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504 --- 504 Environment. Environmental science --- Environment. Environmental science --- General ecology and biosociology

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504 --- Environment. Environmental science --- Environmental protection --- Environmental sciences --- Human ecology --- 504 Environment. Environmental science --- Ecology --- Environment, Human --- Human beings --- Human environment --- Ecological engineering --- Human geography --- Nature --- Environmental quality management --- Protection of environment --- Applied ecology --- Environmental engineering --- Environmental policy --- Environmental quality --- Social aspects --- Effect of environment on --- Effect of human beings on

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8.1 General conclusions This dissertation aimed at the development of a methodology to quantify vegetation regrowth and burn severity over large areas based on time series of satellite data. The pixel based regeneration index has been the driving force of this research, since it allows to monitor the vegetation regrowth at pixel level without the use of detailed local reference maps. The first general objective of this research was the development of this pixel based regeneration index using time series similarity measures and spatial context. The second general objective focused on the evaluation of the developed pixel based regeneration index by assessing the amount of change in post-fire vegetative development and by relating that change to burn severity and fractions of woody and herbaceous vegetation. In the first part (Chapters 3-5), the use of time series similarity and spatial context to develop the pixel based regeneration index is extensively described. Chapter 3 provides a theoretical comparison between the advantages and disadvantages of the commonly used time series similarity measures. The theoretical comparison focused on the specific properties of each time series similarity measure to provide a valuable basis for identifying, monitoring and classifying vegetation dynamics. Additionally, u numerical experiment elaborated on these theoretical differences and illustrated the utility of each of these similarity measures to discriminate between specific differences between time series (assumption I.i). The use of spatial context and hierarchical concepts as a additional information source was subsequently introduced in Chapter 4. This chapter focused on the development of an multi-temporal hierarchical image segmentation methodology that clusters adjoining pixels with similar temporal properties into hierarchical segments at various scales. Application of the methodology demonstrated the concept of MTHIS and illustrated the importance of the average and annual term to describe the majority of the spatio-temporal variability in the NDVI time series. The correspondence between MTHIS results and reference layers of vegetation characteristics at different scales revealed moreover a close relationship between segmentation output and landcover-landuse reference map (assumption I.ii). In Chapter 5, the concepts of time series similarity and spatial context were combined in a methodology for the image based selection of control pixels on regional to global scale (Chapter 5). Validation based on non-burnt pixels showed that the selection of the control pixels based on similarity of the one year VIt before fire, provides an improvement for the selection of control pixels over large areas (assumption I.iii). The time series similarity approaches specifically minimize the drawbacks of the classic approach based on reference areas,namely the within-class heterogeneity and dependence of static reference data, by selecting only pixels that effectively resemble the focal pixel based on similarity of the one year VI before fire. Comparison of the time series similarity approaches showed moreover that optimal reference pixels were obtained for the TSS-RMSD approach with x = 4 and NT = 8 due to beneficial averaging effects and minimal window size. As such, the effects of spatial heterogeneity and noise are minimized and the control pixels provide optimally the temporal profile of the focal pixel VI-focal in case the fire had not occurred. Pre-fire RMSD values of the control pixels of the TSS- approach allowed moreover to derive the quality of the control pixels before using them in pRI calculations. In the second part of this dissertation (Chapters 6-7) the developed pixel based regeneration index was used to assess the amount of change in post-fire vegetation growth. The focus of Chapter 6 was on the development of an indicator of burn severity (IBS) that quantifies the integrated change caused by vegetation fires. Comparison of the IBS with detailed estimates of burn severity showed that the IBS allows to quantify the burn severity at pixel level over large areas (assumption II.i). The IBS also showed an improvement over the traditional burn severity, since it must be collected throughout the growing season and is not dependent on the moment of Landsat image acquisition. Consequently, IBS estimates can be used as alternative input to global wildland fire emissions models to quantify the variable component related to burning efficiency. Finally, the contribution of different vegetation components to the pRI time series was studied in Chapter 7. In this chapter, the use of the STL method was evaluated to decompose the original time series of vegetation growth into separate long-term and seasonally varying components, which can be related to woody and herbaceous vegetation. Results of the methodology confirmed the assumption that temporal variations of woody and herbaceous vegetation are different, where high post-fire severities lead to a high decrease in woody vegetation. For the herbaceous component this is not necessarily true which can be explained by the general fast recovery of herbaceous vegetation, the increased amount of nutrients, and the high dependency of herbaceous vegetation on rainfall events (assumption II.ii). In general the results of this research point out the large amount of information that is contained in time series of coarse resolution satellite imagery. Standardized methodologies need however be developed to overcome the difficulties associated with these data sets. The use of relative estimates and incorporation of spatial context may provide a first steps towards such standardized methodologies. 8.2 Relevance and potential applications Assessment of the impact of fire emissions on atmospheric chemistry and understanding, in terms of ecological processes, the changes of terrestrial ecosystems after fire at various spatial and temporal scales are major challenges for a wide range of researchers, ecologists and resource managers worldwide. The developed methodologies and obtained results of this dissertation can contribute to this assessment and understanding at different scale levels. The TSS methodology, for example, allows the calculation of pRI time series based on any multi-temporal data set. As such, it can be used to examine the global effects of fire disturbances from regional to continental scales and can contribute to measure how fire effects vary within burnt areas (e.g., by using the IBS). This within-burn variability is crucial to accurately estimate the impact of fire on vegetation, but also is essential for ecologists and resource managers who want to understand fire effects on ecosystems and want to plan post-fire rehabilitation. Moreover, it is essential to reduce current uncertainties in the current emission models that quantify the impact of fire on atmospheric chemistry. Moreover, the developed methodologies are not restricted to burnt areas. The proposed methodologies are generalized approaches that can be applied to any type of disturbance or change based on any multi-temporal data set. As such, they can contribute to obtain a better understanding of factors affecting land-use and land-cover resulting in potential climate warming, land degradation and bio-diversity loss. 8.3 Further research suggestions and perspectives Several new research possibilities arise from this work. Broadly, without claiming the completeness of the list, these research possibilities can be grouped into (i) potential improvements of the current approach and (ii) completely new research pathways. 8.3.1 Potential improvements In the framework of this research, emphasis was on NDVI time series of VGT S10 time series. This data set has however its limitations, which lead to the following suggestions that can enhance the performance of the methodology: BRDF corrected data sets may provide u useful improvement to overcome the noise associated with the high variability due to variation in illumination and observation angles. The use of BRDF corrected data sets (e.g., SPOT-Vegetation D10, MODIS corrected BRDF data) should therefore certainly considered towards future research. Adapted vegetation indices may provide a useful alternative to the current use of NDVI time series. NDVI time series were not designed to capture specific vegetation variation after fire and consequently are rather insensitive to changes induced by the fire on the vegetation cover (Lasaponara, 2006). The use of adapted wavelengths and spectral design may therefore provide an improvement to the proposed approaches. Improved compositing criteria are necessary when studying vegetation regrowth. The S10 data set is a maximum NDVI value composite. As such, it selects pixel measurements of the date when the NDVI is maximum and tends to select pixels that are minimally affected by fire occurrence due to the expected NDVI decrease after fire. The use of alternative compositing criteria (e.g., minimum NIR composites) should therefore certainly be studied. Improved spatial resolution will allow to obtain similar characteristics at a more detailed scale level. The use of other data sets with higher spatial resolution (e.g., MODIS and MERIS) should therefore be considered to improve accuracy at more detailed scales. Improved validation is essential before applying the methodologies on global scale levels. This requires however a large sample of in situ measurements and fine spatial resolution

