Extreme value theory applied to the auroral electrojet indices

The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.

Detection of Burned Areas through Spectral Indices Analysis of Sentinel-2A Satellite Images in the Abokouamékro Wildlife Reserve (Central, Côte D’Ivoire)

In Côte d’Ivoire, the recurring and unregulated use of bushfires, which cause ecological damage, presents a pressing concern for the custodians of protected areas. This study aims to enhance our comprehension of the dynamics of burnt areas within the Abokouamékro Wildlife Reserve (AWR) by employing the analysis of spectral indices derived from satellite imagery. The research methodology began with the calculation of mean indices and their corresponding spectral sub-indices, including NDVI, SAVI, NDWI, NDMI, BAI, NBR, TCW, TCG, and TCB, utilizing data from the Sentinel-2A satellite image dated January 17, 2022. Subsequently, a fuzzy classification model was applied to these various indices and sub-indices, guided by the degree of membership α, with the goal of effectively distinguishing between burned and unburned areas. Following the classification, the accuracies of the classified indices and sub-indices were validated using the coordinates of 100 data points collected within the AWR through GPS technology. The results revealed that the overall accuracy of all indices and sub-indices declines as the degree of membership α decreases from 1 to 0. Among the mean spectral indices, NDVI-mean, SAVI-mean, NDMI-mean exhibited the highest overall accuracies, achieving 97%, 95%, and 90%, respectively. These results closely mirrored those obtained by sub-indices using band 8 (NDVI-B8, SAVI-B8, and NDMI-B8), which yield respective overall accuracies of 93%, 92%, and 89%. At a degree of membership α = 1, the estimated burned areas for the most effective indices encompassed 2144.38 hectares for NDVI-mean, 1932.14 hectares for mean SAVI-mean, and 4947.13 hectares for mean NDMI-mean. A prospective approach involving the amalgamation of these three indices could have the potential to yield improved outcomes. This study could be a substantial contribution to the discrimination of bushfires in Côte d’Ivoire.

Comparison of different preoperative objective nutritional indices for evaluating 30-d mortality and complications after liver transplantation

BACKGROUND The nutritional status is closely related to the prognosis of liver transplant re-cipients,but few studies have reported the role of preoperative objective nutri-tional indices in predicting liver transplant outcomes.AIM To compare the predictive value of various preoperative objective nutritional indicators for determining 30-d mortality and complications following liver transplantation(LT).METHODS A retrospective analysis was conducted on 162 recipients who underwent LT at our institution from December 2019 to June 2022.RESULTS This study identified several independent risk factors associated with 30-d mor-tality,including blood loss,the prognostic nutritional index(PNI),the nutritional risk index(NRI),and the control nutritional status.The 30-d mortality rate was 8.6%.Blood loss,the NRI,and the PNI were found to be independent risk factors for the occurrence of severe postoperative complications.The NRI achieved the highest prediction values for 30-d mortality[area under the curve(AUC)=0.861,P<0.001]and severe complications(AUC=0.643,P=0.011).Compared to those in the high NRI group,the low patients in the NRI group had lower preoperative body mass index and prealbumin and albumin levels,as well as higher alanine aminotransferase and total bilirubin levels,Model for End-stage Liver Disease scores and prothrombin time(P<0.05).Furthermore,the group with a low NRI exhibited significantly greater incidences of intraabdominal bleeding,primary graft nonfunction,and mortality.CONCLUSION The NRI has good predictive value for 30-d mortality and severe complications following LT.The NRI could be an effective tool for transplant surgeons to evaluate perioperative nutritional risk and develop relevant nutritional therapy.

