Geographically Referenced Data for Social Science

An estimated 80% of all information has a spatial reference. Information about households as well as environmental data can be linked to precise locations in the real world. This offers benefits for combining different datasets via the spatial location and, furthermore, spatial indicators such as distance and accessibility can be included in analyses and models. HSpatial patterns of real-world social phenomena can be identified and described and possible interrelationships between datasets can be studied. Michael F. GOODCHILD, a Professor of Geography at the University of California, Santa Barbara and principal investigator at the Center for Spatially Integrated Social Science (CSISS), summarizes the growing significance of space, spatiality, location, and place in social science research as follows: "(...) for many social scientists, location is just another attribute in a table and not a very important one at that. After all, the processes that lead to social deprivation, crime, or family dysfunction are more or less the same everywhere, and, in the minds of social scientists, many other variables, such as education, unemployment, or age, are far more interesting as explanatory factors of social phenomena than geographic location. Geographers have been almost alone among social scientists in their concern for space; to economists, sociologists, political scientists, demographers, and anthropologists, space has been a minor issue and one that these disciplines have often been happy to leave to geographers. But that situation is changing, and many social scientists have begun to talk about a "spatial turn," a new interest in location, and a new "spatial social science" that crosses the traditional boundaries between disciplines. Interest is rising in GIS (Geographic Information Systems) and in what GIS makes possible: mapping, spatial analysis, and spatial modelling. At the same time, new tools are becoming available that give GIS users access to some of the big ideas of social science."

Geographically referenced data for social science

"Die Autoren beschreiben in ihrem Beitrag den Mehrwert der Nutzung von Geodaten in den Sozialwissenschaften. Sie liefern vor allem eine Reihe praktischer Hinweise auf die Bezugsquellen von Geodaten. Beispielhaft legen sie dar, wie sich Geodaten mit Daten des Sozio-oekonomischen Panels (SOEP) kombinieren lassen. Der erste Teil ihres Beitrags enthält eine nähere Beschreibung von Geodaten und des Geographischen Informationssystems (GIS). Das zweite Kapitel beschäftigt sich mit den Zielgruppen und Nutzern, es erläutert die der Dokumentation zugrunde liegende Definition der Geodaten und zeigt die Vorzüge und Herausforderungen beim Einsatz von Geodaten in der sozialwissenschaftlichen Forschung auf. Das dritte Kapitel verdeutlicht anhand zahlreicher Beispiele das Potenzial von Geodaten als eine zusätzliche Informationsquelle für die empirische Forschung. Abschließend wird ein Überblick über verfügbare Geodaten in Deutschland und die am meisten nachgefragten Daten in den Sozialwissenschaften gegeben. Der Anhang des Beitrags enthält Internet-Links für Datenquellen, Hinweise zur verfügbaren GIS-Software und weitere Informationen." (ICI

Wayne E. Sabbe Arkansas Soil Fertility Studies 2018

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas

Recent Progress in Urbanisation Dynamics Research

This book is dedicated to urbanization, which is observed every day, as well as the methods and techniques of monitoring and analyzing this phenomenon. In the 21st century, urbanization has gained momentum, and the awareness of the significance and influence of this phenomenon on our lives make us take a closer look at it not only with curiosity, but also great attention. There are numerous reasons for this, among which the economy is of special significance, but it also has many results, namely, economic, social, and environmental. First of all, it is a spatial phenomenon, as all of the aspects can be placed in space. We would therefore like to draw special attention to the results of urbanization seen on the Earth's surface and in the surrounding space. The urbanization–land relation seems obvious, but is also interesting and multi-layered. The development of science and technology provides a lot of new tools for observing urbanization, as well as the analyses and inference of the phenomenon in space. This book is devoted to in-depth analysis of past, present and future urbanization processes all over the world. We present the latest trends of research that use experience in the widely understood geography of the area. This book is focused on multidisciplinary phenomenon, i.e., urbanization, with the use of the satellite and photogrammetric observation technologies and GIS analyses

Quantifying terrain factor using GIS applications for real estate property valuation

