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The research shows that primary pipe network leak will cause the fluctuations of temperature and conductance around the leak point. There is a complex non-linear relationship between the pipeline leakage and physical quantity, and the leakage of the pipeline can not be assessed by the change of the single physical quantity. In this paper, the assessment model of the leakage degree of the pipe network...
Scientific workflow plays an important role in complex scientific computing. It can integrate various data and analysis functions to solve complicated geoprocessing problems which usually involve a couple of steps. They could be accomplished manually step by step in Geographic Resources Analysis Support System (GRASS), an open source Geographic Information System (GIS) software, or automated through...
Citizens is becoming an important source of geographic information. Volunteered Geographic Information (VGI) offers an opportunity of involving public to collect disaster information which is individually generated and available in time. This paper propose a VGI oriented approach for Disaster Risk Reduction (DRR) with application to urban waterlogging. An algorithm based on VGI is proposed to deal...
Agriculture cropland soil moisture information plays a significant role in the management of agricultural policy, food security, and food prices. For better utilizing and reusing the agricultural information and knowledge, US Departments of Agriculture (USDA) National Agricultural Statistics Service (NASS) monitors US crop soil moisture condition using weekly field observations for counties in 45...
With the advancement of Web service technologies, more and more spatial data and analysis functions are available on the web. Scientific workflows are widely used to orchestrate services to solve complex geospatial problems. The ontology for processing service orchestration (OPSO) is developed to empower domain experts to explore large datasets and complex processing workflows iteratively and collaboratively...
Big data technologies have shown great promise for managing geospatial data in recent years. In order to deal with the growing spatial data, a high performance spatial data processing system layered on big data technologies is needed. In this paper, we present an approach to process big spatial data with Apache Spark, a fast and generic engine for large-scale data processing. We developed a software...
Traditional relational database management systems (RDBMS) have shown limitations in storing and analyzing big data. For example, a RDBMS is suitable for transactional operations yet not good at large-scale data analysis and processing, since a large-scale record scan or full table scan is often time-consuming. An efficient storage method for reading and writing big geospatial data is still needed...
The Sensor Web is evolving into a complex information space, where large volumes of sensor observation data are often consumed by complex applications. Provenance has become an important issue in the Sensor Web, since it allows applications to answer “what”, “when”, “where”, “who”, “why”, and “how” queries related to observations and consumption processes, which helps determine the usability and reliability...
Geospatial web service of agricultural information has a wide variety of consumers. An operational agricultural service will receive considerable requests and process a huge amount of datasets each day. To ensure the service quality, many strategies have to be taken during developing and deploying agricultural information services. This paper presents a set of methods to build robust geospatial web...
Agricultural drought greatly impacts the crop yield. Monitoring agricultural drought can deliver critical information to farmers on when, where and how much to irrigate. However, precisely monitoring which requires many kinds of data sources and data fusion and mining is still a huge challenge for scientists. In recent years, many data sources like remote sensed hyperspectral images are released online...
Integrated environmental modelling (IEM) couples interdependent environmental models and data together to solve complex environmental problems. There are two major modelling frameworks for IEM: component based framework, and service oriented framework. This paper suggests to take the best of both to couple modelling components and services together. The result is a hybrid method to leverage Open Modelling...
The advancement of Sensor Web technologies shows great promise to complement satellite remote sensing observations with fine-grained observations from in-situ sensors. One possibility is to use the timely observations from in-situ sensors to overcoming the limitation of long-term revisit periods in remote sensing products in time-critical situations. This often requires the timely processing of real-time...
Visible Light Communication (VLC) has drawn much interest from telematics and adaptive cruise control system due to its high communication safety and license-free. At present, most researches about VLC Medium Access Control (MAC) protocol are carried out in indoor environments, studies in inter-vehicles communication are less relatively. In this paper, we first present a Vehicle-to-Vehicle (V2V) communication...
Recent trends on big Earth-observing (EO) data lead to some questions that the Earth science community needs to address. Are we experiencing a paradigm shift in Earth science research now? How can we better utilize the explosion of technology maturation to create new forms of EO data processing? Can we summarize the existing methodologies and technologies scaling to big EO data as a new field named...
The Pub/Sub, short for Publish-Subscribe, is a flexible mechanism perferred by many users who'd like to passively know the changes of situation. Once a new message is published by a provider, all the subscribers to the specific kind of messages will receive the message and make corresponding responses. In agricultural crop monitoring, such mechanism is very helpful in enhancing the efficiency of message...
In recent years, the Unmanned Aerial Vehicles (UAVs) technologies are widely employed in many fields such as disaster monitoring, map revision, and aerial imagery. A UAV aerial remote sensing system has several advantages such as low cost, high spatial resolution, and flexibility. However, one single UAV image can only cover a small area due to the limited altitude of the vehicle and the restricted...
The timely retrieval of remote sensing imagery by farmers and decision makers is very important for current agricultural activities. Through the various kinds of imageries of agricultural fields, people can conclude the status of the fields and figure out what kind of crops are suitable and how to cultivate and irrigate the fields. This paper demonstrates how to take advantage of open web service...
Recently scientific data are increasingly managed by array database technologies such as SciDB and Rasdaman. Some work has shown that array database technologies are particularly useful to support multi-dimensional data management and analysis. In the geospatial domain, remote sensing images, as a kind of multi-dimensional scientific data, could certainly take advantage of array database technologies...
The demands placed on hydrologic analyses have increased considerably in recent years. Hydrologic analyses involve numerous methods and are useful in many fields, such as agriculture, forestry and grassland farming. In order to catch information and knowledge from Digital Elevation Models (DEM), processing data step by step in software is available, which needs many manual workloads and is not convenient...
Semantic location-based services (LBS) aims to provide intelligent LBS that can find and integrate various information to better meet user requirements in location-aware context. This paper argues that traditional approaches for semantic GIServices in the Cyberinfrastructure context could be extended into the LBS. After highlighting the distinguished features of semantic LBS, i.e. context semantics...
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