Relative active tectonic in the metamorphic rocks of the Yaounde group: insights from geomorphic indices and topographic analysis

The Yaounde Group(YG),representing the southern edge of the North Equatorial PanAfrican Belt,consists of quartzites,schists,micaschists,amphibolites,gneisses and migmatites.Tectonism has formed a landscape characterized by the development of linear and folded valleys and ridges,fault scarps,V-shaped valleys,incised rivers and knickpoints.These landforms constitute important markers of the regional tectonic activity,which have been computed from spatial sources such as SRTM,DEM,hydrographical networks and geomorphic indices such as AF,T,Smf,Vf,Bs,Hi,U,SI and Li.The results highlighted a mature relief consisting of asymmetric basins generated by tilting and uplift phenomena.The relative index of active tectonics(RIAT)has been estimated from an average of eight geomorphic indices evaluated on 24 subbasins,in the study area.Four classes have been defined:class 1(1.38),very high active(1.0≤RIAT<1.5);class 2(1.50-1.88),high active(1.5≤RIAT<2.0);and class 3(2.00-2.13)moderate active(2.0≤RIAT<2.5).These three classes,respectively covering 10.20%(458 km2),80.10%(3595 km2)and 9.69%(435 km2)of the study area,have shown a highly active tectonic zone,and imply the existence of a neotectonic event in the YG.This tectonic unit(YG)was also affected by the dextral NW-SE strike-slip faulting,which cross-cut the Sanaga Shear Zone(SSZ)at Ebebda and the foliation oriented NW-SE.The tilting and uplift of rocks related to Moho ascending are responsible for crustal thinning in the Cameroon basement,more important to the Adamawa Plateau from the Cretaceous age and the reactivation of existing tectonic accidents.The presence of hills,fault scarps,reverse faults,knickpoints,V and U shaped valleys and rounded mountains testify to the interaction between tectonic uplift,lithology,climate,weathering and erosion.

Assessment of forest dieback on the Moroccan Central Plateau using spectral vegetation indices

Cork oak forests in Morocco are rich in resources and services thanks to their great biological diversity,playing an important ecological and socioeconomic role.Considerable degradation of the forests has been accentuated in recent years by signifi cant human pressure and eff ects of climate change;hence,the health of the stands needs to be monitored.In this study,the Google Engine Earth platform was leveraged to extract the normalized diff erence vegetation index(NDVI)and soil-adjusted vegetation index,from Landsat 8 OLI/TIRS satellite images between 2015 and 2017 to assess the health of the Sibara Forest in Morocco.Our results highlight the importance of interannual variations in NDVI in forest monitoring;the variations had a signifi cantly high relationship(p<0.001)with dieback severity.NDVI was positively and negatively correlated with mean annual precipitation and mean annual temperature with respective coeffi cients of 0.49 and−0.67,highlighting its ability to predict phenotypic changes in forest species.Monthly interannual variation in NDVI between 2016 and 2017 seemed to confi rm fi eld observations of cork oak dieback in 2018,with the largest decreases in NDVI(up to−38%)in December in the most-aff ected plots.Analysis of the infl uence of ecological factors on dieback highlighted the role of substrate as a driver of dieback,with the most severely aff ected plots characterized by granite-granodiorite substrates.

Assessing fire severity in Turkey's forest ecosystems using spectral indices from satellite images

Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.

Proposing a novel geo-structural model for Torbat-e-Jam-Fariman plain(Northeast of Iran),based on Geomorphic indices calculation,conjugating the field evidences

There are various faults in northern and southern margins of Torbat-e-Jam-Fariman plain which show the probability of enormous earthquake in the future.In present study the geomorphic indices contain Asymmetry Function(Af),Sinuosity of mountain front(Smf),Valley floor index(Vf),Hypsometric index(Hi),Mean Axial slope of channel index(MASC)and Drainage Basin Shape(Bs),have been utilized to determine the relative tectonic activity index(IAT)to recognize,eventually,the geo-structural model of the study area.Faults and folds control the geo-structural activities of the study area,and the geomorphic indices are being affected in consequence of their activities.The intensity of these activities is different throughout the plain.There are many geomorphic evidences,related to active transform fault which are detectable all over the study area such as deviated rivers,quaternary sediments transformation,fault traces.Therefore,recognition of geo-structural model of the study area is extremely vital.Field study,then,approved the results of geomorphic indices calculation in determining the geo-structural model of the study area.Results depicted that the geostructural model of the study area is a kind of Horsetail splay form which is in accordance to the relative tectonic activity of the study area.Based on the above mentioned results it can be predicted that the splays are the trail of Neyshabour fault.

