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Zhang X.,Karlsruhe Institute of Technology | Zhang X.,Tsinghua University | Huang M.,Beijing Institute of Surveying and Mapping
Journal of Hazardous Materials | Year: 2017

Dispersion model is an important tool for decision makers to accurately assess risks and effectively plan countermeasures during river pollution accidents, but their applications suffer from significant modeling uncertainties, primarily due to the scarce information of the source. A fully sequential inverse estimation method is proposed to reconstruct the temporal release for accidental river pollution. The method is based on a one-dimensional advection-dispersion model in conjunction with the augmented ensemble Kalman filter method. Detailed analysis of the ensemble background error covariance (BEC) matrix is conducted to elucidate the “flow-dependent” mechanism, which enables the inversion method to simultaneously take into account the uncertainties in the hydrological parameters (mean flow velocity and longitudinal dispersion coefficient). The method is evaluated with six field tracer experiments with various mean flow velocities, ranging from 0.085 to 0.889 m s−1, and also compared with the commonly used Tikhonov regularization inverse estimation method to demonstrate its performance improvement. The results indicate that it successfully reconstructs the temporal release and reduces the relative errors of the total release estimation by about 12.4% on average compared with the Tikhonov method, since the errors caused by the uncertainties in mean flow velocity and longitudinal dispersion coefficient are effectively alleviated. © 2017 Elsevier B.V.

Lu X.,Peking University | Cheng C.,Peking University | Gong J.,Wuhan University | Guan L.,Beijing Institute of Surveying and Mapping
Science China Technological Sciences | Year: 2011

Aiming at the storage and management problems of massive remote sensing data, this paper gives a comprehensive analysis of the characteristics and advantages of thirteen data storage centers or systems at home and abroad. They mainly include the NASA EOS, World Wind, Google Earth, Google Maps, Bing Maps, Microsoft TerraServer, ESA, Earth Simulator, GeoEye, Map World, China Centre for Resources Satellite Data and Application, National Satellite Meteorological Centre, and National Satellite Ocean Application Service. By summing up the practical data storage and management technologies in terms of remote sensing data storage organization and storage architecture, it will be helpful to seek more suitable techniques and methods for massive remote sensing data storage and management. © 2011 Science China Press and Springer-Verlag Berlin Heidelberg.

Zhang X.,Peking University | Zhao J.,Beijing Institute of Surveying and Mapping | Tian J.,Clark University
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

Optical remote sensing has been widely used to estimate soil moisture. However, modeling soil moisture dynamics across a large area based on remotely sensed optical data still poses a problem because of its spatial discontinuity due to cloud contamination. This study proposes a multisensor strategy for better mapping surface soil moisture on a daily basis at a regional scale. The basic idea is to decompose the surface soil moisture at any location into two terms, namely, baseline value in an observed period and daily variation, and to estimate for each term differently. For a certain day of interest, the corresponding 16-day composite of Moderate Resolution Imaging Spectroradiometer (MODIS) data is used to estimate the soil moisture baseline values across space, and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) data are employed to estimate the daily variations. The proposed model was applied to produce daily surface soil moisture maps at a 1-km resolution for the fairly large study area of Xinjiang, China, regardless of the local weather conditions. It was found that the integrated use of MODIS and AMSR-E data was able to achieve significantly higher accuracy in surface soil moisture estimation (with a root-mean-square error of 3.99% in May and 4.43% in August, 2009) than the approaches based on either data alone could. The proposed model is expected to perform well for mapping surface soil moisture in other arid areas after the required parameters are calibrated with the local field data. © 1980-2012 IEEE.

Toutin T.,Canada Center For Remote Sensing | Zhu X.,Beijing Institute of Surveying and Mapping
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

Due to the specificity of space borne synthetic aperture radar (SAR) sensors, the stereoscopic pair can only be generated in across-track direction. However, the stereo can also be generated with triplet images when SAR system can span large values of incidence angle, such as Radarsat, TerraSAR and CosmoSky-Med. In this paper, the triplet stereo was introduced to high-resolution Radarsat-2 data for generating DTM. For this study, three high-resolution images from Radarsat-2 were acquired with 31°, 38° and 47° incidence angles over a rolling topography of north of Quebec City, Canada. Two main steps of generation of DTM, including the geometry for 3-D modeling and the radiometry for image matching were carried out. For 3-D modeling, one deterministic model, Tontin's 3-D Radargrammetric Model, was applied to mono/stereo/triplet Radarsat-2 data. For image matching, a NCC algorithm was used. The differential GPS points and LiDAR products were used as reference data. Preliminaries results of triplet stereo with simulated SAR HR data of the new Canadian Radar Constellation Mission will be presented at IGARSSS 2012. © 2012 IEEE.

