A Dynamical Model to Classify the Content of Multitemporal Images employing Distributed Computing Techniques

An intelligent post-processing paradigm based on the use of a dynamical filtering technique modified to enhance the reconstruction quality of remote sensing indexes using multitemporal images and distributed computing techniques is proposed. As a matter of particular study, a robust algorithm is reported for the analysis of the dynamic behavior of geophysical signatures extracted from remotely sensed scenes. The simulation results prove the efficiency of the proposed technique along with the computational implementation based on a big-data framework using distributed processing.ITESO, A.C

Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

Time Series Classification and Extrinsic Regression are important and challenging machine learning tasks. Deep learning has revolutionized natural language processing and computer vision and holds great promise in other fields such as time series analysis where the relevant features must often be abstracted from the raw data but are not known a priori. This paper surveys the current state of the art in the fast-moving field of deep learning for time series classification and extrinsic regression. We review different network architectures and training methods used for these tasks and discuss the challenges and opportunities when applying deep learning to time series data. We also summarize two critical applications of time series classification and extrinsic regression, human activity recognition and satellite earth observation

Use of National Forest Inventories to Downscale European Forest Diversity Spatial Information in Five Test Areas, Covering Different Geo-Physical and Geo-Botanical Conditions

The project ¿Use of National Forest Inventories to downscale European forest diversity spatial information in five test areas, covering different geo-physical and geo-botanical conditions¿, referred also as ¿forest downscaling¿ (JRC contract 382340 F1SC) covers one of the seven topics that have been studied in the frame of the Regulation (EC) 2152/2003 on the monitoring of forest and environmental interactions, the so-called "Forest Focus" Regulation. This study was conducted by a European consortium coordinated by the Italian Academy of Forest Sciences (Italy) and included partners from the Swedish University of Agricultural Sciences, the Institute of Forest Ecosystem Research of the Czech Republic, the German Federal Research Centre for Forestry and Forest Products, and the Swiss Federal Institute for Forest, Snow and Landscape Research. The overall supervision of the project and the processing of forest spatial pattern were done by the Joint Research Centre. This study addressed the link between field based forest biological diversity data and landscape-level forest pattern information. The former were made available from National Forest Inventories (NFIs) at plot level in five different countries; their harmonisation was implemented for the first time and benefited from outcomes of the COST Action-E43 on core biodiversity variables. For the latter, landscape level forest spatial pattern maps were automatically derived from available remote sensing based forest cover maps. The relation-ships between selected pattern and biodiversity variables available from the two different data sources were studied. Seven case studies for a total area of about 100,000 km2 were selected in five European ecological regions: one site in Germany (Atlantic zone), one in Sweden (Boreal zone), two in Czech Republic (Continental zone), one in Switzerland (Alpine zone) and two in Italy (Mediterranean zone).JRC.DDG.H.7-Land management and natural hazard

Earth Resources: A continuing bibliography with indexes, issue 40

This bibliography lists 423 reports, articles, and other documents introduced into the NASA scientific and technical information system between October 1 and December 31, 1983. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Computational socioeconomics

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies

Earth resources: A continuing bibliography with indexes (issue 61)

This bibliography lists 606 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors, and economic analysis

Advances in Remote Sensing and GIS applications in Forest Fire Management: from local to global assessments

This report contains the proceedings of the 8th International Workshop of the European Association of Remote Sensing Laboratories (EARSeL) Special Interest Group on Forest Fires, that took place in Stresa, (Italy) on 20-21 October 2011. The main subject of the workshop was the operational use of remote sensing in forest fire management and different spatial scales were addressed, from local to regional and from national to global. Topics of the workshops were also grouped according to the fire management stage considered for the application of remote sensing techniques, addressing pre fire, during fire or post fire conditions.JRC.H.7-Land management and natural hazard

Earth Resources. A continuing bibliography with indexes, issue 34, July 1982

This bibliography lists 567 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System between April 1, and June 30, 1982. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis