The integration of LwM2M and OPC UA : an interoperability approach for industrial IoT

Over the past years, Internet of Things (IoT) has been emerging with connected and smart things that can communicate with each other and exchange information. Similarly, with the emergence of Industry 4.0, the industrial world is also undergoing a strong evolution by connecting devices, sensors and machines to the Internet. In this paper, we investigate the integration of these two domains and examine the interconnection of two of the promising interoperability standards in these domains, namely OPC Unified Architecture and Lightweight Machine-to-Machine (LwM2M) protocol. For this purpose, we introduce an efficient and scalable approach, based on Docker Containers, for the cross-domain integration and interoperation. Besides, we also demonstrate and validate our interoperability approach by means of real world implementations and also theoretical and practical analysis

Thirty years of land cover and fraction cover changes over the Sudano-Sahel using landsat time series

Historical land cover maps are of high importance for scientists and policy makers studying the dynamic character of land cover change in the Sudano-Sahel, including anthropogenic and climatological drivers. Despite its relevance, an accurate high resolution record of historical land cover maps is currently lacking over the Sudano-Sahel. In this study, 30 m resolution historically consistent land cover and cover fraction maps are provided over the Sudano-Sahel for the period 1986–2015. These land cover/cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification/regression model, while historical consistency is achieved using the hidden Markov model. Using these historical maps, a multitude of variability in the dynamic Sudano-Sahel region over the past 30 years is revealed. On the one hand, Sahel-wide cropland expansion and the re-greening of the Sahel is observed in the discrete land cover classification. On the other hand, subtle changes such as forest degradation are detected based on the cover fraction maps. Additionally, exploiting the 30 m spatial resolution, fine-scale changes, such as smallholder or subsistence farming, can be detected. The historical land cover/cover fraction maps presented in this study are made available via an open-access platform

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

30 Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel using Landsat Timeseries

30m resolution historically consistent land cover and cover fraction maps over the Sudano-Sahel for the period 1986-2015. These land cover / cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification / regression model, while historical consistency is achieved using the Hidden Markov Model. Validated land cover / cover fraction maps covering the full Sudano-Sahel are provided for 2015 (2015_Sahel.zip), while historical maps are available for four focus areas. The extent of the areas are displayed in 11_study_area.jpe

Thirty years of land cover and fraction cover changes over the Sudano-Sahel using Landsat time series.

Despite the relevance of historical land cover maps for scientists and policy makers, an accurate high resolution record is currently lacking over the Sudano-Sahel. In this study, 30m resolution historically consistent land cover and cover fraction maps are provided over the Sudano-Sahel for the period 1986-2015. These land cover/cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification/regression model, while historical consistency is achieved using the hidden Markov model. Using these historical maps, a multitude of variability in the dynamic Sudano-Sahel region over the past 30 years is revealed. These include cropland expansion and the re-greening of the Sahel, forest degradation & the detection of fine-scale changes, such as smallholder or subsistence farming. The historical land cover/cover fraction maps are made available via an open-access platform

FINAL REPORT PHASE I "Impact of Phenology and Environmental Conditions on BVOC Emissions from Forest Ecosystems” «IMPECVOC»

IMPECVOC: Impact of Phenology and Environmental Conditions on BVOC Emissions from Forest Ecosystem

TRY plant trait database - enhanced coverage and open access

10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18