分层随机抽样下全球30 m火烧迹地产品验证

火烧迹地是全球及区域碳循环和气候变化等研究所需的重要参数之一,卫星遥感技术为快速获取大区域火烧迹地空间分布信息提供了有效手段。中国科学院基于Landsat系列卫星数据研发了首个30 m空间分辨率全球火烧迹地产品GABAM (Global Annual Burned Area Map)。遥感数据产品的精度验证对产品使用具有重要意义,迄今尚未有研究机构对GABAM产品精度进行独立评价和分析。为系统评价GABAM产品精度,利用2010年全球30 m空间分辨率火烧迹地产品(GABAM2010)开展精度验证研究工作,在全球和几个陆地生物群落中估算了产品精度,并探索了全球遥感专题产品精度验证的技术框架。基于分层随机抽样选择80个非重叠的泰森多边形区域TSA (Thiessen Scene Areas),采用误差矩阵和6个精度指标对GABAM2010产品做全面精度评价和分析,以满足火烧迹地产品用户的使用要求。结果表明:在全球范围内,GABAM2010产品的错分率和漏分率分别为24.32%和31.60%,总体精度为97.85%;由于数据质量(如条带、云)等的影响,火烧迹地的范围会被低估,对于较容易发生火灾的生物群落,如热带亚热带草原区域,GABAM2010产品精度较高;在生物群落内部,高密度火烧迹地区域的精度高于低密度火烧迹地区域。     

Investigation of Image Fusion Between High—Resolution Image and Multi—Spectral Image

On the basis of a thorough understanding of the physical characteristics of remote sensing image,this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm.The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China The experimental results show that a perfect image fusion can be built up by using the image analytical solution and reconstruction in the image frequency domain based on the physical characteristics of the image formation.The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.     

Similar single-difference model and its algorithm for solving GPS monitoring deformation directly at single epoch

A new similar singledifference mathematical model ( SS-DM) and its corresponding algorithm are advanced to solve the deformation of monitoring point directly in single epoch. The method for building the SSDM is introduced in detail, and the main error sources affecting the accuracy of deformation measurement are analyzed briefly, and the basic algorithm and steps of solving the deformation are discussed. In order to validate the correctness and the accuracy of the similar single-difference model, the test with five dual frequency receivers is carried out on a slideway which moved in plane in Feb. 2001. In the test, five sessions are observed. The numerical results of test data show that the advanced model is correct.     

SAR image classification based on its texture features

SAR images not only have the characteristics of all-ay, all-eather, but also provide object infor-mation which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The au-thors conducted the experiments of texture statistics analysis on SAR im-age features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpreta-tion.     

System structure and calibration models of intelligent photogrammetron

This paper describes the structure,geometric model and geo-metric calibration of Photogrammetron I-the first type of photogrammetron which is designed to be a coherent stereo photogrammetric system in which two cameras are mounted on a physical base but driven by an intelligent agent architecture.The system calibration is divided into two parts:the in-lab calibration determines the fixed parameters in advance of system operation,and the insitu calibration keeps tracking the free parameters in real-time during the system operation.In a video surveillance set-up, prepared control points are tracked in stereo image sequences,so that the free parameters of the system can be continuously updated through iterative bundle adjustment and kalman filtering.     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

In-flight performance analysis of the CHAMP BlackJack GPS Receiver

JPL's BlackJack receiver currently represents the most widely used geodetic grade GPS receiver for space applications. Using data from the CHAMP science mission, the in-flight performance of the BlackJack receiver has been assessed and the impact of various software updates performed during the 2.5 years since launch is described. Key aspects of the study comprise the channel allocation, anomalous data points, and the noise level of the code and carrier data. In addition, it has been demonstrated that the code measurements collected onboard the CHAMP satellite are notably affected by multipath errors in the aft-looking hemisphere, which can be attributed to cross-talk between the occultation antenna string and the primary precise orbit determination antenna. For carrier smoothed 10 s normal points, the code noise itself varies between a minimum of 5 cm at high elevations and 0.5 m (C/A) to 1.0 m (P₁, P₂) at 10° elevation. Carrier-phase data exhibit representative errors of 0.2 to 2.5 mm. The results of the CHAMP GPS data analysis contribute to a better understanding and possible improvement of the BlackJack receiver and support the design of optimal data editing and weighting strategies in precise orbit determination applications.