Global land cover (LC) changes threaten sustainability and yet we lack a comprehensive understanding of the gains and losses of LC types, including the magnitudes, locations and timings of transitions. We used a novel, fine-resolution and temporally consistent satellite-derived dataset covering the entire Earth annually from 1992 to 2018 to quantify LC changes across a range of scales. At global and continental scales, the observed trajectories of change for most LC types were fairly smooth and consistent in direction through time. We show these observed trajectories in the context of error margins produced by extrapolating previously published accuracy metrics associated with the LC dataset. For many LC classes the observed changes were found to be within the error margins. However, an important exception was the increase in urban land, which was consistently larger than the error margins, and for which the LC transition was unidirectional. An advantage of analysing the global, fine spatial resolution LC time-series dataset is the ability to identify where and when LC changes have taken place on the Earth. We present LC change maps and trajectories that identify locations with high dynamism, and which pose significant sustainability challenges. We focused on forest loss and urban growth at the national scale, identifying the top 10 countries with the largest percentages of forest loss and urban growth globally. Crucially, we found that most of these 'worst-case' countries have stabilized their forest losses, although urban expansion was monotonic in all cases. These findings provide crucial information to support progress towards the UN's SDGs.
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http://dx.doi.org/10.1038/s41598-021-92256-2 | DOI Listing |
Sci Rep
January 2025
Faculty of Computer and Control Engineering, Qiqihar University, Qiqihar, 161000, China.
The rapid advancement of quantum key distribution technology in recent years has spurred significant innovation within the field. Nevertheless, a crucial yet frequently underexplored challenge involves the comprehensive evaluation of security quantum state modulation. To address this issue, we propose a novel framework for quantum group key distribution.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
December 2024
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Patients with recurrent high-grade glioma (rHGG) have a poor prognosis with median progression-free survival (PFS) of <7 months. Responses to treatment are heterogenous, suggesting a clinical need for prognostic models. Bayesian data analysis can exploit individual patient follow-up imaging studies to adaptively predict the risk of progression.
View Article and Find Full Text PDFPract Radiat Oncol
December 2024
Department of Radiation Oncology, Willis Knighton Cancer Center, 2600 Kings Highway, Shreveport, Louisiana, USA 71103 &, Department of Clinical Research, University of Jamestown, Fargo, ND, USA. Electronic address:
Purpose: Motion management presents a significant challenge in thoracic stereotactic ablative radiotherapy (SABR). Currently, a 5.0 mm standard planning target volume (PTV) margin is widely used to ensure adequate dose to the tumor.
View Article and Find Full Text PDFSci Rep
December 2024
School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613 401, India.
Cement ball mills in the finishing stage of the cement industries consume the highest energy in the cement manufacturing stage. Therefore, suitable controllers that result in good productivity and product quality with reduced energy consumption are required for the cement ball mill grinding process to increase the profit margins. In this study, generalised predictive controllers (GPC)have been designed for the cement ball mill grinding operation using the model obtained from the step response data taken from the industrially recognized simulator.
View Article and Find Full Text PDFJ Imaging
December 2024
Laboratoire Imagerie et Vision Artificielle (ImVia), Université de Bourgogne, 21000 Dijon, France.
Determining the maturity of cocoa pods early is not just about guaranteeing harvest quality and optimizing yield. It is also about efficient resource management. Rapid identification of the stage of maturity helps avoid losses linked to a premature or late harvest, improving productivity.
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