In remote sensing, the application determines the type of platform and scale used during air or space –borne data collection as the pixel size of the collected data varies depending on the sensor or platform used. Applications involving some cryospheric environments require the use of the microwave band of the electromagnetic spectrum, with snow water equivalent (SWE) studies making use of passively emitted microwave radiation. A key issue in the use of passive microwave remotely sensed data is its spatial resolution, which ranges from 10 to 25 kilometres. The Climate Research Branch division of the Meteorological Service Canada is using passive microwave remote sensing as a means to monitor and obtain SWE values for Canada’s varying land-cover regions for use in climate change studies. Canada’s diverse landscape necessitated the creation of a snow water equivalent retrieval algorithm suite comprised of four different algorithms; all reflecting different vegetative covers. The spatial resolution of small scale remotely sensed data does provide a means for monitoring Canada’s large landmass, but it does, however, result in generalizations of land-cover, and in particular, vegetative structure, which is shown to influence both snow cover and algorithm performance. The Climate Research Branch is currently developing its SWE algorithm for Canada’s boreal forest region. This thesis presents a means of successfully and easily collecting in situ remotely sensed data in the form of hemispherical photographs for gathering vegetative structure data to ground-truth remotely sensed data. This thesis also demonstrates that the Gap Light Analyzer software suite used for analyzing hemispherical photographs of mainly deciduous environments during the spring-fall months can be successfully applied towards cryospheric studies of predominantly coniferous environments.

A suitable climate, varied scenic terrain, and proximity of communities along Ontario’s system of 39,742 km of snowmobile trails have provided for domestic and international snowmobile tourism. Outdoor winter tourism in many parts of the world has been identified to be at risk to changes in global climate. The Intergovernmental Panel on Climate Change in its Fourth Assessment Report (AR4) reported a global increase of temperature of 0.74 degrees Celsius for the period 1906 to 2005 and estimates that by the end of the 21st century the global mean temperature will increase between 1.8 degrees Celsius to 4.0 degrees Celsius. Temperature increases of only a few degrees may contribute to variances in snow-based tourism reliant on the reliability of natural snow cover. This study examines the spatial and temporal impacts of climate change scenarios upon snowmobile season length and operations within the snowmobile industry in the Province of Ontario Canada to six climate change scenarios for the 21st century. Snowmobile trail operations in Ontario are reliant upon a minimum natural snow cover of 15 cm for smooth terrain trails and 30 cm to 60 cm for rough terrain trails, temperatures less than 0 degrees Celsius and, human and financial capital. Three or more consecutive snowmobile seasons with ≤ 28 days have been identified as having serious implications for human and financial capital necessary to develop and maintain the snowmobile trail system. As early as the 2020s, north eastern snowmobile districts are projected to be least vulnerable to changes in climate with the longest snowmobile seasons > 28 days, while south central snowmobile districts are projected to be the most vulnerable to changes in climate with the shortest snowmobile seasons of < 28 days. Snowmobile trail managers identified possible strategies to adapt to a changing climate (2020s to 2080s) including: pre-season preparation of the terrain including early season packing of snow cover, re-location of the most vulnerable snowmobile trails, and strengthening inter-district alliances.

Rapporten innefattar hur en funktionsprototyp till ett vinterhjälpmedel för en rollatorutvecklats. Alla de väsentliga stegen i utformningen beskrivs grundligt, från det att idéerkläcks tills dess att prototypen är klar för tillverkning. Utifrån en idé om ett vinterhjälpmedelhar arbetet fortlöpt till en prototyp bestående av en konstruktion med skidor som enkeltmonteras på rollatorn. Arbetet berör ergonomiska analyser på användande av prototypen samtdimensionering.Stor vikt under utvecklandet har lagts vid människan och hennes funktion för att få en produktanpassad efter rörelseapparatens förmågor och begränsningar.En nyhetsgranskning över produkten har utförts där utfallet var positivt, vilket innebär attprodukten nu är i ett läge där en patentansökan planeras.Produkten lämnar utrymme för vidareutveckling. / The report describes how a functional prototype of a winter aid for a rollator is developed.The essential steps of the design are described in detail, from brainstorming the ideas to theprototype being ready for production. Based on the idea of a winter aid of some sort the workhas proceeded to a prototype consisting of a design with skis that are easily mounted on therollator. The report describes the ergonomic aspects, the analysis conducted on the prototypeand strength of materials.Emphasis during development has been on the man and his function in order to get a productadapted to the musculoskeletal system's limitations and capabilities.A news review of the product has been performed where the outcome was positive, meaningthat the product is now in a situation where a patent application is being planned.The product leaves room for further development.

