Teknisk utveckling och ökad användning av GIS har ökat behovet av data som snabbt kan insamlas över stora geografiska områden. Behovet är internationellt samtidigt som det också kräver samarbete mellan alla berörda parter då systemet har förmågan att presentera geografisk information med ett brett användningsområde. Höjdförhållanden i terräng erhålls genom flygburen laserskanning och presenteras i 3D med olika klassningar för att bemöta variation i signalens reflektion. Behovet av sådan information har använts för produkter baserat på data erhållen från laserskanning. I examensarbetet användes laserdata från två skanningsomgångar beställda av Lantmäteriet. Den första laserskanningen (2011) utfördes i syfte att skapa en noggrann nationell höjdmodell innehållande klassificering av de laserpunkter som representerar mark och vatten. Den senare (2019) i syfte att uppnå en punkttäthet >1 punkt/m2 utan kriterier för vad som skall klassificeras. Syftet med examensarbetet är att testa och utvärdera olika metoder i ArcGIS Pro, QGIS samt FME för att kvalitetssäkra kartering av hustak. Målet är att visa om extraheringen kan utföras med en tillräcklig kvalitet för att metoden ska rekommenderas. Tidigare studier har fokuserat på att skapa tre olika typer höjdmodeller DEM/DTM, DSM och nDSM, samt hur man kan skapa en markyta med objekten över marken. Examensarbetet fokuserade på att klassificera oklassificerade punkter som byggnader finns inom. Detta utfördes med olika metoder i de program som användes med samma parametrar. Klassificering, extrahering och skapande av polygoner var de tre steg som användes för att extrahera hustak. Extrahering av hustak gav ett bättre resultat med ArcGIS Pro med 97 % från båda skanningsomgångarna. Detta värde berodde på cellstorlek som användes och hur buffertzoner omkring varje punkt påverkas på polygoner som i sin tur påverkades av hustakens areal. En enkät utfördes för att svara på en fråga och resultatet gav att ArcGIS Pro är bäst med 93,5 %. De problem som uppstod berodde främst på att vegetation inte kunde tas bort. Extrahering av byggnader från laserdata rekommenderas för ett punktmoln med den senare laserskanningen som har mer än 1 punkt/m². Vidare rekommenderas att använda ArcGIS Pro för att extrahera hustak från laserpunktmoln. ESRI’s ArcGIS Pro är ett komplett program som har alla verktyg som behövs. / The development of technology within GIS has increased the need for the data that being quickly added while covering large geographical areas. Such need is at the international level, while requiring a willingness to cooperate for all parties involved, as the system can present geographical information with a wide range of applications. The need for such information has been used for products based on data obtained from laser scanning. In this thesis, laser data from two scanning sessions ordered by the Swedish Land Survey were used. The first laser scan (2011) was carried out with the aim of creating an accurate national elevation model (RH 2000) containing a classification of the laser points representing soil and water. The latter (2019) was done to achieve a spot density >1 point/m2 without criteria for classification. The purpose of the current thesis is to test and evaluate the available methods in ArcGIS Pro, QGIS and FME to ensure quality mapping of roofs. The aim was to investigate whether the extraction of roofs? can be carried out with an adequate quality so that the method can be recommended for the future works. Previous studies have focused on creating three types of elevation models DEM / DTM, DSM and nDSM. So, one can create an earth surface with the objects above the ground. In this thesis, the focus was on classifying point clouds for unassigned points (unassigned == 1) in which the buildings are located. This was done by testing different methods on different programs while keeping the parameters same. Classification, extraction and creation of polygons are the three steps used to extract roofs. Extraction of rooftops showed better results using ArcGIS Pro with 97 % from both scanning sessions. This was due to the cell size used in the study and that the buffer zones around each point were affected by polygons, which in turn were affected by the rooftop area. A survey was conducted to answer a question and the result showed that ArcGIS Pro is the best with 93,5 %. Problems that arose the study were mainly caused by the vegetation cover that could not be removed. As a conclusion, extraction of buildings from LiDAR-data is recommended for a point cloud with the latter laser scan with more than 1 point/m². Furthermore, it is recommended to use ArcGIS Pro to extract rooftops from laser scanning which is a comprehensive program i.e. that all the tools used in this thesis were freely downloaded from ESRI's ArcGIS Pro.

