The Experts below are selected from a list of 112869 Experts worldwide ranked by ideXlab platform
Richard Lucas - One of the best experts on this subject based on the ideXlab platform.
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remap an online remote Sensing Application for land cover classification and monitoring
Methods in Ecology and Evolution, 2018Co-Authors: Nicholas J Murray, David A Keith, Daniel Simpson, John H Wilshire, Richard LucasAbstract:Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to the maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to develop ecosystem maps from remote Sensing data. We have developed a free and open-access online remote Sensing and environmental modelling Application, the Remote Ecosystem Monitoring and Assessment Pipeline (Remap; https://remap-app.org), that enables volunteers, managers and scientists with little or no experience in remote Sensing to generate classifications (maps) of land cover and land use change over time. Remap utilizes the geospatial data storage and analysis capacity of Google Earth Engine and requires only spatially resolved training data that define map classes of interest (e.g. ecosystem types). The training data, which can be uploaded or annotated interactively within Remap, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in Remap represent topographic (e.g. slope, elevation), spectral (archival Landsat image composites) and climatic variables (precipitation, temperature) that are relevant to the distribution of ecosystems and land cover classes. The ability of Remap to develop and export high-quality classified maps in a very short (<10 min) time frame represents a considerable advance towards globally accessible and free Application of remote Sensing technology. By enabling access to data and simplifying remote Sensing classifications, Remap can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales and supporting environmental education initiatives.
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remap an online remote Sensing Application for land cover classification and monitoring
bioRxiv, 2018Co-Authors: Nicholas J Murray, David A Keith, Daniel Simpson, John H Wilshire, Richard LucasAbstract:Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to make ecosystem maps from remote Sensing data. We have developed a free and open-access online remote Sensing and environmental modelling Application, REMAP (the remote ecosystem monitoring and assessment pipeline; https://remap-app.org) that enables volunteers, managers, and scientists with little or no experience in remote Sensing to develop high-resolution classified maps of land cover and land use change over time. REMAP utilizes the geospatial data storage and analysis capacity of the Google Earth Engine, and requires only spatially resolved training data that define map classes of interest (e.g., ecosystem types). The training data, which can be uploaded or annotated interactively within REMAP, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in REMAP represent topographic (e.g. slope, elevation), spectral (Landsat Archive image composites) and climatic variables (precipitation, temperature) that can inform on the distribution of ecosystems and land cover classes. The ability of REMAP to develop and export high-quality classified maps in a very short (
Wanjiang Shen - One of the best experts on this subject based on the ideXlab platform.
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mesoporous three dimensional network of crystalline wo3 nanowires for gas Sensing Application
ChemInform, 2012Co-Authors: Yuxiang Qin, Fei Wang, Wanjiang ShenAbstract:A three-dimensional network of crystalline WO3 nanowires is prepared by impregnation of a three-dimensional SBA-15 silica template with a solution of silicotungstic acid in EtOH for 6 h at room temperature followed by mineralization (300 °C for 1 h in air and 600 °C for 4 h in air) and template removal (HF solution, 20 °C, 6 h).
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mesoporous three dimensional network of crystalline wo3 nanowires for gas Sensing Application
Journal of Alloys and Compounds, 2012Co-Authors: Yuxiang Qin, Fei Wang, Wanjiang ShenAbstract:Abstract Mesoporous three-dimensional (3D) network of crystalline WO 3 nanowires was prepared by nanocasting method using 3D SBA-15 silica with hexagonally ordered mesopores as hard template. After impregnation, mineralization and template removal, a mesoporous 3D framework of ordered crystalline WO 3 nanowires with high specific surface area and stable mesopore channels was formed through the randomly distributed bridging between the neighboring nanowires. The mesostructure of the product was confirmed by low-angle X-ray diffraction (XRD) and nitrogen physisorption measurements. High resolution transmission electron microscopy (HRTEM) images indicate the single crystal structure with different crystal orientation for mesoporous particles. The gas Sensing properties of the mesoporous 3D WO 3 nanowires replica were investigated at 50 °C up to 200 °C over NO 2 concentration ranging from 15 to 500 ppb. The results indicate that the mesoporous 3D WO 3 nanowires exhibits high response, good selectivity and fast response–recovery characteristics in the detection of sub-ppm and ppb level NO 2 at the optimal operating temperature of 125 °C due to the stable mesopore channels, large surface area and perfect single-crystal structure.
Lucio Pinotti - One of the best experts on this subject based on the ideXlab platform.
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Remote Sensing Application to estimate fish kills by Saprolegniasis in a reservoir.
The Science of the total environment, 2019Co-Authors: Matias Bonansea, Miguel Mancini, Micaela Ledesma, Susana Ferrero, Claudia Rodriguez, Lucio PinottiAbstract:Saprolegniasis is one of the most economical and ecologically harmful diseases in different species of fish. Low water temperature is one of the most important factors which increases stress and creates favourable conditions for the proliferation of Saprolegniasis. Therefore, the monitoring of water surface temperature (WST) is fundamental for a better understanding of Saprolegniasis. The objective of this study was to develop a predictive algorithm to estimate the probability of fish kills caused by Saprolegniasis in Rio Tercero reservoir (Argentina). WST was estimated by Landsat 7 and 8 imagery using the Single-Channel method. Logistic regression was used to relate WST estimated from 2007 to 2017 with different episodes of fish kills by Saprolegniasis registered in the reservoir during this period of time. Results showed that the algorithm created with the first quartile (25th percentile) of the WST values estimated by Landsat sensors was the most suitable model to estimate Saprolegniasis in the studied reservoir.
Shuting Liu - One of the best experts on this subject based on the ideXlab platform.
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switchable textile triboelectric nanogenerators s tengs for continuous profile Sensing Application without environmental interferences
Nano Energy, 2020Co-Authors: Shuting Liu, Hao Wang, Shurong Dong, Chengkuo LeeAbstract:Abstract Conventionally, the output amplitude of triboelectric nanogenerators (TENGs) sensors is detected as the Sensing output, where the accuracy and stability are easily affected by environmental interferences such as humidity, temperature and electrostatic coupling with surrounding objects. Meanwhile, the nature of pulse mode voltage output cannot provide information to further generate a detailed profile of the varying force with time interval when users press a typical TENG working in the contact-separation mode. These two critical issues hinder the TENGs sensors to be competitive with conventionally commercialized sensors. In this study, a switchable textile-triboelectric nanogenerator (S-TENG) is proposed to address these issues. By working on a switchable mode to generate resistor-capacitor (RC) discharging voltage, i.e, enabling capacitive Sensing, the capacitance of the TENGs device is not affected by environmental interferences. Moreover, a high-frequency switching approach is investigated to generate a continuous profile of time-dependent capacitance as a function of force along time, referring to the continuous Sensing parameter. Therefore, S-TENGs offer the sensory information which could not be achieved by any other TENGs so far.
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a switchable fabric triboelectric nanogenerators sf tengs profile Sensing Application
2019 19th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), 2019Co-Authors: Hao Wang, Shuting Liu, Shurong Dong, Chengkuo LeeAbstract:Conventionally, the output amplitude of TENGs sensors is detected as the Sensing output, where the accuracy and stability are easily affected by environmental interferences such as humidity, temperature and electrostatic coupling with surrounding objects. Meanwhile, the nature of pulse mode voltage output cannot provide information to further generate detailed profile of force variation along time interval when users press a typical TENG working in contact-separation mode. These two critical issues stop the TENGs sensors to be competitive with conventionally commercialized sensors.In this study, a switchable textile-triboelectric nanogenerator (S-TENG) is proposed to offer a solution for these issues. By working on a switchable mode to generate RC discharging voltage, i.e, enabling capacitive Sensing, the capacitance of TENGs devices is not affected by environmental interferences. Moreover, a high-frequency switching approach is investigated to generate a continuous profile of time-dependent capacitance change as a function of force variation along time, referring to the continuous Sensing parameter. Therefore, S-TENGs offer the sensory information which could not be achieved by any other TENGs so far.
Chengkuo Lee - One of the best experts on this subject based on the ideXlab platform.
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switchable textile triboelectric nanogenerators s tengs for continuous profile Sensing Application without environmental interferences
Nano Energy, 2020Co-Authors: Shuting Liu, Hao Wang, Shurong Dong, Chengkuo LeeAbstract:Abstract Conventionally, the output amplitude of triboelectric nanogenerators (TENGs) sensors is detected as the Sensing output, where the accuracy and stability are easily affected by environmental interferences such as humidity, temperature and electrostatic coupling with surrounding objects. Meanwhile, the nature of pulse mode voltage output cannot provide information to further generate a detailed profile of the varying force with time interval when users press a typical TENG working in the contact-separation mode. These two critical issues hinder the TENGs sensors to be competitive with conventionally commercialized sensors. In this study, a switchable textile-triboelectric nanogenerator (S-TENG) is proposed to address these issues. By working on a switchable mode to generate resistor-capacitor (RC) discharging voltage, i.e, enabling capacitive Sensing, the capacitance of the TENGs device is not affected by environmental interferences. Moreover, a high-frequency switching approach is investigated to generate a continuous profile of time-dependent capacitance as a function of force along time, referring to the continuous Sensing parameter. Therefore, S-TENGs offer the sensory information which could not be achieved by any other TENGs so far.
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a switchable fabric triboelectric nanogenerators sf tengs profile Sensing Application
2019 19th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), 2019Co-Authors: Hao Wang, Shuting Liu, Shurong Dong, Chengkuo LeeAbstract:Conventionally, the output amplitude of TENGs sensors is detected as the Sensing output, where the accuracy and stability are easily affected by environmental interferences such as humidity, temperature and electrostatic coupling with surrounding objects. Meanwhile, the nature of pulse mode voltage output cannot provide information to further generate detailed profile of force variation along time interval when users press a typical TENG working in contact-separation mode. These two critical issues stop the TENGs sensors to be competitive with conventionally commercialized sensors.In this study, a switchable textile-triboelectric nanogenerator (S-TENG) is proposed to offer a solution for these issues. By working on a switchable mode to generate RC discharging voltage, i.e, enabling capacitive Sensing, the capacitance of TENGs devices is not affected by environmental interferences. Moreover, a high-frequency switching approach is investigated to generate a continuous profile of time-dependent capacitance change as a function of force variation along time, referring to the continuous Sensing parameter. Therefore, S-TENGs offer the sensory information which could not be achieved by any other TENGs so far.