In remote sensing, the application determines the type of platform and scale used during air or space –borne data collection as the pixel size of the collected data varies depending on the sensor or platform used. Applications involving some cryospheric environments require the use of the microwave band of the electromagnetic spectrum, with snow water equivalent (SWE) studies making use of passively emitted microwave radiation. A key issue in the use of passive microwave remotely sensed data is its spatial resolution, which ranges from 10 to 25 kilometres. The Climate Research Branch division of the Meteorological Service Canada is using passive microwave remote sensing as a means to monitor and obtain SWE values for Canada’s varying land-cover regions for use in climate change studies. Canada’s diverse landscape necessitated the creation of a snow water equivalent retrieval algorithm suite comprised of four different algorithms; all reflecting different vegetative covers. The spatial resolution of small scale remotely sensed data does provide a means for monitoring Canada’s large landmass, but it does, however, result in generalizations of land-cover, and in particular, vegetative structure, which is shown to influence both snow cover and algorithm performance. The Climate Research Branch is currently developing its SWE algorithm for Canada’s boreal forest region. This thesis presents a means of successfully and easily collecting in situ remotely sensed data in the form of hemispherical photographs for gathering vegetative structure data to ground-truth remotely sensed data. This thesis also demonstrates that the Gap Light Analyzer software suite used for analyzing hemispherical photographs of mainly deciduous environments during the spring-fall months can be successfully applied towards cryospheric studies of predominantly coniferous environments.

A suitable climate, varied scenic terrain, and proximity of communities along Ontario’s system of 39,742 km of snowmobile trails have provided for domestic and international snowmobile tourism. Outdoor winter tourism in many parts of the world has been identified to be at risk to changes in global climate. The Intergovernmental Panel on Climate Change in its Fourth Assessment Report (AR4) reported a global increase of temperature of 0.74 degrees Celsius for the period 1906 to 2005 and estimates that by the end of the 21st century the global mean temperature will increase between 1.8 degrees Celsius to 4.0 degrees Celsius. Temperature increases of only a few degrees may contribute to variances in snow-based tourism reliant on the reliability of natural snow cover. This study examines the spatial and temporal impacts of climate change scenarios upon snowmobile season length and operations within the snowmobile industry in the Province of Ontario Canada to six climate change scenarios for the 21st century. Snowmobile trail operations in Ontario are reliant upon a minimum natural snow cover of 15 cm for smooth terrain trails and 30 cm to 60 cm for rough terrain trails, temperatures less than 0 degrees Celsius and, human and financial capital. Three or more consecutive snowmobile seasons with ≤ 28 days have been identified as having serious implications for human and financial capital necessary to develop and maintain the snowmobile trail system. As early as the 2020s, north eastern snowmobile districts are projected to be least vulnerable to changes in climate with the longest snowmobile seasons > 28 days, while south central snowmobile districts are projected to be the most vulnerable to changes in climate with the shortest snowmobile seasons of < 28 days. Snowmobile trail managers identified possible strategies to adapt to a changing climate (2020s to 2080s) including: pre-season preparation of the terrain including early season packing of snow cover, re-location of the most vulnerable snowmobile trails, and strengthening inter-district alliances.