This thesis studies the use of GIS applications to derive adjustment figures for the terrain factor in property valuation tasks. It aims at suggesting a quantitative approach alternative to evaluate the terrain factor as opposed to traditional methods and current industry practices where terrain is qualitatively judged based on visual observation at site and subjected to individual opinion. In this study, the terrain factor is considered by analysing the slope and surface roughness elements of terrain. To achieve this, slope and surface roughness values are generated from available open source digital elevation models (DEMs) within the Esri ArcGIS software environment. For the purposes of this study, the Shuttle Radar Topography Mission (SRTM) DEM developed by National Geospatial-Intelligence Agency (NGA) and United States National Aeronautics and Space Administration (NASA), as well as the Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM jointly developed by Ministry of Economy, Trade and Industry, Japan (METI) and NASA, were used to derive terrain values. The output adjustments were tested on several hypothetical valuation cases, consisting of small and large properties, to see the effects of DEM resolution upon the results. In order to test the accuracy of the proposed-adjustment outputs and applicability of the study methods, feedbacks from industry experts were collected via an online survey for analysis. Upon analysing the feedbacks, this study finds that industry experts are of the opinion that the terrain adjustments proposed by this method are reasonable for use in the industry practice, although some apprehensions were also noted, as property valuers tend to exercise caution when using automated valuation methods. The proposed method is simple to apply and does not require advanced knowledge of GIS functions to operate. Therefore, considering the positive feedback from the valuation community, it could pave way towards future incorporation of geostatistical methods/ components in value analysis.Tesis ini mengkaji kegunaan aplikasi GIS untuk mendapatkan pekali pelarasan bagi faktor rupabumi dalam kerja-kerja penilaian. Maksud kajian adalah untuk mencadangkan pendekatan kuantitatif bagi mempertimbangkan faktor rupabumi sebagai alternatif kepada kaedah tradisional dan amalan semasa industri yang bersifat kualitatif, yang mana faktor rupabumi diputuskan berdasarkan pemerhatian visual di tapak dan tertakluk kepada pendapat peribadi. Dalam kajian ini, faktor rupabumi dipertimbangkan melalui analisis ke atas elemen kecerunan dan kekasaran permukaan rupabumi. Nilai kecerunan dan kekasaran rupabumi dijana daripada model aras digital (DEM) yang diperolehi daripada sumber terbuka (open source) menggunakan pakej perisian Esri ArcGIS. Untuk tujuan kajian ini, nilai elemen cerun diperolehi dari DEM Shuttle Radar Topography Mission (SRTM) yang dibangunkan oleh National Geospatial-Intelligence Agency (NGA) dan United States National Aeronautics and Space Administration (NASA) serta DEM Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) yang dibangunkan melalui usahasama Kementerian Ekonomi, Perdagangan dan Industri, Jepun (METI) dan NASA. Cadangan pelarasan yang dijana (output) daripada kajian ini diuji dalam beberapa kes penilaian andaian (hypothetical) yang terdiri daripada harta tanah bersaiz kecil dan besar, bagi mengkaji kesan perincian resolusi DEM ke atas penilaian. Bagi menguji ketepatan output pelarasan yang disyorkan dan kesesuaian aplikasi syor pelarasan oleh kaedah-kaedah kajian, maklum balas daripada pakar-pakar industri dikumpul melalui soal-selidik atas talian (online) untuk dianalisis. Berdasarkan maklum balas soal-selidik, pakar-pakar industri pada umumnya berpandangan kadar pelarasan faktor rupabumi yang disyorkan oleh kaedah-kaedah kajian ini adalah munasabah untuk digunakan walaupun beberapa keraguan turut dikesan, tetapi ini adalah kerana penilai berjaga-jaga dengan nilaian janaan komputer. Kaedah yang dicadangkan oleh kajian ini adalah mudah untuk diaplikasi dan tidak memerlukan pengetahuan yang mendalam tentang GIS untuk digunapakai. Oleh itu, memandangkan maklum balas yang diterima daripada komuniti penilai adalah positif, kaedah kajian mungkin dapat membuka langkah bagi memasukkan (include) komponen analisis geostatistik dalam analisis nilai di masa hadapan.The comparison method of valuation is based on the basic principal that properties that are close to one another in location and most similar to each other in feature would logically be similar in value. Using this method, the value of a subject property at a specific time and for a specific purpose is determined by gathering comparable sale evidences at the stated date of transaction, whereby the transacted amount of the comparable is adjusted to account for factors of dissimilarity between the comparable and the subject. While some factors (e.g.: size) is numerical in nature and thus may be analysed quantitatively, in current practice, many other factors are being analysed qualitatively based on observation and personal opinion. Although this qualitative way of analysing property factors is widely accepted within the valuation community, such approach allows for a wide area for interpretation as it is difficult to put a scale on personal views and opinions. Studies in spatial statistics have contributed towards the development of GIS applications that is able to deal with spatial data in a quantitative manner. In relation to that, this project attempts to use GIS application to analyse a selected adjustment factor to be incorporated into the valuation practice. This project will propose adjustment values for the surface terrain factor, by generating slope and surface roughness values from free Digital Elevation Models (DEMs). These values are then linked to the corresponding property unit to obtain the average terrain value per property. The terrain value of the comparable property unit is then compared to the terrain value of the subject property and the difference is analysed to suggest a reasonable adjustment value for the comparable. The adjustment outputs derived from the study methods are tested by gathering feedback from property experts via an online survey based on several hypothetical valuation cases. Response from the survey notes that most respondents find the derived adjustment outputs as reasonable for application in industry, although there are some inconsistencies noted in the survey results, likely due to the small sample size used in the project, as well as due to the coarse resolution of the DEMs used. It should be noted that the methods proposed in this project is simple to use and does not require advance knowledge in GIS to operate. In fact, it should be said that this method may readily be used, especially in the event of available high quality elevation data

