Computational socioeconomics

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies

Land Use Change from Non-urban to Urban Areas

This reprint is related to land-use change and non-urban and urban relationships at all spatiotemporal scales and also focuses on land-use planning and regulatory strategies for a sustainable future. Spatiotemporal dynamics, socioeconomic implication, water supply problems and deforestation land degradation (e.g., increase of imperviousness surfaces) produced by urban expansion and their resource requirements are of particular interest. The Guest Editors expect that this reprint will contribute to sustainable development in non-urban and urban areas

Research in remote sensing of agriculture, earth resources, and man's environment

Progress is reported for several projects involving the utilization of LANDSAT remote sensing capabilities. Areas under study include crop inventory, crop identification, crop yield prediction, forest resources evaluation, land resources evaluation and soil classification. Numerical methods for image processing are discussed, particularly those for image enhancement and analysis

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Land Degradation Assessment with Earth Observation

This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

SPATIAL ANALYSES AND REMOTE SENSING FOR LAND COVER CHANGE DYNAMICS: ASSESSING IN A SPATIAL PLANNING

ABSTRACT (EN) Spatial planning is a crucial discipline for the identification and implementation of sustainable development strategies that take into account the environmental impacts on the soil. In recent years, the significant development of technology, like remote sensing and GIS software, has significantly increased the understanding of environmental components, highlighting their peculiarities and criticalities. Geographically referenced information on environmental and socio-economic components represents a fundamental database for identifying and monitoring vulnerable areas, also distinguishing different levels of vulnerability. This is even more relevant considering the increasingly significant impact of land transformation processes, consisting of rapid and frequent changes in land use patterns. In order to achieve some of the Sustainable Development Goals of the 2030 Agenda, the role of environmental planning is crucial in addressing spatial problems, such as agricultural land abandonment and land take, which cause negative impacts on ecosystems. Remote sensing, and in general all Earth Observation techniques, play a key role in achieving SDG 11.3 and 15.3 of Agenda 2030. Through a series of applications and investigations in different areas of Basilicata, it has been demonstrated how the extensive use of remote sensing and spatial analysis in a GIS environment provide a substantial contribution to the results of the SDGs, enabling an informed decisionmaking process and enabling monitoring of the results expected, ensuring data reliability and directly contributing to the calculation of SDG objectives and indicators by facilitating local administrations approaches to work in different development and sustainability sectors. In this thesis have been analyse the dynamics of land transformation in terms of land take and soil erosion in sample areas of the Basilicata Region, which represents an interesting case example for the study of land use land cover change (LULCC). The socio-demographic evolutionary trends and the study of marginality and territorial fragility are fundamental aspects in the context of territorial planning, since they are important drivers of the LULCC and territorial transformation processes. In fact, in Basilicata, settlement dynamics over the years have occurred in an uncontrolled and unregulated manner, leading to a constant consumption of land not accompanied by adequate demographic and economic growth. To better understand the evolution and dynamics of the LULCCs and provide useful tools for formulating territorial planning policies and strategies aimed at a sustainable use of the territory, the socio-economic aspects of the Region were investigated. A first phase involved the creation of a database and the study and identification of essential services in the area as a fundamental parameter against which to evaluate the quality of life in a specific area. The supply of essential services can be understood as an assessment of the lack of minimum requirements with reference to the urban functions exercised by each territorial unit. From a territorial point of view, the level of peripherality of the territories with respect to the network of urban centres profoundly influences the quality of life of citizens and the level of social inclusion. In these, the presence of essential services can act as an attractor capable of generating discrete catchment areas. The purpose of this first part of the work was above all to create a dataset of data useful for the calculation of various socio-economic indicators, in order to frame the demographic evolution and the evolution of the stock of public and private services. The first methodological approach was to reconstruct the offer of essential services through the use of open data in a GIS environment and subsequently estimate the peripherality of each municipality by estimating the accessibility to essential services. The study envisaged the use of territorial analysis techniques aimed at describing the distribution of essential services on the regional territory. It is essential to understand the role of demographic dynamics as a driver of urban land use change such as, for example, the increase in demand for artificial surfaces that occurs locally. Social and economic analyses are important in the spatial planning process. Comparison of socio-economic analyses with land use and land cover change can highlight the need to modify existing policies or implement new ones. A particular land use can degrade and thereby destroy other land resources. If the economic analysis shows that the use is beneficial from the point of view of the land user, it is likely to continue, regardless of whether the process is environmentally friendly. It is important to understand and investigate which drivers have been and will be in the future the most decisive in these dynamics that intrinsically contribute to land take, agricultural abandonment and the consequent processes of land degradation and to define policies or thresholds to mitigate and monitor the effects of these processes. Subsequently, the issues of land take and abandonment of agricultural land were analysed by applying models and techniques of remote sensing, GIS and territorial analysis for the identification and monitoring of abandoned agricultural areas and sealed areas. The classic remote sensing methods have also been integrated by some geostatistical analyses which have provided more information on the investigated phenomenon. The aim was the creation of a quick methodology that would allow to describe the monitoring and analysis activities of the development trends of soil consumption and the monitoring and identification of degraded areas. The first methodology proposed allowed the automatic and rapid detection of detailed LULCC and Land Take maps with an overall accuracy of more than 90%, reducing costs and processing times. The identification of abandoned agricultural areas in degradation is among the most complicated LULCC and Land Degradation processes to identify and monitor as it is driven by a multiplicity of anthropic and natural factors. The model used to estimate soil erosion as a degradation phenomenon is the Revised Universal Soil Loss Equation (RUSLE). To identify potentially degraded areas, two factors of the RUSLE have been correlated: Factor C which describes the vegetation cover of the soil and Factor A which represents the amount of potential soil erosion. Through statistical correlation analysis with the RUSLE factors, on the basis of the deviations from the average RUSLE values and mapping of the areas of vegetation degradation, relating to arable land, through statistical correlation with the vegetation factor C, the areas were identified and mapped that are susceptible to soil degradation. The results obtained allowed the creation of a database and a map of the degraded areas to be paid attention to

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog