The Kumamoto area of Kyusyu Island was attacked by a series of large earthquakes (EQs) in April, 2016. The first two foreshocks had the magnitudes of 6.5 and 6.4, and about 1 day later there was the main shock on 15 A...The Kumamoto area of Kyusyu Island was attacked by a series of large earthquakes (EQs) in April, 2016. The first two foreshocks had the magnitudes of 6.5 and 6.4, and about 1 day later there was the main shock on 15 April (UT) with magnitude 7.3. These are fault-type EQs, and so we would expect a variety of electromagnetic precursors to these EQs because we had detected different phenomena for the 1995 Kobe EQ, same fault-type EQ. As for the lithospheric effect, the ULF data at Kanoya observatory (about 150 km from the EQ epicenters) are used, but the simple statistical analysis could not provide us with any clear evidence of ULF radiation from the lithosphere. However, our conventional analyses indicated clear signatures in the atmosphere as ULF/ELF impulsive emissions and also in the ionosphere as observed by means of VLF propagation anomalies and ULF depression. ULF/ELF radiation appeared on 8-11 April (in UT) (maximum on 10 and 11 April (UT)), while ULF depression took place on 8 and 10 April (in UT), so that both atmospheric radiation and ionospheric perturbation took place nearly during the same time period.展开更多
In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees wi...In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees with an irregular crown shape such as trained peach trees. Here, we propose an efficient method of segmenting the individual trees and measuring the crown width and crown projection area (CPA) of peach trees with time-series information, based on gathered images. The images of peach trees were collected by unmanned aerial vehicles in an orchard in Okayama, Japan, and then the digital surface model was generated by using a Structure from Motion (SfM) and Multi-View Stereo (MVS) based software. After individual trees were identified through the use of an adaptive threshold and marker-controlled watershed segmentation in the digital surface model, the crown widths and CPA were calculated, and the accuracy was evaluated against manual delineation and field measurement, respectively. Taking manual delineation of 12 trees as reference, the root-mean-square errors of the proposed method were 0.08 m (R^(2) = 0.99) and 0.15 m (R^(2) = 0.93) for the two orthogonal crown widths, and 3.87 m2 for CPA (R^(2) = 0.89), while those taking field measurement of 44 trees as reference were 0.47 m (R^(2) = 0.91), 0.51 m (R^(2) = 0.74), and 4.96 m2 (R^(2) = 0.88). The change of growth rate of CPA showed that the peach trees grew faster from May to July than from July to September, with a wide variation in relative growth rates among trees. Not only can this method save labour by replacing field measurement, but also it can allow farmers to monitor the growth of orchard trees dynamically.展开更多
The 17 Sustainable Development Goals present clear directions toward the green transformation being sought by the global com-munity.The SDGs are an integrated framework,with a complex network of interlinkages between ...The 17 Sustainable Development Goals present clear directions toward the green transformation being sought by the global com-munity.The SDGs are an integrated framework,with a complex network of interlinkages between the goals,targets and indicators,and they pose wicked problems to society.Consequently,measur-ing progress and achievements with the SDGs requires the integra-tion of various spatio-temporal datasets from different domains and the synthesis of disciplines to describe a system of systems.The Group on Earth Observations has developed the concept of Essential Variables to describe systems across Societal Benefit Areas that are applicable for this purpose.Digital Earth is a virtual representation of the planet,potentially encompassing all its sys-tems and life forms,including human societies.Designed as a multidimensional,multi-scale,multi-temporal,and multi-layer informa-tion facility,Digital Earth is a valuable platform that can contribute to the achievement of the SDGs and a green transformation.To that end,a set of Essential SDGs Variables(ESDGVs)for the platform are proposed and cases of implementation and use are introduced.展开更多
