Lixin Wu

A Geographically and Temporally Weighted Regression Model for Ground-Level PM2.5 Estimation from Satellite-Derived 500 m Resolution AOD

Regional haze episodes have occurred frequently in eastern China over the past decades. As a critical indicator to evaluate air quality, the mass concentration of ambient fine particulate matters smaller than 2.5 μm in aerodynamic diameter (PM2.5) is involved in many studies. To overcome the limitations of ground measurements on PM2.5 concentration, which is featured in disperse representation and coarse coverage, many statistical models were developed to depict the relationship between ground-level PM2.5 and satellite-derived aerosol optical depth (AOD). However, the current satellite-derived AOD products and statistical models on PM2.5–AOD are insufficient to investigate PM2.5 characteristics at the urban scale, in that spatial resolution is crucial to identify the relationship between PM2.5 and anthropogenic activities. This paper presents a geographically and temporally weighted regression (GTWR) model to generate ground-level PM2.5 concentrations from satellite-derived 500 m AOD. The GTWR model incorporates the SARA (simplified high resolution MODIS aerosol retrieval algorithm) AOD product with meteorological variables, including planetary boundary layer height (PBLH), relative humidity (RH), wind speed (WS), and temperature (TEMP) extracted from WRF (weather research and forecasting) assimilation to depict the spatio-temporal dynamics in the PM2.5–AOD relationship. The estimated ground-level PM2.5 concentration has 500 m resolution at the MODIS satellite’s overpass moments twice a day, which can be used for air quality monitoring and haze tracking at the urban and regional scale. To test the performance of the GTWR model, a case study was carried out in a region covering the adjacent parts of Jiangsu, Shandong, Henan, and Anhui provinces in central China. A cross validation was done to evaluate the performance of the GTWR model. Compared with OLS, GWR, and TWR models, the GTWR model obtained the highest value of coefficient of determination (R2) and the lowest values of mean absolute difference (MAD), root mean square error (RMSE), and mean absolute percentage error (MAPE).

Infrared radiation of rock impacted at low velocity

Impact is one of the issues in dynamic mechanics, the impacting velocities ranging from low to hypervelocity. Usually, the reaction of the impacted material is the main purpose of research on high-velocity or hypervelocity impacts [1–3], such as piercing and blasting. Recent research on low-velocity impact emphasizes the dynamic change of material parameters and the transient processes [4]. However, research on solid impact, whatever the velocity, has common features:

Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST) retrieved from Thermal Infra-Red (TIR) images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM) algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT) in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD) and absolute average difference (AAD) are smaller than 1.7 K, where the correlation coefficient (CC) and root-mean-square error (RMSE) are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

Study on 3D Modeling Method of Faults Based on GTP Volume

3D fault modeling is one of the key issues of three-dimensional geosciences modeling system (3DGMS). Summarized the 3D modeling methods of faults at present, a new method, named as partition recursively modeling of the rock pillar body (RPB), for 3D modeling of faults (3DMF) based on generalized tri-prism (GTP) volume is put forward. This method takes borehole data as its original data source. The process for 3DMF includes: a) to generate the constrained delaunay TIN (CD-TIN) of terrain according to the collar data of borehole and the outcrops of faults; b) to construct the limit triangles in each PRB; c) to create 3D faults models according to the limit triangles. The test shows that the RPB method can accurately describe 3D complicated faults system involving obverse faults and reverse faults.3D fault modeling is one of the key issues of three-dimensional geosciences modeling system (3DGMS). Summarized the 3D modeling methods of faults at present, a new method, named as partition recursively modeling of the rock pillar body (RPB), for 3D modeling of faults (3DMF) based on generalized tri-prism (GTP) volume is put forward. This method takes borehole data as its original data source. The process for 3DMF includes: a) to generate the constrained delaunay TIN (CD-TIN) of terrain according to the collar data of borehole and the outcrops of faults; b) to construct the limit triangles in each PRB; c) to create 3D faults models according to the limit triangles. The test shows that the RPB method can accurately describe 3D complicated faults system involving obverse faults and reverse faults.

3D Integral Modeling for City Surface & Subsurface

With the rapid development of urban, city space extended from surface to subsurface. As the important data source for the representation of city spatial information, 3D city spatial data have the characteristics of multi-object, heterogeneity and multi-structure. It could be classified referring to the geo-surface into three kinds: above-surface data, surface data and subsurface data. The current research on 3D city spatial information system is divided naturally into two different branch, 3D City GIS (3D CGIS) and 3D Geological Modeling (3DGM). The former emphasizes on the 3D visualization of buildings and the terrain of city, while the latter emphasizes on the visualization of geological bodies and structures. Although, it is extremely important for city planning and construction to integrate all the city spatial information including above-surface, surface and subsurface objects to conduct integral analysis and spatial manipulation.

Experimental study on infrared anomaly of tectonic earthquake

Many scientists believe that the earthquake cannot be predicted. But, the fact that there were positive infrared (IR) anomalies in satellite remote sensing images 15 - 60 days before some moderate-strong tectonic earthquakes in Asia is changing the situation. To reveal the mechanism and to seek for the spatio-temporal laws of IR anomaly evaluation before tectonic earthquakes, a series of fundamental experiments detecting the surface IR radiation images on loaded rock samples, which were designed to model the incubation of tectonic earthquakes, were conducted. This article introduced the spatio-temporal evaluation laws of IR anomaly from rock surface for the condition of compressively sheared rock, bi-axial loaded en echelon faults, compressively-sheared sliding faults and compressively loaded intersected faults, respectively simulating the four gestation mechanisms of tectonic earthquake. The experiments concluded that the tectonic earthquake is predictable, and the satellite IR remote sensing is a prospecting technique for earthquake prediction, especially in the condition that remote sensing is assisted with analyzing to rock properties of regional crust and locations of active faults.

