A directive, legislated by the South African Department of Minerals and Energy(DME) in 1997, was introduced to reduce the dust exposures of continuous miner(CM) operators to below 5 mg/m3, when measured at the operato...A directive, legislated by the South African Department of Minerals and Energy(DME) in 1997, was introduced to reduce the dust exposures of continuous miner(CM) operators to below 5 mg/m3, when measured at the operator's cab position. The focus of this paper is to review the effectiveness of observing this rule for almost two decades and discuss industry perceptions arising from the application of this rule. The results have demonstrated that the engineering sample cannot predict the personal shift dust exposure of a CM operator. Therefore, it is recommended that the engineering sampling, as currently practiced,should be reviewed with the objective to discontinue and replace it by the approved PDM3700 realtime dust monitor.展开更多
Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated an...Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.展开更多
文摘A directive, legislated by the South African Department of Minerals and Energy(DME) in 1997, was introduced to reduce the dust exposures of continuous miner(CM) operators to below 5 mg/m3, when measured at the operator's cab position. The focus of this paper is to review the effectiveness of observing this rule for almost two decades and discuss industry perceptions arising from the application of this rule. The results have demonstrated that the engineering sample cannot predict the personal shift dust exposure of a CM operator. Therefore, it is recommended that the engineering sampling, as currently practiced,should be reviewed with the objective to discontinue and replace it by the approved PDM3700 realtime dust monitor.
基金supported by the National Natural Science Foundation of China(grant numbers 42071393,U1901219 and U21A2022).
文摘Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.
