scholarly journals RESEARCH ON ACCURACY EVALUATION METHOD BASED ON THE RESULT OF IMAGE CORRECTION AT 10000-SCENES CLASS

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 595-599
Author(s):  
M. Li ◽  
H. P. Chen ◽  
B. Qiu ◽  
W. J. Xie ◽  
Y. H. Chen
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Evaluation Method ◽  
Geographic Information ◽  
Accuracy Evaluation ◽  
Image Correction ◽  
Improved Method ◽  
Automatic Matching ◽  
Economic Construction ◽  
Mean Square Errors

Abstract. In the project of National Fundamental Geographic Information Database Updating, the high-qualified orthorectification to a bulk of remote sensing images are the foundations that guarantee the reliable geographic information for national economic construction and social developments. Therefore, quality control for orthorectification, as a crucial step during remote sensing, is of great significance. Basically, the image orthorectification have been achieved by automatic matching of millions of frame-referenced images. In this paper, a make-to-measure method is devised with improvement in the way of sampling and plane precision evaluation. The improved method is verified through nine 1:1million scenes across the nation. Stratified sampling is deployed according to the topographical features and locations geo-information is collected referring to the digital orthorectification model (DOM) results of geographical conditions Monitoring in 2017. The results show that the root mean square errors (RMSEs) calculated by improved methods described in this paper are highly consistent with the RMSEs that are calculated by automatic image matching, which means the improved method can adequately evaluate the nationwide accuracy of image correction and enable to provide reference and instruction for the large-scale, 10000-scenes class quality assurance of the image correction.

scholarly journals Application and analysis of image modeling based on UAV

2020 ◽  
Vol 206 ◽  
pp. 01026
Author(s):  
Shuheng Wang ◽  
Xuefeng Niu ◽  
Chunyu Zhu ◽  
Xiang Wu ◽  
Shi Liu
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Line Drawing ◽  
Geographic Information ◽  
Good Effect ◽  
Image Modeling ◽  
Rapid Acquisition ◽  
Ground Control Points ◽  
Information Products ◽  
Economic Construction

As one of the important geographic information products, orthophotos play an extremely important role in the field of geographic information. With the rapid development of China’s economic construction and the continuous improvement of photogrammetry technology, traditional orthophoto has been replaced by real orthophoto to meet the requirements of large-scale accurate mapping. This article discusses the method of generating real shot images, uses drone images, and uses Zhanwei New Village in Wuhan as the survey area to lay out the ground control points. Based on Pix4D modeling, the air and three encryptions are completed and based on high-precision DSM Quickly generate real radiography products. The research in this paper shows that the corrected real image can eliminate the phenomenon of blocking the wall and the problem of occlusion. It has a good effect and can be used in the field of line drawing maps. It provides a simple and quick solution for the rapid acquisition of orthophotos in the field of photogrammetry.

scholarly journals A Precision Evaluation Method for Remote Sensing Data Sampling Based on Hexagon Discrete Grid

2020 ◽  
Author(s):  
Yue Ma ◽  
Guoqing Li ◽  
Xiaochuang Yao ◽  
Jin Ben ◽  
Qianqian Cao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation System ◽  
Evaluation Method ◽  
Remote Sensing Data ◽  
Accuracy Evaluation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Hexagonal Grids ◽  
Discrete Grid

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

scholarly journals STUDY ON MODELING AND VISUALIZING THE POSITIONAL UNCERTAINTY OF REMOTE SENSING IMAGE

2016 ◽  
Vol XLI-B2 ◽  
pp. 305-312
Author(s):  
Weili Jiao ◽  
Tengfei Long ◽  
Saiguang Ling ◽  
Guojin He
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Traditional Method ◽  
Evaluation Method ◽  
Control Point ◽  
Remote Sensing Image ◽  
Error Distribution ◽  
Distribution Model ◽  
Control Points ◽  
Mean Square Errors

It is inevitable to bring about uncertainty during the process of data acquisition. The traditional method to evaluate the geometric positioning accuracy is usually by the statistical method and represented by the root mean square errors (RMSEs) of control points. It is individual and discontinuous, so it is difficult to describe the error spatial distribution. In this paper the error uncertainty of each control point is deduced, and the uncertainty spatial distribution model of each arbitrary point is established. The error model is proposed to evaluate the geometric accuracy of remote sensing image. Then several visualization methods are studied to represent the discrete and continuous data of geometric uncertainties. The experiments show that the proposed evaluation method of error distribution model compared with the traditional method of RMSEs can get the similar results but without requiring the user to collect control points as checkpoints, and error distribution information calculated by the model can be provided to users along with the geometric image data. Additionally, the visualization methods described in this paper can effectively and objectively represents the image geometric quality, and also can help users probe the reasons of bringing the image uncertainties in some extent.

