尺度效应的叶面积指数产品真实性检验方法     

廖嫣然  盖颖颖  姚延娟  范闻捷  徐希孺  闫彬彦 《遥感学报》2015,19(1):134-152

真实性检验是评价遥感反演产品质量和验证遥感应用产品是否准确、真实地反映实际情况的重要途径。叶面积指数(LAI)是表征陆地植被结构和长势的关键参数,全面准确评价和验证LAI产品是产品用于陆面过程模型的前提。本文以MODIS LAI与GLASS LAI产品为研究对象,在尺度效应和尺度转换的基础上,建立了针对非均匀像元的低分辨率LAI产品真实性检验方法。在考虑空间异质性和植被长势差异的情况下,借助中分辨率的遥感影像,分别利用1 km像元平均叶面积指数和反演表观叶面积指数实现了对LAI算法和产品的真实性检验。为了比较作物长势差异和地表非均匀度对产品的影响,本文选择有代表性的河南鹤壁和甘肃张掖两个地区进行两种LAI产品真实性检验研究。研究结果表明,GLASS LAI和MODIS LAI产品均存在明显的低估现象。这并不是产品算法的问题,而是由于地表异质性和非均匀度的影响。在异质性更显著的张掖盈科灌区,低估现象更明显。GLASS LAI产品是多种LAI产品的融合,它的平均LAI比MODIS更接近真实情况,但是LAI的动态范围比MODIS窄。  相似文献   

Modelling sediment deposition and phosphorus retention in a river floodplain          下载免费PDF全文

M. González‐Sanchis  J. Murillo  A. Cabezas  J. E. Vermaat  F. A. Comín  P. García‐Navarro 《水文研究》2015,29(3):384-394

Phosphorus (P) is one of the major limiting nutrient in many freshwater ecosystems. During the last decade, attention has been focused on the fluxes of suspended sediment and particulate P through freshwater drainage systems because of severe eutrophication effects in aquatic ecosystems. Hence, the analysis and prediction of phosphorus and sediment dynamics constitute an important element for ecological conservation and restoration of freshwater ecosystems. In that sense, the development of a suitable prediction model is justified, and the present work is devoted to the validation and application of a predictive soluble reactive phosphorus (SRP) uptake and sedimentation models, to a real riparian system of the middle Ebro river floodplain. Both models are coupled to a fully distributed two‐dimensional shallow‐water flow numerical model. The SRP uptake model is validated using data from three field experiments. The model predictions show a good accuracy for SRP concentration, where the linear regressions between measured and calculated values of the three experiments were significant (r² ≥ 0.62; p ≤ 0.05), and a Nash–Sutcliffe coefficient (E) that ranged from 0.54 to 0.62. The sedimentation model is validated using field data collected during two real flooding events within the same river reach. The comparison between calculated and measured sediment depositions showed a significant linear regression (p ≤ 0.05; r² = 0.97) and an E that ranged from 0.63 to 0.78. Subsequently, the complete model that includes flow dynamics, solute transport, SRP uptake and sedimentation is used to simulate and analyse floodplain sediment deposition, river nutrient contribution and SRP uptake. According to this analysis, the main SRP uptake process appears to be the sediment sorption. The analysis also reveals the presence of a lateral gradient of hydrological connectivity that decreases with distance from the river and controls the river matter contribution to the floodplain. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

利用GLAS激光测高数据评估DSM产品质量及精度优化   总被引：2，自引：0，他引：2  

胡柳茹  唐新明  李国元  付冬暇  窦显辉  赵世湖 《测绘通报》2019,(11):39-43

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。  相似文献   

Severe soil erosion during a 3‐day exceptional rainfall event: combining modelling and field data for a fallow cereal field          下载免费PDF全文

Manuel López‐Vicente  Laura Quijano  Leticia Gaspar  Leticia Palazón  Ana Navas 《水文研究》2015,29(10):2358-2372

