We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation meas...We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation measurement configuration,without requiring a specific form of the incident pulse function.A rigorous solution of the nonlinear coupled wave equation is obtained in the time domain and expressed in a general analytical form.The global model fully accounts for the nonlinear interaction and propagation effects within nonlinear crystals,which are not captured by the classical local model.To assess the performance of the global model compared to the classic local model,we investigate the autocorrelation signals obtained from both models for different incident pulse waveforms and different full-widthes at half-maximum(FWHMs).When the incident pulse waveform is Lorentzian with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 399.9 fs,while the classic local model predicts an FWHM of 331.4 fs.The difference between the two models is 68.6 fs,corresponding to an error of 17.2%.Similarly,for a sech-type incident pulse with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 343.9 fs,while the local model predicts an FWHM of 308.8 fs.The difference between the two models is 35.1 fs,with an error of 10.2%.We further examine the behavior of the models for Lorentzian pulses with FWHMs of 100 fs,200 fs and 500 fs.The differences between the global and local models are 17.1 fs,68.6 fs and 86.0 fs,respectively,with errors approximately around 17%.These comparative analyses clearly demonstrate the superior accuracy of the global model in intensity autocorrelation modeling.展开更多
Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensi...Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensive database of transboundary natural tourism resources(TNTR)through amalgamation of diverse data sources.Utilizing the Getis-Ord Gi^(*),kernel density estimation,and geographical detectors,we scrutinize the spatial patterns of TNTR,focusing on both named and unnamed entities,while exploring the influencing factors.Our findings reveal 7883 identified TNTR in China,with mountain tourism resources emerging as the predominant type.Among provinces,Hunan boasts the highest count,while Shanghai exhibits the lowest.Southern China demonstrates a pronounced clustering trend in TNTR distribution,with the spatial arrangement of biological landscapes appearing more random compared to geological and water landscapes.Western China,characterized by intricate terrain,exhibits fewer TNTR,concurrently unveiling a significant presence of unnamed natural tourism resources.Crucially,administrative segmentation influences TNTR development,generating disparities in regional goals,developmental stages and intensities,and management approaches.In response to these variations,we advocate for strengthening the naming of the unnamed transboundary tourism resources,constructing a geographic database of TNTR for government and establishing a collaborative management mechanism based on TNTR database.Our research contributes to elucidating the intricate landscape of TNTR,offering insights for tailored governance strategies in the realm of cross-provincial tourism resource management.展开更多
Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,ther...Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,there is a lack of research on the optimization of the probing process.This study investigates how to optimize correlated parameters to maximize the SKG rate(SKGR)in the time-division duplex(TDD)mode.First,we build a probing model which includes the effects of transmitting power,the probing period,and the dimension of sample vectors.Based on the model,the analytical expression of the SKGR is given.Next,we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it.We conclude the SKGR monotonically increases as the transmitting power increases.Relevant mathematical proofs are given in this study.From the simulation results,increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick,which indicates the importance of optimizing the parameters related to the channel probing phase.展开更多
Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding s...Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.展开更多
This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in th...This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.展开更多
The population spatial distribution pattern and its evolving pattern play an important role in regional allocation of social resources and production factors, formulation of regional development plans, construction of...The population spatial distribution pattern and its evolving pattern play an important role in regional allocation of social resources and production factors, formulation of regional development plans, construction of a better life society, and promotion of regional economic development. Based on the resident population statistics data of Henan province from 2006 to 2021, with county as the basic study unit, the paper studies the spatial morphology characteristics and its evolution patterns of resident population distribution, by using spatial analysis methods such as population distribution center, standard deviation ellipse, and spatial auto correlation analysis. The results show that: the resident population spatial distribution shows unbalanced state, the population agglomeration areas mainly distribute in the northeast part and north part, where the resident population growth rate is significantly higher than other regions, over time, this trend is gradually becoming significant. The resident population distribution has a trend of centripetal concentration, with the degree and trend of centripetal gradually strengthening. The resident population distribution has obvious directional characteristics, but the significance is not high, the weighted resident population average center is approximately located at (4.13740˚N, 113.8935˚E), and the azimuth of the distribution axis is approximately 11.19˚. The population distribution has obvious agglomeration characteristics, with the built-up areas of Zhengzhou and Luoyang as their centers, where have a significant siphon effect on the surrounding population. The southern and southwestern regions in the province form a relatively stable belt area of Low-Low agglomeration areas.展开更多
