Nengcheng Chen

Geo-processing workflow driven wildfire hot pixel detection under sensor web environment

Integrating Sensor Web Enablement (SWE) services with Geo-Processing Workflows (GPW) has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. This paper presents a common GPW framework for Sensor Web data service as part of the NASA Sensor Web project. This abstract framework includes abstract GPW model construction, GPW chains from service combination, and data retrieval components. The concrete framework consists of a data service node, a data processing node, a data presentation node, a Catalogue Service node, and a BPEL engine. An abstract model designer is used to design the top level GPW model, a model instantiation service is used to generate the concrete Business Process Execution Language (BPEL), and the BPEL execution engine is adopted. This framework is used to generate several kinds of data: raw data from live sensors, coverage or feature data, geospatial products, or sensor maps. A prototype, including a model designer, model instantiation service, and GPW engine-BPELPower is presented. A scenario for an EO-1 Sensor Web data service for wildfire hot pixel detection is used to test the feasibility of the proposed framework. The execution time and influences of the EO-1 live Hyperion data wildfire classification service framework are evaluated. The benefits and high performance of the proposed framework are discussed. The experiments of EO-1 live Hyperion data wildfire classification service show that this framework can improve the quality of services for sensor data retrieval and processing.

Flood detection and mapping of the Thailand Central plain using RADARSAT and MODIS under a sensor web environment

Abstract Flooding in general is insignificant event worldwide and also in Thailand. The Central plain, the Northern plain and the northeast of Thailand are frequently flooded areas, caused by yearly monsoons. The Thai government has extra expenditure to provide disaster relief and for the restoration of flood affected structures, persons, livestock, etc. Current flood detection in real time or near real time has become a challenge in the flood emergency response. In this paper, an automatic instant time flood detection approach consisting of a data retrieval service, flood sensor observation service (SOS), flood detection web processing service (WPS) under a sensor web environment, is presented to generate dynamically real-time flood maps. A scenario of a RADARSAT and MODIS sensor web data service for flood detection cover of the Thailand Central plain is used to test the feasibility of the proposed framework. MODIS data are used to overview the wide area, while RADARSAT data are used to classify the flood area. The proposed framework using the transactional web coverage service (WCS-T) for instant flood detection processes dynamic real-time remote sensing observations and generates instant flood maps. The results show that the proposed approach is feasible for automatic instant flood detection.

Cloud Computing Enabled Web Processing Service for Earth Observation Data Processing

The OpenGIS Web Processing Service (WPS) can process both simple and complex geospatial tasks including Earth Observation tasks. As the requirements of Earth Observation data, algorithms, calculation models, and daily life become increasingly complicated; WPS needs to provide high-performance service-oriented computing capability. This paper proposes a cloud computing enabled WPS framework for Earth Observation data processing. It consists of a client layer and a WPS layer, which further consists of a WPS server layer and a cloud computing layer. The cloud computing environment is based on the open-source software Apache Hadoop. The three layers of the proposed cloud computing enabled WPS are outlined, followed by a workflow that processes a users task using these three layers. Then technological implementation details are explained. An experiment processing Moderate Resolution Imaging Spectroradiometer (MODIS) data shows that WPS can be enabled in a cloud computing environment.

Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations

Recent advances in Sensor Web geospatial data capture, such as high-resolution in satellite imagery and Web-ready data processing and modeling technologies, have led to the generation of large numbers of datasets from real-time or near real-time observations and measurements. Finding which sensor or data complies with criteria such as specific times, locations, and scales has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. In this paper, an architecture for use of the integration Sensor Observation Service (SOS) with the Open Geospatial Consortium (OGC) Catalogue Service-Web profile (CSW) is put forward. The architecture consists of a distributed geospatial sensor observation service, a geospatial catalogue service based on the ebXML Registry Information Model (ebRIM), SOS search and registry middleware, and a geospatial sensor portal. The SOS search and registry middleware finds the potential SOS, generating data granule information and inserting the records into CSW. The contents and sequence of the services, the available observations, and the metadata of the observations registry are described. A prototype system is designed and implemented using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of observations are evaluated using a realistic Earth Observing-1 (EO-1) SOS scenario. Extracting information from SOS requires the same execution time as record generation for CSW. The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode. The proposed architecture has the more advantages of SOS search and observation data retrieval than the existing sensor Web enabled systems.

Integrated open geospatial web service enabled cyber-physical information infrastructure for precision agriculture monitoring

We proposed an integrated geospatial service enabled cyber-physical infrastructure.Sensor web enablement and web processing service are mainly utilized.Two interaction patterns are designed to cooperate SOA based geospatial services.Providing interoperable access for heterogeneous sensors, data, and algorithms.The infrastructure is capable in sensor-based precision agriculture monitoring. Various wireless and wired sensors serve vital functions in situational awareness for precision agriculture (PA) monitoring. Achieving the seamless integration of these heterogeneous sensors into information systems to achieve interoperability is challenging. To solve this problem, an integrated open geospatial web service-enabled cyber-physical infrastructure was proposed in this study to acquire, integrate, process, and distribute monitoring information from the physical sensor space of the PA system over the World Wide Web space. This infrastructure was designed as a service-oriented architecture middleware between heterogeneous physical sensors and different PA information clients. In particular, sensor web enablement and web processing services were utilized. Ten types of distributed agricultural sensors were deployed in Baoxie field, Wuhan City, and two different experiments were conducted to verify the proposed cyber-physical infrastructure. Results demonstrated that this infrastructure was capable of handling data and analyses in sensor-based PA monitoring. The proposed approach was then compared with existing typical PA infrastructures. Results indicated that the proposed cyber-physical infrastructure provided interoperable access for heterogeneous sensors, data, and algorithms. The proposed infrastructure thus provides a new feasible method for information system design in PA.