Diploma thesis deals with the evaluation of threats on agriculture land by water erosion in the cadastral area of village Čikov before and after proposing of counter – erosion measures. For the calculation of erosion was used Universal equation (USLE) according to Wischmeier and Smith. The analytical operations leading to the calculation individual factors Universal equation and average long-term loss of soil by water erosion were made using the software ArcGIS, USLE2D and LS – Converter. Partial analysis are presented in the form of map outputs. In the interest area, after the calculating of the USLE, it was found that on 30,39 ha occurs very strong erosion which represents 4,73 % of the solved area. Strong erosion occurs on 36,56 ha (5,68 %), medium erosion on 229,94 ha (35,75 %) and slight erosion on 346,33 ha (53,84 %). Thanks to the proposed counter – erosion measures, very strong erosion in the interest area was completely eliminated. Strong erosion was reduced to only 2,52 ha (0,39 %) and medium erosion to 74,79 ha (11,58 %). Slight erosion increased to 566,21 ha (88,03 %).

State Departments of Transportation (DOTs) in the U.S. have an increasing amount of digital data from various sources. One such set of data is structured unit price data collected from bid lettings. Such data contain unit prices of thousands of bid items from hundreds of projects every year. While state DOTs have such data from over a decade-long period, utilizing such data has been challenging because of the lack of automated analytical and visualization methodologies and tools to generate meaningful and actionable insights. This study develops an automated methodology to quickly and accurately generate color-coded visualization maps representing unit price variation across a geographical region. It uses Inverse Distance Weighted (IDW) technique that is based on the Tobler’s First Law of Geography. The law states that points closer together in space are more likely to have a similar value than points that are farther away. The methodology is automated using ArcPy site package in ArcGIS. It imports unit price data from preformatted spreadsheets and boundary maps from existing ArcGIS shape files to generate unit price maps. The tool and the visualizations are expected to aid state DOTs in generating and communicating meaningful insights for making data-driven decisions. It can be used to investigate areas with higher unit prices for various items which can aid state DOTs in identifying potential causes of higher unit prices such as lack of competition and lack of sources of materials (e.g. quarry) in nearby locations.

The aim of diploma thesis is to compare methods of accessibility analysis in regions. The result of the analysis must cover only the region itself and not to overlap the neighbouring regions. This condition must be valid for every single region in the multi region system. The first part of the thesis deals with the methods which make the analysis possible. There are described their main characteristics and their advantages and disadvantages. The core part of the thesis consists of the detailed description of the functions and the approaches in the models and scripts, which were based on the methods identified in the former part. The methods are evaluated by the broad use of the models and scripts with various data samples. For every method is found an applicable use. The results are basis for the further inquires and questions eventually leading to the better understanding and the enhancement of the current approaches in that matters.

Diploma thesis is focused on creating anlysis of erosin risks on agriculture soils in cadastral areas Bor u Nedvědice and Sejřek. Thesis deals with calculation of erosion risks on ArcGIS program platform using the map baisics of State land office and Czech Geodetic and Cadastral Office. The fundamental goal of thesis is find out a present of erosion risks in interests area. For calculation of erosion will be used universal equation of USLE (Universal soil loss equation). The result of thesis is proposal of measures which will lead to reduce the influence of water erosion on agriculture soils. Protection of agriculture soils should be integral part of rural development and maintaining natural functions of rural, agriculture landscape.

This thesis deals with geoinformation analysis of comprehensive landscaping. The thesis compares calculations of the long-term soil loss using different digital terrain models and topographical factors. Subsequently the thesis focuses on the rating of the drain and erosive ratio on the basis of the analysis of the current status of the examined area, that is the circumference of the outcoming comprehensive landscaping in Kunovice cadastral area under the conditions of the conventional agriculture scenario. These resource materials helped the diploma thesis to design anti-erosion measures including the main agricultural roads and the system of ecological stability that was extended with the interactive elements for the needs of these measures. Afterwards their efectivity was succesfully measured. Results of plans are designed in the next part of the thesis to the form of map outputs and in the discussion were debated contributions of the plan from the perspetcive of the opening the water regime of the landscape, the danger of erosion and the ecological stability.

