Development of Distributed Research Center for analysis of regional climatic and environmental changes

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Oceans of Tomorrow sensor interoperability for in-situ ocean monitoring

The Oceans of Tomorrow (OoT) projects, funded by the European Commission’s FP7 program, are developing a new generation of sensors supporting physical, biogeochemical and biological oceanographic monitoring. The sensors range from acoustic to optical fluorometers to labs on a chip. The result is that the outputs are diverse in a variety of formats and communication methodologies. The interfaces with platforms such as floats, gliders and cable observatories are each different. Thus, sensorPeer ReviewedPostprint (author's final draft

EcoGIS – GIS tools for ecosystem approaches to fisheries management

Executive Summary: The EcoGIS project was launched in September 2004 to investigate how Geographic Information Systems (GIS), marine data, and custom analysis tools can better enable fisheries scientists and managers to adopt Ecosystem Approaches to Fisheries Management (EAFM). EcoGIS is a collaborative effort between NOAA’s National Ocean Service (NOS) and National Marine Fisheries Service (NMFS), and four regional Fishery Management Councils. The project has focused on four priority areas: Fishing Catch and Effort Analysis, Area Characterization, Bycatch Analysis, and Habitat Interactions. Of these four functional areas, the project team first focused on developing a working prototype for catch and effort analysis: the Fishery Mapper Tool. This ArcGIS extension creates time-and-area summarized maps of fishing catch and effort from logbook, observer, or fishery-independent survey data sets. Source data may come from Oracle, Microsoft Access, or other file formats. Feedback from beta-testers of the Fishery Mapper was used to debug the prototype, enhance performance, and add features. This report describes the four priority functional areas, the development of the Fishery Mapper tool, and several themes that emerged through the parallel evolution of the EcoGIS project, the concept and implementation of the broader field of Ecosystem Approaches to Management (EAM), data management practices, and other EAM toolsets. In addition, a set of six succinct recommendations are proposed on page 29. One major conclusion from this work is that there is no single “super-tool” to enable Ecosystem Approaches to Management; as such, tools should be developed for specific purposes with attention given to interoperability and automation. Future work should be coordinated with other GIS development projects in order to provide “value added” and minimize duplication of efforts. In addition to custom tools, the development of cross-cutting Regional Ecosystem Spatial Databases will enable access to quality data to support the analyses required by EAM. GIS tools will be useful in developing Integrated Ecosystem Assessments (IEAs) and providing pre- and post-processing capabilities for spatially-explicit ecosystem models. Continued funding will enable the EcoGIS project to develop GIS tools that are immediately applicable to today’s needs. These tools will enable simplified and efficient data query, the ability to visualize data over time, and ways to synthesize multidimensional data from diverse sources. These capabilities will provide new information for analyzing issues from an ecosystem perspective, which will ultimately result in better understanding of fisheries and better support for decision-making. (PDF file contains 45 pages.

Integrating GRASS GIS and Jupyter Notebooks to facilitate advanced geospatial modeling education

Open education materials are critical for the advancement of open science and the development of open-source soft-ware. These accessible and transparent materials provide an important pathway for sharing both standard geospa-tial analysis workflows and advanced research methods. Computational notebooks allow users to share live code with in-line visualizations and narrative text, making them a powerful interactive teaching tool for geospatial analyt-ics. Specifically, Jupyter Notebooks are quickly becoming a standard format in open education. In this article, we intro-duce a new GRASS GIS package, grass.jupyter, that enhances the existing GRASS Python API to allow Jupyter Notebook users to easily manage and visualize GRASS data including spatiotemporal datasets. While there are many Python-based geospatial libraries available for use in Jupyter Notebooks, GRASS GIS has extensive geospatial functionality including support for multi-temporal analysis and dynamic simulations, making it a powerful teaching tool for advanced geospatial analytics. We discuss the devel-opment of grass.jupyter and demonstrate how the package facilitates teaching open-source geospatial mode-ling with a collection of Jupyter Notebooks designed for a graduate-level geospatial modeling course. The open educa-tion notebooks feature spatiotemporal data visualizations, hydrologic modeling, and spread simulations such as the spread of invasive species and urban growthpublishedVersio

From SpaceStat to CyberGIS: Twenty Years of Spatial Data Analysis Software

This essay assesses the evolution of the way in which spatial data analytical methods have been incorporated into software tools over the past two decades. It is part retrospective and prospective, going beyond a historical review to outline some ideas about important factors that drove the software development, such as methodological advances, the open source movement and the advent of the internet and cyberinfrastructure. The review highlights activities carried out by the author and his collaborators and uses SpaceStat, GeoDa, PySAL and recent spatial analytical web services developed at the ASU GeoDa Center as illustrative examples. It outlines a vision for a spatial econometrics workbench as an example of the incorporation of spatial analytical functionality in a cyberGIS.

From global observations to local information: The Earth Observation Monitor

Earth Observation (EO) data are available around the globe and can be used for a range of applications. To support scientists and local stakeholders in the usage of information from space, barriers, especially in data processing, need to be reduced. To meet this need, the software framework Earth Observation Monitor provides access and analysis tools for global EO vegetation time-series data based on standard-compliant geo-processing services. Data are automatically downloaded from several data providers, processed, and time-series analysis tools for vegetation analyses extract further information. A web portal and a mobile application have been developed to show the usage of interoperable geospatial web services and to simplify the access and analysis of global EO time-series data. All steps from data download to analysis are automated and provided as operational geo-processing services. Open-source software has been used to develop the services and client applications

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping

We present a Digital Elevation Model (DEM)-based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc-second (10m) Height Above Nearest Drainage (HAND) raster data for the conterminous U.S. (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc-second CONUS HAND raster dataset was computed in 1.5 days on the CyberGIS ROGER supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model (NWM) forecast data to enable near real-time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process was profiled to gain insights into the computational characteristics in high-performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies