共查询到18条相似文献，搜索用时 31 毫秒
1.
LUMBRES Roscinto Ian Canicosa LEE Young Jin CHOI Hyung Soon KIM Sung Yong JANG Mi Na ABINO Azyleah Caizares SEO Yeon Ok KIM Chan Soo PARK Jung Hwan 《山地科学学报》2014,11(2):442-448
This study was conducted to fit the diameter-height data of Quercusglaucain Jeju Island, South Korea to the four commonly used stem taper equations andto evaluate the performance of the four stem taper models using four statistical criteria： Fit index （FI）, root mean square error （RMSE）, bias （）,and absolute mean difference （AMD）. Results showed that the Kozak02stem taper equation provided the best FI（0.9847）, RMSE（1.5745）,（-0.0030 cm） and AMD （1.0990 cm） whileMax and Burkhart model had the poorest performance among the four stem taper models based on the four evaluation statistics （FI ： 0.9793,RMSE ： 1.8272, ： 0.3040 cm and AMD ： 1.3060 cm）. These stem taper equations can serve as a useful tool for forest managers in estimating the diameter outside bark at any given height, merchantable stem volumes and total stem volumesof the standing trees of Quercusglaucain theGotjawal forests located in Mount Halla, Jeju Island, South Korea. 相似文献
2.
This study was conducted to evaluate the performance of six stem taper models on four tropical tree species, namely Celtis luzonica (Magabuyo), Diplodiscus paniculatus (Balobo), Parashorea malaanonan (Bagtikan), and Swietenia macrophylla (Mahogany) in Mount Makiling Forest Reserve (MMFR), Philippines using fit statistics and lack-of-fit statistics. Four statistical criteria were used in this study, including the standard error of estimate (SEE), coefficient of determination (R 2), mean bias \(( \bar E )\), and absolute mean difference (AMD). For the lack-offit statistics, SEE, \(\bar E\) and AMD were determined in different relative height classes. The results indicated that the Kozako2 stem taper model offered the best fit for the four tropical species in most statistics. The Kozako2 model also consistently provided the best performance in the lack-of-fit statistics with the best SEE, \(\bar E\) and AMD in most of the relative height classes. These stem taper equations could help forest managers and researchers better estimate the diameter of the outside bark with any given height, merchantable stem volumes and total stem volumes of standing trees belonging to the four species of the tropical forest in MMFR. 相似文献
3.
Compatible taper and stem volume equations for Larix kaempferi(Japanese larch) species of South Korea 总被引：1，自引：0，他引：1
《山地科学学报》2017,(7)
In this study, compatible taper and stem volume equations were developed for Larix kaempferi species of South Korea. The dataset was split into two groups: 80% of the data were used in model fitting and the remaining 20% were used for validation. The compatible MB76 equations were used to predict the diameter outside bark to a specific height, the height to a specific diameter and the stem volume of the species. The result of the stem volume analysis was compared with the existing stem volume model of Larix kaempferi species of South Korea which was developed by the Korea Forest Research Institute and with a simple volume model that was developed with fitting dataset in this study. The compatible model provided accurate prediction of the total stem volume when compared to the existing stem volume model and with a simple volume model. It is concluded that the compatible taper and stem volume equations are more convenient to use and therefore it is recommended to be applied in the Larix kaempferi species of South Korea. 相似文献
4.
In this study, compatible taper and stem volume equations were developed for Larix kaempferi species of South Korea. The dataset was split into two groups: 80% of the data were used in model fitting and the remaining 20% were used for validation. The compatible MB76 equations were used to predict the diameter outside bark to a specific height, the height to a specific diameter and the stem volume of the species. The result of the stem volume analysis was compared with the existing stem volume model of Larix kaempferi species of South Korea which was developed by the Korea Forest Research Institute and with a simple volume model that was developed with fitting dataset in this study. The compatible model provided accurate prediction of the total stem volume when compared to the existing stem volume model and with a simple volume model. It is concluded that the compatible taper and stem volume equations are more convenient to use and therefore it is recommended to be applied in the Larix kaempferi species of South Korea. 相似文献
5.
