Gotowa bibliografia na temat „GIS Techniques/Remote Sensing”

Information relating to the spatial characteristics of biophysical resources has been difficult to incorporate into land management. In this study statistical analysis was used to demonstrate that forage yield and quality were influenced by the water balance and soil physical properties. Traditional empirical modelling techniques were of limited utility as predictors of yield and quality. However, multivariate statistical techniques provide predictor variables for individual forage cuts but not for a complete growing season. GIS provided several distinct advantages over traditional statistical techniques. First, it provided techniques to interpolate point data (such as forage yield and quality variables), and provide spatial distributions for a wide number of biophysical properties. Secondly, overlaying forage variables such as yield with a digital elevation model in a categoric manner provided output displaying the spatial relationships between the variables. Relationships derived from overlays using elevation and water retention properties provided good spatial predictions for several forage variables. Thirdly, digitized colour-IR aerial photographs were incorporated into the GIS where the pixel information was combined as map overlays via a regression equation. The resulting output provided very accurate spatial predictions for forage yield and quality parameters. Finally, economic data was generated in a spatial context and the resulting display was used to assess the effects of irrigation and management on forage yield and quality. The results suggest that the GIS techniques combined with remote sensing and economic data offer exciting possibilities to model and present spatial data.<br>Land and Food Systems, Faculty of<br>Graduate

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 71-76).<br>City planners use information about a city's vegetation, urban morphology, and land-use to make decisions. The availability of high-resolution imagery is now expanding the type of information that can be used for planning as well as for understanding urbanization dynamics. This research uses very high resolution orthoimagery with three bands to obtain information about specific urban structures, such as roads and pavement, buildings, and solar panels, as well as non-impervious surface areas of vegetation and water. The maximum likelihood classifier (MLC) was used for the analysis of the images, and geographical information system (GIS) techniques were used to extract features. Two case studies were done for the cities of Phoenix, Arizona for the years 2004, 2006, 2008, and 2012 and for Seattle, Washington for 2002, 2005, and 2009. Results indicate that the area of buildings and the number buildings with solar panels have increased while the area of vegetation has increased for both Phoenix.and Seattle. The area of water has decreased for Seattle while the increase in water for Phoenix could suggest that more people are installing pools. The length of roads increases slightly for Seattle but decreases for Phoenix, a potential result of parking lots being converted into parking garages. The quantitative trends in the infrastructure were then compared to power law relationships between population and urban growing and scaling indicators.<br>by Lisa Yang.<br>S.M.

From the Proceedings of the 1995 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 22, 1995, Northern Arizona University, Flagstaff, Arizona

The Matsqui area of the Lower Fraser Valley exhibits extreme soil heterogeneity, as the alluvial soils in the area have been deposited by the Fraser River as a series of coarse-textured ridges and finer-textured depressional areas. This variability poses some obvious problems with respect to agricultural management. The main aim of this study was to evaluate soil spatial variability in four fields, and to relate this soil variability to corn production and quality. Site conditions, topography, and soil chemical and physical variables were related to corn biomass and nutrient concentrations using conventional correlation/regression analyses, and more spatially representative techniques such as those provided by remote sensing and geographic information systems. Variations in such biophysical variables as soil moisture, elevation, and bulk density had consistent impacts on corn productivity, although these effects varied from field to field, being influenced by inherent soil properties and individual field management. Good relationships were found between pixel brightness values extracted from digitized colour infra-red photos and corn quality variables. In three out of four fields, near infra-red pixel values gave good estimates of total corn crude protein content. Significant relationships were also found between pixel brightness values and corn phosphorus and calcium contents in certain fields. The spatial variability of corn quality and biomass could be quantified using image analysis classification techniques. The resulting classified images indicate to the farm operator where high vs low quality corn is being produced, and thereby provide a tool for selectively managing and harvesting the fields. The relationships and quantification of corn productivity and quality in the fields can further be improved through incorporation of the image data with the biophysical data base using GIS techniques. A multiple regression equation showing a significant relationship between elevation and pixel brightness values, and total corn phosphorus concentration was incorporated within the GIS to produce a quantitative corn quality map for the field exhibiting this relationship. The GIS overlay capability facilitates the classification of several corn variables, and allows the results to be displayed in a spatial manner. For example, corn biomass and quality maps were overlain using GIS techniques, to produce a combination map which then reflected both the quality and quantity of corn found in the field. Through integration of remote sensing and GIS techniques, soil and crop variability can be displayed in a spatial manner. The output from such procedures can aid farm operators in making selective field management and harvesting decisions.<br>Land and Food Systems, Faculty of<br>Graduate

