Land cover change detection using Landsat imagery - comparison of three methods

Environmental changes are amongst the most important research subjects in geography. The changes may be natural, but also may be caused by human activity. Land cover is a significant component of the changing environment. Monitoring of its changes involves usage of satellite techniques. Landsat mission provides comparable data since forty years, very useful in land cover studies. Utilization of satellite techniques in such researches is developing quickly. This paper is an example of methods that enable quick and quite accurate assessment of range and spatial distribution of land cover changes. Practical application of image difference, principal component analysis and supervised classification to detect land cover changes is presented. Methods are applied to study area containing different land cover classes. Accuracy of methods was tested and compared. Combining methods presented in earlier researches, five new methods were developed: image difference, image difference with classification, classification, principal component analysis, principal component analysis with classification. Methods were applied to three different input datasets: pairs of images with different level of preprocessing. First dataset was a pair of georeferenced Landsat Thematic Mapper images. The second dataset was the same pair of images, atmospherically corrected using dark object subtraction method. Normalization of one image to the other provided the third dataset. Accuracy assessment was executed. Results were obtained from confusion matrices. Overall accuracy of methods was high, from 77% to 91%. Supervised classification was the most accurate method. Combining fully automatic methods with supervised classification has increased overall accuracy of automatic change detection, however not significantly. Studies on combining change detection methods should be continued. Future studies should concentrate on the automation of change detection process

Diversification in the fuel gas sector

Na rynku paliwowym nastąpiły diametralne zmiany. Niepewność cen oraz względy ekologiczne zmuszają do zastanowienia się nad wyborem najbardziej racjonalnego rodzaju paliwa. Gaz jest paliwem przyjaznym dla środowiska a dzięki wprowadzaniu coraz to nowych technologii, łatwości obsługi z punktu widzenia użytkownika oraz jego ogólnej dostępności może trafić do każdego odbiorcy. Paliwo to znajduje swoje zastosowanie zarówno w gospodarstwie domowym, przemyśle, a także w motoryzacji. Należy poznać różne odmiany gazu oraz ich właściwości, aby prawidłowo je wykorzystać. Ciągle odkrywane są nowe źródła pozyskiwania tego surowca - także na terenie Polski. Opracowywane są technologie ułatwiające, a w niektórych przypadkach umożliwiające, jego wydobycie.The fuel market has been changed. The hesitancy of prices and environmental considerations force us to think about the most efficient type of fuel. Gas is an environmental friendly fuel. Because of the newest technologies it is generally approachable and used in the householders, industry and motorization. It is necessary to know the different kinds of gas and their properties in order to use them properly. The new gas poles are discovered - also in Poland. New technologies help or even let us extract gas from new places

Application of satellite imagery and GIS tools for land surface temperature estimation and verification

Land surface temperature (LST) plays an important role in many land-surface processes on regional as well on global scales. It is also a good indicator of energy flux phenomena and is used as a parameter in various Earth observation related studies. However, LST estimation based on processing and utilisation of satellite derived data constitutes several problems in terms of time limitations, accessibility, atmospheric influence etc. The aim of the study was to verify and compare the algorithms especially in the context of minimalisation of errors in LST estimation by satellite observation using various means of GIS data processing and integration. Also, the indirect verification of the LST estimation methods, based on the utilisation of statistics and dependencies of LST, NDVI and air temperature values has been presented and discussed. The presented work has the form of a case study, and due to limited amount of verification data used in the current stage of the investigation, the results should be treated as preliminary. The developed GIS solution for integrating spatial data from many sources needed in the course of this study is also presented