Considerable economic losses and ecological damage can be caused by forest fi res,and compared to suppression,prevention is a much smarter strategy.Accordingly,this study focuses on developing a novel framework to ass...Considerable economic losses and ecological damage can be caused by forest fi res,and compared to suppression,prevention is a much smarter strategy.Accordingly,this study focuses on developing a novel framework to assess forest fi re risks and policy decisions on forest fi re management in China.This framework integrated deep learning algorithms,geographic information,and multisource data.Compared to conventional approaches,our framework featured timesaving,easy implementation,and importantly,the use of deep learning that vividly integrates various factors from the environment and human activities.Information on 96,594 forest fi re points from 2001 to 2019 was collected on Moderate Resolution Imaging Spectroradiometer(MODIS)fi re hotspots from 2001 to 2019 from NASA’s Fire Information Resource Management System.The information was classifi ed into factors such as topography,climate,vegetation,and society.The prediction of forest fi re risk was generated using a fully connected network model,and spatial autocorrelation used to analyze the spatial aggregation correlation of active fi re hotspots in the whole area of China.The results show that high accuracy prediction of fi re risks was achieved(accuracy 87.4%,positive predictive value 87.1%,sensitivity 88.9%,area under curve(AUC)94.1%).Based on this,it was found that Chinese forest fi re risk shows signifi cant autocorrelation and agglomeration both in seasons and regions.For example,forest fi re risk usually raises dramatically in spring and winter,and decreases in autumn and summer.Compared to the national average,Yunnan Province,Guangdong Province,and the Greater Hinggan Mountains region of Heilongjiang Province have higher fi re risks.In contrast,a large region in central China has been recognized as having a long-term,low risk of forest fi res.All forest risks in each region were recorded into the database and could contribute to the forest fi re prevention.The successful assessment of forest fi re risks in this study provides a comprehensive knowledge of fi re risks in China over the last 20 years.Deep learning showed its advantage in integrating multiple factors in predicting forest fi re risks.This technical framework is expected to be a feasible evaluation tool for the occurrence of forest fi res in China.展开更多
Seismometers of the InSight probe(Interior Exploration using Seismic Investigation,Geodesy and Heat Transport)currently operating on Mars have recorded not only seismic events but also high-frequency non-seismic perio...Seismometers of the InSight probe(Interior Exploration using Seismic Investigation,Geodesy and Heat Transport)currently operating on Mars have recorded not only seismic events but also high-frequency non-seismic periodic signals that appear to have been induced by variations in the Martian environment and the hardware.Here,we report an observation of a long-period signal with a dominant period of~20 s from Martian solar days(Sol)800 to Sol 1,000.This 20-s signal is detected mostly at quiet nighttime—from22:00 to 04:00 LMST(Local Mean Solar Time)—at the InSight landing site.The measurement of the particle motion suggests that this linearly polarized signal focuses on the horizontal plane with an angle of~30°from the north.By examining the temporal variation of the signal’s amplitude and polarization angle and its times of occurrence in relation to the planet’s atmospheric data,we suggest that this20-s signal may be relevant to wind and temperature variations on Mars.Furthermore,we study the possible influence of this 20-s signal on the noise autocorrelation and find that the stacked autocorrelograms can be quite different when the 20-s signal is present.展开更多
In the Anthropocene era,human activities have become increasingly complex and diversified.The natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization a...In the Anthropocene era,human activities have become increasingly complex and diversified.The natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization and industrialization as well as other intensified human activities,especially in arid and semi-arid areas.In the study,we chose the economic belt on the northern slope of the Tianshan Mountains(EBNSTM)in Xinjiang Uygur Autonomous Region of China as a case study.By collecting geographic data and statistical data from 2010 and 2020,we constructed an ecological resilience assessment model based on the ecosystem habitat quality(EHQ),ecosystem landscape stability(ELS),and ecosystem service value(ESV).Further,we analyzed the temporal and spatial variation characteristics of ecological resilience in the EBNSTM from 2010 to 2020 by spatial autocorrelation analysis,and explored its responses to climate change and human activities using the geographically weighted regression(GWR)model.The results showed that the ecological resilience of the EBNSTM was at a low level and increased from 0.2732 to 0.2773 during 2010–2020.The spatial autocorrelation analysis of ecological resilience exhibited a spatial heterogeneity characteristic of"high in the western region and low in the eastern region",and the spatial clustering trend was enhanced during the study period.Desert,Gobi and rapidly urbanized areas showed low level of ecological resilience,and oasis and mountain areas exhibited high level of ecological resilience.Climate factors had an important impact on ecological resilience.Specifically,average annual temperature and annual precipitation were the key climate factors that improved ecological resilience,while average annual evapotranspiration was the main factor that blocked ecological resilience.Among the human activity factors,the distance from the main road showed a negative correlation with ecological resilience.Both night light index and PM2.5 concentration were negatively correlated with ecological resilience in the areas with better ecological conditions,whereas in the areas with poorer ecological conditions,the correlations were positive.The research findings could provide a scientific reference for protecting the ecological environment and promoting the harmony and stability of the human-land relationship in arid and semi-arid areas.展开更多
Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two...Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries(Morocco and 35 of its partner member countries in the Organization for Economic Co-operation and Development(OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains(economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model by taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we found that β-convergence of regions is significant for well-being and three of its domains(economic, social, and governance). These convergences are made by a spatially autocorrelated error model(SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.展开更多
Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array tr...Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array transducers. Methods: When the beamforming SoS settings are adjusted to match the real tissue’s SoS, the ultrasound image at regions of interest will be in focus and the image quality will be optimal. Based on this principle, both a tissue-mimicking ultrasound phantom and normal human liver in vivo were used in this study. Ultrasound image was acquired using different SoS settings in beamforming channels ranging from 1420 m/sec to 1600 m/sec. Two regions of interest (ROIs) were selected. One was in a fully developed speckle region, while the other contained specular reflectors. We evaluated the image quality of these two ROIs in images acquired at different SoS settings in beamforming channels by using the normalized autocorrelation function (ACF) of the image data. The values of the normalized ACF at a specific lag as a function of the SoS setting were computed. Subsequently, the soft tissue’s SoS was determined from the SoS setting at the minimum value of the normalized ACF. Results: The value of the ACF as a function of the SoS setting can be computed for phantom and human liver images. SoS in soft tissue can be determined from the SoS setting at the minimum value of the normalized ACF. The estimation results show that the SoS of the tissue-mimicking phantom is 1460 m/sec, which is consistent with the phantom manufacturer’s specification, and the SoS of the normal human liver is 1540 m/sec, which is within the range of the SoS in a healthy human liver in vivo. Conclusion: Soft tissue’s SoS can be determined by analyzing the normalized ACF of ultrasound images. The method is based on searching for a minimum of the normalized ACF of ultrasound image data with a specific lag among different SoS settings in beamforming channels.展开更多
The tide level displays information about the state of the sea current and the tidal motion. The tide level of the southern coast of Japan Island is affected strongly by Kuroshio Current flowing in the western part of...The tide level displays information about the state of the sea current and the tidal motion. The tide level of the southern coast of Japan Island is affected strongly by Kuroshio Current flowing in the western part of North Pacific Ocean. When Kuroshio takes the straight path and flow along the Japan Islands, the tide level increases, and it is calculated from two tide level data observed at Kushimoto and Uragami in the southern part of Kii Peninsula. In contrast, the tide level decreases at the time when Kuroshio leaves from the Japan Islands. In this paper, the hourly tidal data are analyzed using the Autocorrelation Function (ACF) and the Mutual Information (MI) and the phase trajectories at first. We classify the results into 5 types of tidal motion. Each categorized type is investigated and characterized precisely using the mean tide level and the unit root test (ADF test) next. The frequency of the type having unstable tidal motion increases when the Kuroshio Current is non-meandering or in a transition state or the tide level is high, and the type shows a non-stationary process. On the other hand, when the Kuroshio Current meanders, the tidal motion tends to take a periodical and stable state and the motion is a stationary process. Though it is not frequent, we also discover a type of stationary and irregular tidal motion.展开更多
Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system (GIS) technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d'Observation de la Terre (SPOT-5) imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran's/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units (Moran's / varied from 0.49 to 0.89), irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity (CPI) as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.展开更多
Overgrazing has been considered one of the maj or causes that trigger shrub encroachment of grassland. Proliferation of shrubs in grassland is recognized as an important indicator of grassland degradation and desertif...Overgrazing has been considered one of the maj or causes that trigger shrub encroachment of grassland. Proliferation of shrubs in grassland is recognized as an important indicator of grassland degradation and desertification. In China, various conservation measures, including enclosures to reduce livestock grazing, have been taken to reverse the trend of grassland desertification, yet shrubs have been reported to increase in the grasslands over the past decades. In late 2007, we set up a 400-m-by-50-m exclosure in a long-term overgrazed temperate grassland in Inner Mongolia, with the ob- jective to quantify the spatiotemporal relationship between vegetation dynamics, soil variables, and grazing exclusion. Soil moisture was continuously monitored within the exclosure, and cover and aboveground biomass of the shrubs were measured inside the exclosure in 2007, 2009, 2010, 2012, and 2013, and outside the exclosure in 2012 and 2013. We found the average shrub cover and biomass significantly increased in the six years by 103 % and 120%, respectively. The result supported the hypothesis that releasing grazing pressure following long-term overgrazing tends to trigger shrub invasion into grassland. Our results, limited to a single gradient, suggest that any conservation measures with quick release of overgrazing pressure by enclosure or other similar means might do just the opposite to accelerate shrub en- croachment in grassland. The changes in vegetation cover and biomass were regressed on the temporal average of the soil moisture content by means of the generalized least square technique to quantify the effect of the spatial autocor- relation. The result indicates that the grass cover and biomass significantly increased with the top, but decreased with the bottom layer soil moisture. The shrub cover and biomass, on the other hand, decreased with the top, but increased with bottom soil moisture, although the regression coefficients for the shrubs were not statistically significant. Hence this study supports the two-layered soil model which assumes grasses and shrubs use belowground resources in dif- ferent depths.展开更多
Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cove...Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model (Autologistic model), and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves (AUC) was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.展开更多
A novel algorithm is proposed to solve the poor per- formance problem of the Tent chaos-based frequency modulation (FM) signal for range-Doppler imaging, which takes it into complex multi-segment system by increasin...A novel algorithm is proposed to solve the poor per- formance problem of the Tent chaos-based frequency modulation (FM) signal for range-Doppler imaging, which takes it into complex multi-segment system by increasing its segments. The simulation results show that the effectiveness of the proposed algorithm, as well as the performance of the improved Tent FM signal is obvious in a multipath or noise propagation environment.展开更多
The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) dis...The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.展开更多
The perfect sequences are so ideal that all out-of-phase autocorrelation coefficients are zero, and if the sequences are used as the coding modulating signal for the phase-modulated radar, there will be no interferenc...The perfect sequences are so ideal that all out-of-phase autocorrelation coefficients are zero, and if the sequences are used as the coding modulating signal for the phase-modulated radar, there will be no interference of side lobes theoretically. However, it has been proved that there are no binary perfect sequences of period 4 〈 n ≤ 12100. Hence, the almost perfect sequences with all out-of-phase autocorrelation coefficients as zero except one are of great practice in engineering. Currently, the cyclic difference set is one of most effective tools to analyze the binary sequences with perfect periodic autocorrelation function. In this article, two characteristic formulas corresponding to the autocorrelation and symmetric structure of almost perfect sequences are calculated respectively. All almost perfect sequences with period n, which is a multiple of 4, can be figured out by the two formulas. Several almost perfect sequences with different periods have been hunted by the program based on the two formulas and then applied to the simulation program and practical application for ionospheric sounding.展开更多
Accurate prediction of stem diameter is an important prerequisite of forest management.In this study,an appropriate stem taper function was developed for upper stem diameter estimation of white birch(Betula platyphyll...Accurate prediction of stem diameter is an important prerequisite of forest management.In this study,an appropriate stem taper function was developed for upper stem diameter estimation of white birch(Betula platyphylla Sukaczev)in ten sub-regions of the Daxing’an Mountains,northeast China.Three commonly used taper functions were assessed using a diameter and height dataset comprising 1344 trees.A first-order continuous-time error structure accounted for the inherent autocorrelation.The segmented model of Max and Burkhart(For Sci 22:283–289,1976.https://doi.org/10.1093/fores tscie nce/22.3.283)and the variable exponent taper function of Kozak(For Chron 80:507–515,2004.https://doi.org/10.5558/tfc80507-4)described the data accurately.Owing to its lower multicollinearity,the Max and Burkhart(1976)model is recommended for diameter estimation at specific heights along the stem for the ten sub-regions.After comparison,the Max and Burkhart(1976)model was refitted using nonlinear mixed-effects techniques.Mixed-effects models would be used only when additional upper stem diameter measurements are available for calibration.Differences in region-specific taper functions were indicated by the method of the non-linear extra sum of squares.Therefore,the particular taper function should be adjusted accordingly for each sub-region in the Daxing’an Mountains.展开更多
基金Project supported by the Science and Technology Project of Guangdong(Grant No.2020B010190001)the National Natural Science Foundation of China(Grant No.11974119)+1 种基金the Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2016ZT06C594)the National Key R&D Program of China(Grant No.2018YFA0306200)。
文摘We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation measurement configuration,without requiring a specific form of the incident pulse function.A rigorous solution of the nonlinear coupled wave equation is obtained in the time domain and expressed in a general analytical form.The global model fully accounts for the nonlinear interaction and propagation effects within nonlinear crystals,which are not captured by the classical local model.To assess the performance of the global model compared to the classic local model,we investigate the autocorrelation signals obtained from both models for different incident pulse waveforms and different full-widthes at half-maximum(FWHMs).When the incident pulse waveform is Lorentzian with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 399.9 fs,while the classic local model predicts an FWHM of 331.4 fs.The difference between the two models is 68.6 fs,corresponding to an error of 17.2%.Similarly,for a sech-type incident pulse with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 343.9 fs,while the local model predicts an FWHM of 308.8 fs.The difference between the two models is 35.1 fs,with an error of 10.2%.We further examine the behavior of the models for Lorentzian pulses with FWHMs of 100 fs,200 fs and 500 fs.The differences between the global and local models are 17.1 fs,68.6 fs and 86.0 fs,respectively,with errors approximately around 17%.These comparative analyses clearly demonstrate the superior accuracy of the global model in intensity autocorrelation modeling.
