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Biomass of the Arctic Birch in Fennoscandia. MSc Dissertation.


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The change in biomass and extent of trees can be an indication of the effects of climate change. Higher latitudes and elevations have been identified as regions which are particularly sensitive to changes in global temperature. The Arctic birch which occupies the ecotone between tundra and forest has been increasing in extent and biomass toward higher latitudes and elevations. This could results in a net release of carbon from the soil to the atmosphere, but also the locking of atmospheric carbon in the biomass of these trees. We have proposed new methods that could be used to estimate and monitor the change in extent and biomass of Arctic birch. The first relies on tree crown extraction techniques from true colour aerial images and lidar tree heights taken over Abisko, Sweden. The second uses tree shadow length extraction on snow using template matching from IKONOS-2 images over Kevo, Finland. Tree characteristic have been sampled at both sites and biomass calculated using allometric relations. The third uses the biomass modelled using the previous methods as independent variable and MODIS summer EVI or the difference between summer and winter EVI as dependent variable in a non-linear regression based model to estimate biomass over Fennoscandia. A MODIS percentage tree cover mask was used to remove soil and vegetation background signal influences. Results have been validated at every stage and compared with NFI data at country and regional level. Results are comparable if not better than previous research.
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Described are field measurements of daylight radiation reflected upward from the crowns of six tree species in visible and near-infrared frequencies of the electromagnetic spectrum. A portable mast and two permanent towers provided platforms for a spectroradiometer at a height of 3 to 5 m above the tree canopy. Each site was measured on at least two different dates to account for variations in species' phenological stages during the summer season. In addition, some of the species were measured in two different locations. Described are the instruments used for the measurement of incident and reflected daylight radiation, the field measurement technique and computational procedure.
Cultural feature is important element in geospatial information library and the height information is important information of cultural features. The existences of the height information and its precision have direct influence over topographic map, especially the quality of large-scale and medium-scale topographic map, and the level of surveying and mapping support. There are a lot of methods about height information extraction, in which the main methods are ground survey (field direct measurement) spatial sensor and photogrammetric ways. However, automatic extraction is very tough. This paper has had an emphasis on segmentation algorithm on shadow areas under multiple constraints and realized automatic extraction of height information by using shadow. Binarization image can be obtained using gray threshold estimated under the multiple constraints. On the interesting area, spot elimination and region splitting are made. After region labeling and non-shadowed regions elimination, shadow area of cultural features can be found. Then height of the cultural features can be calculated using shadow length, sun altitude angle, azimuth angle, and sensor altitude angle, azimuth angle. A great many of experiments have shown that mean square error of the height information of cultural features extraction is close to 2 meter and automatic extraction rate is close to 70%.
Essential Image Processing and GIS for Remote Sensing is an accessible overview of the subject and successfully draws together these three key areas in a balanced and comprehensive manner. The book provides an overview of essential techniques and a selection of key case studies in a variety of application areas. Key concepts and ideas are introduced in a clear and logical manner and described through the provision of numerous relevant conceptual illustrations. Mathematical detail is kept to a minimum and only referred to where necessary for ease of understanding. Such concepts are explained through common sense terms rather than in rigorous mathematical detail when explaining image processing and GIS techniques, to enable students to grasp the essentials of a notoriously challenging subject area. The book is clearly divided into three parts, with the first part introducing essential image processing techniques for remote sensing. The second part looks at GIS and begins with an overview of the concepts, structures and mechanisms by which GIS operates. Finally the third part introduces Remote Sensing Applications. Throughout the book the relationships between GIS, Image Processing and Remote Sensing are clearly identified to ensure that students are able to apply the various techniques that have been covered appropriately. The latter chapters use numerous relevant case studies to illustrate various remote sensing, image processing and GIS applications in practice.
In forestry, the availability of high spatial resolution (<1 m/pixel) imagery from new earth observation satellites like Ikonos favours a shift in the image analysis paradigm from a pixel-based approach towards one dealing directly with the essential structuring element of such images: the individual tree crown (ITC). This paper gives an initial assessment of the effects of 1 m and 4 m/pixel spatial resolutions (panchromatic and multispectral bands, respectively) on the detection, delineation, and classification of the individual tree crowns seen in Ikonos images. Winter and summer Ikonos images of the Hudson plantation of the Petawawa Research Forest, Ontario, Canada were analyzed. The panchromatic images were resampled to 0.5 m/pixel and then smoothed using a 3 × 3 kernel mean filter. A valley-following algorithm and rule-based isolation module were applied to delineate the individual tree crowns. Local maxima within a moving 3 × 3 window (i.e., Tree Tops) were also extracted from the smoothed images for comparison. Crown delineation and detection results were summarised and compared with field tree counts. Overall, the ITC delineation and the local maxima approaches led to tree counts that were on average 15 percent off for both seasons. Visual inspection reveals delineation of clusters of two or three crowns as a common source of error. Crown-based species spectral signatures were generated for six classes representing conifer species, plus a hardwood class and a shrub class. After the ITC-based classification, classification accuracy was ascertained using separate test areas of known species. The overall accuracy was 59 percent. Important confusion exists between red and white spruces, and mature versus immature white pines, but post-classification regroupings into single spruce and white pine classes led to an overall accuracy of 67 percent.