Mechanical properties and fracture patterns of graphene (graphitic) nanowiggles

publisher: Elsevier articletitle: Mechanical properties and fracture patterns of graphene (graphitic) nanowiggles journaltitle: Carbon articlelink: http://dx.doi.org/10.1016/j.carbon.2017.04.018 content_type: article copyright: © 2017 Elsevier Ltd. All rights reserved.publisher: Elsevier articletitle: Mechanical properties and fracture patterns of graphene (graphitic) nanowiggles journaltitle: Carbon articlelink: http://dx.doi.org/10.1016/j.carbon.2017.04.018 content_type: article copyright: © 2017 Elsevier Ltd. All rights reserved.This work was supported in part by the Brazilian Agencies CNPq, CAPES and FAPESP. The authors would like to thank the Center for Computational Engineering and Sciences at Unicamp for financial support through the FAPESP/CEPID Grant 2013/08293-7. N.M.P. is supported by the European Research Council PoC 2015 “Silkene” No. 693670, by the European Commission H2020 under the Graphene Flagship Core 1 No. 696656 (WP14 “Polymer Nanocomposites”) and under the Fet Proactive “Neurofibres” No. 732344

Utilizing image texture to detect land-cover change in Mediterranean coastal wetlands

Land-use/cover change dynamics were investigated in a Mediterranean coastal wetland. Change Vector Analysis (CVA) without and with image texture derived from the co-occurrence matrix and variogram were evaluated for detecting land-use/cover change. Three Landsat Thematic Mapper (TM) scenes recorded on July 1985, 1993 and 2005 were used, minimizing change detection error caused by seasonal differences. Images were geometrically, atmospherically and radiometrically corrected. CVA without and with texture measures were implemented and assessed using reference images generated by object-based supervised classification. These outputs were used for cross-classification to determine the ‘from–to’ change used to compare between techniques. The Landsat TM image bands together with the variogram yielded the most accurate change detection results, with Kappa statistics of 0.7619 and 0.7637 for the 1985–1993 and 1993–2005 image pairs, respectively