Academic collection --- 574.9 --- 504 --- 630*231 --- 630*43 --- 528.8 --- Biogeography in general. Geographical distribution of organisms --- Environment. Environmental science --- Natural regeneration --- Forest fires. Prevention and control. Salvage. Revegetation etc. Use of fire in silviculture --- Remote sensing. Teledetection --- Theses --- 528.8 Remote sensing. Teledetection --- 630*43 Forest fires. Prevention and control. Salvage. Revegetation etc. Use of fire in silviculture --- 630*231 Natural regeneration --- 504 Environment. Environmental science --- 574.9 Biogeography in general. Geographical distribution of organisms

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Europan --- 72.072 --- 71.072 --- 711.4 --- 504 --- 711.61 --- 72.037 --- Nederland --- Almere --- Amsterdam --- Groningen --- Nijmegen --- 711.4 <4> --- 72.039 --- 72.092 --- Architectuurwedstrijden --- Wedstrijden (architectuur) --- Stedenbouw (wedstrijden) --- Wedstrijden (stedenbouw) --- Stedenbouw --- Duurzaamheid --- Openbare ruimte --- Eenentwintigste eeuw (architectuur) --- 21ste eeuw (architectuur) --- Environment. Environmental science --- Gemeentelijke planologie. Stadsplanning. Stedenbouw--Europa --- Hedendaagse architectuur. Bouwkunst sinds 1960 --- Contains audio-visual material --- 72.092 Architectuurwedstrijden --- 72.039 Hedendaagse architectuur. Bouwkunst sinds 1960 --- 711.4 <4> Gemeentelijke planologie. Stadsplanning. Stedenbouw--Europa --- 504 Environment. Environmental science

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72:574 --- Duurzaam bouwen --- Bouweconomie --- Energiebesparende constructies --- Architectuur en ecologie --- 504 --- 574 --- 620.9 --- 69.003 --- 728.1 --- 69.003 Building (construction) trade. Building materials. Building practice and procedure--?.003 --- Building (construction) trade. Building materials. Building practice and procedure--?.003 --- 620.9 Economics of energy in general --- Economics of energy in general --- 574 General ecology. Biocoenology. Hydrobiology. Biogeography --- General ecology. Biocoenology. Hydrobiology. Biogeography --- 504 Environment. Environmental science --- Environment. Environmental science --- 728.1 Woonhuizen. Woningbouw (algemeen) --- Woonhuizen. Woningbouw (algemeen) --- duurzaam wonen