基金funded by the by the Youth Program of the National Natural Science Foundation of China(Grants No.42001243,and 42201311)the Humanities and Social Science Project of the Ministry of Education,China(Grants No.20YJC630212,and 22YJCZH071)+1 种基金the Youth Program of the Natural Science Foundation of Shandong Province,China(Grants No.ZR2020QD008)Frontier Science Research Support Program,Management College,OUC(Grants No.MCQYZD2305,and MCQYYB2309).
文摘Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensive database of transboundary natural tourism resources(TNTR)through amalgamation of diverse data sources.Utilizing the Getis-Ord Gi^(*),kernel density estimation,and geographical detectors,we scrutinize the spatial patterns of TNTR,focusing on both named and unnamed entities,while exploring the influencing factors.Our findings reveal 7883 identified TNTR in China,with mountain tourism resources emerging as the predominant type.Among provinces,Hunan boasts the highest count,while Shanghai exhibits the lowest.Southern China demonstrates a pronounced clustering trend in TNTR distribution,with the spatial arrangement of biological landscapes appearing more random compared to geological and water landscapes.Western China,characterized by intricate terrain,exhibits fewer TNTR,concurrently unveiling a significant presence of unnamed natural tourism resources.Crucially,administrative segmentation influences TNTR development,generating disparities in regional goals,developmental stages and intensities,and management approaches.In response to these variations,we advocate for strengthening the naming of the unnamed transboundary tourism resources,constructing a geographic database of TNTR for government and establishing a collaborative management mechanism based on TNTR database.Our research contributes to elucidating the intricate landscape of TNTR,offering insights for tailored governance strategies in the realm of cross-provincial tourism resource management.
基金supported in part by the national natural science foundation of China (NSFC) under Grant61871193in part by the R&D Program of key science and technology fields in Guangdong province under Grant 2019B090912001in part by the Guangzhou Key Field R&D Program under Grant 202206030005
文摘Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,there is a lack of research on the optimization of the probing process.This study investigates how to optimize correlated parameters to maximize the SKG rate(SKGR)in the time-division duplex(TDD)mode.First,we build a probing model which includes the effects of transmitting power,the probing period,and the dimension of sample vectors.Based on the model,the analytical expression of the SKGR is given.Next,we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it.We conclude the SKGR monotonically increases as the transmitting power increases.Relevant mathematical proofs are given in this study.From the simulation results,increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick,which indicates the importance of optimizing the parameters related to the channel probing phase.
基金Under the auspices of the National Social Science Found of China(No.21XGL019)Hainan Provincial Natural Science Foundation of China(No.421RC1034)Professor/Doctor Research Foundation of Huizhou University(No.2022JB080)。
文摘Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.
文摘This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.
文摘The population spatial distribution pattern and its evolving pattern play an important role in regional allocation of social resources and production factors, formulation of regional development plans, construction of a better life society, and promotion of regional economic development. Based on the resident population statistics data of Henan province from 2006 to 2021, with county as the basic study unit, the paper studies the spatial morphology characteristics and its evolution patterns of resident population distribution, by using spatial analysis methods such as population distribution center, standard deviation ellipse, and spatial auto correlation analysis. The results show that: the resident population spatial distribution shows unbalanced state, the population agglomeration areas mainly distribute in the northeast part and north part, where the resident population growth rate is significantly higher than other regions, over time, this trend is gradually becoming significant. The resident population distribution has a trend of centripetal concentration, with the degree and trend of centripetal gradually strengthening. The resident population distribution has obvious directional characteristics, but the significance is not high, the weighted resident population average center is approximately located at (4.13740˚N, 113.8935˚E), and the azimuth of the distribution axis is approximately 11.19˚. The population distribution has obvious agglomeration characteristics, with the built-up areas of Zhengzhou and Luoyang as their centers, where have a significant siphon effect on the surrounding population. The southern and southwestern regions in the province form a relatively stable belt area of Low-Low agglomeration areas.
