To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides unde...To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides under uncertainty.The model decomposed displacements into trend and periodic components via Variational Mode Decomposition(VMD)and K-shape clustering.The Residual and Moving Block Bootstrap methods were used to generate pseudo datasets.Polynomial regressionwas adopted for trend forecasting,whereas the Dense Convolutional Network(DenseNet)and Long Short-Term Memory(LSTM)networks were employed for periodic displacement prediction.An Extreme Learning Machine(ELM)was used to estimate the noise variance,enabling the construction of Prediction Intervals(PIs)and quantificationof displacement uncertainty.Failure probabilities(Pf)were derived from PIs using an improved tangential angle criterion and reliability analysis.The model was validated on three step-like landslides in the Three Gorges Reservoir Area,achieving stability assessment accuracies of 99.88%(XD01),99.93%(ZG93),99.89%(ZG118),and 100%for ZG110 and ZG111 across the Baishuihe and Bazimen landslides.For the Shuping landslide,the predictions aligned with fieldobservations before and after the 2014–2015 remediation,with P_(f)remaining near zero post-2015 except for occasional peaks.The model outperformed conventional ML approaches by yielding narrower PIs.At XD01 with 90%PI nominal confidencelevel(PINC),the coverage width-based criterion(CWC)and PI average width(PIAW)were 3.38 mm.The mean values of the PIs exhibited high accuracy,with a Mean Absolute Error(MAE)of 0.28 mm and Root Mean Square Error(RMSE)of 0.39 mm.These results demonstrate the robustness of the proposed model in improving landslide risk assessment and decision-making under uncertainty.展开更多
In this paper,we use the Riemann-Hilbert(RH)method to investigate the Cauchy problem of the reverse space-time nonlocal Hirota equation with step-like initial data:q(z,0)=o(1)as z→-∞and q(z,0)=δ+o(1)as z→∞,where...In this paper,we use the Riemann-Hilbert(RH)method to investigate the Cauchy problem of the reverse space-time nonlocal Hirota equation with step-like initial data:q(z,0)=o(1)as z→-∞and q(z,0)=δ+o(1)as z→∞,whereδis an arbitrary positive constant.We show that the solution of the Cauchy problem can be determined by the solution of the corresponding matrix RH problem established on the plane of complex spectral parameterλ.As an example,we construct an exact solution of the reverse space-time nonlocal Hirota equation in a special case via this RH problem.展开更多
The precision of landslide displacement prediction is crucial for effective landslide prevention and mitigation strategies.However,the role of surface monitoring frequency in influencing prediction accuracy has been l...The precision of landslide displacement prediction is crucial for effective landslide prevention and mitigation strategies.However,the role of surface monitoring frequency in influencing prediction accuracy has been largely neglected.This study examined the effect of varying monitoring frequencies on the accuracy of displacement predictions by using the Baijiabao landslide in the Three Gorges Reservoir Area(TGRA)as a case study.We collected surface automatic monitoring data at different intervals,ranging from daily to monthly.The Ensemble Empirical Mode Decomposition(EEMD)algorithm was utilized to dissect the accumulated displacements into periodic and trend components at each monitoring frequency.Polynomial fitting was applied to forecast the trend component while the periodic component was predicted with two state-of-the-art neural network models:Long Short-Term Memory(LSTM)and Gated Recurrent Unit(GRU).The predictions from these models were integrated to derive cumulative displacement forecasts,enabling a comparative analysis of prediction accuracy across different monitoring frequencies.The results demonstrate that the proposed models achieve high accuracy in landslide displacement forecasting,with optimal performance observed at moderate monitoring intervals.Intriguingly,the daily mean average error(MAE)decreases sharply with increasing monitoring frequency,reaching a plateau.These findings were corroborated by a parallel analysis of the Bazimen landslide,suggesting that moderate monitoring intervals of approximately 7 to 15 days are most conducive to achieving enhanced prediction accuracy compared to both daily and monthly intervals.展开更多
