1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique.

https://research.aalto.fi/files/11427365/liang_isprsjournal.pdf

Terrestrial laser scanning in forest inventories

Forest inventory and management requirements are changing rapidly in the context of an increasingly complex set of economic, environmental, and social policy objectives. Advanced remote sensing technologies provide data to assist in addressing these escalating information needs and to support the subsequent development and parameterization of models for an even broader range of information needs. This special issue contains papers that use a variety of remote sensing technologies to derive forest inventory or inventory-related information. Herein, we review the potential of 4 advanced remote sensing technologies, which we posit as having the greatest potential to influence forest inventories designed to characterize forest resource information for strategic, tactical, and operational planning: airborne laser scanning (ALS), terrestrial laser scanning (TLS), digital aerial photogrammetry (DAP), and high spatial resolution (HSR)/very high spatial resolution (VHSR) satellite optical imagery. ALS, in ...

https://tandfonline.com/doi/pdf/10.1080/07038992.2016.1207484

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The

Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture

Zusammenfassung: Der DGPF-Test zur Evaluation digitaler Luftbildkameras – Uberblick und Testdesign. Dieser Artikel konzentriert sich auf grundsatzliche Anmerkungen zum Test von digitalen photogrammetrischen Luftbildkamerasystemen, durchgefuhrt von der Deutschen Gesellschaft fur Photogrammetrie, Fernerkundung und Geoinformation (DGPF). Der Beitrag soll einen Uberblick uber die Rahmenbedingungen des Tests geben, die verfugbaren Referenz- und Testdaten vorstellen und die Struktur und Organisation der Datenauswertung erlautern. Die detaillierten Ergebnisse der Auswertungen werden in separaten Beitragen vorgestellt, die ebenfalls Bestandteil dieser Ausgabe der Zeitschrift sind.

The DGPF-Test on Digital Airborne Camera Evaluation - Over- view and Test Design

Summary: During the implementation of the DGPF-project on Digital Photogrammetric Camera Evaluation a team “Digital Elevation Models” was established. The main goal was to use the test’s framework for documentation and evaluation of the current state-of-the-art on photogrammetric 3D data capture from automatic image matching. During these investigations the accuracy and reliability of DSM rasters and 3D point clouds as derived from imagery of digital photogrammetric camera systems were evaluated. For this purpose they were compared to reference measurements from ground truth and airborne LiDAR. In addition to the evaluation of standard products, the usability of elevation data from image matching was investigated while aiming at specific applications in the context of urban modeling and forestry. Zusammenfassung: Wahrend des DGPF-Projektes zur Evaluierung digitaler photogrammetrischer Luftbildkamerasysteme wurde auch eine Auswertegruppe fur die Bewertung der Genauigkeit der Hohenmodellgenerierung etabliert. Dabei sollte der DGPF-Test genutzt werden, um den derzeitigen Stand der Technik der photogrammetrischen 3D Erfassug mittels automatischer Bildzuordnung zu dokumentieren. Hierfur wurden DSM Raster und 3D Punktwolken aus Bildern der photgrammetrischen Kamerasysteme abgeleitetet und die Qualitat dieser Ergebnisse in Bezug auf Genauigkeit und Zuverlassigkeit bewertet. Dabei wurde ein Vergleich zu terrestrischen Referenzmessungen und flugzeuggestutzen LiDAR Daten durchgefuhrt. Neben der qualitativen Bewertung von Standardprodukten wurde auch die Nutzbarkeit der Hohendaten fur spezielle Anwendungen beispielsweise im Kontext der 3D Stadmodellierung und Forstwirtschaft untersucht.

Digital Photogrammetric Camera Evaluation - Generation of Di- gital Elevation Models

A correspondence framework for ALS strip adjustments based on variants of the ICP algorithm

This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds.

Extracting 3D tree models based on terrestrial laser scanning (TLS) point clouds is a challenging task as trees are complex objects. Current TLS devices acquire high-density data that allow a detailed reconstruction of the tree topology. However, in dense forests a fully automatic reconstruction of trees is often limited by occlusion, wind influences and co-registration issues. In this paper, a semi-automatic method for extracting branching and stem structure based on equirectangular projections (range and intensity maps) is presented. The digitization of branches and stems is based on 2D maps, which enables simple navigation and raster processing. The modeling is performed for each viewpoint individually instead of using a registered point cloud. Previously reconstructed 2D-skeletons are transformed between the maps. Therefore, wind influences, orientation imperfections of scans and data gaps can be overcome. The method is applied to a TLS dataset acquired in a forest in Germany. In total 34 scans were carried out within a managed forest to measure approximately 90 spruce trees with minimal occlusions. The results demonstrate the feasibility of the presented approach to extract tree models with a high completeness and correctness and provide an excellent input for further modeling applications.

A Practical Approach for Extracting Tree Models in Forest Environments Based on Equirectangular Projections of Terrestrial Laser Scans

The geometric performance of digital airborne cameras also including the impact of direct sensor orientation has been evaluated by a test of the German Society of Photogrammetry, Remote Sensing and Geoinformation (DGPF). This test includes following airborne photogrammetric cameras: the large format frame cameras Z/I Imaging DMC, Vexcel Imaging UltraCamX and the line scanning camera system Leica Geosystems ADS40 (2 generation) and Jena Optronik JAS-150 as well as the mid-format camera Rolleimetric AIC-x1 and the combination of four mid-format cameras Quattro-DigiCAM. The results presented in this paper were achieved by a group of researchers from different institutions, working independently from each other and with different programs for data acquisition and bundle block adjustment. Moreover, different adjustment configurations (i.e. with/without use of perspective centre coordinates and/or attitude information from GPS/inertial systems), and also different control point configurations have been used in the test; this results in a wide range of solutions and accuracy results which are not easy to compare, on the other hand this just shows the spectrum of possible solutions in operational applications.

Camillo Ressl

Papers

Digital Photogrammetric Camera Evaluation - Generation of Di- gital Elevation Models

A correspondence framework for ALS strip adjustments based on variants of the ICP algorithm

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds.

A Practical Approach for Extracting Tree Models in Forest Environments Based on Equirectangular Projections of Terrestrial Laser Scans

DGPF-Project: Evaluation of Digital Photogrammetric Camera Systems - Geometric Performance