期刊:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021年14:2046-2057 ISSN:1939-1404
通讯作者:
Li, Chang
作者机构:
[Li, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Analyzing & Modeling, Wuhan 430079, Peoples R China.;[Li, Xi] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China.;[Li, Tian] Johns Hopkins Univ, Baltimore, MD 21218 USA.;[Yu, Wenjie; Meng, Qi] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构:
[Li, Chang] C;Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Analyzing & Modeling, Wuhan 430079, Peoples R China.
关键词:
Calibration;Radiometry;Mathematical model;Automation;Taylor series;Analytical models;Linear regression;Accuracy;adjusted root-mean-square error (RMSE);automation;defense meteorological satellite program operational linescan system (DMSP-OLS) night-time light (NTL) imagery;least median of squares (LMedS)-based power regression (LBPR);radiometric intercalibration
摘要:
The further scientific applications of DMSP-OLS night-time light (NTL) imagery have been being limited by the accuracy, automation, and speed of radiometric intercalibration. In order to solve the aforementioned problems, this article is the first to propose a new least-median-of-squares (LMedS)-based power regression (LBPR) for automatically radiometric intercalibration and investigate the reasons for the optimal model of radiometric intercalibration, especially those based on the Taylor expansion and probability principle. NTL data in six regions all over the world, from 1994 and 1997 to 2007, were used as the test datasets. When the five kinds of LMedS-based radiometric intercalibration models (i.e., linear, quadratic, power, exponential, and logarithmic regression) are synthetically compared in absolute accuracy (adjusted RMSE) and running speed, it is concluded that the LBPR, which has the highest accuracy and preferable running speed, is recommended as the optimal method, which can also be used as a reference for other types of imagery preprocessing.
关键词:
Epipolar geometry;Graph matching;Line segment matching;Reweighted random walks
摘要:
This paper presents a novel method for matching line segments between stereo images. Given the fundamental matrix, the local homography can be over determined with pairwise line segment candidates. We exploit this constraint to initialize the candidate and construct the novel homography graph. Because the constraint between the node is based on the epipolar geometry, the homography graph is invariant to the local projective transformation. We employ the reweighted random walk on the graph to rank the candidate, then, we propose the constrained-greedy algorithm to obtain the reliable match. To the best of our knowledge, this is the first study to embed the epipolar geometry into the graph matching theory for the line segment matching. When evaluated on the 32 image patches, our method outperformed the state of the art methods, especially in the scenes of the wide baseline, steep viewpoint changes and dense line segments. The proposed algorithm is available at https://github.com/weidong-whu/linematch-RRW. (C) 2020 Elsevier Ltd. All rights reserved.
作者机构:
[Zhu, Heli; Wang, Di; Dong, Jing; Wu, Yijin; Li, Chang; Jiang, Chang] Cent China Normal Univ, Key Lab Geog Proc Analysing & Modelling, 152 Luoyu Rd, Wuhan 430079, Peoples R China.;[Zhu, Heli; Wang, Di; Dong, Jing; Wu, Yijin; Li, Chang; Jiang, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, 152 Luoyu Rd, Wuhan 430079, Peoples R China.;[Ye, Xinyue] New Jersey Inst Technol, Dept Informat, Newark, NJ USA.
通讯机构:
[Li, Chang] C;Cent China Normal Univ, Key Lab Geog Proc Analysing & Modelling, 152 Luoyu Rd, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, 152 Luoyu Rd, Wuhan 430079, Peoples R China.
摘要:
In this paper, the annually average Defense Meteorological Satellite Program-Operational Linescan System (DMSP/OLS) night-time light data is first proposed as a surrogate indicator to mine and forecast the average housing prices in the inland capital cities of China. First, based on the time-series analysis of individual cities, five regression models with gross error elimination are established between average night-time light intensity (ANLI) and average commercial residential housing price (ACRHP) adjusted by annual inflation rate or not from 2002 to 2013. Next, an optimal model is selected for predicting the ACRHPs in 2014 of these capital cities, and then verified by the interval estimation and corresponding official statistics. Finally, experimental results show that the quadratic polynomial regression is the optimal mining model for estimating the ACRHP without adjustments in most provincial capitals and the predicted ACRHP of these cities are almost in their interval estimations except for the overrated Chengdu and the underestimated Wuhan, while the adjusted ACRHP is all in prediction interval. Overall, this paper not only provides a novel insight into time-series ACRHP data mining based on time-series ANLI for capital city scale but also reveals the potentiality and mechanism of the comprehensive ANLI to characterize the complicated ACRHP. Besides, other factors influencing housing prices, such as the time-series lags of government policy, are tested and analysed in this paper.
