論文

The paper divided the whole coal life cycle, explained each phase characteristics, and took coal mine in China as a study case to assess the ecological risk in coal utilization phase. The main conclusions are as follows: (1) the whole coal life cycle is divided into coal mining, processing, transportation, utilization, and waste disposal. (2) The key points of production organization and characteristics in the five phases have great differences. The coal mining phase is characterized by the damage of the key ecological factors (water, soil, atmosphere, vegetation, etc.) damaged while the coal processing phase by discharging waste. The characteristics in coal transportation phase mainly performance as escaping and migration of atmospheric pollutants. In coal utilization phase, the main characteristics are aggravation of greenhouse effect. The main characteristics of waste disposal phase are accumulation of negative ecological effects on the land. (3) The ecological risk of soil heavy metals is serious in coal utilization phase. The potential ecological hazard coefficients of Pb and As in coal, residue and ash are all lower than 40, presenting low environmental impact on soil; the potential ecological risk coefficients of Cd are higher than 60, nearly half of their potential ecological risk coefficients are higher than 160, which presents high environmental pollution impact on soil; Hg's potential ecological risk coefficients are higher than 320, presenting the highest environmental pollution impact on soil; the comprehensive pollution indexes in coal, residue, and ash are relatively high, which means the pollution hazard potential to soil environment is high. (4) The ecological risk of the atmospheric solid suspended matter is relatively strong in coal utilization phase. The ecological risk of Cd and As in primary flue gas is both lower than net flue gas. The geoaccumulation indexes of Cd and Hg in primary flue gas and net flue gas are both higher than 5, presenting the very strong ecological risk; 50 % of the geoaccumulation index values of As are between 3 and 4, which has also presenting a strong ecological risk while Pb does not present the ecological risk characterization.

Detection of surface water from satellite images is important for water management purposes like for mapping flood extents, inundation dynamics, and water resources distributions. In this research, we introduce a supervised contextual classification model to detect surface water bodies from polarimetric Synthetic Aperture Radar (SAR) data. A complex Wishart Markov Random Field (WMRF) combines Markov Random Fields with the complex Wishart distribution. It is applied on Single Look Complex Sentinel 1 data. Using Markov Random Fields, we utilize the geometry of surface water to remove speckle from SAR images. Results were compared with the Wishart Maximum Likelihood Classification (WMLC), the Gaussian Maximum Likelihood Classification, and a median filter followed by thresholding. Experiments demonstrate that the statistical representation of data using the Wishart distribution improves the F-score to 0.95 for WMRF, while it is 0.67, 0.88, and 0.91 for Gaussian Maximum Likelihood Classification, WMLC, and thresholding, respectively. The main improvement in the precision increases from 0.80 and 0.86 for WMLC and thresholding to 0.96 for WMRF. The WMRF model accurately distinguishes classes that have a similar backscatter, like water and bare soil. Hence, the high accuracy of the proposed WMRF model is a result of its robustness for water detection from Single Look Complex data. We conclude that the proposed model is a great improvement on existing methods for the detection of calm surface water bodies.

This paper aims to estimate the economic value of ecosystem services in the suburban Satoyama area. First, we have grouped ecosystem services into 13 indices based on Millennium Ecosystem Assessment. Land use data at 1/2500 scale is used for mapping ecosystems and 12 categories were classified, in consideration of the characteristic of the suburban Satoyama region such as paddy field and abandoned cultivation. Then, we have made 5 terms of land use maps(1955-2005) with GIS and traced the transition of the land use for 50 years. Agricultural productive service was estimated from statistical data. Regulating services were estimated from models of research in the past that is applicable to Satoyama region. Cultural service and supporting service were surveyed with questionnaires and estimated by Contingent Valuation Method (CVM). Consequently, productive service value of 3 billion yen and Regulating and cultural service of 0.6 billion yen were estimated.

The authors have developed the Geo CPS platform, which incorporates the advantages of cyber-physical systems, geographic information systems, and tangible user interfaces, and provides a platform to connect the three components for interactive sensing, processing, and actuation in smart city development. It can be also applied for education in environmental and disaster management, as a tool for technical training, or as a testbed for business solutions.

This study is aimed at synthesizing the social value-based model of Shimokawa, Hokkaido with economic value-based model of Hita, Oita to implement woody biomass renewable energy business in Japan. These two areas were chosen to highlight their contradictory economic and social situations in utilizing their abundant forest resources. The research uses an in-depth interview of stakeholders involved in the woody biomass project in both regions. The role of woody biomass in Hita and neighboring areas deals with renewable energy business, while in Shimokawa it handles an aging society issue and sustainability. By 2013, Hita has two woody biomass power plants operated, which utilized a total of 160,000 tons/year wood chips. Shimokawa promotes sustainable life by implementing Forest Future City model in which resources, society, and industry are integrated to achieve quality life. (C) 2015 The Authors. Published by Elsevier B.V.

