The role of morphometric parameters in Digital Terrain Models interpolation accuracy: a case study

AbstractIn the present study different algorithms, usually available in GIS environment, are analyzed in order to spot an optimal interpolation methodology and to define, by classification techniques, which morphological variable affects the interpolation quality. The investigated dataset is a helicopter-borne laser scanner survey carried out on a mountain slope. It has been interpolated at various resolutions, and a percentage of the entire set has been employed to evaluate the interpolation accuracy.The analysis has highlighted, among the tested interpolators, the Natural Neighbour as the best one. The classification has drawn the attention to the total curvature and slope as the main factors affecting interpolation accuracy. The next goal is the mapping of such classification results

Análisis y validación de modelos digitales de elevaciones mediante datos LIDAR

entre otras, siendo en muchas ocasiones uno de los factores determinantes de la calidad de sus estudios. En este trabajo se realiza un análisis comparativo entre Modelos Digitales de Elevaciones (MDE) generados mediante diferentes métodos de interpolación y uno obtenido mediante tecnología LIDAR. De esta forma, asumiendo este último como verdad-terreno, se establece cual de los modelos interpolados representa con mayor fidelidad la superficie terrestre. Las técnicas de interpolación utilizadas han sido la lineal, splines, TIN y ANUDEM obteniendo un total de 4 MDEs interpolados. El análisis de los errores en los diferentes modelos se ha llevado a cabo mediante tres procedimientos 1. Análisis de la distribución del error de las elevaciones en los MDEs interpolados. 2. Evaluación de los errores en varias capas de variables derivadas del MDE 3. Evaluación de los errores de localización de las redes de drenaje extraídas de los diferentes modelos respecto a la red generada a partir del modelo LIDAR. Con respecto a la ubicación de la red de drenaje, se han estimado dos tipos de error: error de omisión y error de comisión.Terrain modelling is an important task in many scientific areas such as climatology, hydrology among others, with a deep influence on the quality of the results. In this work we make a comparative analysis of Digital Elevation Model (DEM) generated by different interpolation algorithms with one obtained by LIDAR technology, assuming the later as ground truth. Four different interpolation algorithms have been used: linear splines, TIN and ANUDEM, that means a total of four interpolated DEMs. The analysis of errors in the different models was carried out with three different procedures: 1. Error distribution analysis in the interpolated DEMs. 2. Error evaluation in terrain parameters derived from DEM. 3. Analysis of the positional errors in the extract

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

Using historical aerial photography for monitoring of environment changes: a case study of Bovan Lake, Eastern Serbia

Useful and important information for the spatial, ecological, and many other changes in the living environment may be obtained using the analysis of historical aerial photography, with comparison to contemporary imagery. This method provides the ability to determine the state of elements of the space over a long period, encompassing the time when it was not possible to acquire the data from satellite imagery or some other contemporary sources. Aerial images are suitable for mapping spatial phenomena with relatively limited spatial distribution because they possess a high level of details and low spatial coverage. With a comparative analysis of aerial imagery from the past, contemporary aerial imagery, and other sources of aerial imagery, we can obtain information about the nature and trends of the observed phenomena as well as directions of future actions, considering changes detected in the environment, whether they are preventive or corrective in nature. This paper gives the methodological framework for the appliance of the existing knowledge from various fields, intending to use historical aerial photography for monitoring of environmental changes of the Bovan Lake in Eastern Serbia

On generating digital elevation models from liDAR data – resolution versus accuracy and topographic wetness index indices in northern peatlands

Global change and GHG emission modelling are dependent on accurate wetness estimations for predictions of e.g. methane emissions. This study aims to quantify how the slope, drainage area and the TWI vary with the resolution of DEMs for a flat peatland area. Six DEMs with spatial resolutions from 0.5 to 90 m were interpolated with four different search radiuses. The relationship between accuracy of the DEM and the slope was tested. The LiDAR elevation data was divided into two data sets. The number of data points facilitated an evaluation dataset with data points not more than 10 mm away from the cell centre points in the interpolation dataset. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. It showed independence of the resolution when using the same search radius. The accuracy of the estimated elevation for different slopes was tested using the 0.5 meter DEM and it showed a higher deviation from evaluation data for steep areas. The slope estimations between resolutions showed differences with values that exceeded 50%. Drainage areas were tested for three resolutions, with coinciding evaluation points. The model ability to generate drainage area at each resolution was tested by pair wise comparison of three data subsets and showed differences of more than 50% in 25% of the evaluated points. The results show that consideration of DEM resolution is a necessity for the use of slope, drainage area and TWI data in large scale modelling