The design of the active region structures,including the modifications of structures of the quantum barrier(QB)and electron blocking layer(EBL),in the deep ultraviolet(DUV)Al Ga N laser diode(LD)is investigated numeri...The design of the active region structures,including the modifications of structures of the quantum barrier(QB)and electron blocking layer(EBL),in the deep ultraviolet(DUV)Al Ga N laser diode(LD)is investigated numerically with the Crosslight software.The analyses focus on electron and hole injection efficiency,electron leakage,hole diffusion,and radiative recombination rate.Compared with the reference QB structure,the step-like QB structure provides high radiative recombination and maximum output power.Subsequently,a comparative study is conducted on the performance characteristics with four different EBLs.For the EBL with different Al mole fraction layers,the higher Al-content Al Ga N EBL layer is located closely to the active region,leading the electron current leakage to lower,the carrier injection efficiency to increase,and the radiative recombination rate to improve.展开更多
In this paper, the effective pyroelectric coefficient and polarization offset of the compositionally step-like graded multilayer ferroelectric structures have been studied by use of the first-principles approach. It i...In this paper, the effective pyroelectric coefficient and polarization offset of the compositionally step-like graded multilayer ferroelectric structures have been studied by use of the first-principles approach. It is exhibited that the dielectric gradient has a nontrivial influence on the effective pyroelectric coefficient, but has a little influence on the polarization offset; and the polarization gradient plays an important role in the abnormal hysteresis loop phenomenon of the co.mpositionally step-like graded ferroelectric structures. Moreover, the origin of the polarization offset is explored,which can be attributed to the polarization gradient in the compositionally step-like graded structure.展开更多
Within the frames of semiclassical approach, intra-atomic electric field potentials are parameterized in form of radial step-like functions. Corresponding parameters for 80 chemical elements are tabulated by fitting o...Within the frames of semiclassical approach, intra-atomic electric field potentials are parameterized in form of radial step-like functions. Corresponding parameters for 80 chemical elements are tabulated by fitting of the semiclassical energy levels of atomic electrons to their first principle values. In substance binding energy and electronic structure calculations, superposition of the semiclassically parameterized constituent-atomic potentials can serve as a good initial approximation of its inner potential: the estimated errors of the determined structural and energy parameters make up a few percent.展开更多
Scientific and precise evaluations of the megafaunal and landform characteristics of seamounts are important guides for their protection and study.A series of manned and unmanned submersibles have provided invaluable ...Scientific and precise evaluations of the megafaunal and landform characteristics of seamounts are important guides for their protection and study.A series of manned and unmanned submersibles have provided invaluable observational imaging data for the ecological study of seamounts.However,traditional methods of artificial observation of seamount imaging data cannot accurately and efficiently determine the characteristics of megafauna and landforms.This research harnesses data-driven technology to systematically investigate the distributional traits and morphological features of megafaunal organisms,as well as the topographical characteristics,in the Caiwei Guyot region of the western Pacific’s Magellan Seamounts.To construct the landform and megafauna dataset of the Caiwei Guyot region,we used a data preprocessing technology based on image enhancement to provide high-quality imaging data for data-driven technologies.A megafaunal identification and counting algorithm based on YOLOv5(You Only Look Once Version 5)was developed to efficiently assess the abundance,variety,and dominant species of megafauna.Simultaneously,a landform three-dimensional(3D)reconstruction algorithm based on PatchmatchNet was developed to reconstruct the 3D form of the terrain accurately.This study pioneers the application of data-driven technology to deep-sea imaging within the Caiwei Guyot region,offering an innovative approach to accurately and efficiently characterize the region’s unique megafauna and landforms.展开更多
In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst ...In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst landforms and planation surfaces formed and how they evolved along drainage development are scarce.Fortunately,horizontal caves with numerous fluvial deposits in high karst mountains can be served as time markers in landform evolution.Here we select large horizontal caves to perform studies of geomorphology,sedimentology,and geochronology.Fieldwork revealed that more than 25 km long horizontal cave passages are perched 1500 m higher than the local base level,but filled with several phases of fluvial sediments and breakdown slabs.The first phase of fluvial gravels and related cave drainage was dated back to 6.4 Ma using cosmogenic nuclide burial dating,and the stalagmite covering the cave collapse was dated by the U-Pb method to be older than 1.56 Ma.These results show that the continuous horizontal cave drainage system and the planation surface were developed before the Late Miocene.The lowering process of the base level as a result of the sharp fluvial incision and water level lowering,along with the regional uplift,led to the abandonment of the horizontal cave and the elevated planation surface at the Late Miocene.After that,the phase of cave collapse,thick fluvial sand,and clay sediments in the recharge of cave areas were deposited at around 1.6 Ma and during the Middle Pleistocene,respectively.Subsequently,speleothems were widely deposited on the collapse and clay sediments during the period from 600 to 90 ka,whereas the deposition of cave fluvial sediments terminated suddenly.The tectonic could control the denudation of surface caprocks and the development of karst conduits before the Late Miocene,whereas the river incision acted as the main driver for the base level lowering and the destruction of the horizontal cave drainage at high altitudes.In addition,the rapid incision and retreat of Silurian gorges finally caused the formation of karst mesas in the Middle Pleistocene.展开更多
Loess landforms in the Loess Plateau are typical landforms in arid and semiarid areas and have a significant impact on the environment and soil erosion.Quantitative analyses on loess landform have been employed from v...Loess landforms in the Loess Plateau are typical landforms in arid and semiarid areas and have a significant impact on the environment and soil erosion.Quantitative analyses on loess landform have been employed from various perspectives.Peak intervisibility can provide the potential topographic information implied in the visual connectivity of peaks,however,its application in loess landform analysis remains unexplored.In this study,the interwoven sightlines among peaks,representing peak intervisibility,were extracted from the digital elevation model and simulated into a peak intervisibility network(PIN).Nine indices were proposed to quantify the PIN.Through a case study in Northern Shaanxi,China,three tasks were conducted,including,landform interpretation,spatial pattern mining,and landform classification.The main findings are as follows:(1)PIN responds to terrain morphology and is beneficial for loess landform interpretation.(2)The spatial patterns of PIN indices are heterogeneous and strongly coupled with the terrain morphologies,showing anisotropy and autocorrelation in spatial variations.(3)Using the light gradient boost machine classifier,the PIN index-based classification reaches a mean accuracy of 86.09%,an overall accuracy of 86%and a kappa coefficient of 0.84.These findings shed light on the applicability of PIN in loess landform analysis.Peak intervisibility not only enriches the theories and methodologies of relation-based digital terrain analysis,but also enhances our comprehension of loess landform genesis,morphology,distribution,and evolution.展开更多
Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a...Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a.s.l.).The objectives of this study were to assess how climate influenced the formation of periglacial landforms in Mount Ilgar,identify the morphological characteristics of each patterned ground by periglacial landforms,and investigate the pedological processes,physicochemical,biological,and mineralogical characteristics of the soils that developed on each of them.Non-sorted steps,mud circles,and stony earth circles are examples of periglacial landforms found on the slopes of the hills?küzkoku(2804 m a.s.l.)and Misikan(2674 m a.s.l.)to the north of Mount Ilgar.In terms of soil physical characteristics,the average aggregate stability and clay content of soils created on non-sorted steps are 43.52%and 8.9%,respectively;these values,however,rise dramatically in soils formed on mud circles and stony earth circles.Chemically,the soils generated on the mud and stony earth circles have lower pH values than the soils formed on the non-sorted steps,but they have higher levels of organic matter.The microbial biomass carbon and basal respiration values of the soils generated on mud circles and stony earth circles are high due to the low pH values and high organic matter contents of these soils,which also have an impact on biological activity.The rate at which soils weather is also influenced by variations in their physical,chemical,and biological characteristics.It is found that the quartz mineral is more prevalent in the soils developed on mud circles landforms,despite the fact that the distribution of the basic clay minerals in the soils is essentially the same.Additionally,smectite clay minerals with a 2:1 layer are present,according to clay mineral analysis,especially in soils that are produced from mud circle formations.One may argue that the influence of local microtopographic landforms on soil formations were the primary cause of the differences in soils on periglacial landforms developed on identical geological material and at similar elevations.展开更多
Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil o...Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.展开更多
Suzhou area in north Anhui Province is a low hilly area on the Huaibei Plain where carbonate rocks and karstification are widely distributed, and karst landscapes form major physical contours of the bedrock outcrops. ...Suzhou area in north Anhui Province is a low hilly area on the Huaibei Plain where carbonate rocks and karstification are widely distributed, and karst landscapes form major physical contours of the bedrock outcrops. Through field investigation, karst landscapes of Suzhou area were divided into two categories based on their morphological characteristics: macro-geomorphologic landscapes including normal hills, dry valleys, karst springs and caves, and micro-corrosion landscapes including corrosion pits, dissolved pores, dissolution traces, corrosion cracks, clints and karrens. Distribution, development and scale of karst landscapes in this region are controlled by climate, rock type, structure, topography and other factors. It was suggested that karst landscapes in the study area could be used as a representative of karst landforms in North China.展开更多
Landform types in gardens are introduced in this study,significance and application principles of landform in the garden design are elaborated,and the comprehensive application of landform are proposed.
基金funding support from the National Science Fund for Distinguished Young Scholars(Grant No.52125904)the National Key R&D Plan(Grant No.2022YFC3004403)the National Natural Science Foundation of China(Grant No.52039008).
文摘To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides under uncertainty.The model decomposed displacements into trend and periodic components via Variational Mode Decomposition(VMD)and K-shape clustering.The Residual and Moving Block Bootstrap methods were used to generate pseudo datasets.Polynomial regressionwas adopted for trend forecasting,whereas the Dense Convolutional Network(DenseNet)and Long Short-Term Memory(LSTM)networks were employed for periodic displacement prediction.An Extreme Learning Machine(ELM)was used to estimate the noise variance,enabling the construction of Prediction Intervals(PIs)and quantificationof displacement uncertainty.Failure probabilities(Pf)were derived from PIs using an improved tangential angle criterion and reliability analysis.The model was validated on three step-like landslides in the Three Gorges Reservoir Area,achieving stability assessment accuracies of 99.88%(XD01),99.93%(ZG93),99.89%(ZG118),and 100%for ZG110 and ZG111 across the Baishuihe and Bazimen landslides.For the Shuping landslide,the predictions aligned with fieldobservations before and after the 2014–2015 remediation,with P_(f)remaining near zero post-2015 except for occasional peaks.The model outperformed conventional ML approaches by yielding narrower PIs.At XD01 with 90%PI nominal confidencelevel(PINC),the coverage width-based criterion(CWC)and PI average width(PIAW)were 3.38 mm.The mean values of the PIs exhibited high accuracy,with a Mean Absolute Error(MAE)of 0.28 mm and Root Mean Square Error(RMSE)of 0.39 mm.These results demonstrate the robustness of the proposed model in improving landslide risk assessment and decision-making under uncertainty.
基金supported by the National Natural Science Foundation of China under Grant No.12147115the Discipline(Subject)Leader Cultivation Project of Universities in Anhui Province under Grant Nos.DTR2023052 and DTR2024046+2 种基金the Natural Science Research Project of Universities in Anhui Province under Grant No.2024AH040202the Young Top Notch Talents and Young Scholars of High End Talent Introduction and Cultivation Action Project in Anhui Provincethe Scientific Research Foundation Funded Project of Chuzhou University under Grant Nos.2022qd022 and 2022qd038。
文摘In this paper,we use the Riemann-Hilbert(RH)method to investigate the Cauchy problem of the reverse space-time nonlocal Hirota equation with step-like initial data:q(z,0)=o(1)as z→-∞and q(z,0)=δ+o(1)as z→∞,whereδis an arbitrary positive constant.We show that the solution of the Cauchy problem can be determined by the solution of the corresponding matrix RH problem established on the plane of complex spectral parameterλ.As an example,we construct an exact solution of the reverse space-time nonlocal Hirota equation in a special case via this RH problem.