Kamae P. Anacioco Judy Ann L. Gorio Mary Relia S. Padsico Roscinto Ian C. Lumbres Nova D. Doyog Young Jin Lee 《山地科学学报》2018,15(11):2422-2432
The study was conducted to develop height-diameter at breast height (HT-DBH) models for Alnus japonica in La Trinidad, Benguet, Philippines and evaluate their predictive capability. The six widely used nonlinear growth models that were selected in this study were the Chapman-Richards, Schnute, Modified logistic, Korf/Lundqvist, Weibull and Exponential. A total of 208 Alnus japonica trees were measured using standard diameter tape for DBH (1.3 m above the ground) and Vertex and transponder was used for the total height measurement. The performance of the developed models were evaluated using the fit statistics including coefficient of determination (R2), root mean square error (RMSE), mean bias (ē), absolute mean difference (AMD), and Akaike Information Criterion (AIC). The lack-of-fit statistics was also performed for further evaluation of the performance of the models. Based on the evaluation criteria, all six models were able to determine the DBH-height relationships and fitted the data well. Using the rank analysis, the Weibull HT-DBH model had the best performance among the six commonly used nonlinear growth models. The results of this study will help forest managers especially in La Trinidad, Benguet to easily predict the total height using the Weibull model for Alnus japonica utilizing the DBH as the predicting variable. 相似文献
6.
Ulvacean green seaweeds are common worldwide; they formed massive green tides in the Yellow Sea in recent years, which caused
marine ecological problems as well as a social issue. We investigated two major genera of the Ulvaceae, Ulva and Enteromorpha, and collected the plastid rbcL and nuclear ITS sequences of specimens of the genera in two sides of the Yellow Sea and analyzed them. Phylogenetic trees
of rbcL data show the occurrence of five species of Enteromorpha (E. compressa, E. flexuosa, E. intestinalis, E. linza and E. prolifera) and three species of Ulva (U. pertusa, U. rigida and U. ohnoi). However, we found U. ohnoi, which is known as a subtropical to tropical species, at two sites on Jeju Island, Korea. Four ribotypes in partial sequences
of 5.8S rDNA and ITS2 from E. compressa were also found. Ribotype network analysis revealed that the common ribotype, occurring in China, Korea and Europe, is connected
with ribotypes from Europe and China/Japan. Although samples of the same species were collected from both sides of the Yellow
Sea, intraspecific genetic polymorphism of each species was low among samples collected worldwide. 相似文献
7.
The performance of six statistical approaches,which can be used for selection of the best model to describe the growth of individual fish,was analyzed using simulated and real length-at-age data.The six approaches include coefficient of determination(R2),adjusted coefficient of determination(adj.-R2),root mean squared error(RMSE),Akaike's information criterion(AIC),bias correction of AIC(AICc) and Bayesian information criterion(BIC).The simulation data were generated by five growth models with different num... 相似文献
8.
Spatial downscaling methods are widely used for the production of bioclimatic variables(e.g. temperature and precipitation) in studies related to species ecological niche and drainage basin management and planning. This study applied three different statistical methods, i.e. the moving window regression(MWR), nonparametric multiplicative regression(NPMR), and generalized linear model(GLM), to downscale the annual mean temperature(Bio1) and annual precipitation(Bio12) in central Iran from coarse scale(1 km × 1 km) to fine scale(250 m ×250 m). Elevation, aspect, distance from sea and normalized difference vegetation index(NDVI) were used as covariates to create downscaled bioclimatic variables. Model assessment was performed by comparing model outcomes with observational data from weather stations. Coefficients of determination(R2), bias, and root-mean-square error(RMSE) were used to evaluate models and covariates. The elevation could effectively justify the changes in bioclimatic factors related to temperature and precipitation. Allthree models could downscale the mean annual temperature data with similar R2, RMSE, and bias values. The MWR had the best performance and highest accuracy in downscaling annual precipitation(R2=0.70; RMSE=123.44). In general, the two nonparametric models, i.e. MWR and NPMR, can be reliably used for the downscaling of bioclimatic variables which have wide applications in species distribution modeling. 相似文献
9.