基金funded by the Key R&D Projects in Hainan Province (ZDYF2021SHFZ256)Natural Science Foundation of Hainan University,grant numbers KYQD (ZR)21,115
文摘Considerable economic losses and ecological damage can be caused by forest fi res,and compared to suppression,prevention is a much smarter strategy.Accordingly,this study focuses on developing a novel framework to assess forest fi re risks and policy decisions on forest fi re management in China.This framework integrated deep learning algorithms,geographic information,and multisource data.Compared to conventional approaches,our framework featured timesaving,easy implementation,and importantly,the use of deep learning that vividly integrates various factors from the environment and human activities.Information on 96,594 forest fi re points from 2001 to 2019 was collected on Moderate Resolution Imaging Spectroradiometer(MODIS)fi re hotspots from 2001 to 2019 from NASA’s Fire Information Resource Management System.The information was classifi ed into factors such as topography,climate,vegetation,and society.The prediction of forest fi re risk was generated using a fully connected network model,and spatial autocorrelation used to analyze the spatial aggregation correlation of active fi re hotspots in the whole area of China.The results show that high accuracy prediction of fi re risks was achieved(accuracy 87.4%,positive predictive value 87.1%,sensitivity 88.9%,area under curve(AUC)94.1%).Based on this,it was found that Chinese forest fi re risk shows signifi cant autocorrelation and agglomeration both in seasons and regions.For example,forest fi re risk usually raises dramatically in spring and winter,and decreases in autumn and summer.Compared to the national average,Yunnan Province,Guangdong Province,and the Greater Hinggan Mountains region of Heilongjiang Province have higher fi re risks.In contrast,a large region in central China has been recognized as having a long-term,low risk of forest fi res.All forest risks in each region were recorded into the database and could contribute to the forest fi re prevention.The successful assessment of forest fi re risks in this study provides a comprehensive knowledge of fi re risks in China over the last 20 years.Deep learning showed its advantage in integrating multiple factors in predicting forest fi re risks.This technical framework is expected to be a feasible evaluation tool for the occurrence of forest fi res in China.
基金supported by B-type Strategic Priority Program of the Chinese Academy of Sciences,Grant XDB41000000National Natural Science Foundation of China 42241117.
文摘Seismometers of the InSight probe(Interior Exploration using Seismic Investigation,Geodesy and Heat Transport)currently operating on Mars have recorded not only seismic events but also high-frequency non-seismic periodic signals that appear to have been induced by variations in the Martian environment and the hardware.Here,we report an observation of a long-period signal with a dominant period of~20 s from Martian solar days(Sol)800 to Sol 1,000.This 20-s signal is detected mostly at quiet nighttime—from22:00 to 04:00 LMST(Local Mean Solar Time)—at the InSight landing site.The measurement of the particle motion suggests that this linearly polarized signal focuses on the horizontal plane with an angle of~30°from the north.By examining the temporal variation of the signal’s amplitude and polarization angle and its times of occurrence in relation to the planet’s atmospheric data,we suggest that this20-s signal may be relevant to wind and temperature variations on Mars.Furthermore,we study the possible influence of this 20-s signal on the noise autocorrelation and find that the stacked autocorrelograms can be quite different when the 20-s signal is present.
基金supported by the Third Xinjiang Scientific Expedition Program (2021xjkk0905).