© 2018 by the authors. This paper presents a collective sensing approach that integrates imperfect Volunteered Geographic Information (VGI) obtained through Citizen Science (CS) tree mapping projects with very high resolution (VHR) optical remotely sensed data for low-cost, fine-scale, and accurate mapping of trees in urban orchards. To this end, an individual tree crown (ITC) detection technique utilizing template matching (TM) was developed for extracting urban orchard trees from VHR optical imagery. To provide the training samples for the TM algorithm, remotely sensed VGI about trees including the crowdsourced data about ITC locations and their crown diameters was adopted in this study. A data quality assessment of the proposed approach in the study area demonstrated that the detected trees had a very high degree of completeness (92.7%), a high thematic accuracy (false discovery rate (FDR) = 0.090, false negative rate (FNR) = 0.073, and F1 score (F1) = 0.918), and a fair positional accuracy (root mean square error (RMSE) = 1.02 m). Overall, the proposed approach based on the crowdsourced training samples generally demonstrated a promising ITC detection performance in our pilot project.

© 2019 by the authors. In recent years, customer pick-up at collection and delivery points has become a popular alternative to traditional home delivery, which is under great pressure. However, current service of pick-up facilities has seldom been geographically evaluated despite its general uneven distribution and diverse needs. In this paper, in order to interpret the differentiation in customers' service demands toward reception alternatives and in facilities' service excludability in different built environments, a two-step floating catchment area (2SFCA) method is improved to measure customers' spatial accessibility to pick-up facilities, providing a methodology to evaluate the match relation between the differentiated supply and demand of pick-up service. A case study of widespread automated parcel stations (APSs) is conducted in Hangzhou, China and correlative factors to residents' accessibility are discussed. From the results, residents' accessibility to pick-up service shows significant spatial unevenness and social inequity in the study area, which is found to correlate most to residences' maintenance management. As well-managed, gated communities generally hold effective access to exclusive services, most open communities and self-built, single houses are in need of improvement due to inadequate service stemming from a high aging rate, lack of property management, and low service availability of nonexclusive facilities in open areas.

Recent achievement of the Internet of Things (IoT) have brought a great opportunity for GIS to be integrated with physical space as Cyber-Physical Systems (CPS). This article reviews the concepts of IoT and CPS from the perspective of geospatial spaces and clarifies the complementary relationshp of the two technologies. Two forms of CPS were discussed: Pseudo-CPS (PCPS) which projects spatial data on a display without interaction among data sources and True-CPS (TCPS) with handles data sources deeply and semantically. While PCPS is widely industrialized TCPS is in its infant, lack of common schemes and platforms for data sharing, security and privacy etc. Dissolving the barriers requires collaborations cross sectors and disciplines. A transformation of our mindset on GIS from ‘location + attributes’ to ‘location×attributes’ is recommended for creating value-added GI services.

© Springer International Publishing AG 2017. After the Great Eastern Japan Earthquake on March 11, 2011, which resulted in a triple disaster (earthquake, tsunami and nuclear accident), the Japanese government both at local and national level has implemented reconstruction and revitalization measures. In this chapter, the author discusses the importance of human recovery after the disaster and specifically examines one project; the Reconstruction Supporters Project. This project initiated the restoration of the psychological health of communities and residents. The Ministry of Internal Affairs and Communications established the project, and has currently arranged 452 supporters to settle in the devastated area helping local residents and to revitalize the region.

Limited flood disaster information causes insufficient justification for public awareness, therefore, improving flood practice management is needed. This paper applies the flood forecasting model and atmospheric model to identify rainfall distribution and to investigate the threshold values for alert system. The entire system aims to improve flood monitoring, information distribution and an alert system. The geospatial web based system is established to facilitate public awareness by allocating information in timely manner without cumbersome software installation.The process to obtain rainfall and river discharge data, input and transfer data, through the database can be launched after other parameters i.e. elevation, soil, land cover, and basin boundary are set. The entire process takes approximately 15 minutes. The flood warning system and the geospatial web based system are connected to the database and promptly alert in the case of emergency.The yields prove promising results, based on the amount of time and viable function. The existing rainfall spatial based pattern, received from the atmospheric model, takes about 72 minutes to achieve one hourly image. It is a suitable model for observing regional rainfall distribution. It does not serve immediate alert purpose in the emergency situation due to it is too time consuming.

