Expert Knowledge as Basis for Assessing an Automatic Matching Procedure

In the past number of years there has been an amazing flourishing of spatial data products released with open licenses. Researchers and professionals are extensively exploiting open geodata for many applications, which, in turn, include decision-making results and other (derived) geospatial datasets among their outputs. Despite the traditional availability of metadata, a question arises about the actual quality of open geodata, as their declared quality is typically given for granted without any systematic assessment. The present work investigates the case study of Milan Municipality (Northern Italy). A wide set of open geodata are available for this area which are released by national, regional and local authoritative entities. A comprehensive cataloguing operation is first performed, with 1061 geospatial open datasets from Italian providers found which highly differ in terms of license, format, scale, content, and release date. Among the many quality parameters for geospatial data, the work focuses on positional accuracy. An example of positional accuracy assessment is described for an openly-licensed orthophoto through comparison with the official, up-to-date, and large-scale vector cartography of Milan. The comparison is run according to the guidelines provided by ISO and shows that the positional accuracy declared by the orthophoto provider does not correspond to the reality. Similar results are found from analyses on other datasets (not presented here). Implications are twofold: raising the awareness on the risks of using open geodata by taking their quality for granted; and highlighting the need for open geodata providers to introduce or refine mechanisms for data quality control.

Download Full-text

Study of NSSDA Variability by Means of Automatic Positional Accuracy Assessment Methods

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8120552 ◽

2019 ◽

Vol 8 (12) ◽

pp. 552 ◽

Cited By ~ 2

Author(s):

Juan José Ruiz-Lendínez ◽

Francisco Javier Ariza-López ◽

Manuel Antonio Ureña-Cámara

Keyword(s):

Theoretical Analysis ◽

Sample Size ◽

Spatial Data ◽

Graphical Representation ◽

Accuracy Assessment ◽

Experimental Tests ◽

National Standard ◽

Positional Accuracy ◽

Check Points ◽

Spatial Dataset

Point-based standard methodologies (PBSM) suggest using ‘at least 20’ check points in order to assess the positional accuracy of a certain spatial dataset. However, the reason for decreasing the number of checkpoints to 20 is not elaborated upon in the original documents provided by the mapping agencies which develop these methodologies. By means of theoretical analysis and experimental tests, several authors and studies have demonstrated that this limited number of points is clearly insufficient. Using the point-based methodology for the automatic positional accuracy assessment of spatial data developed in our previous study Ruiz-Lendínez, et al (2017) and specifically, a subset of check points obtained from the application of this methodology to two urban spatial datasets, the variability of National Standard for Spatial Data Accuracy (NSSDA) estimations has been analyzed according to sample size. The results show that the variability of NSSDA estimations decreases when the number of check points increases, and also that these estimations have a tendency to underestimate accuracy. Finally, the graphical representation of the results can be employed in order to give some guidance on the recommended sample size when PBSMs are used.

Download Full-text

Automatic Positional Accuracy Assessment of Imagery Segmentation Processes: A Case Study

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10070430 ◽

2021 ◽

Vol 10 (7) ◽

pp. 430

Author(s):

Juan J. Ruiz-Lendínez ◽

Manuel A. Ureña-Cámara ◽

José L. Mesa-Mingorance ◽

Francisco J. Quesada-Real

Keyword(s):

High Resolution ◽

Quality Assessment ◽

Accuracy Assessment ◽

Geographic Information ◽

Aerial Image ◽

Positional Accuracy ◽

Key Aspects ◽

Very High ◽

The Ideal

There are many studies related to Imagery Segmentation (IS) in the field of Geographic Information (GI). However, none of them address the assessment of IS results from a positional perspective. In a field in which the positional aspect is critical, it seems reasonable to think that the quality associated with this aspect must be controlled. This paper presents an automatic positional accuracy assessment (PAA) method for assessing this quality component of the regions obtained by means of the application of a textural segmentation algorithm to a Very High Resolution (VHR) aerial image. This method is based on the comparison between the ideal segmentation and the computed segmentation by counting their differences. Therefore, it has the same conceptual principles as the automatic procedures used in the evaluation of the GI´s positional accuracy. As in any PAA method, there are two key aspects related to the sample that were addressed: (i) its size—specifically, its influence on the uncertainty of the estimated accuracy values—and (ii) its categorization. Although the results obtained must be taken with caution, they made it clear that automatic PAA procedures, which are mainly applied to carry out the positional quality assessment of cartography, are valid for assessing the positional accuracy reached using other types of processes. Such is the case of the IS process presented in this study.