Azyleah Cañizares Abino Sung Yong Kim Roscinto Ian Canicosa Lumbres Mi Na Jang Ho Joong Youn Ki Hyung Park Young Jin Lee 《山地科学学报》2016,13(5):822-830
This study was carried out to determine the performance of percentile-based Weibull diameter distribution model for Pinus thunbergii stands thriving along the eastern coast of South Korea. The parameter recovery technique was used to estimate the three parameters of the Weibull model. The analysis demonstrated satisfactory results based on the following test statistics for the principal percentile models: fit index (FI) range from 0.501 (minimum diameter) to 0.932 (50th diameter percentiles) and root mean square error (RMSE) range from 0.112 (quadratic mean diameter) to 3.572 (minimum diameter). The developed model was further evaluated by determining the mean bias (ē) in trees per ha (TPH) for each diameter class, and the results showed highest over-prediction in the 20 cm, and under-prediction in the 16 cm and 24 cm diameter classes. The goodness of fit tested by Kolmogorov-Smirnov (KS) test showed no significant differences (p>0.05) between the observed and predicted diameter distributions for almost all plots. Using site index and aboveground biomass (AGB) models developed for P. thunbergii in South Korea, a model to predict the AGB per ha for each diameter class and subsequently the total AGB of the stand was created. An application guide was also created, which will serve as a decision-support tool for forest managers in quantifying the future total AGB in P. thunbergii stands located in the eastern coast of South Korea and, subsequently, the quantification of potential carbon stocks aside from being a vital input in designing efficient management and protection strategies for these stands. 相似文献
10.
Study of the distribution and migration of the common squid,Todarodes pacificus Steenstrup,basedon the index of important fishing ground(P) and fisheries statistics on the Yellow Sea and northern EastChina Sea during 1980—1991 showed that:1.Its catch in the fishing period(June to November) is 91.77% of the annual yield.The fishingground distributes over the northem and middle Yel1ow Sea and adjacent area of the Changjiang Estuary.2. It over-winters in the northem East China Sea and waters adjacent to Goto Island from De-cember to February and spawns in waters near Haijiao Is1and and west of Kyushu. The main stock mi-grates along 123°30′E to the ChangJiang Estuary, Haizhou Bay. offsea from Shidao to Qingdao,mideastern Yellow Sea, and offsea Weihai and Haiyang Island succesively for feeding after April. The sur-plus stock migrates again to the wintering ground in December.3.The favorable feeding temperature is 6-23℃(optimum of l3-20℃ in the Changjiang Estua-ry and 7-13℃ in the northern and middle Yel 相似文献
11.
以水汽辐射计（WVR）精确测定的天顶方向延迟值作为参考,评估Saastamoinen、GPT2、EGNOS、UNB3M四种常用对流层模型在上海地区的改正精度;并将WVR观测值及以上4种对流层模型计算的对流层延迟值作为真值应用到GNSS精密单点定位（PPP）中,评估其对定位精度的影响。比较发现,GPT2模型的对流层改正精度比其余3种要好,其天顶干延迟（ZHD）的偏差均值与中误差分别为-0.11 cm、±0.75 cm,天顶湿延迟（ZWD）的平均偏差与中误差分别为-2.34 cm、±7.67 cm;和传统的PPP结果相比,采用WVR对流层观测值的定位精度提高了16%。 相似文献
12.
乘客出行需求预测是智能交通系统的组成部分,准确的出行需求预测,对于车辆调度具有重要的意义;然而现有的预测方法无法准确的挖掘其潜在的时空相关性,且大都忽略历史流入量对出行需求的影响。为了进一步挖掘时空大数据中的时空特性及提升模型预测乘客出行需求的精度,本文提出了一种乘客出租出行需求短时预测CLAB(Conv-LSTM Attention BiLSTM)模型。CLAB模型设置了3个模块分别为基于注意力机制的Conv-LSTM模块和2个BiLSTM模块,基于注意力机制的Conv-LSTM模块提取临近时刻乘客出行需求量中的空间特征和短时时间特征,其中注意力机制能自动分配不同的权重来判别不同时间的需求量序列重要性;为了探索长期时间特征,用2个BiLSTM模块来提取历史流入量序列时间特征和日乘客需求量序列的时间特征。采用厦门岛的网约车和巡游车的订单数据进行实验,结果表明：(1) CLAB模型更适用于使用30 min历史数据预测未来5 min短时乘客出行需求;(2)与基准预测模型相比,CLAB模型的整体的效果误差更低,具有更好的预测效果,CLAB模型比CNN-LSTM、LSTM、BiLSTM、CNN... 相似文献
13.
