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Zhang L.,Wuhan University | Liu Y.,Wuhan University | Wei X.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Wei X.,East China University of Technology
Sustainability (Switzerland) | Year: 2017

Forest fragmentation, the process of changing original large and intact forest patches into smaller and isolated areas, significantly influences the balance of surface physical environment, biodiversity, and species richness. Sufficient knowledge of forest fragmentation is necessary to maintain ecological balance and promote sustainable resource utilization. This study combines remote sensing, geographical information systems, and landscape metrics to assess forest fragmentation at landscape and pixel levels during different time periods (2000-2005, 2005-2010, and 2010-2015) in the Yingkou region. Spatial statistical analysis is also used to analyze the relationship between forest landscape fragmentation and its determinants (e.g., natural factors, socioeconomic factors, and proximity factors). Results show that forest patches became smaller, subdivided, and isolated during 2010-2015 at the total landscape level. Local changes occurred in the southwest of the study region or around the development area. Our data also indicate that shrinkage and subdivision were the main forest fragmentation processes during three times, and attrition became the main forest fragmentation process from 2010 to 2015. These changes were significantly influenced by natural factors (e.g., elevation and slope), proximity factors (e.g., distance to city and distance to province roads), and socioeconomic factors (e.g., gross domestic product). Results presented in this study provide valuable insights into the pattern and processes of forest fragmentation and present direct implications for the protection and reasonable utilization of forest resources. © 2017 by the authors.


He H.,East China University of Technology | He H.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Du J.,East China University of Technology | Chen X.,East China University of Technology | And 2 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2017

Compared with vertical photogrammtry, oblique photogrammetry is radically different for images acquired from sensor with big yaw, pitch, and roll angles. Image matching is a vital step and core problem of oblique low-altitude photogrammetric process. Among the most popular oblique images matching methods are currently SIFT/ASIFT and many affine invariant feature-based approaches, which are mainly used in computer vision, while these methods are unsuitable for requiring evenly distributed corresponding points and high efficiency simultaneously in oblique photogrammetry. In this paper, we present an oblique low-altitude images matching approach using robust perspective invariant features. Firstly, the homography matrix is estimated by a few corresponding points obtained from top pyramid images matching in several projective simulation. Then images matching are implemented by sub-pixel Harris corners and descriptors after shape perspective transforming on the basis of homography matrix. Finally, the error or gross error matched points are excluded by epipolar geometry, RANSAC algorithm and back projection constraint. Experimental results show that the proposed approach can achieve more excellent performances in oblique low-altitude images matching than the common methods, including SIFT and SURF. And the proposed approach can significantly improve the computational efficiency compared with ASIFT and Affine-SURF. © 2017 SPIE.


He H.,East China University of Technology | He H.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | You Q.,East China University of Technology | Chen X.,East China University of Technology | Chen X.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2017

The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation. © 2017 SPIE.


Wang L.,East China Institute of Technology | Wang L.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Wu F.,East China Institute of Technology | Wu F.,China University of Mining and Technology | Wu L.,East China Institute of Technology
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2016

In the current research on the total least squares method in the conversion of GPS height, the calculation of the conversion parameter and elevation abnormities of the check points are generally performed in two steps, and only consider the error in the coefficient matrix used to calculate the parameters; errors in the coordinate of the check point are ignored. In view of this gap, we put forward a total least squares fitting estimation model of GPS height transformation, that combines the calculation of fitting parameters with the calculation of elevation abnormities at inspection points, and considers the position error of all points. Collocation calculation experiemental results verify the feasibility of this method. These test results show that the method can effectively improve the accuracy of elevation conversion. © 2016, Research and Development Office of Wuhan University. All right reserved.