The accurate estimation of snow water equivalent (SWE) in the Canadian sub-arctic is integral to climate variability studies and water availability forecasts for economic considerations (drinking water, hydroelectric power generation). Common passive microwave (PM) snow water equivalent (SWE) algorithms that utilize the differences in brightness temperature (Tb) at 37 GHz – 19 GHz falter in lake-rich tundra environments because of the inclusion of lakes within PM pixels. The overarching goal of this research was to investigate the use of multiple platforms and methodologies to observe and quantify the effects of lake ice and sub-ice water on passive microwave emission for the purpose of improving snow water equivalent (SWE) retrieval algorithms. Using in situ snow and ice measurements as input, the Helsinki University of Technology (HUT) multi-layer snow emission model was modified to include an ice layer below the snow layer. Emission for 6.9, 19, 37 and 89 GHz were simulated at horizontal and vertical polarizations, and were validated by high resolution airborne passive microwave measurements coincident with in situ sampling sites over two lakes near Inuvik, Northwest Territories (NWT). Overall, the general magnitude of brightness temperatures were estimated by the HUT model for 6.9 and 19 GHz H/V, however the variability was not. Simulations produced at 37 GHz exhibited the best agreement relative to observed temperatures. However, emission at 37 GHz does not interact with the radiometrically cold water, indicating that ice properties controlling microwave emission are not fully captured by the HUT model. Alternatively, active microwave synthetic aperture radar (SAR) measurements can be used to identify ice properties that affect passive microwave emission. Dual polarized X-band SAR backscatter was utilized to identify ice types by the segmentation program MAGIC (MAp Guided Ice Classification). Airborne passive microwave transects were grouped by ice type classes and compared to backscatter measurements. In freshwater, where there were few areas of high bubble concentration at the ice/water interface Tbs exhibited positive correlations with cross-polarized backscatter, corresponding to ice types (from low to high emission/backscatter: clear ice, transition zone between clear and grey ice, grey ice and rafted ice). SWE algorithms were applied to emission within each ice type producing negative or near zero values in areas of low 19 GHz Tbs (clear ice, transition zone), but also produced positive values that were closer to the range of in situ measurements in areas of high 19 GHz Tbs (grey and rafted ice). Therefore, cross-polarized X-band SAR measurements can be used as a priori ice type information for spaceborne PM algorithms, providing information on ice types and ice characteristics (floating, frozen to bed), integral to future tundra-specific SWE retrieval algorithms.