基金supported by the Open Fund of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University)of the Ministry of Education(Grant Nos.2022KDZ14 and 2022KDZ15)the Open Fund of Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202304)+3 种基金the Science and Technology Project of Department of Natural Resources of Hubei Province(Grant No.ZRZY2024KJ15)the Natural Science Foundation of Hubei Province(Grant No.2022CFB557)the National Natural Science Foundation of China(Grant No.42107489)the 111 Project of Hubei Province(Grant No.2021EJD026)。
文摘The precision of landslide displacement prediction is crucial for effective landslide prevention and mitigation strategies.However,the role of surface monitoring frequency in influencing prediction accuracy has been largely neglected.This study examined the effect of varying monitoring frequencies on the accuracy of displacement predictions by using the Baijiabao landslide in the Three Gorges Reservoir Area(TGRA)as a case study.We collected surface automatic monitoring data at different intervals,ranging from daily to monthly.The Ensemble Empirical Mode Decomposition(EEMD)algorithm was utilized to dissect the accumulated displacements into periodic and trend components at each monitoring frequency.Polynomial fitting was applied to forecast the trend component while the periodic component was predicted with two state-of-the-art neural network models:Long Short-Term Memory(LSTM)and Gated Recurrent Unit(GRU).The predictions from these models were integrated to derive cumulative displacement forecasts,enabling a comparative analysis of prediction accuracy across different monitoring frequencies.The results demonstrate that the proposed models achieve high accuracy in landslide displacement forecasting,with optimal performance observed at moderate monitoring intervals.Intriguingly,the daily mean average error(MAE)decreases sharply with increasing monitoring frequency,reaching a plateau.These findings were corroborated by a parallel analysis of the Bazimen landslide,suggesting that moderate monitoring intervals of approximately 7 to 15 days are most conducive to achieving enhanced prediction accuracy compared to both daily and monthly intervals.
基金Project supported by the Special Project for Inter-government Collaboration of State Key Research and Development Program,China(Grant No.2016YFE0118400)the Key Project of Science and Technology of Henan Province,China(Grant No.172102410062)the National Natural Science Foundation of China and Henan Provincial Joint Fund Key Project(Grant No.U1604263)
文摘The design of the active region structures,including the modifications of structures of the quantum barrier(QB)and electron blocking layer(EBL),in the deep ultraviolet(DUV)Al Ga N laser diode(LD)is investigated numerically with the Crosslight software.The analyses focus on electron and hole injection efficiency,electron leakage,hole diffusion,and radiative recombination rate.Compared with the reference QB structure,the step-like QB structure provides high radiative recombination and maximum output power.Subsequently,a comparative study is conducted on the performance characteristics with four different EBLs.For the EBL with different Al mole fraction layers,the higher Al-content Al Ga N EBL layer is located closely to the active region,leading the electron current leakage to lower,the carrier injection efficiency to increase,and the radiative recombination rate to improve.
文摘In this paper, the effective pyroelectric coefficient and polarization offset of the compositionally step-like graded multilayer ferroelectric structures have been studied by use of the first-principles approach. It is exhibited that the dielectric gradient has a nontrivial influence on the effective pyroelectric coefficient, but has a little influence on the polarization offset; and the polarization gradient plays an important role in the abnormal hysteresis loop phenomenon of the co.mpositionally step-like graded ferroelectric structures. Moreover, the origin of the polarization offset is explored,which can be attributed to the polarization gradient in the compositionally step-like graded structure.