作者机构:
[龚胜生; 李畅; 王安丽; 孙攸宁] Key Laboratory for Geographical Process Analysis & Simulation, Hubei Province, College of Urban and Environmental Science, Central China Normal University, Wuhan;430079, China;[龚胜生; 李畅; 王安丽; 孙攸宁] 430079, China
通讯机构:
[Gong, S.] K;Key Laboratory for Geographical Process Analysis & Simulation, China
作者机构:
[吴宜进; 赵行双; 奚悦; 李畅] Key Laboratory for Geographical Process Analysis & Simulation, Wuhan;430079, China;College of City and Environmental Science, Central China Normal University, Wuhan;[刘慧] Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing;100101, China
通讯机构:
[Li, C.] K;Key Laboratory for Geographical Process Analysis & Simulation, Wuhan, China
期刊:
International Journal of Geographical Information Science,2018年32(9):1837-1859 ISSN:1365-8816
通讯作者:
Li, Chang
作者机构:
[Zhao, Sisi; Li, Chang] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.;[Zhao, Sisi; Wang, Qing; Li, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.;[Shi, Wenzhong] Hong Kong Polytech Univ, Joint Spatial Informat Res Lab, Hong Kong, Hong Kong, Peoples R China.;[Shi, Wenzhong] Wuhan Univ, Wuhan, Hubei, Peoples R China.
通讯机构:
[Li, Chang] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
关键词:
Digital terrain analysis (DTA);digital elevation model (DEM);surface area calculation (SAC);truncation error (TE);uncertainty modeling
摘要:
In the field of digital terrain analysis (DTA), the principle and method of uncertainty in surface area calculation (SAC) have not been deeply developed and need to be further studied. This paper considers the uncertainty of data sources from the digital elevation model (DEM) and SAC in DTA to perform the following investigations: (a) truncation error (TE) modeling and analysis, (b) modeling and analysis of SAC propagation error (PE) by using Monte-Carlo simulation techniques and spatial autocorrelation error to simulate DEM uncertainty. The simulation experiments show that (a) without the introduction of the DEM error, higher DEM resolution and lower terrain complexity lead to smaller TE and absolute error (AE); (b) with the introduction of the DEM error, the DEM resolution and terrain complexity influence the AE and standard deviation (SD) of the SAC, but the trends by which the two values change may be not consistent; and (c) the spatial distribution of the introduced random error determines the size and degree of the deviation between the calculated result and the true value of the surface area. This study provides insights regarding the principle and method of uncertainty in SACs in geographic information science (GIScience) and provides guidance to quantify SAC uncertainty.
期刊:
International Journal of Remote Sensing,2018年39(21):7350-7369 ISSN:0143-1161
通讯作者:
Li, Chang
作者机构:
[Li, Chang] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.;[Li, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
通讯机构:
[Li, Chang] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
摘要:
To address the problems of parameter selection and accuracy optimization of models in image rectification, this article first proposes a novel stepwise-then-intelligent algorithm (STIA) for image rectification optimization, which includes the following steps. First, stepwise regression is suggested to simultaneously solve the over-parameterization problem and select the optimum parameters of the polynomial model and rational function model according to different terrains. Second, intelligent algorithms, e.g. the genetic algorithm (GA) and particle swarm optimization (PSO), are proposed to search for better results based on an innovative search range determined by the uncertainty propagation and 3-sigma rule. The experimental results show that the proposed STIA can achieve higher accuracy than conventional methods; and in most cases, the PSO algorithm used in STIA is superior to the GA used in STIA in measures of time and accuracy. Moreover, stepwise-then-PSO algorithm exhibits the best performance of all compared methods, including least squares, stepwise regression, total least squares and partial least squares.
摘要:
The grey value g (x, y)of pixel on radiometric spectrum is regarded as a function of the geometric coordinates (x, y). Hence, there is a unity of opposite relationships between the geometric and radiometric information, such that, these two types of information cannot be separated. Therefore, this paper proposes a novel geometric and radiometric simultaneous correction model (GRSCM) framework inspired and developed from least squares matching (LSM). Based on the Gauss-Markov model, geometric and radiometric correction coefficients are integrated and solved by an iterative method with variable weights in the proposed model. Moreover, many state-of-the-art models and methods can be integrated into the proposed general GRSCM framework. In the GRSCM of this paper, RAN-dom SAmple Consensus (RANSAC), step wise regression and significance testing are integrated and used. The experimental results demonstrate that the accuracy of the GRSCM is significantly improved compared with that of geometric correction and radiometric correction separately.