There has been enormous progress in the field of electromagnetic phenomena associated with earthquakes (EQs) and EQ prediction during the last three decades, and it is recently agreed that electromagnetic effects do a...There has been enormous progress in the field of electromagnetic phenomena associated with earthquakes (EQs) and EQ prediction during the last three decades, and it is recently agreed that electromagnetic effects do appear prior to an EQ. A few phenomena are well recognized as being statistically correlated with EQs as promising candidates for short-term EQ predictors: the first is ionospheric perturbation not only in the lower ionosphere as seen by subionospheric VLF (very low frequency, 3 kHz f 30 kHz)/LF (low frequency, 30 kHz f 300 kHz) propagation but also in the upper F region as detected by ionosondes, TEC (total electron content) observations, satellite observations, etc, and the second is DC earth current known as SES (Seismic electric signal). In addition to the above two physical phenomena, this review highlights the following four physical wave phenomena in ULF (ultra low frequency, frequency Hz)/ELF (extremely low frequency, 3 Hz frequency 3 kHz) ranges, including 1) ULF lithospheric radiation (i.e., direct radiation from the lithosphere), 2) ULF magnetic field depression effect (as an indicator of lower ionospheric perturbation), 3) ULF/ELF electromagnetic radiation (radiation in the atmosphere), and 4) Schumann resonance (SR) anomalies (as an indicator of the perturbations in the lower ionosphere and stratosphere). For each physical item, we will repeat the essential points and also discuss recent advances and future perspectives. For the purpose of future real EQ prediction practice, we pay attention to the statistical correlation of each phenomenon with EQs, and its predictability in terms of probability gain. Of course, all of those effects are recommended as plausible candidates for short-term EQ prediction, and they can be physically explained in terms of the unified concept of the lithosphere-atmosphere-ionosphere coupling (LAIC) process, so a brief description of this coupling has been carried out by using these four physical parameters though the mechanism of each phenomenon is still poorly understood. In conclusion, we have to emphasize the importance of more statistical studies for more abundant datasets sometimes with the use of AI (artificial intelligence) techniques, more case studies for huge (M greater than 7) EQ events, recommendation of critical analyses, and finally multi-parameters observation (even though it is tough work).展开更多
This study investigated variations in nitrogen dioxide(NO_(2))levels in Ukraine during two significant periods:the COVID-19 pandemic lockdown in 2020 and the armed conflict with Russia in 2022.Original and reprocessed...This study investigated variations in nitrogen dioxide(NO_(2))levels in Ukraine during two significant periods:the COVID-19 pandemic lockdown in 2020 and the armed conflict with Russia in 2022.Original and reprocessed Sentinel 5P data products were utilized for the analysis.A machine learning model was employed to generate a business-as-usual NO_(2)time series that accounted for meteorological variability.For the nine most populous cities in Ukraine,during the lockdown in 2020 we observed a moderation of increases in NO_(2)levels during the lockdown compared to the pre-lockdown levels.Looking at the same months during the conflict period in 2022,we identified much more significant reductions in NO_(2)level in these cities,averaging 12.1%for original and 18.1%for reprocessed datasets.Besides our examination of major urban areas,we observed reductions in NO_(2)levels in areas surrounding coal power plants damaged or destroyed by the conflict.For the major urban areas in Ukraine,we conclude that changes in daily anthropogenic activities due to the conflict-related events had more substantial impacts on NO_(2)levels than did COVID-19 lockdown.展开更多
Monthly Visible Infrared Imaging Radiometer Suite(VIIRS)Day-Night Band(DNB)composite data are widely used in research,such as estimations of socioeconomic parameters.However,some surface conditions affect the VIIRS DN...Monthly Visible Infrared Imaging Radiometer Suite(VIIRS)Day-Night Band(DNB)composite data are widely used in research,such as estimations of socioeconomic parameters.However,some surface conditions affect the VIIRS DNB radiance,which may create some estimation bias in certain regions.In this paper,we propose a novel normalization algorithm for VIIRS DNB monthly composite data.The aim is to normalize VIIRS radiance,collected under different surface conditions,to a reference point,so that the bias is reduced.The algorithm is based on the utilization of stable lit pixels as a reference and a nonlinear regression algorithm,to match un-normalized data to the reference data.Experimental results show that the algorithm could improve correlation(R2)between the total sum of nightlights(TOL),electric power consumption(EPC),and gross domestic product(GDP)at both a global and local scale.The algorithm could significantly diminish the seasonal component of un-normalized nightlights radiance caused by snow.The intensified nightlights radiance in sandy regions could also be reduced to a more reasonable range in comparison with other regions.Visual inspection shows that the brightness of snow-affected and sandy regions was strongly reduced after undergoing normalization.展开更多