为了合理有效地分析和挖掘海洋涡旋移动数据中的规律和模式,本文以基于空间交互性流聚类的区域化方法为基础,提出了一种海洋涡旋移动特征的网格区域化方法。该方法以网格为统计单元,对涡旋移动数据进行组织,通过图论模型构建海洋涡旋的移动网络图,然后采用基于平均邻接的层次聚类和基于模块度的划分2个步骤,实现涡旋移动特征的区域划分。基于该算法,对1992-2011年中国南海海洋涡旋移动数据进行算法实验,结果表明,南海海洋涡旋按照其移动频繁性特征可分为越南东南部（R1）、越南东部-巴拉望岛（R2）、南海北部（R3）3个区域。其中,R1区域包含了南海西南部深海盆地区的涡旋活跃条带;R2区域体现了南海中部涡旋向西移动的活动规律;R3区域则包含了南海北部东北-西南走向条带。3个区域内冷涡和暖涡具有明显的季节性变化特征：R1和R3区域冷暖涡变化相似,暖涡在夏秋季移动最多,冬季最少,而冷涡则相反,夏秋季移动最少,随后逐渐增加,并在春季达到峰值;R2区域暖涡在春季移动最多,而冷涡在夏冬移动最多,春秋移动相对较弱。 相似文献
14.
In watersheds that have not sufficient meteorological and hydrometric data for simulating rainfall-runoff events, using geomorphologic and geomorphoclimatic characteristics of watershed is a conventional method for the simulation. A number of rainfall-runoff models utilize these characteristics such as Nash-IUH, Clark-IUH, Geomorphologic Instantaneous Unit Hydrograph(GIUH), Geomorphoclimatic Instantaneous Unit Hydrograph(GcIUH), GIUH-based Nash(GIUH-Nash) and GcIUH-based Clark(GcIUH-Clark). But all these models are not appropriate for mountainous watersheds. Therefore, the objective of this study is to select the best of them for the simulation. The procedure of this study is: a) selecting appropriate rainfall-runoff events for calibration and validation of six hybrid models, b) distinguishing the best model based on different performance criteria(Percentage Error in Volume(PEV); Percentage Error in Peak(PEP); Percentage Error in Time to Peak(PETP); Root Mean Square Error(RMSE) and Nash-Sutcliffe model efficiency coefficient(ENS)), c) Sensitivity analysis for determination of the most effective parameter at each model, d) Uncertainty determination of different parameters in each model and confirmation of the obtained results by application of the performance criteria. For application of this procedure, the Navrood watershed in the north of Iran as a mountainous watershed has been considered. The results showed that the ClarkIUH and GcIUH-Clark are suitable models for simulation of flood hydrographs, while other models cannot simulate flood hydrographs appropriately. The sensitivity analysis shows that the most sensitive parameters are the infiltration constant rate and time of concentration in the Clark-IUH model. Also, the most sensitive parameters include the infiltration constant rate and storage coefficient in the GcIUHClark model. The Clark-IUH and GcIUH-Clark models are more sensitive to their parameters. The Latin Hypercube Sampling(LHS) on Monte Carlo(MC) simulation method was used for evaluation of uncertainty of data in rainfall-runoff models. In this method 500 sets of data values are produced and then the peak discharge of flood hydrographs for each produced data set is simulated with rainfall-runoff models. The uncertainty of data changes the value of simulated peak discharge of flood hydrograph. The uncertainty analysis shows that the observed peak discharges of different rainfall-runoff events are within the range of values of simulated by the six hybrid rainfall-runoff models and IUH that inputs of these models were the produced data sets. The range of the produced peak discharge of flood hydrographs by the Clark-IUH and GcIUH-Clark models is wider than those of other models. 相似文献
15.
基于神经网络模型的干旱区绿洲土壤盐渍化评价分析 总被引：1，自引：0，他引：1
土壤盐渍化严重制约了农业可持续发展和生态安全,土壤盐渍化的精确评价分析,对土壤盐渍化的改善和治理具有重要的意义。本文以新疆焉耆盆地为研究对象,Landsat8 OLI遥感影像和实测采样数据相结合,提取地下水埋深（GD）、盐分指数（SI）、地表蒸散量（SET）和改进型温度植被干旱指数（MTVDI）建立了土壤盐渍化评价模型。结果表明：①结合野外实测土壤盐分数据,对BP神经网络模型进行训练。最终以最优的4-4-1结构的3层BP神经网模型对研究区土壤盐渍化进行了预测（R2=0.864,RMSE=0.569）。相比传统多元线性回归模型（R2=0.741,RMSE=0.767）,神经网络模型对土壤盐渍化的预测精度更高;②土壤盐渍化分布与GD、SI、SET和MTVDI等存在较强的关联性,不同等级的土壤盐渍化是不同影响因素不同程度上组合而引起的结果,盐渍化土地主要分布在地下水位较低以及土地开垦之后没有利用的荒地区域;③整个研究区大部分区域受到不同程度的盐渍化影响,耕地退化为盐渍地导致该区域土壤盐渍化以及土壤次生盐渍化进一步加剧。 相似文献
16.
