LiDAR-Derived High Quality Ground Control Information and DEM for Image Orthorectification

Abstract

Orthophotos (or orthoimages if in digital form) have long been recognised as a supplement or alternative to standard maps. The increasing applications of orthoimages require efforts to ensure the accuracy of produced orthoimages. As digital photogrammetry technology has reached a stage of relative maturity and stability, the availability of high quality ground control points (GCPs) and digital elevation models (DEMs) becomes the central issue for successfully implementing an image orthorectification project. Concerns with the impacts of the quality of GCPs and DEMs on the quality of orthoimages inspire researchers to look for more reliable approaches to acquire high quality GCPs and DEMs for orthorectification. Light Detection and Ranging (LiDAR), an emerging technology, offers capability of capturing high density three dimensional points and generating high accuracy DEMs in a fast and cost-effective way. Nowadays, highly developed computer technologies enable rapid processing of huge volumes of LiDAR data. This leads to a great potential to use LiDAR data to get high quality GCPs and DEMs to improve the accuracy of orthoimages. This paper presents methods for utilizing LiDAR intensity images to collect high accuracy ground coordinates of GCPs and for utilizing LiDAR data to generate a high quality DEM for digital photogrammetry and orthorectification processes. A comparative analysis is also presented to assess the performance of proposed methods. The results demonstrated the feasibility of using LiDAR intensity image-based GCPs and the LiDAR-derived DEM to produce high quality orthoimages.

Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan

“…However, due to the facts that most landslide areas are often located in areas with high mountains and forests featuring rugged terrain and poor traffic accessibility, with only a limited number of image characteristic points, the representativeness of error assessment might be adversely influenced due to the lack of sufficient ground measurement points, leading to potential underestimation. There are reported studies in which aerotriangulation or aerial photogrammetry operations were conducted by using high-precision LiDAR DEM data as control points or a reference terrain surface [48][49][50]. With the six periods of DTM data generated using various techniques in this study, in order to avoid the impacts of insufficient ground control points on error estimation, the DEM data from 2011 were used as the reference elevation.…”

Quantifying the Accuracy of LiDAR-Derived DEM in Deciduous Eastern Forests of the Cumberland Plateau

“…In forestry, DEMs are commonly used in hydrological applications (i.e., [4] [5]) and increasingly in forest operations planning (i.e., [6] [7] [8]). The accuracy of LiDAR-derived DEMs is considerably higher than DEMs derived from alternative sources such as aerial photography or satellite imagery [1] [2] [9], which facilitates the creation of high-resolution DEMs (≤1 m) and in turn increases their applications.…”

“…The accuracy in altimetry of high-resolution LiDAR-derived DEMs is commonly reported by data providers to be between 15 -25 cm [9] [10] [11]. However, elevation errors are typically measured on flat, smooth terrain with no vegetation cover [12] [13].…”

A Linear Feature-Based Approach for the Registration of Unmanned Aerial Vehicle Remotely-Sensed Images and Airborne LiDAR Data

“…The feature-based methods are relatively well suited for the registration of UAVRS optical images and airborne LiDAR data as they both contain enough distinctive and easily-detectable objects for the registration. There has been a considerable amount of research into feature-based registration [6,[12][13][14][15][16][20][21][22][27][28][29][30][31], among which the point features are the most commonly used features, which can be attributed to their uniqueness and simplicity.…”