Limited knowledge exists of the terrain variables that have an influence on gopher tortoise (Gopherus polyphemus) burrow locations. Previous studies suggest that terrain features may play a role in preference of burrow location. LiDAR- (Light Detection and Ranging) derived terrain features can be evaluated through GIS (Geographic Information System) analysis at a fine spatial scale. LiDAR data acquired at 0.5 meter post spacing over three locations on Camp Shelby Joint Forces Training Center, MS were used to develop DTMs (Digital Terrain Models) for use in burrow site characterization. Terrain variables (e.g. elevation, slope, aspect) were developed from the LiDAR DTM in ArcGIS. Burrows and randomly allocated non-burrow points were used in logistic regression analysis to model the relationship between burrow occurrence and terrain features. Four models correctly classified more than 83% of the burrow locations. The R2 were 34.83%, 49.31%, 28.09%, and 31.51%.

Understanding and improving the state of the nation's levees has become a national priority following the devastating events surrounding Hurricanes Katrina and Rita. Federal legislation passed in 2007 created a new national Committee on Levee Safety and spurred the development of the National Levee Database, a central repository of information relating to the location and state of levees across the United States (Water Resources Development Act, 2007). One of the major goals in developing such a database is to improve the safety of America's levees. The National Levee Database, however, does not include features for storing seepage and slope stability data related to numerical analyses of levees. These data are critical in analyzing current levee conditions and predicting future failure scenarios, thus providing a path for further improving the safety of levees. The Levee Analyst is a new GIS data model and set of geoprocessing tools that make it possible to store and manipulate model data associated with seepage and slope stability analyses. The data model provides a concise structure for storing large amounts of levee seepage and slope stability data and also provides a structure that is expandable and compatible with the National Levee Database. The Levee Analyst combines the capabilities of various software systems in providing a data model and suite of tools that assists in further understanding and analyzing the state of America's levees.

Geoscience data sharing and processing is very advanced in terms of surface data. Subsurface data sharing has not received the attention that surface data sharing has received and so there are fewer applications or software packages which focus on it. This research is funded by the NSF EarthCube GEO Domain program in an effort to develop a continental-scale repository of 3D subsurface data to facilitate the sharing of complex 3D data and to enable the development of geoprocessing tools and workflows that operate on that data. The work in this thesis is a small part of the EarthCube project with two parts. The first part is to research current tools for 3D subsurface data visualization, specifically virtual globes, and to recommend one for use in the development of the EarthCube project. The second part is to develop an online prototype visualization platform for the EarthCube project referred to as the "Digital Crust" using the recommended virtual globe. Additional work was done with the Digital Crust to develop geoprocessing tools to show the ability for the Digital Crust to work with a data repository. These tools convert geoscience data file types, and interpolate soil cross-sections from borehole log data.

<p>Over the last few decades, household incomes have been rising steadily but the biggest share of that growth has been in the top income quintile. This unequitable growth is exacerbated by spatial factors, such as a household’s home location and the distribution of opportunities and resources around it. This thesis examines the effects of the distribution of places of employment and healthy food retailers on socioeconomic outcomes for households in the Phoenix Metropolitan Statistical Area (MSA). The main research objectives are to: i) calculate accessibility to employment and healthy food for public transit and automobile and identify low-access areas for the two modes; ii) determine the underlying reasons and recommend mitigation measures for the access gaps; and iii) investigate the associations between the calculated accessibility measures and socioeconomic outcomes for households. This is achieved by calculating healthy food accessibility, general job accessibility, industry job accessibility (i.e., access to jobs by the different North American Industry Classification System (NAICS) different industry sectors) and industry job mismatch (i.e., the difference in the general job accessibility and the industry job accessibility). We employ a modified Enhanced 2-step Floating Catchment Area (E2SFCA) method with continuously decaying weights using census data at the census block level, employment data from the Longitudinal Employer-Household Dynamics (LEHD) program in various North American Industry Classification System (NAICS) sectors, and locations of grocery stores from the Safegraph places dataset. Using spatial regression models, we estimate the associations between these calculated measures and socioeconomic outcomes. The analysis shows that there is a lack of transit access to healthy food and employment in the periphery of the MSA and that greater access is clustered around interstates and primary roads. The access by transit is worse than access by automobiles for most of the block groups. The spatial regression results show that renters find block groups with better access more attractive, and homeowners trade off that accessibility for better living conditions and other factors, such as school districts. People using the Supplemental Nutrition Assistance Program (SNAP) and people not high school educated have worse industry job accessibility; jobs that they are employed and qualified in are not accessible to these vulnerable populations. City planners and policy makers can use these findings to implement policies that can address the access gaps found and impact communities. </p>