植被分类是森林资源调查与动态监测的基础与前提。当前植被分类研究大都利用光学遥感影像,然而,光学遥感成像易受到云雨覆盖的影响,难以构建完整时间序列,植被分类精度有限。微波遥感具有全天时全天候、时间序列完整的优势,在植被调查与分析中具有巨大的应用潜力。本文利用2018年Sentinel-1A微波遥感时间序列数据和深度循环网络方法,对秦岭太白山区的森林植被进行分类制图。首先利用Sentinel-2光学影像与数字高程数据对研究区进行多尺度分割;然后将处理后的时间序列Sentinel-1A数据空间叠加到分割地块上,构建地块的多元时间序列曲线;最后利用深度循环网络提取与学习多元时间序列的时序特征并分类。实验结果表明：① 与传统机器学习方法（如RF、SVM）相比,本文提出的深度循环网络方法的分类精度提高10%以上;② 在Sentinel-1A微波极化特征组合中VV+VH表现最好,与VV+VH+VV/VH极化特征组合的精度相近;③ 使用全年的时间影像构建时间序列分类精度最高,达到82%。研究表明,利用深度循环网络与时间序列Sentinel-1A数据的方法能够有效提高植被分类的精度,从数据源与分类方法上为森林植被分类研究提供了新的思路。 相似文献
17.
时空融合技术是目前解决单一遥感数据源难以同步获取高时空分辨率数据的有效途径。然而,如何设置参数使模型融合效果最佳,如何设置在植被监测中广泛应用的植被指数的融合步骤,进而获得最佳的植被指数时序数据,目前仍不明晰。本文以长江中下游平原地区的典型县域—南昌县为例,基于Landsat和MODIS多时相数据对当前主流时空融合模型—ESTARFM （Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model）进行参数敏感性分析,并系统地对比分析了2组融合实验RI（先融合波段反射率后计算植被指数）和IR（先计算植被指数后直接融合）的融合效果。结果表明： ① ESTARFM算法中参数的敏感性在波段反射率、植被指数融合中表现出相似的特征,随着滑动窗口与相似像元数量的增大,融合误差整体呈现出先减小后趋于稳定或增大的趋势;在ESTARFM算法应用中,存在着最佳参数设置范围;② 相较于RI组,IR组模拟结果精度更高（R2RI-NDVI=0.866,R2IR-NDVI=0.953,R2RI-EVI =0.814,R2IR-EVI =0.930）,且能够较好地削弱“斑块”现象,更好地表征出细小地物和纹理特征。研究结果为遥感数据时空融合模型在地块破碎、种植制度多变的复杂环境中的应用提供借鉴和参考。 相似文献
18.
土壤水分是陆面生态系统和能量循环的核心变量之一,利用微波遥感技术获得的土壤水分产品的时间分辨率一般是2-3 d,因此精确地获得具有较高时间分辨率的土壤水分成了人们关注的焦点。本文尝试将SMAP (the Soil Moisture Passive and Active）土壤水分和MODIS光学数据相结合,利用广义回归神经网络进行全球36 km土壤水分的估算,提升SMAP土壤水分的时间分辨率。结果显示,广义回归神经网络估算土壤水分与SMAP保持了高相关性(r = 0.7528),但其却保留了较高的误差 (rmse = 0.0914 m3/m3)。尽管如此,估算的土壤水分能够很好地保持SMAP土壤水分的整体空间变化,并且提升了土壤水分的时间分辨率（1 d）。此处,本文研究了SMAP土壤水分与MODIS光学数据之间的关系,这对今后利用机器学习进行SMAP土壤水分降尺度研究提供了重要的参考价值。 相似文献