文摘The Kumamoto area of Kyusyu Island was attacked by a series of large earthquakes (EQs) in April, 2016. The first two foreshocks had the magnitudes of 6.5 and 6.4, and about 1 day later there was the main shock on 15 April (UT) with magnitude 7.3. These are fault-type EQs, and so we would expect a variety of electromagnetic precursors to these EQs because we had detected different phenomena for the 1995 Kobe EQ, same fault-type EQ. As for the lithospheric effect, the ULF data at Kanoya observatory (about 150 km from the EQ epicenters) are used, but the simple statistical analysis could not provide us with any clear evidence of ULF radiation from the lithosphere. However, our conventional analyses indicated clear signatures in the atmosphere as ULF/ELF impulsive emissions and also in the ionosphere as observed by means of VLF propagation anomalies and ULF depression. ULF/ELF radiation appeared on 8-11 April (in UT) (maximum on 10 and 11 April (UT)), while ULF depression took place on 8 and 10 April (in UT), so that both atmospheric radiation and ionospheric perturbation took place nearly during the same time period.
基金This study was partially funded by the“Collaboration Research Program of IDEAS”,Chubu University(IDEAS 201603 and IDEAS201702)the CREST Program“Knowledge Discovery by Constructing AgriBigData”(JPMJCR1512)the SICORP Program“Data Science-based Farming Support System for Sustainable Crop Production under Climatic Change”of the Japan Science and Technology Agency.
文摘In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees with an irregular crown shape such as trained peach trees. Here, we propose an efficient method of segmenting the individual trees and measuring the crown width and crown projection area (CPA) of peach trees with time-series information, based on gathered images. The images of peach trees were collected by unmanned aerial vehicles in an orchard in Okayama, Japan, and then the digital surface model was generated by using a Structure from Motion (SfM) and Multi-View Stereo (MVS) based software. After individual trees were identified through the use of an adaptive threshold and marker-controlled watershed segmentation in the digital surface model, the crown widths and CPA were calculated, and the accuracy was evaluated against manual delineation and field measurement, respectively. Taking manual delineation of 12 trees as reference, the root-mean-square errors of the proposed method were 0.08 m (R^(2) = 0.99) and 0.15 m (R^(2) = 0.93) for the two orthogonal crown widths, and 3.87 m2 for CPA (R^(2) = 0.89), while those taking field measurement of 44 trees as reference were 0.47 m (R^(2) = 0.91), 0.51 m (R^(2) = 0.74), and 4.96 m2 (R^(2) = 0.88). The change of growth rate of CPA showed that the peach trees grew faster from May to July than from July to September, with a wide variation in relative growth rates among trees. Not only can this method save labour by replacing field measurement, but also it can allow farmers to monitor the growth of orchard trees dynamically.
文摘The 17 Sustainable Development Goals present clear directions toward the green transformation being sought by the global com-munity.The SDGs are an integrated framework,with a complex network of interlinkages between the goals,targets and indicators,and they pose wicked problems to society.Consequently,measur-ing progress and achievements with the SDGs requires the integra-tion of various spatio-temporal datasets from different domains and the synthesis of disciplines to describe a system of systems.The Group on Earth Observations has developed the concept of Essential Variables to describe systems across Societal Benefit Areas that are applicable for this purpose.Digital Earth is a virtual representation of the planet,potentially encompassing all its sys-tems and life forms,including human societies.Designed as a multidimensional,multi-scale,multi-temporal,and multi-layer informa-tion facility,Digital Earth is a valuable platform that can contribute to the achievement of the SDGs and a green transformation.To that end,a set of Essential SDGs Variables(ESDGVs)for the platform are proposed and cases of implementation and use are introduced.