I Sverige utförs dagligen observationer av snöns djup och utbredning under snösäsongen.Observationerna används till exempel för att årsvis avgöra maximalt snödjup, snötäckets första ochsista dag samt antal dygn med snötäcke på olika platser. Traditionellt utförs snödjupsmätningarmanuellt med en enkel mätpinne, men med ny teknik kommer nya möjligheter. Med enultraljudssnömätare kan automatiserade snödjupsmätningar utföras med bättre upplösning i bådetiden och rummet vilket därmed ger bättre uppfattning av snöns tillväxt, hopsjunkning samtsmältning och innebär att alla signifikanta förändringar i snötäcket garanterat kommer observeras. I denna utvärdering har en jämförelse gjorts av manuella och automatiska snödjupsmätningarutförda parallellt på samma plats men med olika frekvens. Instrumentet som utvärderats är enSR50A Sonic Ranging Sensor uppmonterad vid Institutionen för geovetenskapers mätstation vidUppsala universitet. Vid mätstationen görs även manuella snödjupsmätningar en gång per dag. Deautomatiska snödjupsmätningarna genomförs varje minut och medelvärdesbildas över ett 10minuters intervall. Utvärderingen visar att de båda metodernas mätresultat stämmer mycket väl överrens förutomen mer eller mindre systematisk skillnad. I medeltal ger Sonic Ranging Sensorn 1,6 cm större snödjup,något som till största del kommer av en osäkerhet vid kalibreringen av instrumentet. Resultaten visartydligt på en bättre upplösning hos de automatiska mätningarna men att de manuella mätningarnaändå fått med de stora förändringarna av snötäcket vad gäller tillväxt, minskning samt max‐ ochmindjup. Rådata från Sonic Ranging Sensorn visade på större och mindre fluktuationer som berodde påosäkra mätningar. Kvaliteten på mätningarna har avgjorts antingen med instrumentets inbyggdakvalitetsnummer eller utifrån max‐ och minvärden på snödjupet tagna under varje 10 minutersintervall. De faktorer som försämrade kvaliteten i mätningarna var först och främst snöfall, men ävenregndroppar eller snö som drev på grund av vinden gav försämrad kvalitet. Instrumentets känslighetför temperaturdifferensen i skiktet precis ovanför snöytan har också utvärderats vilket visade att detemperaturmätningar som görs i nuläget på 1,5 m höjd ger tillräckligt bra mätresultat. Det skildeendast 0,14 cm i medeltal om temperaturdifferensen togs med i beräkningarna av snödjupet. Förutom en systematisk skillnad visade sig drivbildning inom mätområdet vara den faktor som gavstörst skillnad mellan manuella och automatiska snödjupsmätningar. För att avgöra hurrepresentativa snödjupsmätningarna vid mätstationen är i jämförelse med närområdet och därmedockså eliminera påverkan av drivbildning genomfördes ytterligare manuella mätningar av snödjupetpå ett homogent fält i närheten. Resultaten visar att de manuella mätningarna vid mätstationen gerett för området representativt snödjup. / During the snow season, daily observations of snow depth and distribution are performed all aroundSweden. The observations are for example used to yearly determine maximum snow depth, first andlast day of snow coverage and number of days with snow coverage in different areas. Manual snowdepth measurements are traditionally performed with a simple measurement stick but with newtechnology new possibilities arise. With an ultrasonic snow depth sensor, automatic snow depthmeasurements can be performed with much better resolution in both time and space, thus give amore detailed picture of the growth, compaction and melting of the snow coverage. There is also norisk to miss out on any important changes in the snow coverage. In this evaluation, a comparison has been made between manual and automatic snow depthmeasurements performed parallel on the same place but with different frequency. The instrumentthat has been evaluated is a SR50A Sonic Ranging Sensor mounted at a measuring station near theDepartment of Earth Sciences, Uppsala University. At the measuring station manual snow depthmeasurements are made once a day. The automatic snow depth measurements are made everyminute and an average is taken over a 10 minute interval. The evaluation shows that the measuring results of both techniques follow each other very wellexcept for a more or less systematic difference. The Sonic Ranging Sensor gives in average 1.6 cmlarger snow depth which mostly is due to in uncertainty in the calibration of the instrument. Theresults clearly show a better resolution in the automatic snow depth measurements, although themanual measurements still show all significant changes of the snow coverage when it comes togrowth, compaction, maximum and minimum depth. Raw data from the Sonic Ranging Sensor showed some large amplitude and small amplitudefluctuations that were implemented by uncertainty in the measurements. The quality of themeasurements have been determined either with the built in quality number of the instrument orfrom maximum and minimum snow depth measurements during each 10 minute interval. The factorsthat reduced the quality of the measurements was mainly snow fall, but also rain drops or driftingsnow reduced the quality. The sensitivity of the instrument due to the temperature difference in thelayer just above the snow surface was also evaluated, showing that the temperature measurementsthat currently are performed at 1.5 m height give good enough measuring results. The difference wasonly 0.14 cm in average if the temperature difference was taken into account when calculating thesnow depth. Except for a systematic difference, drifting snow inside the measuring area was the factor givinglargest difference between manual and automatic snow depth measurements. To determine howrepresentative the snow coverage at the measuring station is compared to the local area, extramanual measurements were performed at a field near the station. The result shows that themeasuring station has a representative snow depth.

