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Geographic information systems to spatial data infrastructure : a global perspective
This book draws on author's wealth of knowledge working on numerous projects across many countries. It provides a clear overview of the development of the SDI concept and SDI worldwide implementation and brings a logical chronological approach to the linkage of GIS technology with SDI enabling data. The theory and practice approach help understand that SDI development and implementation is very much a social process of learning by doing. The author masterfully selects main historical developments and updates them with an analytical perspective promoting informed and responsible use of geographic information and geospatial technologies for the benefit of society from local to global scales. -- Provided by publisher.
Book
K-means Clustering Method Based on Kernel Density Estimation to Analysis Residents Travel Features: A Case Study of Chengdu
In order to study the spatiotemporal features of urban centre residents during peak hours during workdays and rest days, based on taxi on and off location information and urban points of interest data, a Geographic Information System (GIS) Kernel density estimation (KED) is used. Combined with the K-means clustering algorithm, the peak hours of residents 'travel and hotspot areas for boarding and alighting are identified, and the strength of the interaction between residents in each area is analysis using the structured Georgy Voronoi, and the spatiotemporal features of residents' travel are summarized.
Journal Article
Handbook of research methods and applications in spatially integrated social science
\"The chapters in this book provide coverage of the theoretical underpinnings and methodologies that typify research using a Spatially Integrated Social Science (SISS) approach. This insightful Handbook is intended chiefly as a primer for students and budding researchers who wish to investigate social, economic and behavioural phenomena by giving explicit consideration to the roles of space and place. The majority of chapters provide an emphasis on demonstrating applications of methods, tools and techniques that are used in SISS research, including long-established and relatively new approaches.\" --Cover.
Book
Spatial Mapping of Diphtheria Vulnerability Level in East Java, Indonesia, using Analytical Hierarchy Process - Natural Break Classification
Diphtheria is a serious infectious disease induced by the Corynebacterium Diphtheriae bacteria and often causes outbreaks (extraordinary events) in various regions. Based on data from the Ministry of Health, East Java is the biggest benefactor to diphtheria cases in Indonesia. Diphtheria cases in East Java tend to increase, especially in 2018 there were 753 diphtheria cases in 38 districts. Efforts made to prevent, treat, and control diphtheria outbreaks by the government are to analyze the level of susceptibility to diphtheria. This paper proposes a new approach to analyze the level of diphtheria susceptibility using the analytical hierarchy process (AHP) and natural breaks classification in East Java Province, Indonesia. AHP method is used to obtain diphtheria susceptibility values based on seven criteria, such as the number of sufferers, number of deaths, DPT 1, DPT 2, DPT 3 immunization, population density, and humidity. Natural break classification is used to classify the vulnerability values from AHP into three levels of vulnerability, consisting of low, medium, and high. The results of the grouping are displayed in the form of spatial mapping in the form of a web-based geographic information system (web-GIS) on the determination of the diphtheria vulnerability level using the AHP-natural breaks classification. The GVF evaluation for 2016, 2017, and 2018 are respectively 0.66, 0.67, and 0.65 (more than 0.5), which means that the proposed method achieved accurate and significant classification. Spatial-temporal analysis for 2013-2018 also achieves accurate and significant with a GVF value of 0.77. The spatial-temporal analysis can predict the high potential for vulnerability.
Journal Article
Advanced geoinformation science
Many of the challenges of the next century will have physical dimensions, such as tsunamis, hurricanes, and climate change as well as human dimensions such as economic crises, epidemics, and emergency responses. With pioneering editors and expert contributors, Advanced Geoinformation Science explores how certain technical aspects of geoinformation have been used and could be used to address such global issues. The editors and chapter authors have been involved in global initiatives such as Global Earth Observation System of Systems (GEOSS) and Digital Earth, and research problems such as air quality, public health, and cloud computing. The book delineates the problems communities are likely to face and how advanced geoinformation science can be a part of their solution. It introduces different methods in collecting spatial data as the initial feeds to geoinformation science and computing platforms. It discusses systems for data management, data integration and analysis, the geoinformation infrastructure, as well as knowledge capture, formatting, and utilization. The book then explores a variety of geoinformation applications, highlighting environmental, agriculture, and urban planning uses.--Publisher's description.
Book
Renewable energy resources in the system of sustainable development of Carpathian region of Ukraine
The scientific novelty presented in this paper is to substantiate the extension of the resource potential of renewable energy sources in the Carpathian region with the creation of a set of maps in the geographic information system \"Map Info\". For each type of renewable energy (solar, wind, small hydropower) a number of technical issues and advantages, technological ecologically safe priorities are defined. The detailed regional calculation of wind, solar, hydropower potential for the Carpathian region of Ukraine has been performed. The spatial limitations and possibilities of introducing renewable energy sources in the sustainable development of the region are scientifically substantiated. Renewable energy scenarios are proposed.
Journal Article
Lighting the World: the first application of an open source, spatial electrification tool (OnSSET) on Sub-Saharan Africa
In September 2015, the United Nations General Assembly adopted Agenda 2030, which comprises a set of 17 Sustainable Development Goals (SDGs) defined by 169 targets. 'Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030' is the seventh goal (SDG7). While access to energy refers to more than electricity, the latter is the central focus of this work. According to the World Bank's 2015 Global Tracking Framework, roughly 15% of the world's population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity services. The majority of those without access (87%) reside in rural areas. This paper presents results of a geographic information systems approach coupled with open access data. We present least-cost electrification strategies on a country-by-country basis for Sub-Saharan Africa. The electrification options include grid extension, mini-grid and stand-alone systems for rural, peri-urban, and urban contexts across the economy. At low levels of electricity demand there is a strong penetration of standalone technologies. However, higher electricity demand levels move the favourable electrification option from stand-alone systems to mini grid and to grid extensions.
Journal Article
Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan
Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to − 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government.
Journal Article
Survey on Land Use/Land Cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges
The surface of the earth is rapidly changing every day due to certain natural reasons and other impacts by society. Over the last few decades, the hottest topics in the field of remote sensing and GIS (geographic information system) environments have evolved from observing the nature of the earth. Owing to the enlargement of several worldwide modifications related to the nature of the earth, land use/land cover (LU/LC) change is considered as the matter of utmost importance in the natural atmosphere, and it has also become an interesting area to be studied by the researchers. As there is a lack of review articles in the land use/land cover change analysis process, we presented a comprehensive review which may help the researchers to proceed further. This paper deals with the most frequent methods used by researchers on various processes like pre-processing, classification, and prediction of time series satellite images for analyzing the LU/LC changes using satellite images. The generic flow of the LU/LC change analysis process and the challenges faced during each process by the researchers are discussed. Varied resolutions of the environmental image captured by remote sensing satellites for analyzing the LU/LC changes are discussed. Various LU/LC classes depending on change in the earth’s surface are also studied and the constraint used in each application is stated. The importance of this review lies in the motivation for future researchers to work on the LU/LC change analysis problem effectively.
Journal Article