Earth observation-based damage assessment has been widely studied in recent years. Considering that the height and spatial variability of buildings change significantly in earthquake-devastated ...areas, a novel multi-stage urban building damage extraction method that uses bi-temporal spectral, height and corner information is proposed in this study. The post-event height features were directly derived from airborne light detection and ranging (LiDAR) data, whereas pre-event height features were generated using pre-event stereo-paired images from different satellites. The spatial features were quantified using the density of corner points (DCP) in spectral images. The proposed method of urban building damage extraction is summarised as follows. Bi-temporal height and corner features were first generated from bi-temporal very high resolution (VHR) satellite data and post-event airborne LiDAR data. Then, vegetation, bare land (pavement and soil) and shadow were extracted from post-event VHR image and height data, and masked out. Finally, building damage was extracted from the remaining areas using the height difference and DCP difference between pre- and post-event images. A post-processing procedure was used to further refine the initial extraction results. The proposed method was evaluated using bi-temporal VHR images and post-event LiDAR data collected in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010. The results showed that the proposed method significantly outperformed the two comparative methods in the extraction of urban building damage.
This paper gives a brief survey of recent developments on mathematical modeling and analysis of the open cavity scattering problems, which arise in diverse scientific areas and have significant ...industrial and military applications. The scattering problems are studied for the two-dimensional Helmholtz equation corresponding to the transverse magnetic or electric polarization, and the three-dimensional time-harmonic and time-domain Maxwell equations. Since these problems are imposed in open domains, a key step of the analysis is to develop transparent boundary conditions and reformulate them equivalently into boundary value problems in bounded domains. The well-posedness of weak solutions are shown for the associated variational problems by using either the Lax-Milgram theorem or the Fredholm alternative.
Using spectral features, morphological features and Hough transformation from UAV images, a method of mapping com seedling is proposed. First, spectral features and morphological features are ...extracted from UAV images and then are separately classified using an improved one-class random forest for mapping of corn seedling. Second, Hough transform is used to extract the com seedling rows from the classification results with morphological features. Third, the com seedling classification results with spectral features and the com seedling rows from Hough transform are combined to obtain the final seedling mapping result. The proposed mapping method is evaluated in two study areas. The results demonstrated that the proposed method, effectively combines morphological features and Hough transform in mapping of corn seedling, thus obtaining better results compared with the existing methods.
Consider the scattering of a time-harmonic plane wave by a rigid obstacle embedded in a homogeneous and isotropic elastic medium in two dimensions. In this paper, a novel boundary integral ...formulation is proposed and its highly accurate numerical method is developed for the elastic obstacle scattering problem. More specifically, based on the Helmholtz decomposition, the model problem is reduced to a coupled boundary integral equation with singular kernels. A regularized system is constructed in order to handle the degenerated integral operators. The semi-discrete and full-discrete schemes are studied for the boundary integral system by using the collocation method. Convergence is established for the numerical schemes in some appropriate Sobolev spaces. Numerical experiments are presented for both smooth and nonsmooth obstacles to demonstrate the superior performance of the proposed method. Furthermore, we extend this numerical method to the Neumann problem and the three-dimensional elastic obstacle scattering problem.
The soil water retention curve is the fundamental soil hydraulic property to characterize soil water movement and solute transport. Many efforts have been devoted in the past decades to developing ...models to describe soil water retention curves. However, most of them are empirical equations or assume that soil pore size distributions conform to a lognormal distribution. Yet, few effects have been undertaken to systematically propose and compare a series of possible alternative probability density functions to describe the sigmoid retention curves with parameters physically explainable. Here, we proposed a family of five soil water retention models based on sigmoid functions with parameters of clear physical implications coinciding with the statistical measures of soil pore size distribution. Compared with the widely used models (i.e., Brooks & Corey, 1964; Kosugi, 1996; van Genuchten, 1980), the proposed models have somewhat improved performances to characterize water retention data for a wide range of soil textures without introducing additional model parameters. Two of the proposed models are capable of characterizing the observed two local extrema in the moisture capacity curves. The associated unsaturated hydraulic conductivity models of the proposed soil water retention models are also derived, which show superior performance in characterizing the observed hydraulic conductivities compared with competing models, especially in macropore regimes. Additionally, we analyzed the parameter‐equivalent conversion between the proposed and the existing models, and a simple linear regression equation can be used to derive the parameters of the proposed models from the existing and other alternative different proposed models.
