Evaluation of aerial remote sensing techniques for vegetation management in power line corridors

The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

Variation of Snowline and Mass Balance of Glaciers of Warwan and Bhut Basins of Western Himalaya Using Remote Sensing Technique

Glaciers are natural reservoirs of fresh water in frozen state and sensitive indicators of climate change. Among all the mountainous glaciated regions, glaciers of Himalayas form one of the largest concentrations of ice outside the Polar Regions. Almost all the major rivers of northern India originate from these glaciers and sustain perennial flow. Therefore, in view of the importance and role of the glaciers in sustaining the life on the Earth, monitoring the health of glaciers is necessary. Glacier's health is monitored in two ways (i) by mapping the change in extent of glaciers (ii) by finding variation in the annual mass balance. This paper has been discussed the later approach for monitoring the health of glaciers of Warwan and Bhut basins. Mass balance of glaciers of these two basins was determined based on the extraction of snow line at the end of ablation season. A series of satellite images of AWiFS sensor were analysed for extraction of snowline on the glaciers for the period of 2005, 2006 and 2007. The snow line at the end of ablation season is used to compute accumulation area ratio (AAR = Accumulation area/Glacier area) for each glacier of basins. An approach based on relationship of AAR to specific mass balance (computed in field) for glaciers of Basapa basin was employed in the present study. Mean of specific mass balance of individual glacier for the year 2005, 2006 and 2007 of Warwan basin was found to be -ve 0.19 m, -ve 0.27 m and -ve 0.2 m respectively. It is 0.05 m, -ve 0.11 m and -ve 0.19 m for Bhut basin. The analysis suggests a loss of 4.3 and 0.83 kmA(3) of glacier in the monitoring period of 3 years for Warwan and Bhut basins respectively. The overall results suggest that the glaciers of Warwan basin and Bhut basins have suffered more loss of ice than gain in the monitoring period of 3 years.

Contributions to the analysis and segmentation of remote sensing hyperspectral images

142 p.

Research on extracting method of micro-scale remote sensing information combination and application in coastal zone

973 Project of China [2006CB701305]; "863" Project of China [2009AA12Z148]; National Natural Science Foundation of China [40971224]

Applications of remote sensing and geographic information systems in geomorphological studies: Safaga - El Quseir area, Red Sea coast, Egypt as an example