On Some Ev-Degree and Ve-Degree Dependent Indices of Benes Network and Its Derived Classes

One of the most recent developments in the field of graph theory is the analysis of networks such as Butterfly networks,Benes networks,Interconnection networks,and David-derived networks using graph theoretic parameters.The topological indices(TIs)have been widely used as graph invariants among various graph theoretic tools.Quantitative structure activity relationships(QSAR)and quantitative structure property relationships(QSPR)need the use of TIs.Different structure-based parameters,such as the degree and distance of vertices in graphs,contribute to the determination of the values of TIs.Among other recently introduced novelties,the classes of ev-degree and ve-degree dependent TIs have been extensively explored for various graph families.The current research focuses on the development of formulae for different ev-degree and ve-degree dependent TIs for s−dimensional Benes network and certain networks derived from it.In the end,a comparison between the values of the TIs for these networks has been presented through graphical tools.

Topological Evaluation of Certain Computer Networks by Contraharmonic-Quadratic Indices

In various fields,different networks are used,most of the time not of a single kind;but rather a mix of at least two networks.These kinds of networks are called bridge networks which are utilized in interconnection networks of PC,portable networks,spine of internet,networks engaged with advanced mechanics,power generation interconnection,bio-informatics and substance intensify structures.Any number that can be entirely calculated by a graph is called graph invariants.Countless mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty years.Nevertheless,no trustworthy evaluation has been embraced to pick,how much these invariants are associated with a network graph or subatomic graph.In this paper,it will discuss three unmistakable varieties of bridge networks with an incredible capacity of assumption in the field of computer science,chemistry,physics,drug industry,informatics and arithmetic in setting with physical and manufactured developments and networks,since Contraharmonic-quadratic invariants(CQIs)are recently presented and have different figure qualities for different varieties of bridge graphs or networks.The study settled the geography of bridge graphs/networks of three novel sorts with two kinds of CQI and Quadratic-Contraharmonic Indices(QCIs).The deduced results can be used for the modeling of the above-mentioned networks.

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators.One of these indicators is material prices.On the other hand,cost is a key concern in all operations of the construction industry.In the uncertain conditions,reliable cost forecasts become an important source of information.Material cost is one of the key components of the overall cost of construction.In addition,cost overrun is a common problem in the construction industry,where nine out of ten construction projects face cost overrun.In order to carry out a successful cost management strategy and prevent cost overruns,it is very important to find reliable methods for the estimation of construction material prices.Material prices have a time dependent nature.In order to increase the foreseeability of the costs of construction materials,this study focuses on estimation of construction material indices through time series analysis.Two different types of analysis are implemented for estimation of the future values of construction material indices.The first method implemented was Autoregressive Integrated Moving Average(ARIMA),which is known to be successful in estimation of time series having a linear nature.The second method implementedwas Non-LinearAutoregressive Neural Network(NARNET)which is known to be successful in modeling and estimating of series with non-linear components.The results have shown that depending on the nature of the series,both these methods can successfully and accurately estimate the future values of the indices.In addition,we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.

Climatic Indices’ Analysis on Extreme Precipitation for Tanzania Synoptic Stations

Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the country is crucial. This study used data from 28 meteorological stations for 1981-2020 period to give an annual and seasonal analysis of the patterns of 10 ETCCDI’s extreme precipitation indices over the regions. At annual scale, the results showed that increasing trends had high frequency percentage than the decreasing ones, collecting about 76% in total. The decreasing trend was approximately 24%, and most of the stations with increasing percentage in trend are concentrated in Northern coast, Central, West, North-eastern highlands and Lake Victoria Basin. Most of the stations depicted negative trend are concentrated over Southern region. This highlights that extreme precipitation events have increased over the country for the period 1981-2020. At seasonal scale, during October to December (OND);the patterns of extreme precipitation climatic indices except R99p, showed positive significant increasing trend over Lake Victoria Basin and some Western parts of the country. In general, spatial patterns indicate decrease of precipitation over most parts of the country during OND. The seasonal average time series depicted non-significant positive trend during March to April (MAM) season, except for Consecutive Wet Days (CWD) which showed non-significant decreasing trend. Over the highest mountain in Africa, Kilimanjaro;the study has revealed significant decrease in Annual total-wet Precipitation (PRCPTOT), the number of heavy (very heavy) days of precipitation R10 mm (R20 mm) and Consecutive Wet Days (CWD) during MAM season. While the maximum one-day precipitation amount (RX1 day) was observed to decrease significantly over the Mountain during OND season. The result is very important in risk assessment and preparedness perspective in planning climate change mitigation and adaptations for different sectors like Tourism, Agriculture, Water and Energy.

Application of Vegetation Indices for Detection and Monitoring Oil Spills in Ahoada West Local Government Area of Rivers State,Nigeria

The study evaluated the environmental effects of an oil spill in Joinkrama 4 and Akimima Ahoada West LGA,Rivers State,Nigeria,using various vegetation indices.Location data for the spill were obtained from the Nigeria Oil Spill Detection and Response Agency,and Landsat imagery was acquired from the United States Geological Survey.Three soil samples were collected from the affected area,and their analysis included measuring total petroleum hydrocarbons(TPH),total hydrocarbons(THC),and polycyclic aromatic hydrocarbons(PAH).The obtained data were processed with ArcGIS software,utilizing different vegetation indices such as the Normalized Difference Vegetation Index(NDVI),Atmospheric Resistant Vegetation Index(ARVI),Soil Adjusted Vegetation Index(SAVI),Green Short Wave Infrared(GSWIR),and Green Near Infrared(GNIR).Statistical analysis was performed using SPSS and Microsoft Excel.The results consistently indicated a negative impact on the environment resulting from the oil spill.A comparison of spectral reflectance values between the oil spill site and the non-oil spill site showed lower values at the oil spill site across all vegetation indices(NDVI 0.0665-0.2622,ARVI-0.0495-0.1268,SAVI 0.0333-0.1311,GSWIR-0.183-0.0517,GNIR-0.0104--0.1980),indicating damage to vegetation.Additionally,the study examined the correlation between vegetation indices and environmental parameters associated with the oil spill,revealing significant relationships with TPH,THC,and PAH.A t-test with a significance level of p<0.05 indicated significantly higher vegetation index values at the non-oil spill site compared to the oil spill site,suggesting a potential disparity in vegetation health between the two areas.Hence,this study emphasizes the harmful effect of oil spills on vegetation and highlights the importance of utilizing vegetation indices and spectral reflectance analysis to detect and monitor the impact of oil spills on vegetation.

Evaluating Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq: A Case Study

The study evaluated the Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq. It calculated the reference evapotranspiration, actual evapotranspiration, and amount of precipitation with effective rainfall to estimate the droughts indicators which are the Standard Precipitation Index (SPI), the Standard Precipitation and Evaporation Rain Index (SPEI) and Reconnaissance Drought Index RDI. The study indicated that the greatest decrease in river flow occurred from 2019-2021 to 2020-2021 due to increasing temperature in summer and decreasing precipitation in winter. This research evaluated a wet and drought indicating for planning and management of water resources to face changes in climate of future. The research showed the last years were years of drought according to the three indicators. SPI ranged from 0.5 to 1.5 in the rainy years, but it was -0.5 to -1 as moderately dry because in the middle of Iraq while in the south of Iraq was severely dry or extremely dry. SPEI of the study area ranged from -1.5 to -2.5 which means severely dry. The SPEI measures are negative values meaning the months and years were drier. RDi ranged from 0 to -1 was dry and moderately dry while some months and years are positive and will be wet through rainfall for ten years (2014-2023). From indices showed that the region was a drying study area due to the impact of climate change because of the reduction of precipitation and increase in temperature which caused a rise of evapotranspiration during the last few years.