文摘There has been enormous progress in the field of electromagnetic phenomena associated with earthquakes (EQs) and EQ prediction during the last three decades, and it is recently agreed that electromagnetic effects do appear prior to an EQ. A few phenomena are well recognized as being statistically correlated with EQs as promising candidates for short-term EQ predictors: the first is ionospheric perturbation not only in the lower ionosphere as seen by subionospheric VLF (very low frequency, 3 kHz f 30 kHz)/LF (low frequency, 30 kHz f 300 kHz) propagation but also in the upper F region as detected by ionosondes, TEC (total electron content) observations, satellite observations, etc, and the second is DC earth current known as SES (Seismic electric signal). In addition to the above two physical phenomena, this review highlights the following four physical wave phenomena in ULF (ultra low frequency, frequency Hz)/ELF (extremely low frequency, 3 Hz frequency 3 kHz) ranges, including 1) ULF lithospheric radiation (i.e., direct radiation from the lithosphere), 2) ULF magnetic field depression effect (as an indicator of lower ionospheric perturbation), 3) ULF/ELF electromagnetic radiation (radiation in the atmosphere), and 4) Schumann resonance (SR) anomalies (as an indicator of the perturbations in the lower ionosphere and stratosphere). For each physical item, we will repeat the essential points and also discuss recent advances and future perspectives. For the purpose of future real EQ prediction practice, we pay attention to the statistical correlation of each phenomenon with EQs, and its predictability in terms of probability gain. Of course, all of those effects are recommended as plausible candidates for short-term EQ prediction, and they can be physically explained in terms of the unified concept of the lithosphere-atmosphere-ionosphere coupling (LAIC) process, so a brief description of this coupling has been carried out by using these four physical parameters though the mechanism of each phenomenon is still poorly understood. In conclusion, we have to emphasize the importance of more statistical studies for more abundant datasets sometimes with the use of AI (artificial intelligence) techniques, more case studies for huge (M greater than 7) EQ events, recommendation of critical analyses, and finally multi-parameters observation (even though it is tough work).
基金supported by the Ministry of Education,Culture,Sports,Science and Technology-Japan,and the International Digital Earth Applied Science Research Center at Chubu University.
文摘This study investigated variations in nitrogen dioxide(NO_(2))levels in Ukraine during two significant periods:the COVID-19 pandemic lockdown in 2020 and the armed conflict with Russia in 2022.Original and reprocessed Sentinel 5P data products were utilized for the analysis.A machine learning model was employed to generate a business-as-usual NO_(2)time series that accounted for meteorological variability.For the nine most populous cities in Ukraine,during the lockdown in 2020 we observed a moderation of increases in NO_(2)levels during the lockdown compared to the pre-lockdown levels.Looking at the same months during the conflict period in 2022,we identified much more significant reductions in NO_(2)level in these cities,averaging 12.1%for original and 18.1%for reprocessed datasets.Besides our examination of major urban areas,we observed reductions in NO_(2)levels in areas surrounding coal power plants damaged or destroyed by the conflict.For the major urban areas in Ukraine,we conclude that changes in daily anthropogenic activities due to the conflict-related events had more substantial impacts on NO_(2)levels than did COVID-19 lockdown.
文摘Monthly Visible Infrared Imaging Radiometer Suite(VIIRS)Day-Night Band(DNB)composite data are widely used in research,such as estimations of socioeconomic parameters.However,some surface conditions affect the VIIRS DNB radiance,which may create some estimation bias in certain regions.In this paper,we propose a novel normalization algorithm for VIIRS DNB monthly composite data.The aim is to normalize VIIRS radiance,collected under different surface conditions,to a reference point,so that the bias is reduced.The algorithm is based on the utilization of stable lit pixels as a reference and a nonlinear regression algorithm,to match un-normalized data to the reference data.Experimental results show that the algorithm could improve correlation(R2)between the total sum of nightlights(TOL),electric power consumption(EPC),and gross domestic product(GDP)at both a global and local scale.The algorithm could significantly diminish the seasonal component of un-normalized nightlights radiance caused by snow.The intensified nightlights radiance in sandy regions could also be reduced to a more reasonable range in comparison with other regions.Visual inspection shows that the brightness of snow-affected and sandy regions was strongly reduced after undergoing normalization.
