A MODIS Imagery Toolkit for ArcGIS Explorer

NASA’s medium spatial resolution MODIS sensor provides near-global, daily remote sensing coverage of the Earth in 36 spectral bands that are optimized for monitoring a wide variety of environmental parameters. MODIS data is provided by NASA at no cost and is easily accessible via the Internet. As such, MODIS provides a rich source of remotely sensed data that can provide timely environmental information to military operations, disaster monitoring, and relief efforts. However, current workflows for downloading MODIS and identifying environmental features of interest require the use of sophisticated software operated by experienced analysts. These software packages have the added limitations of being expensive and not readily available in combat and/or disaster relief environments. This paper discusses the development of a set of software tools using existing geographic information system technology. These tools can enable analysts with limited experience and operating in difficult environments to easily access MODIS data and develop environmental spatial data from it for further analysis. Two different system architectures were developed as solutions—one that exists as a set of standalone tools in a desktop environment using ArcGIS Explorer, and one that exists as a client-server framework using ArcGIS Server with ArcGIS Explorer as the client

Multi-sensor Evolution Analysis: an advanced GIS for interactive time series analysis and modelling based on satellite data

Archives of Earth remote sensing data, acquired from orbiting satellites, contain large amounts of information that can be used both for research activities and decision support. Thematic categorization is one method to extract from satellite data meaningful information that humans can directly comprehend. An interactive system that permits to analyse geo-referenced thematic data and its evolution over time is proposed as a tool to efficiently exploit such vast and growing amount of data. This thesis describes the approach used in building the system, the data processing methodology, details architectural elements and graphical interfaces. Finally, this thesis provides an evaluation of potential uses of the features provided, performance levels and usability of an implementation hosting an archive of 15 years moderate resolution (1 Km, from the ATSR instrument) thematic data

Metadata and provenance management

Scientists today collect, analyze, and generate TeraBytes and PetaBytes of data. These data are often shared and further processed and analyzed among collaborators. In order to facilitate sharing and data interpretations, data need to carry with it metadata about how the data was collected or generated, and provenance information about how the data was processed. This chapter describes metadata and provenance in the context of the data lifecycle. It also gives an overview of the approaches to metadata and provenance management, followed by examples of how applications use metadata and provenance in their scientific processes

FOSS4G 2016 Proceedings: Academic Program - selected papers and posters

This Conference Proceedings is a collection of selected papers and posters submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G 2016), 24th to 26th August 2016 in Bonn, Germany. Like in previous FOSS4G conferences on national and international level the academic papers and posters cover an extensive wide range of topics reflecting the contribution of the academia to this field by the development of open source software components, in the design of open standards, in the proliferation of web-based solutions, in the dissemination of the open principles important in science and education, or in the collection and the hosting of freely available geo-data

Global Change Data Center: Mission, Organization, Major Activities, and 2003 Highlights

Rapid, efficient access to Earth sciences data from satellites and ground validation stations is fundamental to the nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase from current levels to terabytes per day. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink.The Global Change Data Center's (GCDC) mission is to develop and operate data systems, generate science products, and provide archival and distribution services for Earth science data in support of the U.S. Global Change Program and NASA's Earth Sciences Enterprise. The ultimate product of the GCDC activities is access to data to support research, education, and public policy

Regionalization of a Remote Sensing based Spatial Decision Support System for Bush Fire Management in Benin

Wildland fire agencies officers need objective and systematic information to make effective decision on fire management. Getting such information is usually challenging especially in developing countries where the required infrastructures or skills are not always available. Recent developments in the assessment of bush fires using remote sensing techniques and the availability of such results enable a systematic study of fire distribution and regime on different spatial scales. In this dissertation, we propose a development of a spatial decision support system for Bush fire monitoring called FIMAT (FIre MAnagement Tool), as well as a case study using the tool developed for Benin. The purpose of this study was (1) to grasp the theories of fire ecology and (2) state-of-art methods on vegetation fire assessment, (3) to develop a Spatial Decision Support System for Fire Management and (4), to regionalize its use to Benin for spatial and temporal fire distribution description. FIMAT is developed in Java using libraries such as Geotools, Jhdf. The fundamental data used by this system are MODIS burned area level 3 product along with auxiliary layers of geographic information. The MODIS burned areas product is derived from processing of combined MODIS-TERRA and MODIS-AQUA 500m land surface reflectance data using the Bidirectional Reflectance Distribution Function (BRDF) in a model-based change detection approach. This algorithm approximates the dates of burning by locating the occurrence of rapid changes in daily MODIS reflectance time series. FIMAT encompasses many processing and report functionalities. A data management system can automatically downloads the required fire data from MODIS Dataserver, if they are not available locally. A fire statistics calculator can generate the necessary information at small spatial scales (e.g municipality) from the original HDF data tile and save the result as Geotiff raster or other file formats. A map editor displays the processing results as a map along with additional layers. The created map can be customized by using the interactive integrated style editor and graphic editor and a chart editor shows generated statistics. Documents can be added to the project in Pdf format and viewed with the integrated Pdf viewer. The textual and graphical information generated by this monitoring tool can help decision makers to monitor and assess bush fire in simple way without them being necessarily specialists in Programming or Geographic Information Systems. It is an application with a simple user graphical interface. It is useful as a tool for operational assessment of compliance to the laws and arrangements. FIMAT has the following advantages over available tools (e.g Web Fire Mapper) - FIMAT can operate off-line; - it permits mapping of additional data layers; - it includes graphical editor and other useful reporting systems; - the maps and charts generated are highly customizable; - it offers more analysis and output options; - it allows assessment at subnational level (e.g communal level). From the investigations on spatial and temporal distribution of vegetation fire in Benin, it results that fire is a recurrent phenomenon in this region. It distribution in time and space follows approximately the same pattern over the studied period 2000-2009. Fires start usually in October and last until April/Mai with a maximum in December. Most of the burnings occur once at every location but some areas can burn two or three times a year. Those multiple burned areas are generally in protected areas where the fuel load is important and the vegetation more continuous. The multiple burned areas are usually extensions of late burned areas on early burned areas in their neighbourhood

CIRA annual report FY 2014/2015

Reporting period July 1, 2014-March 31, 2015