The 5D World Map System, the Mathematical Model of Meaning technique (MMM) and their applications create new analytical system environments with the SPA concept (Sensing, Processing and Actuation) for the "Global Knowledge Sharing, Analysis and Visualization". 5D World Map System is a knowledge sharing, analysis and visualization system for realizing Global-Environmental Analysis with the integration of various environmental phenomena. We have proposed the 5D World Map System to collect and facilitate various social and natural-environmental information resources, which are characteristics of infrastructure, disaster, traffic, water and energy supply. The collaborative research activities are promising for approaching to the global architecture of a multi-visualized knowledge analysis and sharing system "5D World Map System," applied to "environmental data analysis and visualization. The basic dimensional space of this system consists of a temporal (1st dimension), spatial (2nd, 3rd and 4th dimensions) and semantic dimensions (5th dimension, representing a large-scale and multiple-dimensional semantic space that is based on our semantic associative computing model (MMM: The Mathematical Model of Meaning)). This system is effective to make a progress of "global-environmental analysis" with cyber-physical system integration for detecting and analyzing natural and social environmental phenomena. The 5D World Map System is globally utilized as a Global Environmental Semantic Computing System for SDGs 9, 11, 14, United-Nations-ESCAP.

© 2016 IEEE. It is broadly known that tropical peat forest plays important role for local and regional social and environmental wellbeing. Nonetheless the existence is under serious threat due to unsustainable human activities that often exacerbated by extreme weather events. Monitoring and understanding health of tropical peat forest can help to determine correct measures to tackle any adverse impacts resulted from degraded tropical peat forest as well as mitigate and prevent continuing degradation of the ecosystems itself. This research applies remote sensing and Geographical Information System for investigating historical land cover changes in Sebubus Forest through analysis of Landsat images during period 1995 until 2016. The purpose is to understand how land cover of the 'Productive Forest', as it is classified by Indonesian Regulations on forestry, has been changing over time and the times when its dramatic transformation were happened. A matrix derived from multitemporal satellite image analysis is presented to understand land cover transitions and intensity. This investigation found that the forest were trees' covered until 2005 when some dramatic land cover changes began. Even though protected by regulation, Sebubus Forest area is not safe from adverse impact of human activities. By 2016 it is likely only less then 12% of the total peat land area remains covered by forest.

As an island ecosystem, Djerba, a region of Tunisia located on the southern shore of the Mediterranean Sea, is characterized by limited natural resources and threatened by land degradation due to rapid socio-economic development and heavy human-induced changes to the landscape. The objective of this study is to build a system based on computer vision and remote sensing data for monitoring changes in the coastal zones of an island. We employed monthly Landsat Thematic Mapper (TM) satellite images of the study area ranging from 1984 to 2009. The images were preprocessed using the Speeded Up Robust Features (SURF) algorithm to superimpose remote sensing images at exactly the same coordinates. We then used comparison technique to auto-validate the detection of changes. The technique is based on a window-to-window comparison of the coastal zones. Three highly affected regions were identified. The Bin El-Ouidiane (in the southeast) and Rass Errmal (in the north) regions underwent deposition during the study period, whereas the region of Rass El Kastil (in the north) underwent high erosion. © 2012 IEEE.

This study, conducted to support for urban thermal environment planning, developed a new method for mapping the spatial structure of urban canopy layers. The technique, called Raster-Patch-Cluster Scheme, employs landscape and ecological indicators combined with thermal characteristics identified by use of thermal satellite images. It was found that the urban thermal environment develops at the local scale and exhibits differences in density and forms of canopy layers. ASTER/TIR with 90 m resolution was found to be a useful data source for elucidating such local climatic phenomena. The intensities of local heat or cool islands exhibit significant logarithmic relationships with the size of urban canopy features. This means that the extent and intensity of urban heat islands increases with the expansion of urbanized areas of a city as well as with the agglomeration of land use intensity. The conclusions suggest that mitigation measures for the prevention of urban island development are likely to be effective if implemented at early stages of urbanization.

On average, mashups tagged with the keyword "mapping" account for about 40% of the total mashups currently developed. One major cause for this phenomenon are the widely-available, free, online mapping services provided by mainstream IT firms. For example, Google has developed easy-to-use map application programming interfaces (APIs) and estimates over 150 million visitors to its map services as of May 2009. However, this unprecedented development of Web 2.0 functionality has been subject to existing acceptable use policies accompanying the services and service APIs. This paper reviews and analyzes the existing Terms of Use or Terms of Service from a number of private online mapping service providers, and presents observations on the potential social, organizational, and technical implications of the current acceptable use policies in developing map mashups and related applications. It argues that existing acceptable use policies may not support a healthy mashup ecosystem.