Abstract

This paper introduces a new method to analyze the positional accuracy of georeferenced satellite images without the use of ground control points. Compared to the traditional method used to carry out this kind of analysis, our approach provides a semiautomatic way to obtain a larger number of control points that satisfy the requirements of current standards regarding the size of the set of sample points, the positional accuracy of such points, the distance between points, and the distribution of points in the sample. Our methodology exploits high quality orthoimages, such as those provided by the Aerial Orthography National Plan (PNOA)—developed by the Spanish National Geographic Institute—and has been tested on spatial data from Landsat 8. Our method works under the current international standard (ASPRS 2014) and exhibits similar performance than other well-known methods to analyze the positional accuracy of georeferenced images based on the use of independent ground control points. More specifically, the positional accuracy achieved for a Landsat 8 dataset evaluated by the traditional method is 5.22 ± 1.95 m, and when evaluated with the proposed method, it exhibits a typical accuracy of 5.76 ± 0.50 m. Our experimental results confirm that the method is equally effective and less expensive than other available methods to analyze the positional accuracy of satellite images.

Highlights

  • Remote sensing (RS) and geographical information systems (GIS) are playing an increasingly significant role in Earth science and related disciplines and their applications, including land cover mapping [1], precision agriculture [2], biodiversity [3], climate [4], snow-glacier monitoring, terrestrial temperature, erosion, flood monitoring, ocean coast monitoring, and biodiversity [5]

  • Conforming to the generally accepted traditional method, the analysis of positional accuracy of the satellite image on the study area (SA) selected suggests that the included geo‐references have an accuracy of 5.22 m with a standard deviation of ±1.95 m, which means that geo‐references are typically 5.22 m away from the center of pixel, with a confidence interval of ±1.95 m

  • It is worth noting that distances with a standard deviation of ±1.95 m, which means that geo-references are typically 5.22 m away from the center of pixel, with a confidence interval of ±1.95 m

Read more

Summary

Introduction

Remote sensing (RS) and geographical information systems (GIS) are playing an increasingly significant role in Earth science and related disciplines and their applications, including land cover mapping [1], precision agriculture [2], biodiversity [3], climate [4], snow-glacier monitoring, terrestrial temperature, erosion, flood monitoring, ocean coast monitoring, and biodiversity [5]. RS, GIS, and DSS must provide tools to precisely determine the degree of accuracy, resolution, and integrity of positional data [7]. A geo-referenced image includes an additional data set for each pixel p in the image, which contains a pair of xy-coordinates pxy with terrestrial information about the location of that particular pixel. Taking into account that the geometric resolution of the image defines the pixel size, the geo-referencing process guarantees that each xy-coordinate pair is always inside the limits of the corresponding pixel

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call