文摘Within the frames of semiclassical approach, intra-atomic electric field potentials are parameterized in form of radial step-like functions. Corresponding parameters for 80 chemical elements are tabulated by fitting of the semiclassical energy levels of atomic electrons to their first principle values. In substance binding energy and electronic structure calculations, superposition of the semiclassically parameterized constituent-atomic potentials can serve as a good initial approximation of its inner potential: the estimated errors of the determined structural and energy parameters make up a few percent.
基金The Key Research and Development Program of Shandong Province of China under contract No.2020JMRH0101the National Key Research and Development Project of China under contract No.2021YFC2802100the Qingdao Natural Science Foundation under contract No.24-4-4-zrij-127-jch.
文摘Scientific and precise evaluations of the megafaunal and landform characteristics of seamounts are important guides for their protection and study.A series of manned and unmanned submersibles have provided invaluable observational imaging data for the ecological study of seamounts.However,traditional methods of artificial observation of seamount imaging data cannot accurately and efficiently determine the characteristics of megafauna and landforms.This research harnesses data-driven technology to systematically investigate the distributional traits and morphological features of megafaunal organisms,as well as the topographical characteristics,in the Caiwei Guyot region of the western Pacific’s Magellan Seamounts.To construct the landform and megafauna dataset of the Caiwei Guyot region,we used a data preprocessing technology based on image enhancement to provide high-quality imaging data for data-driven technologies.A megafaunal identification and counting algorithm based on YOLOv5(You Only Look Once Version 5)was developed to efficiently assess the abundance,variety,and dominant species of megafauna.Simultaneously,a landform three-dimensional(3D)reconstruction algorithm based on PatchmatchNet was developed to reconstruct the 3D form of the terrain accurately.This study pioneers the application of data-driven technology to deep-sea imaging within the Caiwei Guyot region,offering an innovative approach to accurately and efficiently characterize the region’s unique megafauna and landforms.
基金supported by the foundation of the Institute of Karst Geology,Chinese Academy of Geological Sciences(Nos.201317,2014005,2014034,2016011)National Natural Science Foundation of China(No.41270226)。
文摘In Southwestern China,the development of karst landforms and planation surfaces is closely related to local tectonics,fluvial incision,and base level changes,and climate changes.However,researches on when these karst landforms and planation surfaces formed and how they evolved along drainage development are scarce.Fortunately,horizontal caves with numerous fluvial deposits in high karst mountains can be served as time markers in landform evolution.Here we select large horizontal caves to perform studies of geomorphology,sedimentology,and geochronology.Fieldwork revealed that more than 25 km long horizontal cave passages are perched 1500 m higher than the local base level,but filled with several phases of fluvial sediments and breakdown slabs.The first phase of fluvial gravels and related cave drainage was dated back to 6.4 Ma using cosmogenic nuclide burial dating,and the stalagmite covering the cave collapse was dated by the U-Pb method to be older than 1.56 Ma.These results show that the continuous horizontal cave drainage system and the planation surface were developed before the Late Miocene.The lowering process of the base level as a result of the sharp fluvial incision and water level lowering,along with the regional uplift,led to the abandonment of the horizontal cave and the elevated planation surface at the Late Miocene.After that,the phase of cave collapse,thick fluvial sand,and clay sediments in the recharge of cave areas were deposited at around 1.6 Ma and during the Middle Pleistocene,respectively.Subsequently,speleothems were widely deposited on the collapse and clay sediments during the period from 600 to 90 ka,whereas the deposition of cave fluvial sediments terminated suddenly.The tectonic could control the denudation of surface caprocks and the development of karst conduits before the Late Miocene,whereas the river incision acted as the main driver for the base level lowering and the destruction of the horizontal cave drainage at high altitudes.In addition,the rapid incision and retreat of Silurian gorges finally caused the formation of karst mesas in the Middle Pleistocene.
基金supported by the National Natural Science Foundation of China(Grant No.41771423)the Natural Science Foundation of Fujian Province(Grant No.2023J01421).