Exceptional rainfall events cause significant losses of soil, although few studies have addressed the validation of model predictions at field scale during severe erosive episodes. In this study, we evaluate the predictive ability of the enhanced Soil Erosion and Redistribution Tool (SERT‐2014) model for mapping and quantifying soil erosion during the exceptional rainfall event (~235 mm) that affected the Central Spanish Pyrenees in October 2012. The capacity of the simulation model is evaluated in a fallow cereal field (1.9 ha) at a high spatial scale (1 × 1 m). Validation was performed with field‐quantified rates of soil loss in the rills and ephemeral gullies and also with a detailed map of soil redistribution. The SERT‐2014 model was run for the six rainfall sub‐events that made up the exceptional event, simulating the different hydrological responses of soils with maximum runoff depths ranging between 40 and 1017 mm. Predicted average and maximum soil erosion was 11 and 117 Mg ha^?1 event^?1, respectively. Total soil loss and sediment yield to the La Reina gully amounted to 16.3 and 9.0 Mg event^?1. These rates are in agreement with field estimations of soil loss of 20.0 Mg event^?1. Most soil loss (86%) occurred during the first sub‐event. Although soil accumulation was overestimated in the first sub‐event because of the large amount of detached soil, the enhanced SERT‐2014 model successfully predicted the different spatial patterns and values of soil redistribution for each sub‐event. Further research should focus on stream transport capacity. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures          下载免费PDF全文

J. L. McCreight  A. G. Slater  H. P. Marshall  B. Rajagopalan 《水文研究》2014,28(3):933-957

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Developing,choosing and using landscape evolution models to inform field‐based landscape reconstruction studies          下载免费PDF全文

A.J.A.M. Temme  J. Armitage  M. Attal  Wouter van Gorp  T.J. Coulthard  J.M. Schoorl 《地球表面变化过程与地形》2017,42(13):2167-2183

Landscape evolution models (LEMs) are an increasingly popular resource for geomorphologists as they can operate as virtual laboratories where the implications of hypotheses about processes over human to geological timescales can be visualized at spatial scales from catchments to mountain ranges. Hypothetical studies for idealized landscapes have dominated, although model testing in real landscapes has also been undertaken. So far however, numerical landscape evolution models have rarely been used to aid field‐based reconstructions of the geomorphic evolution of actual landscapes. To help make this use more common, we review numerical landscape evolution models from the point of view of model use in field reconstruction studies. We first give a broad overview of the main assumptions and choices made in many LEMs to help prospective users select models appropriate to their field situation. We then summarize for various timescales which data are typically available and which models are appropriate. Finally, we provide guidance on how to set up a model study as a function of available data and the type of research question. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

Experimental study of deformable connection consisting of buckling‐restrained brace and rubber bearings to connect floor system to lateral force resisting system          下载免费PDF全文

Georgios Tsampras  Richard Sause  Robert B. Fleischman  Jose I. Restrepo 《地震工程与结构动力学》2017,46(8):1287-1305

This paper presents experimental and numerical studies of a full‐scale deformable connection used to connect the floor system of the flexible gravity load resisting system to the stiff lateral force resisting system (LFRS) of an earthquake‐resistant building. The purpose of the deformable connection is to limit the earthquake‐induced horizontal inertia force transferred from the floor system to the LFRS and, thereby, to reduce the horizontal floor accelerations and the forces in the LFRS. The deformable connection that was studied consists of a buckling‐restrained brace (BRB) and steel‐reinforced laminated low‐damping rubber bearings (RB). The test results show that the force–deformation responses of the connection are stable, and the dynamic force responses are larger than the quasi‐static force responses. The BRB+RB force–deformation response depends mainly on the BRB response. A detailed discussion of the BRB experimental force–deformation response is presented. The experimental results show that the maximum plastic deformation range controls the isotropic hardening of the BRB. The hardened BRB force–deformation responses are used to calculate the overstrength adjustment factors. Details and limitations of a validated, accurate model for the connection force–deformation response are presented. Numerical simulation results for a 12‐story reinforced concrete wall building with deformable connections show the effects of including the RB in the deformable connection and the effect of modeling the BRB isotropic hardening on the building seismic response. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

Validation of a soil water balance model using soil water content and pressure head data     

