With the rapid urban development in China, urbanization has brought more and more pressure on the ecological environment. As one of the most dynamic, open, and innovative regions in China, the eco-environmental issues in the Yangtze River Delta have attracted much attention. This paper takes the central region of the Yangtze River Delta as the research object, through building the index system of urbanization and ecological environment based on statistical data and two new indicators (fraction of vegetation coverage and surface urban heat island intensity) extracted from remote sensing images, uses the Entropy-TOPSIS method to complete the comprehensive assessment, and then analyzes the coupling coordination degree between the urbanization and ecological environment and main obstacle factors. The results showed that the coupling coordination degree in the study region generally shows an upward trend from 0.604 in 2008 to 0.753 in 2017, generally changing from an imbalanced state towards a basically balanced state. However, regional imbalance of urbanization and ecological environment always exists, which is mainly affected by social urbanization, economic urbanization, landscape urbanization, pollution loading and resource consumption. Finally, on the basis of the obstacle factor analysis, some specific suggestions for promoting the coordinated development of the Yangtze River Delta are put forward.
The integration of intelligent video surveillance and GIS (geograhical information system) data provides a new opportunity for monitoring and protecting cultivated land. For a GIS-based video monitoring system, the prerequisite is to align the GIS data with video image. However, existing methods or systems have their own shortcomings when implemented in monitoring cultivated land. To address this problem, this paper aims to propose an accurate matching method for projecting vector data into surveillance video, considering the topographic characteristics of cultivated land in plain area. Once an adequate number of control points are identified from 2D (two-dimensional) GIS data and the selected reference video image, the alignment of 2D GIS data and PTZ (pan-tilt-zoom) video frames can be realized by automatic feature matching method. Based on the alignment results, we can easily identify the occurrence of farmland destruction by visually inspecting the image content covering the 2D vector area. Furthermore, a prototype of intelligent surveillance video system for cultivated land is constructed and several experiments are conducted to validate the proposed approach. Experimental results show that the proposed alignment methods can achieve a high accuracy and satisfy the requirements of cultivated land monitoring.
<p><strong>Abstract.</strong> The traditional way of doing science has been changing with the recent movements on open science, open data and the world-wide spread of volunteer activities. With the help of technological advancements, in particular mobile technologies, do-it-yourself kits and free online education sources, ordinary citizens may contribute to scientific processes based on their interest and abilities. Citizen Science (CitSci) is an active research agenda which draws the interest of scientists from different disciplines. It investigates the various contributions that citizens could do to improve scientific process. These contributions are utilized in diverse areas ranging from biology to environmental monitoring to classification of galaxies, all of which have a spatiotemporal dimension. The emerging developments in spatial information science allow the public to understand their environment better and efficiently. In this way society would have the means to deal with complex modern problems including but not limited to water/air pollution monitoring and mapping a region after a natural disaster to aid relief and recovery efforts. In addition, there is a growing public demand for research projects involving CitSci; because such collaborative efforts can be critical to achieve sustainability goals. The aim of this paper is to provide an overview on the state-of-the art methods and applications where CitSci is a crucial component in different phases of disaster management, from environmental protection to risk analysis and aid provision. Use of CitSci methods in disaster situations can be vital for different reasons, such as acquisition of local and most current information, organization of help during emergency, development of instant rescue plans, accurate information dissemination, and monitoring of the post-disaster influences to the society and the environment. Open issues on the use of CitSci methods in disaster management, such as data quality, technical and management-related barriers, open-standards and interoperability, and volunteer engagement, will also be discussed.</p>
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