Li L.,Wuhan University | Li L.,CSIRO | Chen Y.,CSIRO | Yu X.,Beijing Institute of Surveying and Mapping | And 3 more authors.
ISPRS Journal of Photogrammetry and Remote Sensing | Year: 2015

The study of flood inundation is significant to human life and social economy. Remote sensing technology has provided an effective way to study the spatial and temporal characteristics of inundation. Remotely sensed images with high temporal resolutions are widely used in mapping inundation. However, mixed pixels do exist due to their relatively low spatial resolutions. One of the most popular approaches to resolve this issue is sub-pixel mapping. In this paper, a novel discrete particle swarm optimization (DPSO) based sub-pixel flood inundation mapping (DPSO-SFIM) method is proposed to achieve an improved accuracy in mapping inundation at a sub-pixel scale. The evaluation criterion for sub-pixel inundation mapping is formulated. The DPSO-SFIM algorithm is developed, including particle discrete encoding, fitness function designing and swarm search strategy. The accuracy of DPSO-SFIM in mapping inundation at a sub-pixel scale was evaluated using Landsat ETM. +. images from study areas in Australia and China. The results show that DPSO-SFIM consistently outperformed the four traditional SFIM methods in these study areas. A sensitivity analysis of DPSO-SFIM was also carried out to evaluate its performances. It is hoped that the results of this study will enhance the application of medium-low spatial resolution images in inundation detection and mapping, and thereby support the ecological and environmental studies of river basins. © 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Yu X.,Beijing Institute of Surveying and Mapping | Zheng Z.,Wuhan University
Acta Geodaetica et Cartographica Sinica | Year: 2010

In general, Bayesian networks represent the joint probability distribution and omain (or expert) knowledge in a compact way and provide a comprehensive method of representing relationships and influences among nodes (or feature variables) with a graphical diagram. Accordingly, by advantages of Bayesian networks a new road to texture classification of aerial images for achieving the automatization and intelligentization of photogram-metry and remote sensing can be explored. In this paper, a new method is proposed to extract semantic feature based on classifiers, which constructs the mapping from low-level features to high-level semantic feature. Then it is applied to classification of aerial images' building and shrub. The experiment results demonstrate that the new method can improve the classification precision.

Cao H.,Beijing Forestry University | Feng Z.,Beijing Forestry University | Zhang X.,Beijing Institute of Surveying and Mapping
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012

In order to improve the rapidity and efficiency of forestry mapping, icon and symbol library of forestry was established according to the standard specification of forestry mapping. Furthermore, by making use of AutoCAD secondary development technology ObjectARX and C++ language, the CASS software was developed to integrate with forestry mapping function including zoning, filling, annotation, property editing, query, area measurement, area adjustment, maps finishing, print output as a whole to be a forestry mapping software. The combination of graphics management and visualization in digital forestry mapping to satisfy the requirements of forestry mapping on high speed, activity and concision explore a new way for digital forestry mapping.

Zhang J.,Beijing Institute of Surveying and Mapping
Advances in Intelligent and Soft Computing | Year: 2012

The rapid development of the city makes more urgent protection of Architectural Heritage. In the city overall planning, we need to know the cultural relic building location, height and shape. On the cultural relics repair and maintenance, we need to know the size of the cultural relic, internal structure and various disease information. It can quickly build three-dimensional model of cultural relics with the use of 3D laser scanning technology, and also we can get the accurate position of cultural relics and the relationship between each part. Ground Penetring Radar can find the relics of internal structure and comprehensive detection of disease. With the two new mapping technologies, we can make a comprehensive examination of cultural relics. © 2012 Springer Science+Business Media Dordrecht.

Wei X.,Beijing Forestry University | Wang Y.,Beijing Institute of Surveying and Mapping | Zheng J.,Beijing Forestry University | Wang M.,Beijing Forestry University | Feng Z.,Beijing Forestry University
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | Year: 2013

The tree crown volume is difficult to measure and calculate because of its irregular shape. A calculating method of tree crown volume, named voxel simulation method, was presented based on 3-D laser scanning point clouds data. The main idea of this method was to use a certain size of voxel to estimate tree crown. Firstly, tree crown was cut into segments with a k step-length along tree height. For each segments, all the points were projected to a plane that perpendicular to tree height. Subsequently, the plane was divided into pixels with size of k×k. The effectiveness of each pixel depend on whether there were points projected in it. Then the effective pixels were counted and recorded as T. Finally, formula T×k×k×k was used to calculate the tree crown volume. When the k was equal to a tenth of crown diameter, the calculated crown volume was tending to stability. This algorithm did not need to consider the crown shapes of different tree species, which could reduce human's subjective factor influence. It could be used to calculate tree crown volume based on 3-D laser scanning technology.

Zhu X.,Beijing Institute of Surveying and Mapping | Toutin T.,Canada Center For Remote Sensing
International Journal of Image and Data Fusion | Year: 2013

Airborne light detection and range (LiDAR) with three-dimensional product acquisition capabilities has become an important research hot spot. The classification and information extraction of LiDAR were usually carried out with other earth observation (EO) data (VIR/SAR, spaceborne/airborne). However, if these EO data are not always available, a particularly interesting possibility is to use only the products of LiDAR including the digital elevation model, the digital surface model and the intensity image. In this article, at the study site of Beauport, around Lac-Saint-Charles, Québec, Canada, only airborne LiDAR products are applied to realise land cover interpretation and classification. A two-hierarchy decision-tree classification is suggested and carried out. Six land cover classes are extracted, including water bodies, bare soils, impervious areas, vegetation, buildings and high-voltage electric wires. All the reference and checking data are based on 1:20,000 topographic map of Québec. According to the accuracy statistics with 966 independent checking data, it is an efficient attempt in land cover classification using only airborne LiDAR products in this site. The feasibility of the methods and the classification data sources are verified for use in the scale of 1:25,000-50,000. © 2013 Copyright Taylor and Francis Group, LLC.

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