Martin Wegehenkel 《水文研究》2005,19(6):1139-1164

The validation of soil water balance models and the evaluation of the quality of the model predictions at field‐scale require time‐series of in situ measured model outputs. In our study, we have validated such a model using a 6‐year period with time‐series of automatically recorded, daily volumetric soil water contents measured with the time‐domain reflectometry with intelligent microelements (TRIME) method and daily pressure heads measured with tensiometers. The comparisons of simulated with measured soil water contents and pressure heads were analysed using the modelling efficiency index (IA) and the square root of the mean square error (RMSE) in order to evaluate the prediction quality of the model. In our study, IA and RMSE, obtained either from the comparison of simulated with measured soil water contents or the comparison of calculated with observed pressure heads, in some cases lead to different results regarding the evaluation of the simulation quality of the soil water balance model. For example, a good fit between simulated and observed soil water contents does not necessarily result in a comparably good fit between the corresponding calculated and measured pressure heads. Therefore, a combined use of both measurement techniques, which takes into account their respective advantages and disadvantages, gives a more complete overview on the simulation quality of the soil water balance model than the single use of one of those techniques. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

基于自适应时序剖分与KNN的短时交通流量预测     

祁朵  毛政元 《地球信息科学学报》2022,24(2):339-351

在智能交通系统中,准确和高效的短时交通流量预测是交通诱导、管理和控制的前提。由于交通流量动态变化中表现出的时变性和非平稳性特征,其预测难度较大,是交通领域中亟待解决的难题。为提高短时交通流量的预测精度,本文设计与实现了基于自适应时序剖分与KNN（A-TS-KNN）的短时交通流量预测算法。① 基于动态时间规整（Dynamic Time Warping,DTW）动态剖分单日时序为不同的交通模式;② 在不同交通模式,采用互信息法求解每个预测时刻时间延迟的最大阈值,构造不同时间延迟的状态向量,生成交通流量历史数据库;③ 采用十次十折交叉验证的方法求解每个时刻不同时间延迟与不同K值的正交误差结果分布,提取误差最小的正交结果,得到自适应时间延迟与K值的参数组合;④ 采用K个最相似的近邻的距离倒数加权值作为预测结果。对比K近邻（K-nearest neighbors, KNN）、支持向量回归（Support vector regression,SVR）、长短期记忆神经网络（Long-short term memory neural network,LSTM）以及门控递归单元神经网络（Gate recurrent unit neural network,GRU）共4种主流预测模型,A-TS-KNN算法预测精度显著提升;将A-TS-KNN算法用于福州市城市路网中其他交叉路口的短时交通流量预测,结果表现出良好的泛化能力。  相似文献   

Validation and Improvement of Satellite-Derived Surface Solar Radiation over the Northwestern Pacific Ocean     

Kawai  Yoshimi  Kawamura  Hiroshi 《Journal of Oceanography》2005,61(1):79-89

The purpose of this study is to validate and improve satellite-derived downward surface shortwave radiation (DSSR) over the northwestern Pacific Ocean using abundant in situ data. The DSSR derivation model used here assumes that the reduction of solar radiation by clouds is proportional to the product of satellite-measured albedo and a cloud attenuation coefficient. DSSR is calculated from Geostationary Meteorological Satellite-5/Visible Infrared Spin-Scan Radiometer data in 0.05° × 0.05° grids. The authors first compare the satellite DSSR derived with a cloud attenuation coefficient table determined in past research with in situ values. Although the hourly satellite DSSR agrees well with land in situ values in Japan, it has a bias of +13∼+34 W/m² over the ocean and the bias is especially large in the low latitudes. The authors then improve the coefficient table using the ocean in situ data. Usage of the new table successfully reduces the bias of the satellite DSSR over the ocean. The cloud attenuation coefficient for low-albedo cases over the ocean needs to be larger in the low latitudes than past research has indicated. Daily and hourly DSSR can be evaluated from the satellite data with RMS errors of 11–14% and 30–33%, respectively, over a wide region of the ocean by this model. It is also shown that the cloud attenuation coefficient over land needs to be smaller than over the ocean because the effect of the radiation reflected by the land surface cannot be ignored.  相似文献