The modifiable areal unit problem (MAUP) in physical geography

2007 ◽  
Vol 31 (5) ◽  
pp. 471-479 ◽  
Author(s):  
Shawna J. Dark ◽  
Danielle Bram
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Statistical Analysis ◽  
Geographic Information Systems ◽  
Large Scale ◽  
Geographic Information ◽  
Physical Geography ◽  
Modifiable Areal Unit Problem ◽  
Areal Unit ◽  
Quantitative Studies

Of particular importance to the study of large-scale phenomena in physical geography is the modifiable areal unit problem ( MAUP). While often viewed as only a problem in human geography (particularly demographic studies), the MAUP is an issue for all quantitative studies in geography of spatial phenomena (Openshaw and Taylor, 1979). Increasingly, remote sensing and Geographic Information Systems ( GIS) are being used to assess the distribution of phenomena from a large scale. These phenomena are modelled using areal units that can take any shape or size resulting in complications with statistical analysis related to both the scale and method used to create the areal units. In this paper, we define the modifiable areal unit problem, present examples of when it is a problem in physical geography studies, and review some potential solutions to the problem. Our aim is to increase awareness of this complicated issue and to promote further discussion and interest in this topic.

scholarly journals A Precision Evaluation Index System for Remote Sensing Data Sampling Based on Hexagonal Discrete Grids

2021 ◽  
Vol 10 (3) ◽  
pp. 194
Author(s):  
Yue Ma ◽  
Guoqing Li ◽  
Xiaochuang Yao ◽  
Qianqian Cao ◽  
Long Zhao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation Method ◽  
Remote Sensing Data ◽  
Evaluation Index System ◽  
Accuracy Evaluation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Hexagonal Grids ◽  
Discrete Grid

With the rapid development of earth observation, satellite navigation, mobile communication, and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. As a new form of data management, the global discrete grid can be used for the efficient storage and application of large-scale global spatial data, which is a digital multiresolution georeference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing, and application of current spatial data. There are different types of grid systems according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, as well as establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves the availability of the hexagonal-grid-based remote sensing data of remote sensing images. This evaluation method is generally applicable to all raster remote sensing images based on hexagonal grids, and it can be used to evaluate the availability of hexagonal grid images.

scholarly journals STUDY ON MODELING AND VISUALIZING THE POSITIONAL UNCERTAINTY OF REMOTE SENSING IMAGE

2016 ◽  
Vol XLI-B2 ◽  
pp. 305-312
Author(s):  
Weili Jiao ◽  
Tengfei Long ◽  
Saiguang Ling ◽  
Guojin He
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Traditional Method ◽  
Evaluation Method ◽  
Control Point ◽  
Remote Sensing Image ◽  
Error Distribution ◽  
Distribution Model ◽  
Control Points ◽  
Mean Square Errors

It is inevitable to bring about uncertainty during the process of data acquisition. The traditional method to evaluate the geometric positioning accuracy is usually by the statistical method and represented by the root mean square errors (RMSEs) of control points. It is individual and discontinuous, so it is difficult to describe the error spatial distribution. In this paper the error uncertainty of each control point is deduced, and the uncertainty spatial distribution model of each arbitrary point is established. The error model is proposed to evaluate the geometric accuracy of remote sensing image. Then several visualization methods are studied to represent the discrete and continuous data of geometric uncertainties. The experiments show that the proposed evaluation method of error distribution model compared with the traditional method of RMSEs can get the similar results but without requiring the user to collect control points as checkpoints, and error distribution information calculated by the model can be provided to users along with the geometric image data. Additionally, the visualization methods described in this paper can effectively and objectively represents the image geometric quality, and also can help users probe the reasons of bringing the image uncertainties in some extent.

scholarly journals AUTOMATIC EVALUATION OF THE INITIAL GEOPOSITIONING ACCURACY FOR LARGE AREA PLANETARY REMOTE SENSING IMAGES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1125-1128
Author(s):  
X. Geng ◽  
Q. Xu ◽  
J. Wang ◽  
S. Xing
Keyword(s):  
Remote Sensing ◽  
Image Matching ◽  
Evaluation Method ◽  
Window Size ◽  
Bundle Adjustment ◽  
Conjugate Points ◽  
Accuracy Evaluation ◽  
Automatic Evaluation ◽  
Remote Sensing Images ◽  
Large Area

Abstract. The photogrammetric processing of large area planetary remote sensing images is still a very challenging work. In addition to the lack of ground control data and poor tie points extraction, the insufficient knowledge of the initial geopositioning accuracy of the planetary images also increases the difficulty of processing. This paper presents an automatic evaluation method of the initial geopositioning accuracy for large area planetary remote sensing images. The accuracy evaluation method was conducted through image matching on approximate orthophotos derived using coarse resolution digital elevation model (DEM). To improve the orthophotos generation efficiency of linear pushbroom images, a fast ground-to-image transformation algorithm and multi-threaded parallel computing are adopted. The classical normalized cross correlation (NCC) and pyramid matching schemes are used to perform image matching between overlapping orthophotos. Because the conjugate points on orthophotos contain geographic coordinates, we can derive the statistics information (e.g., maximum errors, mean errors and standard deviation) about the geopositioning accuracy of the planetary images. Although it’s actually an evaluation result of relative accuracy, the quantitative geopositioning accuracy information of stereopairs can be used to (1) specify the search window size and the starting position of conjugate points for tie points extraction; (2) set the weight value of bundle adjustment; and (3) identify images with abnormal geopositioning accuracy. Tens of Mars Express (MEX) High Resolution Stereo Camera (HRSC) images were used to conduct the test. The experimental results demonstrate that the proposed method shows high computational efficiency and automation degree. The automatic evaluation of the initial geopositioning accuracy of the planetary images is helpful to produce large area planetary mapping products.

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