Wang L.,East China Institute of Technology | Wang L.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Xu G.,East China Institute of Technology | Xu G.,Wuhan University
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2016

Considering the situation that the weight matrix of observation vector and coefficient matrix may be inaccurate, an available algorithm is introduced in this paper, which is derived on the basis of combining the Helmert variance component estimation with a kind of fast weighted total least squares algorithm in the errors-in-variables models. And the derivative process of the fast weighted total least squares is described in detail and the comparison with three other algorithms is implemented in this paper. Using the fast weighted total least squares algorithm combining Helmert variance component estimation derived in this paper, the stochastic model and the unknown parameters of the functional model can be solved simultaneously. Three empirical examples, two straight line fitting and one linear parameter estimation, are also used to investigate the application of posteriori estimation of stochastic model on weighted total least squares problem. Results show that the algorithm is very effective. © 2016, Wuhan University. All right reserved.


Li H.,Wuhan University | Li H.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Zhong C.,Chongqing Three Gorges University
Sensor Review | Year: 2016

Purpose - This study aims to find a feasible precise navigation model for the planed Lunar rover. Autonomous navigation is one of the most important missions in the Chinese Lunar exploration project. Machine vision is expected to be a promising option for this mission because of the dramatic development of an image processing technique. However, existing attempts are often subject to low accuracy and errors accumulation. Design/methodology/approach - In this paper, a novel autonomous navigation model was developed, based on the rigid geometric and photogrammetric theory, including stereo perception, relative positioning and absolute adjustment. The first step was planned to detect accurate three-dimensional (3D) surroundings around the rover by matching stereo-paired images; the second was used to decide the local location and orientation changes of the rover by matching adjacent images; and the third was adopted to find the rover's location in the whole scene by matching ground image with satellite image. Among them, the SURF algorithm that had been commonly believed as the best algorithm for matching images was adopted to find matched images. Findings - Experiments indicated that the accurate 3D scene, relative positioning and absolute adjustment were easily generated and illustrated with the matching results. More importantly, the proposed algorithm is able to match images with great differences in illumination, scale and observation angle. All experiments and findings in this study proved that the proposed method could be an alternative navigation model for the planed Lunar rover. Originality/value - With the matching results, an accurate 3D scene, relative positioning and absolute adjustment of rover can be easily generated. The whole test proves that the proposed method could be a feasible navigation model for the planed Lunar rover. © Emerald Group Publishing Limited.


Liu Y.,Wuhan University | Zhang L.,Wuhan University | Wei X.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Wei X.,East China University of Technology | Xie P.,Wuhan University
Ecological Indicators | Year: 2016

The assessment of the value of ecosystem services is a valuable tool for biodiversity conservation that can facilitate better environmental policy decision-making and land management, and can help land managers develop interventions to compensate for biodiversity loss at the patch level. Previous studies have suggested that it is appropriate to assess the value of biodiversity for conservation planning by considering both the condition of the landscape and the spatial configuration of adjacent land uses that can be reflected as a proximity effect. This research examines the influence of spatial proximity on biodiversity conservation from the ecosystem service perspective based on the assumption that the variation in the proximity effect caused by land cover change has positive or negative impacts on ecological services. Three factors related to the spatial characteristics of the landscape were considered in this approach: the relative artificiality of the land cover types, the distance decay effect of patches and the impact of one land cover type on others. The proximity effect change (PEC) parameter reflected the relationship between the spatial proximity effect and biodiversity conservation. The results of a quantitative and spatial comparative analysis of the proposed method and the conventional method in Yingkou for the periods of 2000-2005 and 2005-2010 showed that the former can account for the temporal and spatial changes in ecosystem services for biodiversity conservation that were caused by patch-level changes as well as the interaction between the altered and adjacent patches from a spatial perspective. The metric can also identify the most critical areas for biodiversity protection and inform the efficient allocation of limited land resources for nature conservation to maximize the benefit to biodiversity by guiding the process of land-use change, particularly urbanization and agriculture. Future studies should focus on the other important factors that are applicable to the assessment of the value of biodiversity conservation in socio-ecological systems, where society and nature are mutually capable of fulfilling their roles. © 2016 Elsevier Ltd. All rights reserved.


