Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Studies of electronic structure by x-ray Raman and emission spectroscopy: applications to MgB2 superconductors and high pressure physics

X-ray Raman scattering and x-ray emission spectroscopies were used to study the electronic properties and phase transitions in several condensed matter systems. The experimental work, carried out at the European Synchrotron Radiation Facility, was complemented by theoretical calculations of the x-ray spectra and of the electronic structure. The electronic structure of MgB2 at the Fermi level is dominated by the boron σ and π bands. The high density of states provided by these bands is the key feature of the electronic structure contributing to the high critical temperature of superconductivity in MgB2. The electronic structure of MgB2 can be modified by atomic substitutions, which introduce extra electrons or holes into the bands. X ray Raman scattering was used to probe the interesting σ and π band hole states in pure and aluminum substituted MgB2. A method for determining the final state density of electron states from experimental x-ray Raman scattering spectra was examined and applied to the experimental data on both pure MgB2 and on Mg(0.83)Al(0.17)B2. The extracted final state density of electron states for the pure and aluminum substituted samples revealed clear substitution induced changes in the σ and π bands. The experimental work was supported by theoretical calculations of the electronic structure and x-ray Raman spectra. X-ray emission at the metal Kβ line was applied to the studies of pressure and temperature induced spin state transitions in transition metal oxides. The experimental studies were complemented by cluster multiplet calculations of the electronic structure and emission spectra. In LaCoO3 evidence for the appearance of an intermediate spin state was found and the presence of a pressure induced spin transition was confirmed. Pressure induced changes in the electronic structure of transition metal monoxides were studied experimentally and were analyzed using the cluster multiplet approach. The effects of hybridization, bandwidth and crystal field splitting in stabilizing the high pressure spin state were discussed. Emission spectroscopy at the Kβ line was also applied to FeCO3 and a pressure induced iron spin state transition was discovered.

Thunderstorm climatology and lightning location applications in northern Europe

Thunderstorm is a dangerous electrical phenomena in the atmosphere. Thundercloud is formed when thermal energy is transported rapidly upwards in convective updraughts. Electrification occurs in the collisions of cloud particles in the strong updraught. When the amount of charge in the cloud is large enough, electrical breakdown, better known as a flash, occurs. Lightning location is nowadays an essential tool for the detection of severe weather. Located flashes indicate in real time the movement of hazardous areas and the intensity of lightning activity. Also, an estimate for the flash peak current can be determined. The observations can be used in damage surveys. The most simple way to represent lightning data is to plot the locations on a map, but the data can be processed in more complex end-products and exploited in data fusion. Lightning data serves as an important tool also in the research of lightning-related phenomena, such as Transient Luminous Events. Most of the global thunderstorms occur in areas with plenty of heat, moisture and tropospheric instability, for example in the tropical land areas. In higher latitudes like in Finland, the thunderstorm season is practically restricted to the summer season. Particular feature of the high-latitude climatology is the large annual variation, which regards also thunderstorms. Knowing the performance of any measuring device is important because it affects the accuracy of the end-products. In lightning location systems, the detection efficiency means the ratio between located and actually occurred flashes. Because in practice it is impossible to know the true number of actually occurred flashes, the detection efficiency has to be esimated with theoretical methods.

Mining Sequential Data – in Search of Segmental Structures

Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.

Production process of Scots pine.

The accompanying collective research report is the result of the research project in 1986­90 between The Finnish Academy and the former Soviet Academy of Sciences. The project was organized around common field work in Finland and in the former Soviet Union and theoretical analyses of tree growth determining processes. Based on theoretical analyses, dynamic stand growth models were made and their parameters were determined utilizing the field results. Annual cycle affects the tree growth. Our theoretical approach was based on adaptation to local climate conditions from Lapland to South Russia. The initiation of growth was described as a simple low and high temperature accumulation driven model. Linking the theoretical model with long term temperature data allowed us to analyze what type of temperature response produced favorable outcome in different climates. Initiation of growth consumes the carbohydrate reserves in plants. We measured the dynamics of insoluble and soluble sugars in the very northern and Karelian conditions. Clear cyclical pattern was observed but the differences between locations were surprisingly small. Analysis of field measurements of CO2 exchange showed that irradiance is the dominating factor causing variation in photosynthetic rate in natural conditions during summer. The effect of other factors is so small that they can be omitted without any considerable loss of accuracy. A special experiment carried out in Hyytiälä showed that the needle living space, defined as the ratio between the shoot cylindric volume and needle surface area, correlates with the shoot photosynthesis. The penetration of irradiance into Scots pine canopy is a complicated phenomenon because of the movement of the sun on the sky and the complicated structure of branches and needles. A moderately simple but balanced forest radiation regime submodel was constructed. It consists of the tree crown and forest structure, the gap probability calculation and the consideration of spatial and temporal variation of radiation inside the forest. The common field excursions in different geographical regions resulted in a lot of experimental data of regularities of woody structures. The water transport seems to be a good common factor to analyse these properties of tree structure. There are evident regressions between cross-sectional areas measured at different locations along the water pathway from fine roots to needles. The observed regressions have clear geographical trends. For example, the same cross-sectional area can support three times higher needle mass in South Russia than in Lapland. Geographical trends can also be seen in shoot and needle structure. Analysis of data published by several Russian authors show, that one ton of needles transpire 42 ton of water a year. This annual amount of transpiration seems to be independent of geographical location, year and site conditions. The produced theoretical and experimental material is utilised in the development of stand growth model that describes the growth and development of Scots pine stands in Finland and the former Soviet Union. The core of the model is carbon and nutrient balances. This means that carbon obtained in photosynthesis is consumed for growth and maintenance and nutrients are taken according to the metabolic needs. The annual photosynthetic production by trees in the stand is determined as a function of irradiance and shading during the active period. The utilisation of the annual photosynthetic production to the growth of different components of trees is based on structural regularities. Since the fundamental metabolic processes are the same in all locations the same growth model structure can be applied in the large range of Scots pine. The annual photosynthetic production and structural regularities determining the allocation of resources have geographical features. The common field measurements enable the application of the model to the analysis of growth and development of stands growing on the five locations of experiments. The model enables the analysis of geographical differences in the growth of Scots pine. For example, the annual photosynthetic production of a 100-year-old stand at Voronez is 3.5 times higher than in Lapland. The share consumed to needle growth (30 %) and to growth of branches (5 %) seems to be the same in all locations. In contrast, the share of fine roots is decreasing when moving from north to south. It is 20 % in Lapland, 15 % in Hyytiälä Central Finland and Kentjärvi Karelia and 15 % in Voronez South Russia. The stem masses (115­113 ton/ha) are rather similar in Hyytiälä, Kentjärvi and Voronez, but rather low (50 ton/ha) in Lapland. In Voronez the height of the trees reach 29 m being in Hyytiälä and Kentjärvi 22 m and in Lapland only 14 m. The present approach enables utilization of structural and functional knowledge, gained in places of intensive research, in the analysis of growth and development of any stand. This opens new possibilities for growth research and also for applications in forestry practice.