Key Points
A family of soil water retention models based on sigmoid functions and related relative hydraulic conductivity functions are proposed
Parameters have statistical implications against pore size distributions and can be converted from existing or alternative new models
Characterization of hydraulic properties is improved using new models, especially for macropore properties, without additional parameters
Timely and accurate information about spatial distribution of tree species in urban areas provides crucial data for sustainable urban development, management and planning. Very high spatial ...resolution data collected by sensors onboard Unmanned Aerial Vehicles (UAV) systems provide rich data sources for mapping tree species. This paper proposes a method of tree species mapping from UAV images over urban areas using similarity in tree-crown object histograms and a simple thresholding method. Tree-crown objects are first extracted and used as processing units in subsequent steps. Tree-crown object histograms of multiple features, i.e., spectral and height related features, are generated to quantify within-object variability. A specific tree species is extracted by comparing similarity in histogram between a target tree-crown object and reference objects. The proposed method is evaluated in mapping four different tree species using UAV multispectral ortho-images and derived Digital Surface Model (DSM) data collected in Shanghai urban area, by comparing with an existing method. The results demonstrate that the proposed method outperforms the comparative method for all four tree species, with improvements of 0.61–5.81% in overall accuracy. The proposed method provides a simple and effective way of mapping tree species over urban area.
•The disulfide/sulfhydryl exchange reactions were affected to modulate MP gels.•The effects of GSH on MP gels were in dose and temperature dependence.•Low contents of GSH promoted aggregation and gel ...properties at low temperature.•High contents of GSH inhibited aggregation and improved gels at high temperature.
The present study illustrated modulation of protein aggregation by affecting disulfide/sulfhydryl exchange reactions by adding different concentrations of free thiol represented by reduced-glutathione (GSH) for modulating myofibrillar protein (MP) gel properties at 75 °C or 95 °C. Gel strength and rheological results showed the effects of GSH were dependent on the concentrations (5, 10, 20, 40, and 80 g/kg) and heating temperatures. SEM results showed that the addition of GSH improved the gel microstructure at 95 °C. AFM and DLS results indicated that protein aggregation was also inhibited. At 75 °C, the addition of GSH influenced both MP aggregation and gel properties. Low concentrations (5, 10 g/kg) of GSH promoted aggregation, whereas high concentrations (20, 40, and 80 g/kg) of GSH inhibited this. By analyzing the protein structure and cross-linking pattern changes of MP and MP/GSH composites, a pathway involving GSH influencing MP gel properties was determined.
•Physical model and machine learning are compared for simulating soil moisture.•The effects of model assumptions and observation errors are investigated.•Their performances under extrapolation and ...different soil water dynamics are discussed.
Soil moisture plays a critical role as an essential component of the global water resources by regulating mass and energy exchange between land surface and atmosphere. Quantification of these exchange processes requires accurate characterization and simulation of soil water movement. Physically-based models (PBMs) and machine learning methods (MLMs) can both be used in soil moisture simulation. However, their performances in soil water simulation have only been compared in a limited number of cases. Moreover, almost all of them are conducted in field studies each with fixed soil, initial condition, and boundary condition. Here, we developed three artificial neural network (ANN) frameworks, and made clearer and more systematic comparisons between them and a PBM—Ross numerical model solving Richards equation and parameter estimation using a data assimilation approach (iterative ensemble smoother, Ross-IES) in synthetic and real-world conditions. Compared with the ANNs, Ross-IES is more significantly affected by physical model uncertainties such as soil heterogeneity, initial and boundary conditions, while both methods are affected by observation noise. For Ross-IES, the errors from boundary conditions and hydraulic parameter conceptualization are found to be more prominent than that of observation noise and therefore are suggested to be identified first. Meanwhile, the ANNs have difficulty in simulating the peaks and troughs of the soil water time series as well as in situations where the soil moisture is constantly saturated. ANNs yield a superior simulation when the nonlinear relationship between the response variables and driving data is weak, while the performance of Ross-IES is governed by the prior soil hydraulic information. In addition, Ross-IES approach requires much higher computational cost than the ANNs. ANN-MS performs best among the three ANN-based machine learning models and demonstrates great data mining ability and robustness against overfitting.
To address the problem that quality and quantity of training samples directly affect accuracy of one-class classification (OCC) methods, this paper investigates the use of active learning in ...selection of training samples of target class (positive samples) for improving the performance of OCC, by taking positive and unlabeled learning (PUL) as an example. PUL is first trained with sufficient training samples selected randomly until a stable accuracy is reached. Most informative positive and negative training samples collected by using active learning strategy are then added in PUL classification. The experimental results show that after sufficient samples are used for classification, the use of positive samples selected by using active learning still outperformed that using sufficient positive samples selected randomly. PUL classification by adding both positive and negative samples outperformed that by adding positive samples only. Furthermore, PUL classification using positive samples after removal of redund
PDF
