Land Cover Change Monitoring Using Landsat MSS/TM Satellite Image Data over West Africa between 1975 and 1990

Abstract: Monitoring land cover changes from the 1970s in West Africa is important for assessing the dynamics between land cover types and understanding the anthropogenic impact during this period. Given the lack of historical land cover maps over such a large area, Landsat data is a reliable and consistent source of information on land cover dynamics from the 1970s. This study examines land cover changes occurring between 1975 and 1990 in West Africa using a systematic sample of satellite imagery. The primary data sources for the land cover classification were Landsat Multispectral Scanner (MSS) for 1975 and Landsat Thematic Mapper (TM) for the 1990 period. Dedicated selection of the appropriate image data for land cover change monitoring was performed for the year 1975. Based on this selected dataset, the land cover analysis is based on a systematic sample of 220 suitable Landsat image extracts (out of 246) of 20 km × 20 km at each one degree latitude/longitude intersection. Object-based classification, originally dedicated for Landsat TM land cover change monitoring and adapted for MSS, was used to produce land cover change information for four different land cover classes: dense tree cover, tree cover mosaic, other wooded land and other vegetation cover. Our results reveal that in 1975 about 6% of West Africa was covered by dense tree cover complemented with 12% of tree cover mosaic. Almost half of the area was covered by other wooded land and the remaining 32% was represented by other vegetation cover. Over the 1975–1990 period, the net annual change rate of dense tree cover was estimated at −0.95%, at −0.37% for the other wooded land and very low for tree cover mosaic (−0.05%). On the other side, other vegetation cover increased annually by 0.70%, most probably due to the expansion of agricultural areas. This study demonstrates the potential of Landsat MSS and TM data for large scale land cover change assessment in West Africa and highlights the importance of consistent and systematic data processing methods with targeted image acquisition procedures for long-term monitoring.JRC.H.5-Land Resources Managemen

Vers la modélisation d’une presse à vis : développement d’un modèle statique élastique

The increasing use of superalloys in the forging industry induces the development of new manufacturing processes. These new processes are set up thanks to Finite Element simulation. But regarding the prediction of the energy required to form a part in superalloys, significant differences are observed between numerical and experimental results. In our vision, this can be explained by the fact that forging machines models implemented in Finite Element software are not enough detailed. Thus, this study focuses on the particular case of a forging machine limited in energy: a screw press. This work is a first step toward a complete and detailed modelling of the screw press. To begin, a purely static elastic model of the press uprights has been developed, and this model was validated by comparison with a Finite Element model of the uprights. Then, this Finite Elements model has been made more complex by adding the cross-head of the press. This model has been validated thanks to experiences carried out with the help of a 3D tracking points system, allowing us to analyze the press behavior during blows.Région Grand Est Manoir Industrie Bouzonvill

State and evolution of the African rainforests between 1990 and 2010

This paper presents a 2005 map of Africa’s rainforests with new levels of spatial and thematic detail, being derived from 250m resolution MODIS data, and having an overall accuracy of 84%. A systematic sample of Landsat images (with supplemental data from equivalent platforms to fill sample gaps) is used to produce a consistent assessment of deforestation between 1990, 2000 and 2010 for West Africa, Central Africa and Madagascar. Net deforestation is estimated at 0.28% yr-1 for the period 1990-2000 and 0.14% yr-1 for the period 2000-2010. West Africa and Madagascar exhibit a much higher deforestation rate than the Congo Basin. Based on a simple analysis of the variance over the Congo Basin, we show that expanding agriculture and increasing fuelwood demands are key drivers of deforestation while well-controlled timber exploitation programmes have little or no direct influence on forest-cover reduction at present. Rural and urban population concentrations and fluxes are identified as strong underlying causes of deforestation in this study.JRC.H.5-Land Resources Managemen

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. METHODS: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques. RESULTS: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes (p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years. CONCLUSIONS: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy

Achievements in breeding coconut hybrids for tolerance to coconut foliar decay disease in Vanuatu, South Pacific

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