated. These extensive requirements for prospective monitoring are only feasible with comprehensive and reliable collaborations.
A large portion of the earth's surface is covered with various vegetation classes (i.e. grassland, wetland and agricultural area, forest) of many diverse species and canopy configurations. The ability to assess and to monitor canopy parameters, such as biomass, leaf area index, and vegetation water content, is of vital importance to the study of different agronomic processes. Remote sensing techniques provide a unique capability towards probing different vegetation types and canopy by operating at different bands, observation angle etc. Over the past decades, significant progress has been made in remote sensing techniques of land processes specially vegetation characteristics through development of advanced ground-based, airborne and space-borne microwave sensors, methods and approaches such as theoretical, semi-empirical and empirical models, needed for analyzing the data. These activities have sharply increased in recent years since the launch of different active and passive satellites and sensors. Remote Sensing (RS) science and techniques combined with ground truth data can provide new tools for advanced agricultural crop applications. It has been demonstrated that RS has the ability to estimate biophysical parameters of agricultural crops over time at local, regional, and global scales. In this study, RS images in visible/near infrared (VIS/NIR) domain as well as microwave domain combined with ground truth data were used to assess biophysical parameters of agricultural crop during their whole growing season at Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site in North East Germany. Ground truth studies were carried out for 31 weeks during 17th April – 13th November 2013 over three crop lands including winter wheat, barley and canola. Landsat 8 OLI, Landsat 7 ETM+ were used for the VIS/NIR studies and TerraSAR-X synthetic aperture radar (SAR) images were used to study biophysical parameters of agricultural crops in microwave part of electromagnetic spectrum. The analysis was conducted by calculating different vegetation indices (VIs) to estimate the biomass (fresh and dry), LAI, and vegetation water content (VWC) of three crops using Landsat 8 OLI and Landsat 7 ETM+ combined with ground truth data. A new concept of Soil Line retrieval from Landsat 8 image was also developed to estimate plant biophysical parameters using soil line related vegetation indices in optical domain of electromagnetic spectrum. Different approaches including univariate, multivariate stepwise regression and semi-empirical water cloud model was also used to estimate the biophysical parameters of agricultural crop using TerraSAR-X data in microwave domain of electromagnetic spectrum. Perhaps the most important conclusion of this study is that the RS approach can provide useful information about estimating agricultural crop parameters over time and local scale, which can therefore provide valuable information to aid the agronomy community.