TEMPORAL EVALUATION OF SNOW DEPLETION CURVES DERIVED FOR UPPER EUPHRATES BASIN AND APPLICATIONS OF SNOWMELT RUNOFF MODEL Marim, G&ouml / khan M.S., Department of Geodetic and Geographic Information Technologies Supervisor: Prof.Dr.A.&Uuml / nal Sorman September 2008, 112 pages Water is becoming very important issue day by day with descending usable water and energy resources. In the aspect of water resources management, especially for the optimum reservoir management, predicting runoff for large reservoirs by applying hydrologic model is a recent and crucial topic. The most important model input and predictor parameters to estimate runoff for the mountainous regions are to be distribution of rainfall / temperature and snow cover area, (SCA). It is seen that many predictor variables should be integrated with Geographic Information Systems (GIS) and Remote Sensing Techniques especially for hydrologic model variable preparation. Satellite products have the potential for obtaining those kinds of data in near real time. In this study, the changes of SDC are generated by the analysis of optical satellite and by using SDC as an input to hydrological models runoff is simulated for Upper Euphrates Basin (10215.7 km2) which is a sub basin of Euphrates Basin. Largest dams of Turkey / Keban, Karakaya and Atat&uuml / rk are located on Euphrates River. Optimum operations of these dams depend on forecasting incoming water in early summer season. Euphrates River is fed mainly from snowmelts in spring or early summer time.65-70 % of the annual flow is contributed from snowmelt in that region. Main objective of this study is to obtain the spatially and temporally distributed SCA percentages from optical satellite, which are required as one of the main input variables of the hydrological model used in the application. SCA percentages and SDC are obtained for snowmelt years 2004-2007 by using high temporal resolution optical remote sensing data: Terra Moderate Resolution Imaging Spectroradiometer (MODIS). In this study, Terra MODIS snow cover map product, MOD10A1 which has a spatial resolution of 500 m is used. As a hydrological model Snowmelt Runoff Model (SRM) was applied. SRM was built up on the well-known degree day approach. In this study SRM is simulated for two years 2006 and 2007.The simulation results are compared and resultant model parameters are obtained for future runoff forecast studies. In this study, beside recommendations, discussions on the variables and SRM parameters are also provided.

Kars is an ethnically diverse city located at the North East Turkey, neighboring Armenia. In the year 2002, Nobel laureate author Orhan Pamuk published a political-historical novel named Snow, the story of which is set in Kars. The book created a public debate on national and global scale about cutting edge questions of Turkey. This thesis aims to address these questions from the perspective of inhabitants of Kars, who had reacted fiercely to the representations in the book Snow. By focusing on identification and boundary negotiation processes of people in Kars, this thesis and presents an ethnography of Kars, which was achieved by application of grounded theory method and by discussing local perceptions of ethnicity, nationalism and secularism at the periphery of Turkey.

The accurate estimation of snow water equivalent (SWE) in the Canadian sub-arctic is integral to climate variability studies and water availability forecasts for economic considerations (drinking water, hydroelectric power generation). Common passive microwave (PM) snow water equivalent (SWE) algorithms that utilize the differences in brightness temperature (Tb) at 37 GHz – 19 GHz falter in lake-rich tundra environments because of the inclusion of lakes within PM pixels. The overarching goal of this research was to investigate the use of multiple platforms and methodologies to observe and quantify the effects of lake ice and sub-ice water on passive microwave emission for the purpose of improving snow water equivalent (SWE) retrieval algorithms. Using in situ snow and ice measurements as input, the Helsinki University of Technology (HUT) multi-layer snow emission model was modified to include an ice layer below the snow layer. Emission for 6.9, 19, 37 and 89 GHz were simulated at horizontal and vertical polarizations, and were validated by high resolution airborne passive microwave measurements coincident with in situ sampling sites over two lakes near Inuvik, Northwest Territories (NWT). Overall, the general magnitude of brightness temperatures were estimated by the HUT model for 6.9 and 19 GHz H/V, however the variability was not. Simulations produced at 37 GHz exhibited the best agreement relative to observed temperatures. However, emission at 37 GHz does not interact with the radiometrically cold water, indicating that ice properties controlling microwave emission are not fully captured by the HUT model. Alternatively, active microwave synthetic aperture radar (SAR) measurements can be used to identify ice properties that affect passive microwave emission. Dual polarized X-band SAR backscatter was utilized to identify ice types by the segmentation program MAGIC (MAp Guided Ice Classification). Airborne passive microwave transects were grouped by ice type classes and compared to backscatter measurements. In freshwater, where there were few areas of high bubble concentration at the ice/water interface Tbs exhibited positive correlations with cross-polarized backscatter, corresponding to ice types (from low to high emission/backscatter: clear ice, transition zone between clear and grey ice, grey ice and rafted ice). SWE algorithms were applied to emission within each ice type producing negative or near zero values in areas of low 19 GHz Tbs (clear ice, transition zone), but also produced positive values that were closer to the range of in situ measurements in areas of high 19 GHz Tbs (grey and rafted ice). Therefore, cross-polarized X-band SAR measurements can be used as a priori ice type information for spaceborne PM algorithms, providing information on ice types and ice characteristics (floating, frozen to bed), integral to future tundra-specific SWE retrieval algorithms.