Coastal management and adaptation: an integrated data-driven approach

Coastal regions are some of the most exposed to environmental hazards, yet the coast is the preferred settlement site for a high percentage of the global population, and most major global cities are located on or near the coast. This research adopts a predominantly anthropocentric approach to the analysis of coastal risk and resilience. This centres on the pervasive hazards of coastal flooding and erosion. Coastal management decision-making practices are shown to be reliant on access to current and accurate information. However, constraints have been imposed on information flows between scientists, policy makers and practitioners, due to a lack of awareness and utilisation of available data sources. This research seeks to tackle this issue in evaluating how innovations in the use of data and analytics can be applied to further the application of science within decision-making processes related to coastal risk adaptation. In achieving this aim a range of research methodologies have been employed and the progression of topics covered mark a shift from themes of risk to resilience. The work focuses on a case study region of East Anglia, UK, benefiting from the input of a partner organisation, responsible for the region’s coasts: Coastal Partnership East. An initial review revealed how data can be utilised effectively within coastal decision-making practices, highlighting scope for application of advanced Big Data techniques to the analysis of coastal datasets. The process of risk evaluation has been examined in detail, and the range of possibilities afforded by open source coastal datasets were revealed. Subsequently, open source coastal terrain and bathymetric, point cloud datasets were identified for 14 sites within the case study area. These were then utilised within a practical application of a geomorphological change detection (GCD) method. This revealed how analysis of high spatial and temporal resolution point cloud data can accurately reveal and quantify physical coastal impacts. Additionally, the research reveals how data innovations can facilitate adaptation through insurance; more specifically how the use of empirical evidence in pricing of coastal flood insurance can result in both communication and distribution of risk. The various strands of knowledge generated throughout this study reveal how an extensive range of data types, sources, and advanced forms of analysis, can together allow coastal resilience assessments to be founded on empirical evidence. This research serves to demonstrate how the application of advanced data-driven analytical processes can reduce levels of uncertainty and subjectivity inherent within current coastal environmental management practices. Adoption of methods presented within this research could further the possibilities for sustainable and resilient management of the incredibly valuable environmental resource which is the coast

