Nitrous oxide emission budgets and land-use-driven hotspots for organic soils in Europe

Peer reviewe

Sustainable supply chain management: framework and further research directions

This paper argues for the use of Total Interpretive Structural Modeling (TISM) in sustainable supply chain management (SSCM). The literature has identified antecedents and drivers for the adoption of SSCM. However, there is relatively little research on methodological approaches and techniques that take into account the dynamic nature of SSCM and bridge the existing quantitative/qualitative divide. To address this gap, this paper firstly systematically reviews the literature on SSCM drivers; secondly, it argues for the use of alternative methods research to address questions related to SSCM drivers; and thirdly, it proposes and illustrates the use of TISM and Cross Impact Matrix-multiplication applied to classification (MICMAC) analysis to test a framework that extrapolates SSCM drivers and their relationships. The framework depicts how drivers are distributed in various levels and how a particular driver influences the other through transitive links. The paper concludes with limitations and further research directions

PyTroll : An Open-Source, Community-Driven Python Framework to Process Earth Observation Satellite Data

AbstractPyTroll (http://pytroll.org) is a suite of open-source easy-to-use Python packages to facilitate processing and efficient sharing of Earth Observation (EO) satellite data. The PyTroll software is intended for both 24/7 real-time operations as well as research and development. PyTroll grew out of the need to provide a resilient and agile platform that can respond quickly to new user needs and new data sources. PyTroll, being open source, stimulates international collaboration, which is vital with the rapid increase of satellite information availability. The PyTroll software development is strongly user driven and has grown over the past eight years from a collaborative effort between the Danish and Swedish national meteorological services to encompass a worldwide community with active contributors. PyTroll is being used at least operationally in the national meteorological services of Denmark, Norway, Sweden, Finland, Germany, Switzerland, Italy, Estonia, and Latvia. However, given its simplicity, minimal demand on user resources, and community-driven approach, it also encourages and facilitates usage of EO data for individual applications. While PyTroll was originally developed to cater to the needs of the atmospheric remote sensing community, it could be equally useful for land and ocean applications and within hydrology. This article provides an overview of PyTroll, with examples showing the capability of some of the core packages.</jats:p

pytroll/satpy: v0.10.0

The SatPy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats. SatPy comes with the ability to make various RGB composites directly from satellite instrument channel data or higher level processing output. The pyresample package is used to resample data to different uniform areas or grids. The documentation is available at http://satpy.readthedocs.org/.The SatPy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats. SatPy comes with the ability to make various RGB composites directly from satellite instrument channel data or higher level processing output. The pyresample package is used to resample data to different uniform areas or grids. The documentation is available at http://satpy.readthedocs.org/.0.10.