scholarly journals Free open access data sources for dermatology researchers

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Amylee Martin ◽  
Jeffrey Liu ◽  
Akshitha Thatiparthi ◽  
Jashin J Wu
Keyword(s):  
Open Access ◽  
Data Sources ◽  
Open Access Data ◽  
Access Data

scholarly journals Estimation and Mapping of Forest Structure Parameters from Open Access Satellite Images: Development of a Generic Method with a Study Case on Coniferous Plantation

2019 ◽  
Vol 11 (11) ◽  
pp. 1275 ◽  
Author(s):  
David Morin ◽  
Milena Planells ◽  
Dominique Guyon ◽  
Ludovic Villard ◽  
Stéphane Mermoz ◽  
...  
Keyword(s):  
Feature Selection ◽  
Open Access ◽  
Forest Structure ◽  
Data Sources ◽  
Machine Learning Techniques ◽  
Structure Parameters ◽  
Alos Palsar ◽  
Open Access Data ◽  
Coniferous Plantation ◽  
Access Data

Temperate forests are under climatic and economic pressures. Public bodies, NGOs and the wood industry are looking for accurate, current and affordable data driven solutions to intensify wood production while maintaining or improving long term sustainability of the production, biodiversity, and carbon sequestration. Free tools and open access data have already been exploited to produce accurate quantitative forest parameters maps suitable for policy and operational purposes. These efforts have relied on different data sources, tools, and methods that are tailored for specific forest types and climatic conditions. We hypothesized we could build on these efforts in order to produce a generic method suitable to perform as well or better in a larger range of settings. In this study we focus on building a generic approach to create forest parameters maps and confirm its performance on a test site: a maritime pine (Pinus pinaster) forest located in south west of France. We investigated and assessed options related with the integration of multiple data sources (SAR L- and C-band, optical indexes and spatial texture indexes from Sentinel-1, Sentinel-2 and ALOS-PALSAR-2), feature extraction, feature selection and machine learning techniques. On our test case, we found that the combination of multiple open access data sources has synergistic benefits on the forest parameters estimates. The sensibility analysis shows that all the data participate to the improvements, that reach up to 13.7% when compared to single source estimates. Accuracy of the estimates is as follows: aboveground biomass (AGB) 28% relative RMSE, basal area (BA) 27%, diameter at breast height (DBH) 20%, age 17%, tree density 24%, and height 13%. Forward feature selection and SVR provided the best estimates. Future work will focus on validating this generic approach in different settings. It may prove beneficial to package the method, the tools, and the integration of open access data in order to make spatially accurate and regularly updated forest structure parameters maps effortlessly available to national bodies and forest organizations.

scholarly journals Translational bioinformatics in mental health: open access data sources and computational biomarker discovery

2017 ◽  
Vol 20 (3) ◽  
pp. 842-856 ◽  
Author(s):  
Jessica D Tenenbaum ◽  
Krithika Bhuvaneshwar ◽  
Jane P Gagliardi ◽  
Kate Fultz Hollis ◽  
Peilin Jia ◽  
...  
Keyword(s):  
Mental Health ◽  
Open Access ◽  
Biomarker Discovery ◽  
Data Sources ◽  
Translational Bioinformatics ◽  
Open Access Data ◽  
Access Data

Open source riverscapes: Analyzing the river corridor of the Naryn River in Kyrgyzstan based on open access data

2021 ◽  
Author(s):  
Florian Betz ◽  
Magdalena Lauermann ◽  
Bernd Cyffka
Keyword(s):  
Remote Sensing ◽  
Open Access ◽  
Large Scale ◽  
Data Sets ◽  
Hierarchical Systems ◽  
Geomorphological Mapping ◽  
Open Access Data ◽  
Access Data ◽  
River Corridors ◽  
River Corridor

<p>In fluvial geomorphology as well as in freshwater ecology, rivers are commonly seen as nested hierarchical systems functioning over a range of spatial and temporal scales. Thus, for a comprehensive assessment, information on various scales is required. Over the past decade, remote sensing based approaches have become increasingly popular in river science to increase the spatial scale of analysis. However, data-scarce areas have been mostly ignored so far despite the fact that most remaining free flowing – and thus ecologically valuable – rivers worldwide are located in regions characterized by a lack of data sources like LiDAR or even aerial imagery. High resolution satellite data would be able to fill this data gap, but tends to be too costly for large scale applications what limits the ability for comprehensive studies on river systems in such remote areas. This in turn is a limitation for management and conservation of these rivers.</p><p>In this contribution, we suggest an approach for river corridor mapping based on open access data only in order to foster large scale geomorphological mapping of river corridors in data-scarce areas. For this aim, we combine advanced terrain analysis with multispectral remote sensing using the SRTM-1 DEM along with Landsat OLI imagery. We take the Naryn River in Kyrgyzstan as an example to demonstrate the potential of these open access data sets to derive a comprehensive set of parameters for characterizing this river corridor. The methods are adapted to the specific characteristics of medium resolution open access data sets and include an innovative, fuzzy logic based approach for riparian zone delineation, longitudinal profile smoothing based on constrained quantile regression and a delineation of the active channel width as needed for specific stream power computation. In addition, an indicator for river dynamics based on Landsat time series is developed. For each derived river corridor parameter, a rigor validation is performed. The results demonstrate, that our open access approach for geomorphological mapping of river corridors is capable to provide results sufficiently accurate to derive reach averaged information. Thus, it is well suited for large scale river characterization in data-scarce regions where otherwise the river corridors would remain largely unexplored from an up-to-date riverscape perspective. Such a characterization might be an entry point for further, more detailed research in selected study reaches and can deliver the required comprehensive background information for a range of topics in river science.</p>

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