In den letzten drei Jahrzehnten sind Fernerkundung und GIS in den Geowissenschaften zunehmend wichtiger geworden, um die konventionellen Methoden von Datensammlung und zur Herstellung von Landkarten zu verbessern. Die vorliegende Arbeit befasst sich mit der Anwendung von Fernerkundung und geographischen Informationssystemen (GIS) für geomorphologische Untersuchungen. Durch die Kombination beider Techniken ist es vor allem möglich geworden, geomorphologische Formen im Überblick und dennoch detailliert zu erfassen. Als Grundlagen werden in dieser Arbeit topographische und geologische Karten, Satellitenbilder und Klimadaten benutzt. Die Arbeit besteht aus 6 Kapiteln. Das erste Kapitel gibt einen allgemeinen Überblick über den Untersuchungsraum. Dieser umfasst folgende morphologische Einheiten, klimatischen Verhältnisse, insbesondere die Ariditätsindizes der Küsten- und Gebirgslandschaft sowie das Siedlungsmuster beschrieben. Kapitel 2 befasst sich mit der regionalen Geologie und Stratigraphie des Untersuchungsraumes. Es wird versucht, die Hauptformationen mit Hilfe von ETM-Satellitenbildern zu identifizieren. Angewandt werden hierzu folgende Methoden: Colour Band Composite, Image Rationing und die sog. überwachte Klassifikation. Kapitel 3 enthält eine Beschreibung der strukturell bedingten Oberflächenformen, um die Wechselwirkung zwischen Tektonik und geomorphologischen Prozessen aufzuklären. Es geht es um die vielfältigen Methoden, zum Beispiel das sog. Image Processing, um die im Gebirgskörper vorhandenen Lineamente einwandfrei zu deuten. Spezielle Filtermethoden werden angewandt, um die wichtigsten Lineamente zu kartieren. Kapitel 4 stellt den Versuch dar, mit Hilfe von aufbereiteten SRTM-Satellitenbildern eine automatisierte Erfassung des Gewässernetzes. Es wird ausführlich diskutiert, inwieweit bei diesen Arbeitsschritten die Qualität kleinmaßstäbiger SRTM-Satellitenbilder mit großmaßstäbigen topographischen Karten vergleichbar ist. Weiterhin werden hydrologische Parameter über eine qualitative und quantitative Analyse des Abflussregimes einzelner Wadis erfasst. Der Ursprung von Entwässerungssystemen wird auf der Basis geomorphologischer und geologischer Befunde interpretiert. Kapitel 5 befasst sich mit der Abschätzung der Gefahr episodischer Wadifluten. Die Wahrscheinlichkeit ihres jährlichen Auftretens bzw. des Auftretens starker Fluten im Abstand mehrerer Jahre wird in einer historischen Betrachtung bis 1921 zurückverfolgt. Die Bedeutung von Regentiefs, die sich über dem Roten Meer entwickeln, und die für eine Abflussbildung in Frage kommen, wird mit Hilfe der IDW-Methode (Inverse Distance Weighted) untersucht. Betrachtet werden außerdem weitere, regenbringende Wetterlagen mit Hilfe von Meteosat Infrarotbildern. Genauer betrachtet wird die Periode 1990-1997, in der kräftige, Wadifluten auslösende Regenfälle auftraten. Flutereignisse und Fluthöhe werden anhand von hydrographischen Daten (Pegelmessungen) ermittelt. Auch die Landnutzung und Siedlungsstruktur im Einzugsgebiet eines Wadis wird berücksichtigt. In Kapitel 6 geht es um die unterschiedlichen Küstenformen auf der Westseite des Roten Meeres zum Beispiel die Erosionsformen, Aufbauformen, untergetauchte Formen. Im abschließenden Teil geht es um die Stratigraphie und zeitliche Zuordnung von submarinen Terrassen auf Korallenriffen sowie den Vergleich mit anderen solcher Terrassen an der ägyptischen Rotmeerküste westlich und östlich der Sinai-Halbinsel.

The application of remote sensing to the management of urban wildlife habitats

The project set out with two main aims. The first aim was to determine whether large scale multispectral aerial photography could be used to successfully survey and monitor urban wildlife habitats. The second objective was to investigate whether this data source could be used to predict population numbers of selected species expected to be found in a particular habitat type. Panchromatic, colour and colour infra-red, 1:2500 scale aerial photographs, taken in 1981 and 1984, were used. For the orderly extraction of information from the imagery, an urban wildlife habitat classification was devised. This was based on classifications already in use in urban environments by the Nature Conservancy Council. Pilot tests identified that the colour infra-red imagery provided the most accurate results about urban wildlife habitats in the study area of the Blackbrook Valley, Dudley. Both the 1981 and 1984 colour infra-red photographs were analysed and information was obtained about the type, extent and distribution of habitats. In order to investigate whether large scale aerial photographs could be used to predict likely animal population numbers in urban environments, it was decided to limit the investigation to the possible prediction of bird population numbers in Saltwells Local Nature Reserve. A good deal of research has already been completed into the development of models to predict breeding bird population numbers in woodland habitats. These models were analysed to determine whether they could be used successfully with data extracted from the aerial photographs. The projects concluded that 1:2500 scale colour infra-red photographs can provide very useful and very detailed information about the wildlife habitats in an urban area. Such imagery can also provide habitat area data to be used with population predictive models of woodland breeding birds. Using the aerial photographs, further investigations into the relationship between area of habitat and the breeding of individual bird species were inconclusive and need further research.

Monitoring animal behaviour and environmental interactions : GPS collars and satellite remote sensing within a satellite remote sensing context

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Monitoring animal behaviour and environmental interactions using wireless sensor networks, GPS collars and satellite remote sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.