Liu Y.,Wuhan University | Wei X.,East China University of Technology | Wei X.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Li P.,Wuhan University | Li Q.,Wuhan University
Ecological Indicators | Year: 2016

Sensitivity of landscape metrics to selection of spatial scale (i.e., resolution or areal extent), land-use categories, and different landscapes has led to unreliable conclusions for practitioners of landscape analysis and modeling. Unlike previous studies that mostly considered such metrics and assessed the effect of each factor separately, our study focuses on the sensitivity of the correlation structure of different sets of landscape metrics as a whole under different situations via principal component analysis (PCA). We used the congruence coefficient (rc) to calculate the changes in factor structures under different situations. We used 16 class-level and 15 landscape-level metrics of 900 village-based and 150 town-based samples that were collected from three regions. Five cell sizes, two land-use classes, and two sets of land-use metrics were also considered. We did not control the cell sizes, sample extent, and different landscapes in the sensitivity analysis to study the interactive relationships between different factors. All factors strongly influence the correlation structure of the landscape metrics, with each factor demonstrating a unique influence. Changing cell size significantly affects the correlation structures in the plain region, especially in croplands and built-up lands. Town-based results show a relatively more stable correlation structure than village-based results (except in land-use categories). Different land-use classes show different responses to changing cell size, sample extent, and sets of landscape metrics in different regions. These results show the great interactive influences of these factors, which have often been overlooked in previous studies. The conclusions drawn from fixed factors may be conditional and inapplicable to other situations. The sensitivity of the correlation structure in diverse regions may improve our understanding of landscape metrics as a whole and can provide further insights into the correlation structure of landscape metrics for land-use management and monitoring. © 2015 Elsevier Ltd. All rights reserved.


Chen Z.,East China University of Technology | Chen Z.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Wang S.,East China University of Technology | Wang S.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring | Wang Z.,Yangtze Estuary Hydrology and Water Resources Survey Bureau
Flow Measurement and Instrumentation | Year: 2016

Spatiotemporal fitting by the least squares method is commonly applied to separate the mean flow (runoff) and tidal current from vessel-mounted ADCP data in tidal reach. To analyze this technique in an estuary region with interaction of the runoff and tide, three sets of 29-h periods vessel-mounted ADCP data in Yangtze Estuary is tested. A diverse set of basis functions is studied and a nodes determination method, named gradient algorithm, is proposed for comparison purposes. The Green function together with a nodal configuration determined by gradient algorithm is the best option. In general, the semi-major axis of the principal tidal ellipse (M2) is parallel to the riverbank and the phase of shoal waters is ahead of that of thalweg, in keeping with shallow-water tide wave dynamics. Because the tidal currents in Yangtze Estuary are explained by shallow-water tide wave dynamics, the use of the Green function and gradient algorithm in the spatiotemporal fitting by least squares technique is a promising scheme for detiding vessel-mounted ADCP data in shallow-water tide wave dynamics systems. © 2016 Elsevier Ltd


Lu T.,East China University of Technology | Lu T.,Chang'an University | Lu T.,Key Laboratory of Watershed Ecology and Geographical Environment Monitoring
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | Year: 2016

Computational problem of gross errors estimation is discussed based on the mean shift model, and the gross errors estimation formulas of the observed statistical correlation data snooping method are given. The relationships of gross errors estimation of the data snooping method, the method of simultaneous locating and evaluating multidimensional gross errors (LEGE), quasi-accurate detection of gross errors (QUAD) method and the partial least-squares (PLS) method are discussed. It is proved that ①in the case of correlated observations, calculation of gross errors estimation of the PLS method and the QUAD method are equivalent. However, these two methods are different with the data snooping method and the LEGE method; ②in the case of uncorrelated and unequal weight observations, calculation of gross errors estimation of the QUAD method, the PLS method and the data snooping method are equivalent, but these three methods are different with the LEGE method; ③in the case of uncorrelated and equal weight observations, calculation of gross errors estimated value of these four methods are equivalent. Finally, the case studies verify the conclusions. © 2016, Surveying and Mapping Press. All right reserved.

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