The use of hyperspectral techniques for waters mapping of the Zegrzyńskie Lake

The paper presents a possibility of an application of Imaging Spectroscopy to acquire thematic maps of water quality. Thanks to very high spectral, radiometric and spatial resolution of AISA hyperspectral images, which allow to identify zones of water with different properties. An analysis of the spatial distribution of physico-chemical parameters of water was made in 2014 for the Zegrzyńskie Lake. A Hhyperspectral image was acquired by the MGGP Aero aircraft and the Finnish AISA Eagle scanner. Remote sensing indices of water quality (Secchi Disk Depth (SDD), Colored Dissolved Organic Matter (CDOM)) and vegetation index – Carotenoid Reflectance Index 1 (CRI 1), which determines the content of chlorophyll and other plant pigments in the water, was calculated on the image. Based on spatial distribution of water quality indices the IsoData classification was performed. The result was a set of maps with five zones of concentrations of different substances in of the Zegrzyńskie Lake. The verification was made based on in-situ acquired samples of water during airborne data imaging. Due to differences in suspended substances load and different water velocity Bug and Narew water flow in separate streams and mix in the middle of the artificial lake. Following research showed a high correlation between the calculated indices and field measurements. They also confirmed the usability of AISA hyperspectral images to create thematic maps of water quality

Analysis of the relationships between vegetation water content obtained from field measurements and vegetation indices

Monitoring the plant moisture has a significant role in geographical research. It may be used, among the others, for climate modelling, agricultural predicting, rational water management, drought monitoring and determining vulnerability to the occurrence of the fire. Traditional methods, based on field measurements, are the most accurate, but also time-consuming. Therefore these methods can be applied only in a limited area. In order to explore bigger areas remote sensing methods are useful. To analyse plant condition and water content vegetation indices can be used. Their calculations are based on the reflectance in different bands. Despite many studies conducted on the development of remote sensing indices, still there is a need for verification of their accuracy and usefulness by comparing the results obtained through remote sensing tools with the results of field measurements. In this paper three indices are used: Moisture Stress Index (MSI), Normalized Difference Infrared Index (NDII) and transformation Tasseled Cap (the Wetness band). The aim of this study was to compare the value of vegetation indices calculated using images from Landsat 5 Thematic Mapper with the results of field measurement from five test areas of different type of land cover: cereal crops, non-cereal crops, forests, meadows and pastures. Research was carried out in province Ontario (Canada) and consisted of two stages. The first stage was the fi eld measurements, where the specified number of plant samples was collected and water content was calculated. The second stage consisted of the preparation of relevant satellite images (atmospheric correction and making the mosaic) and the calculation of vegetation indices. The study has shown, that statistical relationships between data sets obtained through remote sensing indices and calculated on the basis of field measurements are diverse for different indices. MSI and NDII values are significantly correlated with the water content in plants (R= -0.62 and 0.56, respectively). The correlation of TCW was rated as moderate (R=0.30). Spatial distribution of water content based on maps created using NDII and MSI is similar. It was noticed that TC Wetness transformation overestimates water content in cereal plants (smaller water content) and underestimates it in natural green plant ecosystems, which generally have higher water content. As a result, the range of water content values obtained from TCW is more narrow (dominates the class of 60-70% water in plants) than the range of values calculated using NDII and MSI. Both indices have more uniform distribution dominated by the classes of moderate water content (50-60%), rather wet plants (60-70%) and very wet plants (70-80%). Each index is characterized by different distribution of the water content. In general values calculated on the basis of NDII and MSI are higher than calculated using TCW. In order to perform more accurate analysis between values calculated using satellite images and the results of field measurements, the values of particular types of land cover should be compared

Traumatic Brain Injury Induces Alterations in Cortical Glutamate Uptake without a Reduction in Glutamate Transporter-1 Protein Expression