Relative active tectonics evaluation using geomorphic and drainage indices, in Dadra and Nagar Haveli, western India

The present study area,Dadra and Nagar Haveli,contains several lineaments and traces of active faults.The various aspect of the geomo rphic analysis,i.e.,stream length(SL) gradient,hypsometric integral(HI),basin shape(BS),valley floor(VF),have been applied to evaluate the relative index of active tectonics(RIAT) of the Damanganga watershed.The high and low zones of tectonic activity have been identified based on the geomorphic analysis of the watershed.After evaluation of all indices,three classes,class IIhigh(1.3 ≤RIAT <1.5),class Ⅲ-moderate(1.5 ≤RIAT <1.8),and class Ⅳ-low(1.8 ≤RIAT),have been obtained to outline the degree/gradation of comparative tectonic activities in the study area.The appraised outcome of the RIAT dispersal is also well reinforced by the geomorphic evidence in the field.The collective outcomes of geomorphic evidence,such as stream deflection and analysis of lineament,deflection of streams,and geomorphic indices,conceal that the Damanganga watershed is affected by tectonic activity.

Damage Assessment of Reinforced Concrete Structures through Damage Indices:A State-of-the-Art Review

Due to the developments of computer science and technology in recent years,computer models and numerical simulations for large and complicated structures can be done.Among the vast information and results obtained from the analysis and simulations,the damage performance is of great importance since this damage might cause enormous losses for society and humanity,notably in cases of severe damage occurring.One of the most effective tools to handle the results about the damage performance of the structure is the damage index(DI)together with the damage states,which are used to correlate the damage indices with the damage that occurred in the actual structures.Numbers of damage indices proposed and developed rely on the fact that the damage causes noticeable changes in the structural and dynamic properties of the structural components or the whole structure.Therefore,this study presents a comprehensive review of the damage assessment of Reinforced Concrete(RC)structures.It presents step by step the development of the damage indices that are most widely used to estimate the performance of structural components in the structure and subsequently assess the damage degree of such these structures either based on the structural properties or dynamic properties of the structure.Also,several damage states have been introduced to estimate the performance level of the structure.Finally,case studies,methodologies,and applications on the damage assessment of RC structures are reviewed and presented.

Meteorological Indices Approach for Prediction of Thunderstorm Probability at Two Coastal Sites in Egypt

Siting of hazardous facilities such as Nuclear power plants requires the investigation of the meteorological and climatologically of the site region to derive extreme values of the meteorological variables to be considered in the design for safety purposes. Not only normally occurring meteorological conditions but also extremely rare events are considered. The present work is devoted to predict the likelihood of the Thunderstorm which is one of the rare events of concern for plant safety. Four atmospheric stability indices such as K-indices, the Showalter-indices, total totals-indices and the SWEAT-indices have been used for that. These function of meteorological parameters such as temperature, wind speed, wind direction and dew point at levels of pressure at 500, 700 and 850 hpa to predict the thunderstorm probability. Two Egyptian coastal sities have been chosen for the investigation, one on the Mediterranean Sea and the other on Red Sea;El Sallum and Sharm El Sheikh. The results show that the probability of thunderstorm occurred within the months January and February during 1989-2003, where the maximum value of SI, K, TT and SWEAT indices at January & February months equals 29.31 & 28.20, 18.4 & 20.3 & 48.1 & 49 and 238.01 & 350.6 for Sallum city respectively, and equals 26.05 & 24.53, 24.6 & 23.9, 50.6 & 51.5 and 253.4 & 265.4 for Sharm El Sheikh city respectively, and this agrees with the pattern reviewed based on world geographic and climatic condition.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Screening of drought resistance indices and evaluation of drought resistance in cotton(Gossypium hirsutum L.)