A Flexible Data and Sensor Planning Service for Virtual Sensors Based on Web Service

How to achieve a flexible data and sensor planning service to schedule, plan, and empower diverse sensors and heterogeneous data ordering systems is a big challenge. In this paper, a service-oriented framework of data and sensor planning service for virtual sensors is proposed. The framework includes an Open Geospatial Consortium (OGC)-compliant Sensor Planning Service (SPS), a Web Notification Service (WNS), a Sensor Observation Service (SOS), and virtual sensors. There are two important key technologies in this framework, namely a flexible SPS middleware and an asynchronous message notification mechanism. The flexible SPS middleware, based on a configuration file and standard interfaces, is adopted to integrate virtual sensors into a sensor Web. A WNS-based asynchronous notification middleware is used to inform the user of the status of a task that may need midterm or long-term actions. The framework has been successfully demonstrated in application scenarios for Simplified General Perturbations Satellite Orbit Model 4 (SGP4) and Earth Observation System ClearingHOuse (ECHO). The results show that the proposed method has the following improvements over the existing SPS implementation: a uniform planning service for more satellites, a seamless connection with data order systems, and a flexible service-oriented framework for virtual sensors.

A Sharable and Interoperable Meta-Model for Atmospheric Satellite Sensors and Observations

How the heterogeneous and distributed atmospheric satellite sensors can achieve precise discovery and collaborative observation is a big challenge. In this study, we propose an atmospheric satellite sensor observation system meta-model that reuses and extends the existing geospatial or sensor-related metadata standards to enable the sharing and interoperability of atmospheric satellite sensors. The Open Geospatial Consortium Sensor Model Language (SensorML) has a clear hierarchy in describing the metadata framework, and it is adopted as the carrier to formalize our proposed meta-model into the Atmospheric Satellite Sensor Observation Information Model (A-SSOIM). Three different types of atmospheric satellite sensors are used to test the versatility of the proposed meta-model and the applicability of this formal expression of A-SSOIM. Results show that the proposed meta-model can be reused in all kinds of atmospheric satellite sensors to enable the sharing of atmospheric satellite sensor information and potentially promoting the interoperability of these satellite sensors.

Using SensorML to construct a geoprocessing e-Science workflow model under a sensor web environment

Many achievements in web-based geoprocessing focus on logically chaining Open Geospatial Consortium (OGC) web services, for example using Business Process Execution Language to orchestrate web services that are interfaced through the OGC Web Processing Service. For e-Science application in a sensor web environment, how to internally integrate the sensor system, observation, and processes (physical and non-physical) as a geoprocessing e-Science workflow model is a critical issue. The OGC Sensor Model Language offers the possibility to construct a geoprocessing e-Science workflow model in the form of observation processes. We propose a construction method for a geoprocessing e-Science workflow model that integrates logical and physical processes into a composite process chain for sensor observations. The three phases of geoprocessing e-Science workflow creation are abstract process chain modeling, process chain instantiation, and process chain workflow execution. An experiment on chaining-related sub-processes for deriving the Normalized Difference Vegetation Index of Hubei Province (China) was conducted to verify the feasibility of the proposed workflow model.

An Efficient Method for Near-Real-Time On-Demand Retrieval of Remote Sensing Observations

Recent advances in sensor web geospatial data capture, have led to the generation of large numbers of real-time or near-real-time observations and measurements. As the magnitude of Web Coverage Service (WCS) and Sensor Observation Service (SOS) becomes increasingly large, a major problem is how to make fast and fully robust use of such data services in a Web-ready sensors environment. A new method is proposed, Real-time Coverage Service (RCS), for serving observational data based on the integration of WCS and SOS. The RCS method hides the complexity of a series of information models and service interfaces in the Earth Observation (EO) and Sensor Web world, allowing near-real-time on-demand access to geospatial observations. The core components-dynamical schema transformer and automatic information extractor-are designed and implemented based on service middleware technology. The Observations & Measurements (O&M) schema of SOS and coverage schema of WCS are matched by schema transformer dynamically. The coverage information is extracted from a SOS “GetObservation” operation by an information extractor and served by a WCS “GetCoverage” operation on-demand. Experiments on the feasibility of Earth Observing-1 (EO-1) Hyperion data retrieval for the RCS method and OGC Sensor Web SOS method were conducted and their efficiency compared. The results show that the proposed RCS has architecture that is more robust and performs more efficiently than the SOS method.

Cyber-Physical Geographical Information Service-Enabled Control of Diverse In-Situ Sensors

Realization of open online control of diverse in-situ sensors is a challenge. This paper proposes a Cyber-Physical Geographical Information Service-enabled method for control of diverse in-situ sensors, based on location-based instant sensing of sensors, which provides closed-loop feedbacks. The method adopts the concepts and technologies of newly developed cyber-physical systems (CPSs) to combine control with sensing, communication, and computation, takes advantage of geographical information service such as services provided by the Tianditu which is a basic geographic information service platform in China and Sensor Web services to establish geo-sensor applications, and builds well-designed human-machine interfaces (HMIs) to support online and open interactions between human beings and physical sensors through cyberspace. The method was tested with experiments carried out in two geographically distributed scientific experimental fields, Baoxie Sensor Web Experimental Field in Wuhan city and Yemaomian Landslide Monitoring Station in Three Gorges, with three typical sensors chosen as representatives using the prototype system Geospatial Sensor Web Common Service Platform. The results show that the proposed method is an open, online, closed-loop means of control.