The Formal Representation of Semantic on Stratum Attribute Data Oriented 3D Geo-Modeling

In geology field, the rock attribute is the reference to judge the strata relationship between boreholes. It is the key issues to transfer the qualitative attribute to quantitative data by using of Geo-ontology. Being a case of Geo-ontology the Stratum-ontology is a formalized representation and an instance to meet the quantitative need. According to the domination features of Carbonate rock, the semantic contents of Stratum-ontology are defined. Based on the construction of Stratum-ontology, the formal representation of semantic with BNF normal form is developed, which is the criterion for the judgment of stratum relation. According to the judgment and stratum inference rule, a digital three-dimensional geological model of a research district is constructed as a case.

Constrained edge dynamic deleting in CD-TIN based on influence domain retriangulation of virtual point

Constrained Delaunay triangulated irregular network is one kind of dynamic data structures used in geosciences. The research on point and edges insertion in CD-TIN is the basis of its application. Comparing with the algorithms of points and constrained edge insertion, there are very a few researches on constrained edge deletion in CD-TIN. Based on the analysis of the polymorphism of constrained edge, virtual points are used to describe the intersection of constrained edges. A new algorithm is presented, called as influence domain retriangulating for virtual point (IDRVP), to delete constrained edges with virtual points. The algorithm is complete in topology. Finally, the algorithm is tested by some applications cases.

An object-oriented 3D integral data model for digital city and digital mine

With the rapid development of urban, city space extended from surface to subsurface. As the important data source for the representation of city spatial information, 3D city spatial data have the characteristics of multi-object, heterogeneity and multi-structure. It could be classified referring to the geo-surface into three kinds: above-surface data, surface data and subsurface data. The current research on 3D city spatial information system is divided naturally into two different branch, 3D City GIS (3D CGIS) and 3D Geological Modeling (3DGM). The former emphasizes on the 3D visualization of buildings and the terrain of city, while the latter emphasizes on the visualization of geological bodies and structures. Although, it is extremely important for city planning and construction to integrate all the city spatial information including above-surface, surface and subsurface objects to conduct integral analysis and spatial manipulation. However, either 3D CGIS or 3DGM is currently difficult to realize the information integration, integral analysis and spatial manipulation. Considering 3D spatial modeling theory and methodologies, an object-oriented 3D integral spatial data model (OO3D-ISDM) is presented and software realized. The model integrates geographical objects, surface buildings and geological objects together seamlessly with TIN being its coupling interface. This paper introduced the conceptual model of OO3D-ISDM, which is comprised of 4 spatial elements, i.e. point, line, face and body, and 4 geometric primitives, i.e. vertex, segment, triangle and generalized tri-prism (GTP). The spatial model represents the geometry of surface buildings and geographical objects with triangles, and geological objects with GTP. Any of the represented objects, no mater surface buildings, terrain or subsurface objects, could be described with the basic geometry element, i.e. triangle. So the 3D spatial objects, surface buildings, terrain and geological objects can be integrated together with the TIN being its coupling interface. The software system, Geomo3D, based on OO3D-ISDM and an application case in the central business district (CBD) of municipal Beijing are introduced. The case shows that the potential applications of OO3D-ISDM and Geomo3D in the domains of digital city, digital geotechnical engineering and digital mine.

Comparisons of thermal radiation characteristics between rocks and PMMA subjected to free-fall impacts

Utilizing the Thermal Infrared (TIR) imaging technology, the transient process of solids (Three kinds of rocks and one kind of PMMA) impacted by free-falling steel balls are monitored with an infrared camera. It is discovered that: (1) as for rock materials, the increments of IR temperature (both the maximum and average, i.e., ΔTmax and ΔTavr) are all linear related to the impacting height, the difference are the statistical correlation coefficients (R): relatively homogeneous rock (marble, R=0.93~0.95); non-homogeneous rocks (granite: R=0.88~0.92; gabbro: R=0.80~0.84); while for PMMA, there exists a critical height (h≈5m), within this height, ΔTmax is quadratic related and ΔTavr is linear related to the impacting height, and when above this critical height, both ΔTmax and ΔTavr are linear related, comparison to rocks, the statistical correlation coefficients are somewhat higher (R=0.94~0.96); (2) the amplitude of IR temperature increments are different, it is somewhat less of IR temperature variations for relatively hard rocks (granite) than others (gabbro, marble and PMMA), for example, when impacted at a height of 2 meter with a standard ball (1 inch in diameter), the higher ΔTmax≈2~4K, while others are within 1K, and (3) it is verified that the parameters about the impaction could be well inversed qualitatively to quantitatively, not only the type of rocks can be identified exactly, but also the impacting height can be accurately estimated especially for the relatively homogenous materials, as for marble rock and PMMA, the relative mean errors of inversion are less than 11.3% and 6.2%, respectively.