Estimating groundwater recharge to aquifer systems is a very important element in assessing the water resources of the West Bank. Of particular interest is the sustainable yield of the aquifers. Previous studies have developed analytical recharge models that are based on the long-term annual rainfall data. These models have been shown to be inadequate and changes over shorter periods, e.g. monthly estimates, must be known in order to study the temporal distribution of recharge. The approach used in this research integrates data derived from satellite images (e.g. land cover, evapotranspiration, rainfall, and digital elevation model) with hydrogeological data in a Geographic Information System (GIS) model to identify and map the surface recharge areas. The Surface Energy Balance Algorithm for Land (SEBAL) is applied to time series of remote sensing MODerate Resolution Imaging Spectroradiometer (MODIS) level 3 data of reflectance and surface temperature measurements to estimate monthly evapotranspiration; precipitation is derived from the monthly data sets of the Tropical Rainfall Measuring Mission (TRMM); runoff is given assumed values of 0.75 mm month-1 and 0.4 mm month-1 for the months of January and February, respectively. Recharge is quantified from November until March by applying the water balance method where evapotranspiration estimates and runoff are subtracted from precipitation. Results show good agreement between data reported in the literature and remote sensing-based analysis. Empirical models that are based on long term rainfall measurements suggest recharge values between 800 and 836 MCM yr-1 while the remote sensing based model results estimate recharge to be 700 MCM yr-1. The Western, North-Eastern, and Eastern Aquifer Basins receive 30%, 23%, and 47% of the total calculated recharge while percentages available in the literature provide 49%, 22%, and 29%, respectively. Discrepancies are mainly due to lack of field data, the overestimation of actual evapotranspiration, and underestimation of TRMM precipitation values. The recharge map indicates that the most effective groundwater recharge zones are located in the north and west of the area that is characterised by thick and well developed soil deposits, heavy vegetation, and a sub-humid climate with the potential of significant recharge occurring during the wet season. Some areas in the east include concentration of drainage and stream flows which increase the ability of to recharge the groundwater system. The least effective areas are in the south and south-west region that is more arid with much less recharge, mainly due to its isolated thin soil deposits. A sensitivity analysis was carried out to demonstrate the impact of land cover change on groundwater and natural recharge. The assessment involved the use of land covers of 1994 and 2004 with the same fixed parameters of evapotranspiration, precipitation, drainage, slope, soil, and geology. Results show a decrease in high and intermediate high recharge areas from 40.25 km2 and 2462.25 km2 in year 1994 to 15.5 km2 and 1994 km2 in 2004, respectively. This illustrates the extent of land cover/land use change influence on recharge and calls for integrated plans and strategies to preserve recharge at least at its current rates.

The Skelton Glacier is one of the many smaller outlet glaciers located in the Transantarctic Mountains, where it drains ice into the Ross Ice Shelf. These outlet glaciers are important when determining the past, present, and future state of the mass balance of the East Antarctic Ice Sheet. This research uses satellite imagery acquired over a period of 15 years to obtain a high resolution velocity field for the Skelton Glacier which is then used to calculate the mass flux and mass balance at ten flux gates along the glacier using the input-output method. The high resolution velocity field is combined with ice thickness data and accumulation data from other sources to obtain the total mass balance. The high resolution velocity field of the Skelton Glacier was created using European Remote-Sensing Satellite 1 and 2 (ERS-1/2) Synthetic Aperture Radar (SAR) data acquired in 1996 with the processing technique of SAR interferometry (InSAR). Because of the lack of differential InSAR pairs, new auxiliary data from the ICESat and TanDEM-X mission were included into the analysis. A velocity field was created at a spatial resolution of 50m which was validated with in situ GPS measurements from 2011/12, and compared to lower resolution velocity fields of the Skelton Glacier. The ice velocity field is at improved accuracy for this area compared to previous studies and is thought to be representative for the mean ice velocity. The analysis of ice flux at several flux gates allowed an improved error estimation of the applied technique to estimate the overall mass balance. Mass flux estimates along the glacier were calculated using the new velocity field and additional thickness data, which was then compared to two accumulation datasets to give mass balance estimates along the glacier at selected flux gates. The mass flux through the grounding line was found to be 1.2165 Gt a⁻¹, which needs to be balanced in a state of mass balance equilibrium by a mean annual snow accumulation of about 185 mm a⁻¹ water equivalent over the total catchment area determined with 6569 km². The mass balance at the grounding line is slightly negative, but the second flux gate is thought to be more representative of the mass balance, which is estimated to be 0.0441 Gt a⁻¹. Error analysis of the mass balance estimates found uncertainties in this data to be approximately 0.110 Gt a⁻¹. It is concluded from the analysis that further improvements in the overall mass balance estimate can be primarily obtained by a better knowledge of ice thickness and snow accumulation.