文摘Loess landforms in the Loess Plateau are typical landforms in arid and semiarid areas and have a significant impact on the environment and soil erosion.Quantitative analyses on loess landform have been employed from various perspectives.Peak intervisibility can provide the potential topographic information implied in the visual connectivity of peaks,however,its application in loess landform analysis remains unexplored.In this study,the interwoven sightlines among peaks,representing peak intervisibility,were extracted from the digital elevation model and simulated into a peak intervisibility network(PIN).Nine indices were proposed to quantify the PIN.Through a case study in Northern Shaanxi,China,three tasks were conducted,including,landform interpretation,spatial pattern mining,and landform classification.The main findings are as follows:(1)PIN responds to terrain morphology and is beneficial for loess landform interpretation.(2)The spatial patterns of PIN indices are heterogeneous and strongly coupled with the terrain morphologies,showing anisotropy and autocorrelation in spatial variations.(3)Using the light gradient boost machine classifier,the PIN index-based classification reaches a mean accuracy of 86.09%,an overall accuracy of 86%and a kappa coefficient of 0.84.These findings shed light on the applicability of PIN in loess landform analysis.Peak intervisibility not only enriches the theories and methodologies of relation-based digital terrain analysis,but also enhances our comprehension of loess landform genesis,morphology,distribution,and evolution.
基金supported by Ardahan University,Scientific Research Projects Office(Project No:2020-001)。
文摘Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a.s.l.).The objectives of this study were to assess how climate influenced the formation of periglacial landforms in Mount Ilgar,identify the morphological characteristics of each patterned ground by periglacial landforms,and investigate the pedological processes,physicochemical,biological,and mineralogical characteristics of the soils that developed on each of them.Non-sorted steps,mud circles,and stony earth circles are examples of periglacial landforms found on the slopes of the hills?küzkoku(2804 m a.s.l.)and Misikan(2674 m a.s.l.)to the north of Mount Ilgar.In terms of soil physical characteristics,the average aggregate stability and clay content of soils created on non-sorted steps are 43.52%and 8.9%,respectively;these values,however,rise dramatically in soils formed on mud circles and stony earth circles.Chemically,the soils generated on the mud and stony earth circles have lower pH values than the soils formed on the non-sorted steps,but they have higher levels of organic matter.The microbial biomass carbon and basal respiration values of the soils generated on mud circles and stony earth circles are high due to the low pH values and high organic matter contents of these soils,which also have an impact on biological activity.The rate at which soils weather is also influenced by variations in their physical,chemical,and biological characteristics.It is found that the quartz mineral is more prevalent in the soils developed on mud circles landforms,despite the fact that the distribution of the basic clay minerals in the soils is essentially the same.Additionally,smectite clay minerals with a 2:1 layer are present,according to clay mineral analysis,especially in soils that are produced from mud circle formations.One may argue that the influence of local microtopographic landforms on soil formations were the primary cause of the differences in soils on periglacial landforms developed on identical geological material and at similar elevations.
文摘Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.
基金Supported by Masters' Scientific Research Initial Funding of Suzhou College (2009YSS05)~~
文摘Suzhou area in north Anhui Province is a low hilly area on the Huaibei Plain where carbonate rocks and karstification are widely distributed, and karst landscapes form major physical contours of the bedrock outcrops. Through field investigation, karst landscapes of Suzhou area were divided into two categories based on their morphological characteristics: macro-geomorphologic landscapes including normal hills, dry valleys, karst springs and caves, and micro-corrosion landscapes including corrosion pits, dissolved pores, dissolution traces, corrosion cracks, clints and karrens. Distribution, development and scale of karst landscapes in this region are controlled by climate, rock type, structure, topography and other factors. It was suggested that karst landscapes in the study area could be used as a representative of karst landforms in North China.
文摘Landform types in gardens are introduced in this study,significance and application principles of landform in the garden design are elaborated,and the comprehensive application of landform are proposed.
