中国科学院机构知识库网格系统: 检索

Spatio-Temporal Characteristics of Drought Events and Their Effects on Vegetation: A Case Study in Southern Tibet, China 期刊论文 OAI收割
REMOTE SENSING, 2020, 卷号: 12, 期号: 24, 页码: 24
作者: Ye, Zu-Xin; Cheng, Wei-Ming; Zhao, Zhi-Qi; Guo, Jian-Yang; Yang, Ze-Xian

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收藏 | 浏览/下载：36/0 | 提交时间：2021/03/15

drought space– time characteristic single event multiple events vegetation southern Tibet

Spatio-Temporal Characteristics of Drought Events and Their Effects on Vegetation: A Case Study in Southern Tibet, China 期刊论文 OAI收割
REMOTE SENSING, 2020, 卷号: 12, 期号: 24, 页码: 24
作者: Ye, Zu-Xin; Cheng, Wei-Ming; Zhao, Zhi-Qi; Guo, Jian-Yang; Yang, Ze-Xian

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收藏 | 浏览/下载：21/0 | 提交时间：2021/03/15

drought space– time characteristic single event multiple events vegetation southern Tibet

Spatio-temporal characteristics of drought events and their effects on vegetation: A case study in Southern Tibet, China 期刊论文 OAI收割
Remote Sensing, 2020, 卷号: 12, 期号: 24, 页码: 1-24
作者: Zu-Xin Ye; Wei-Ming Cheng; Zhi-Qi Zhao; Jian-Yang Guo; Ze-Xian Yang; Rui-Bo Wang; Nan Wang

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收藏 | 浏览/下载：12/0 | 提交时间：2021/03/01

Drought Space–time Characteristic Single Event Multiple Events Vegetation Southern Tibet

Spatiotemporal epidemic characteristics and risk factor analysis of malaria in Yunnan Province, China 期刊论文 OAI收割
BMC PUBLIC HEALTH, 2017, 卷号: 17, 页码: 10
作者: Yang, Dongyang; Xu, Chengdong; Wang, Jinfeng; Zhao, Yong

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收藏 | 浏览/下载：21/0 | 提交时间：2019/09/25

Malaria Epidemiologic characteristic Space-time clusters Risk factors

Spatiotemporal epidemic characteristics and risk factor analysis of malaria in Yunnan Province, China 期刊论文 OAI收割
BMC PUBLIC HEALTH, 2017, 卷号: 17, 页码: 10
作者: Yang, Dongyang; Xu, Chengdong; Wang, Jinfeng; Zhao, Yong

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收藏 | 浏览/下载：13/0 | 提交时间：2019/09/25

Malaria Epidemiologic characteristic Space-time clusters Risk factors

A characteristic space-time conservation element and solution element method for conservation laws 期刊论文 OAI收割
JOURNAL OF COMPUTATIONAL PHYSICS, 2015, 卷号: 288, 页码: 101-118
作者: Shen H; Wen CY; Zhang DL(张德良)

收藏 | 浏览/下载：31/0 | 提交时间：2015/04/28

Space-time conservation element and solution element (CE/SE) method Upwind scheme Characteristic-based scheme Riemann solver

The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Sun H.; Han H.-X.; Sun H.

收藏 | 浏览/下载：57/0 | 提交时间：2013/03/25

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Destriping of TDI-CCD remote sensing image (EI CONFERENCE) 会议论文 OAI收割
2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China
作者: He B.

收藏 | 浏览/下载：28/0 | 提交时间：2013/03/25

Based on the characteristic of striping noise in remote sensing images a new destriping technique for the improved threshold function using lifting wavelet transform is presented in this letter. It can overcome the shortcoming of the hard threshold function and soft threshold function. The lifting wavelet transform is easily realized. Also it is inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the improved threshold function with some traditional threshold functions both by visual inspection and by appropriate indexes of quality of the denoised images. Evaluations of the results based on several image quality indexes indicate that image quality has been improved after destriping. The destriped images are not only visually more plausible but also suitable for computerized analysis and it did better than the existed ones. 2010 IEEE.

Destriping method using lifting wavelet transform of remote sensing image (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者: He B.

收藏 | 浏览/下载：30/0 | 提交时间：2013/03/25

Based on the characteristic of striping noise in remote sensing images a new destriping noise technique for the improved multi-threshold method using lifting wavelet transform applied to remote sensing imagery is presented in this letter. Have used the lifting wavelet decomposition algorithm the thresholds are determined by corresponding wavelet coefficients in every scale. Remote sensing imagery is so large that the algorithm must be fast and effective. The lifting wavelet transform is easily realized and inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the method with some traditional destriping methods both by visual inspection and by appropriate indexes of quality of the denoised images. From the comparison we can see that the adaptive threshold method can preserve the spectral characteristic of the images while effectively remove striping noise and it did better than the existed ones. 2010 IEEE.

An improved two-dimensional entropy method for star trail tracing in deep sky (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Wang Y.-J.; Yao Z.-J.

收藏 | 浏览/下载：30/0 | 提交时间：2013/03/25

The trace of star trail is an important component of deep sky detection. The stars are low contrast targets and their self-rotation will make their brightness change in cycle. Above all the trail trace is vulnerable to the block and disturbance of other stars. Traditional one-dimensional maximum entropy thresholding algorithm is vulnerable to the noise and the calculation of two-dimensional entropy methods is too large and takes too much time. This paper proposes an improved two-dimensional entropy threshold algorithm. We use recursion iteration method to eliminate the redundancy calculation and reduce the size of two-dimensional histogram based on the deep sky stars characteristic such as low contrast fuzziness and the centralized histogram. We also combine our algorithm with the space trail trace model to forecast the star trace. Experiments results show when the star are blocked or they turn dark the method still can well extrapolate the star trace. Our method improves the capability of trailing the ebb and small star and increases the precision of tracing. It is also robust to the noise so there is a good application foreground for the method.