Sixteen cotton cultivars widely planted in China were sowed under five different drought concentrations(0,2.5,5,7.5,and 10%)using PEG6000 to screen the indices of drought resistance identification and explore the drought resistance of different cotton cultivars.Eighteen physiological indices including root,stem,and leaf water contents(RWC,SWC,and LWC),net photosynthetic rate(Pn),the maximum photochemical quantum yield(Fv/Fm),the actual photochemical quantum yield(ΦPSII),non-photochemical quenching coefficient(NPQ),leaf water potential(LWP),osmotic potential(Ψs),leaf relative conductivity(REC),leaf proline content(Pro),leaf and root soluble protein contents(LSPC and RSPC),leaf and root malondialdehyde(MDA)contents(LMDA and RMDA),root superoxide dismutase,peroxidase,and catalase activities(RSOD,RPOD,and RCAT)were measured.Results indicated the 18 physiological indices can be converted into five or six independent comprehensive indices by principal component analysis,and nine typical indices(Fv/Fm,SWC,LWP,Pro,LMDA,RSPC,RMDA,RSOD,and RCAT)screened out by a stepwise regression method could be utilized to evaluate the drought resistance.Moreover,the 16 cotton cultivars were divided into four types:drought sensitive,drought weak sensitive,moderate drought resistant,and drought resistant types.The resistance ability of two selected cotton cultivars(drought resistant cultivar,Dexiamian 1;drought sensitive cultivar,Yuzaomian 9110)with contrasting drought sensitivities were further verified by pot experiment.Results showed that the responses of final cotton biomass,yield,and yield composition to drought were significantly different between the two cultivars.In conclusion,drought resistant cultivar Dexiamian 1 and drought sensitive cultivar Yuzaomian 9110 were screened through hydroponics experiment,which can be used as ideal experimental materials to study the mechanism of different cotton cultivars with contrasting drought sensitivities in response to drought stress.

Changes in freezing and thawing indices over the source region of the Yellow River from 1980 to 2014

Freezing and thawing indices are not only of great significance for permafrost research but also are important indicators of the effects of climate change.However,to date,research on ground-surface freezing and thawing indices and their relationship with air indices is limited.Based on daily air and ground-surface temperatures collected from 11 meteorological stations in the source region of the Yellow River,the freezing and thawing indices were calculated,and their spatial distribution and trends were analyzed.The air-freezing index(AFI),air-thawing index(ATI),ground surface-freezing index(GFI),ground surface-thawing index(GTI),air thawing-freezing index ratio(Na)and surface ground thawing-freezing index ratio(Ng)were 1554.64,1153.93,1.55,2484.85,850.57℃-days and 3.44,respectively.Altitude affected the spatial distribution of the freezing and thawing indices.As the altitude increased,the freezing indices gradually increased,and the thawing indices and thawing-freezing index ratio decreased.From 1980 to 2014,the AFI and GFI decreased at rates of 8.61 and 11.06℃-days a^(-1),the ATI and GTI increased at 9.65 and 14.53℃-days a^(-1),and Na and Ng significantly increased at 0.21 and 0.79 decade^(-1).Changes in the freezing and thawing indices were associated with increases in the air and ground-surface temperatures.The rates of change of the ground surface freezing and thawing indices were faster than the air ones because the rate of increase of the groundsurface temperature was faster than that of the air and the difference between the ground surface and air increased.The change point of the time series of freezing and thawing indices occurred in 2000–2001.After 2000–2001,the AFI and GFI were lower than before the change point,and the changing trend was lower.The ATI,GTI,Na and Ng during 2001–2014 were higher,with faster rates than before.In addition,the annual thawing indices composed a greater proportion of the mean annual air temperature and mean annual ground surface temperature than the annual freezing indices.This study provides the necessary basis for research on and prediction of permafrost changes,especially changes in the depth of the active permafrost layer,climate change,and possible evolution of the ecological environment over the source region of the Yellow River on the Qinghai-Tibet Plateau.

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.