文摘In the Anthropocene era,human activities have become increasingly complex and diversified.The natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization and industrialization as well as other intensified human activities,especially in arid and semi-arid areas.In the study,we chose the economic belt on the northern slope of the Tianshan Mountains(EBNSTM)in Xinjiang Uygur Autonomous Region of China as a case study.By collecting geographic data and statistical data from 2010 and 2020,we constructed an ecological resilience assessment model based on the ecosystem habitat quality(EHQ),ecosystem landscape stability(ELS),and ecosystem service value(ESV).Further,we analyzed the temporal and spatial variation characteristics of ecological resilience in the EBNSTM from 2010 to 2020 by spatial autocorrelation analysis,and explored its responses to climate change and human activities using the geographically weighted regression(GWR)model.The results showed that the ecological resilience of the EBNSTM was at a low level and increased from 0.2732 to 0.2773 during 2010–2020.The spatial autocorrelation analysis of ecological resilience exhibited a spatial heterogeneity characteristic of"high in the western region and low in the eastern region",and the spatial clustering trend was enhanced during the study period.Desert,Gobi and rapidly urbanized areas showed low level of ecological resilience,and oasis and mountain areas exhibited high level of ecological resilience.Climate factors had an important impact on ecological resilience.Specifically,average annual temperature and annual precipitation were the key climate factors that improved ecological resilience,while average annual evapotranspiration was the main factor that blocked ecological resilience.Among the human activity factors,the distance from the main road showed a negative correlation with ecological resilience.Both night light index and PM2.5 concentration were negatively correlated with ecological resilience in the areas with better ecological conditions,whereas in the areas with poorer ecological conditions,the correlations were positive.The research findings could provide a scientific reference for protecting the ecological environment and promoting the harmony and stability of the human-land relationship in arid and semi-arid areas.
文摘Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries(Morocco and 35 of its partner member countries in the Organization for Economic Co-operation and Development(OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains(economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model by taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we found that β-convergence of regions is significant for well-being and three of its domains(economic, social, and governance). These convergences are made by a spatially autocorrelated error model(SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.
文摘Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array transducers. Methods: When the beamforming SoS settings are adjusted to match the real tissue’s SoS, the ultrasound image at regions of interest will be in focus and the image quality will be optimal. Based on this principle, both a tissue-mimicking ultrasound phantom and normal human liver in vivo were used in this study. Ultrasound image was acquired using different SoS settings in beamforming channels ranging from 1420 m/sec to 1600 m/sec. Two regions of interest (ROIs) were selected. One was in a fully developed speckle region, while the other contained specular reflectors. We evaluated the image quality of these two ROIs in images acquired at different SoS settings in beamforming channels by using the normalized autocorrelation function (ACF) of the image data. The values of the normalized ACF at a specific lag as a function of the SoS setting were computed. Subsequently, the soft tissue’s SoS was determined from the SoS setting at the minimum value of the normalized ACF. Results: The value of the ACF as a function of the SoS setting can be computed for phantom and human liver images. SoS in soft tissue can be determined from the SoS setting at the minimum value of the normalized ACF. The estimation results show that the SoS of the tissue-mimicking phantom is 1460 m/sec, which is consistent with the phantom manufacturer’s specification, and the SoS of the normal human liver is 1540 m/sec, which is within the range of the SoS in a healthy human liver in vivo. Conclusion: Soft tissue’s SoS can be determined by analyzing the normalized ACF of ultrasound images. The method is based on searching for a minimum of the normalized ACF of ultrasound image data with a specific lag among different SoS settings in beamforming channels.
文摘The tide level displays information about the state of the sea current and the tidal motion. The tide level of the southern coast of Japan Island is affected strongly by Kuroshio Current flowing in the western part of North Pacific Ocean. When Kuroshio takes the straight path and flow along the Japan Islands, the tide level increases, and it is calculated from two tide level data observed at Kushimoto and Uragami in the southern part of Kii Peninsula. In contrast, the tide level decreases at the time when Kuroshio leaves from the Japan Islands. In this paper, the hourly tidal data are analyzed using the Autocorrelation Function (ACF) and the Mutual Information (MI) and the phase trajectories at first. We classify the results into 5 types of tidal motion. Each categorized type is investigated and characterized precisely using the mean tide level and the unit root test (ADF test) next. The frequency of the type having unstable tidal motion increases when the Kuroshio Current is non-meandering or in a transition state or the tide level is high, and the type shows a non-stationary process. On the other hand, when the Kuroshio Current meanders, the tidal motion tends to take a periodical and stable state and the motion is a stationary process. Though it is not frequent, we also discover a type of stationary and irregular tidal motion.
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system (GIS) technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d'Observation de la Terre (SPOT-5) imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran's/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units (Moran's / varied from 0.49 to 0.89), irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity (CPI) as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.