The Spatial Economics of Clean Energy in New Jersey

Clean energy policy is critically important in driving reductions of greenhouse gases and mitigating climate change. As clean energy technologies improve over time and interact with social systems and broader energy markets, there is a need for innovative environmental management that supports development of new clean energy policy. Understanding where these technologies may be deployed, quantifying the anticipated benefits, and mitigating risks are required for successful policy optimization. With these considerations in mind, this dissertation explores geothermal heat pumps (GHP), solar photovoltaics, and the Regional Greenhouse Gas Initiative (RGGI). We call upon spatial economics to investigate these topics by incorporating the biophysical environment, socioeconomic factors, and economic considerations in our methodology to approach this problem from a holistic environmental management perspective. Reducing energy end use is a climate mitigation strategy that can be applied across the building, industry, and transportation sectors. Increasing energy efficiency, particularly in the building sector, is a promising means to reduce energy end use. In the second chapter of this dissertation, we perform a place-based investigation of GHP systems in New Jersey. In doing so we provide new baseline information on which building sectors this technology is most used and identify areas of significant clustering. Both of which provide insights for new energy efficiency policy within the study area. In the third chapter, we conduct a life cycle assessment of geothermal heat pumps to assess the cradle-to-grave environmental and human health impacts throughout the lifetime of a system operating in New Jersey. The results of this section highlight lower environmental and human impacts associated with GHP systems operating within New Jersey compared to the rest of the United States. We also conclude that GHP systems are significantly less impactful throughout their lifetime and operation as compared to other heating and cooling configurations that are common in the state. A combination of renewable energy technologies such as wind and solar photovoltaics will be an integral part of the clean energy electric generation portfolio of the future. Understanding where these systems are best located and how the public values their benefits can support smart policy decisions. In the fourth chapter, we evaluate solar photovoltaic potential using hosting capacity interpolation, multi-market suitability models, and remote sensing. The findings show hosting capacity of potential solar siting locations varies within each electric distribution company (EDC) territory. The results of the suitability models highlight areas for targeted local investigations of project suitability and community solar off-taker potential. Our municipal remote sensing analysis yield valuable local scale information of roof geometry, flood hazards, and solar radiation potential which can be used to streamline system siting and design. In the fifth chapter, we conduct a consumer willingness to pay survey for potential community solar customers in New Jersey. Evaluating the responses of over six-hundred residents underscores the common barriers to traditional residential net metering, such as home ownership and financial requirement. It also illuminates consumers’ willingness to participate in community solar projects that improve environmental quality and are sited in commercial settings and landfills. Reducing the carbon dioxide emissions associated with the electric generation sector will be crucial in mitigating future climate change. Emission trading schemes (ETS) are a regulatory approach that forces emitters to internalize the negative externalities of carbon dioxide with the goal of driving emission efficiency improvements and creating funding mechanisms to support other climate mitigation and adaptation efforts. In the sixth chapter, we perform a qualitative policy analysis of the Regional Greenhouse Gas Initiative (RGGI) ETS in the context of generation shifting mitigation. We identify the best mitigation approaches as the program expands to be a combination of increased monitoring and modeling, promoting load reductions through efficiency, and expanding the RGGI program to states within distribution systems that have partial state participation. In New Jersey, successful climate mitigation and clean energy transitions are a function of policy, available technology, and energy markets. Historically, stringent air quality regulations and inexpensive natural gas have led to efficient fossil generation within the state. Additionally, early progressive solar policies have led to a robust solar industry and resulting overall in-state solar photovoltaic capacity ranking high in the nation. Although low-hanging fruit may be relatively sparse, current political environments in the state have been supportive of improved climate action and sparked increased potential for academic research to make tangible contributions to new clean energy policy. As the state continues to transition towards a clean energy future, government administrations, regulatory agencies, grid operators, research institutions, and stakeholders must work alongside each other to develop new policies that support increased climate mitigation. Currently in New Jersey, the potential of clean energy has not been adequately researched, particularly on local and regional scales. The goal of this research is to address this gap by contributing to the body of knowledge in our applied subject areas. The spatial economic approach can be used effectively in clean energy investigations because energy is inherently influenced by economics and geography. We anticipate the overall findings of this work to be applied within the study area to increase clean energy generation and access, promote the clean energy economy, and conserve valuable landscapes

Leveraging geospatial statistics for measuring and valuing the urban environment

This thesis looks at emerging uses of geospatial data for analysing the urban environment. As high-dimensional data becomes increasingly available, sophisticated spatial and temporal statistical estimation strategies can assess the minutia of environmental processes in a dynamic urban context. Each essay focuses on the improved measurement of high-resolution non-market environmental amenities and evaluating them using observed impacts on house prices or transportation networks. While valuation techniques for each amenity vary depending on context, these works all highlight a set of spatial methodologies for detailed urban analytics with a particular focus on urban greenery, seismic and flood risk, and pollution mitigation