Interpolation routines assessment in ALS-derived Digital Elevation Models for forestry applications

Airborne Laser Scanning (ALS) is capable of estimating a variety of forest parameters using different metrics extracted from the normalized heights of the point cloud using a Digital Elevation Model (DEM). In this study, six interpolation routines were tested over a range of land cover and terrain roughness in order to generate a collection of DEMs with spatial resolution of 1 and 2 m. The accuracy of the DEMs was assessed twice, first using a test sample extracted from the ALS point cloud, second using a set of 55 ground control points collected with a high precision Global Positioning System (GPS). The effects of terrain slope, land cover, ground point density and pulse penetration on the interpolation error were examined stratifying the study area with these variables. In addition, a Classification and Regression Tree (CART) analysis allowed the development of a prediction uncertainty map to identify in which areas DEMs and Airborne Light Detection and Ranging (LiDAR) derived products may be of low quality. The Triangulated Irregular Network (TIN) to raster interpolation method produced the best result in the validation process with the training data set while the Inverse Distance Weighted (IDW) routine was the best in the validation with GPS (RMSE of 2.68 cm and RMSE of 37.10 cm, respectively)

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 LiDARderived DEM to produce high quality orthoimages

Civil integrated management and the implementation of CIM-related technologies in the transportation industry

As advanced technologies are adopted in the transportation industry, it is important to investigate how they can be integrated and better utilized to facilitate the success of public transportation agencies. It is also important to devise efficient ways to address the considerable amount of digital data created as these technologies are used. A newly introduced concept – Civil Integrated Management (CIM) – has potential for addressing these issues, because it involves collection, organization, and managed accessibility of accurate data and information throughout the transportation asset lifecycle. CIM is also expected to facilitate the use of various advanced technologies, so the purpose of this dissertation is to further explore the concept of CIM and investigate how it can be implemented to assist with transportation projects and programs. After initial preparation (i.e., conducting literature reviews, consulting with experts, developing questionnaires, and identifying target agencies), two weeks of on-site visits were conducted with seven state transportation agencies to document their insights and practices associated with the CIM concept. Coding strategies were used to analyze the field notes collected from the presentations provided by host agencies and discussions throughout the visits. To further investigate one of the CIM enabling technologies – light detection and ranging (LiDAR), a web-based survey was disseminated to 28 LiDAR professionals; it produced 15 responses. Five phone interviews were also conducted using the Delphi method to develop a LiDAR data utilization workflow for 3D modeling. To investigate another CIM enabling technology – an electronic document management (EDM) system, important data related to EDM practices were extracted from field notes obtained from the CIM on-site visits. Meanwhile, follow-up interviews were conducted with the four transportation agencies identified as leading agencies with respect to EDM, and a video interview was conducted with one additional construction company involved with enterprise-level EDM implementation. As pioneering research on CIM, the results of this dissertation provide transportation agencies and other researchers with an essential roadmap for implementing and refining the CIM concept. The findings and recommendations listed in this dissertation are also expected to assist transportation agencies in better utilizing and integrating various CIM-related technologies into their transportation projects and programs

Analysis of LiDAR point data and derived elevation models for mapping and characterizing bouldery landforms

This thesis assessed the viability of using LiDAR-derived elevation data in accurately mapping and characterizing bouldery geomorphic features in a study area in the Allegheny Mountains. This study showed that the ground returns classification process conducted by the Canaan Valley Institute (CVI) for their property using the TerraScan software generally removed 5 to 10 m scale local topographic variability and bouldery landforms in creating the CVI classified ground returns data. In open areas, last returns elevation and intensity data were successfully used in this study to map bouldery landforms in the study area. Identifying and describing boulders under a tree canopy required a relatively reliable ground classification of LiDAR points. This study\u27s classifications conducted within Prologic LiDAR Explorer provided a more useful representation than the CVI classified ground data for mapping bouldery landforms and generalized rugged topography. Index overlay for likelihood of presence of bouldery landforms using supervised classified aerial imagery and LiDAR-derived parameters in a raster environment was explored as an alternative means of detecting bouldery landforms because hillshade imagery derived from CVI classified ground data were inadequate for mapping bouldery landforms