基金supported by the National Science Foundations of China with Grant No.41171445
文摘Overgrazing has been considered one of the maj or causes that trigger shrub encroachment of grassland. Proliferation of shrubs in grassland is recognized as an important indicator of grassland degradation and desertification. In China, various conservation measures, including enclosures to reduce livestock grazing, have been taken to reverse the trend of grassland desertification, yet shrubs have been reported to increase in the grasslands over the past decades. In late 2007, we set up a 400-m-by-50-m exclosure in a long-term overgrazed temperate grassland in Inner Mongolia, with the ob- jective to quantify the spatiotemporal relationship between vegetation dynamics, soil variables, and grazing exclusion. Soil moisture was continuously monitored within the exclosure, and cover and aboveground biomass of the shrubs were measured inside the exclosure in 2007, 2009, 2010, 2012, and 2013, and outside the exclosure in 2012 and 2013. We found the average shrub cover and biomass significantly increased in the six years by 103 % and 120%, respectively. The result supported the hypothesis that releasing grazing pressure following long-term overgrazing tends to trigger shrub invasion into grassland. Our results, limited to a single gradient, suggest that any conservation measures with quick release of overgrazing pressure by enclosure or other similar means might do just the opposite to accelerate shrub en- croachment in grassland. The changes in vegetation cover and biomass were regressed on the temporal average of the soil moisture content by means of the generalized least square technique to quantify the effect of the spatial autocor- relation. The result indicates that the grass cover and biomass significantly increased with the top, but decreased with the bottom layer soil moisture. The shrub cover and biomass, on the other hand, decreased with the top, but increased with bottom soil moisture, although the regression coefficients for the shrubs were not statistically significant. Hence this study supports the two-layered soil model which assumes grasses and shrubs use belowground resources in dif- ferent depths.
基金National High Technology Research and Development Program of China, No.2008AA12Z106 National Natural Science Foundation of China, No.40801166 No.40771198
文摘Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model (Autologistic model), and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves (AUC) was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.
基金supported by the National Natural Science Foundation of China (610320106110117211076006)
文摘A novel algorithm is proposed to solve the poor per- formance problem of the Tent chaos-based frequency modulation (FM) signal for range-Doppler imaging, which takes it into complex multi-segment system by increasing its segments. The simulation results show that the effectiveness of the proposed algorithm, as well as the performance of the improved Tent FM signal is obvious in a multipath or noise propagation environment.
基金supported by Science and Technology Major Project of the Hall of Science and Technology of Fujian (No. 2012NZ0001)the Project of National Natural Science Fund of China (No.30671664)
文摘The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.
基金This poject was supported by the National Natural Science Foundation of China (40474066).
文摘The perfect sequences are so ideal that all out-of-phase autocorrelation coefficients are zero, and if the sequences are used as the coding modulating signal for the phase-modulated radar, there will be no interference of side lobes theoretically. However, it has been proved that there are no binary perfect sequences of period 4 〈 n ≤ 12100. Hence, the almost perfect sequences with all out-of-phase autocorrelation coefficients as zero except one are of great practice in engineering. Currently, the cyclic difference set is one of most effective tools to analyze the binary sequences with perfect periodic autocorrelation function. In this article, two characteristic formulas corresponding to the autocorrelation and symmetric structure of almost perfect sequences are calculated respectively. All almost perfect sequences with period n, which is a multiple of 4, can be figured out by the two formulas. Several almost perfect sequences with different periods have been hunted by the program based on the two formulas and then applied to the simulation program and practical application for ionospheric sounding.
基金fi nancially supported by the National Natural Science Foundation of China(31570624)Applied Technology Research and Development Plan Project of Heilongjiang Province(GA19C006)Fundamental Research Funds for Central Universities(2572019CP15).
文摘Accurate prediction of stem diameter is an important prerequisite of forest management.In this study,an appropriate stem taper function was developed for upper stem diameter estimation of white birch(Betula platyphylla Sukaczev)in ten sub-regions of the Daxing’an Mountains,northeast China.Three commonly used taper functions were assessed using a diameter and height dataset comprising 1344 trees.A first-order continuous-time error structure accounted for the inherent autocorrelation.The segmented model of Max and Burkhart(For Sci 22:283–289,1976.https://doi.org/10.1093/fores tscie nce/22.3.283)and the variable exponent taper function of Kozak(For Chron 80:507–515,2004.https://doi.org/10.5558/tfc80507-4)described the data accurately.Owing to its lower multicollinearity,the Max and Burkhart(1976)model is recommended for diameter estimation at specific heights along the stem for the ten sub-regions.After comparison,the Max and Burkhart(1976)model was refitted using nonlinear mixed-effects techniques.Mixed-effects models would be used only when additional upper stem diameter measurements are available for calibration.Differences in region-specific taper functions were indicated by the method of the non-linear extra sum of squares.Therefore,the particular taper function should be adjusted accordingly for each sub-region in the Daxing’an Mountains.