We hypothesize that the primary mechanism for removal of glutamate from the extracellular space is altered after traumatic brain injury (TBI). To evaluate this hypothesis, we initiated TBI in adult male rats using a 2.0 atm lateral fluid percussion injury (LFPI) model. In the ipsilateral cortex and hippocampus, we found no differences in expression of the primary glutamate transporter in the brain (GLT-1) 24 h after TBI. In contrast, we found a decrease in glutamate uptake in the cortex, but not the hippocampus, 24 h after injury. Because glutamate uptake is potently regulated by protein kinases, we assessed global serine-threonine protein kinase activity using a kinome array platform. Twenty-five kinome array peptide substrates were differentially phoshorylated between LFPI and controls in the cortex, whereas 19 peptide substrates were differentially phosphorylated in the hippocampus (fold change ≥ ± 1.15). We identified several kinases as likely to be involved in acute TBI, including protein kinase B (Akt) and protein kinase C (PKC), which are well-characterized modulators of GLT-1. Exploratory studies using an inhibitor of Akt suggest selective activation of kinases in LFPI versus controls. Ingenuity pathway analyses of implicated kinases from our network model found apoptosis and cell death pathways as top functions in acute LFPI. Taken together, our data suggest diminished activity of glutamate transporters in the prefrontal cortex, with no changes in protein expression of the primary glutamate transporter GLT-1, and global alterations in signaling networks that include serine-threonine kinases that are known modulators of glutamate transport activity

Quantitation of heteroplasmy of mtDNA sequence variants identified in a population of AD patients and controls by array-based resequencing

The role of mitochondrial dysfunction in the pathogenesis of Alzheimer's disease (AD) has been well documented. Though evidence for the role of mitochondria in AD seems incontrovertible, the impact of mitochondrial DNA (mtDNA) mutations in AD etiology remains controversial. Though mutations in mitochondrially encoded genes have repeatedly been implicated in the pathogenesis of AD, many of these studies have been plagued by lack of replication as well as potential contamination of nuclear-encoded mitochondrial pseudogenes. To assess the role of mtDNA mutations in the pathogenesis of AD, while avoiding the pitfalls of nuclear-encoded mitochondrial pseudogenes encountered in previous investigations and showcasing the benefits of a novel resequencing technology, we sequenced the entire coding region (15,452 bp) of mtDNA from 19 extremely well-characterized AD patients and 18 age-matched, unaffected controls utilizing a new, reliable, high-throughput array-based resequencing technique, the Human MitoChip. High-throughput, array-based DNA resequencing of the entire mtDNA coding region from platelets of 37 subjects revealed the presence of 208 loci displaying a total of 917 sequence variants. There were no statistically significant differences in overall mutational burden between cases and controls, however, 265 independent sites of statistically significant change between cases and controls were identified. Changed sites were found in genes associated with complexes I (30.2%), III (3.0%), IV (33.2%), and V (9.1%) as well as tRNA (10.6%) and rRNA (14.0%). Despite their statistical significance, the subtle nature of the observed changes makes it difficult to determine whether they represent true functional variants involved in AD etiology or merely naturally occurring dissimilarity. Regardless, this study demonstrates the tremendous value of this novel mtDNA resequencing platform, which avoids the pitfalls of erroneously amplifying nuclear-encoded mtDNA pseudogenes

Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons

Alzheimer's disease (AD) is associated with regional reductions in fluorodeoxyglucose positron emission tomography (FDG PET) measurements of the cerebral metabolic rate for glucose, which may begin long before the onset of histopathological or clinical features, especially in carriers of a common AD susceptibility gene. Molecular evaluation of cells from metabolically affected brain regions could provide new information about the pathogenesis of AD and new targets at which to aim disease-slowing and prevention therapies. Data from a genome-wide transcriptomic study were used to compare the expression of 80 metabolically relevant nuclear genes from laser-capture microdissected non-tangle-bearing neurons from autopsy brains of AD cases and normal controls in posterior cingulate cortex, which is metabolically affected in the earliest stages; other brain regions metabolically affected in PET studies of AD or normal aging; and visual cortex, which is relatively spared. Compared with controls, AD cases had significantly lower expression of 70% of the nuclear genes encoding subunits of the mitochondrial electron transport chain in posterior cingulate cortex, 65% of those in the middle temporal gyrus, 61% of those in hippocampal CA1, 23% of those in entorhinal cortex, 16% of those in visual cortex, and 5% of those in the superior frontal gyrus. Western blots confirmed underexpression of those complex I–V subunits assessed at the protein level. Cerebral metabolic rate for glucose abnormalities in FDG PET studies of AD may be associated with reduced neuronal expression of nuclear genes encoding subunits of the mitochondrial electron transport chain