Download Full-text

Rigorous Calibration of UAV-Based LiDAR Systems with Refinement of the Boresight Angles Using a Point-to-Plane Approach

Sensors ◽

10.3390/s19235224 ◽

2019 ◽

Vol 19 (23) ◽

pp. 5224

Author(s):

Elizeu Martins de Oliveira Junior ◽

Daniel Rodrigues dos Santos

Keyword(s):

Point Cloud ◽

State Of The Art ◽

Accuracy Assessment ◽

Point Clouds ◽

Navigation Systems ◽

The Novel ◽

Positional Accuracy ◽

Before And After ◽

Very High ◽

Calibration Parameters

Advances in micro-electro-mechanical navigation systems and lightweight LIDAR (light detection and ranging) sensors onboard unmanned aerial vehicles (UAVs) provide the feasibility of deriving point clouds with very high and homogeneous point density. However, the deformations caused by numerous sources of errors should be carefully treated. This work presents a rigorous calibration of UAV-based LiDAR systems with refinement of the boresight angles using a point-to-plane approach. Our method is divided into a calibration and a parameter mounting refinement part. It starts with the estimation of the calibration parameters and then refines the boresight angles. The novel contribution of the paper is two-fold. First, we estimate the calibration parameters conditioning the centroid of a plane segmented to lie on its corresponding segmented plane without an additional surveying campaign. Second, we refine the boresight angles using a new point-to-plane model. The proposed method is evaluated by analyzing the accuracy assessment of the adjusted point cloud to point/planar features before and after the proposed method. Compared with the state-of-the-art method, our proposed method achieves better positional accuracy.

Download Full-text

Positional Accuracy Assessment of Googleearth in Riyadh

Artificial Satellites ◽

10.2478/arsa-2014-0008 ◽

2014 ◽

Vol 49 (2) ◽

pp. 101-106 ◽

Cited By ~ 12

Author(s):

Ashraf Farah ◽

Dafer Algarni

Keyword(s):

Social Interactions ◽

Spatial Data ◽

Accuracy Assessment ◽

Google Earth ◽

Geographical Information ◽

Small Scale ◽

Positional Accuracy ◽

Kingdom Of Saudi Arabia ◽

Information Program ◽

Private And Public

ABSTRACT Google Earth is a virtual globe, map and geographical information program that is controlled by Google corporation. It maps the Earth by the superimposition of images obtained from satellite imagery, aerial photography and GIS 3D globe. With millions of users all around the globe, GoogleEarth® has become the ultimate source of spatial data and information for private and public decision-support systems besides many types and forms of social interactions. Many users mostly in developing countries are also using it for surveying applications, the matter that raises questions about the positional accuracy of the Google Earth program. This research presents a small-scale assessment study of the positional accuracy of GoogleEarth® Imagery in Riyadh; capital of Kingdom of Saudi Arabia (KSA). The results show that the RMSE of the GoogleEarth imagery is 2.18 m and 1.51 m for the horizontal and height coordinates respectively.

Download Full-text

DO OPEN GEODATA ACTUALLY HAVE THE QUALITY THEY DECLARE? THE CASE STUDY OF MILAN, ITALY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b2-609-2016 ◽

2016 ◽

Vol XLI-B2 ◽

pp. 609-614

Author(s):

M. A. Brovelli ◽

M. Minghini ◽

M. E. Molinari ◽

M. Molteni

Keyword(s):

Spatial Data ◽

Large Scale ◽

Accuracy Assessment ◽

Quality Parameters ◽

Data Quality Control ◽

Positional Accuracy ◽

Systematic Assessment ◽

Open Datasets ◽

The Many

In the past number of years there has been an amazing flourishing of spatial data products released with open licenses. Researchers and professionals are extensively exploiting open geodata for many applications, which, in turn, include decision-making results and other (derived) geospatial datasets among their outputs. Despite the traditional availability of metadata, a question arises about the actual quality of open geodata, as their declared quality is typically given for granted without any systematic assessment. The present work investigates the case study of Milan Municipality (Northern Italy). A wide set of open geodata are available for this area which are released by national, regional and local authoritative entities. A comprehensive cataloguing operation is first performed, with 1061 geospatial open datasets from Italian providers found which highly differ in terms of license, format, scale, content, and release date. Among the many quality parameters for geospatial data, the work focuses on positional accuracy. An example of positional accuracy assessment is described for an openly-licensed orthophoto through comparison with the official, up-to-date, and large-scale vector cartography of Milan. The comparison is run according to the guidelines provided by ISO and shows that the positional accuracy declared by the orthophoto provider does not correspond to the reality. Similar results are found from analyses on other datasets (not presented here). Implications are twofold: raising the awareness on the risks of using open geodata by taking their quality for granted; and highlighting the need for open geodata providers to introduce or refine mechanisms for data quality control.

Download Full-text