Extraction of small biotopes and ecotones from multi-temporal RapidEye data and a high-resolution normalized digital surface model

2014 ◽  
Vol 35 (20) ◽  
pp. 7245-7262 ◽  
Author(s):  
Wei Hou ◽  
Ulrich Walz
Author(s):  
J. Fagir ◽  
A. Schubert ◽  
M. Frioud ◽  
D. Henke

The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform – leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.


2020 ◽  
Author(s):  
Helge Smebye

<p>Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure</p><p> </p><p>Helge C. Smebye,<sup>a,* </sup>Sean E. Salazar,<sup>a</sup> Asgeir O. K. Lysdahl,<sup>a</sup></p><p>aNorwegian Geotechnical Institute, Sognsveien 72, 0855 Oslo, Norway</p><p> </p><p><strong>Abstract</strong>.  The A rock wall failure occurred along a major highway in south-eastern Norway, shutting down two lanes of traffic for an extended period of time while the road authority inspected and repaired the wall. It was desired to have a high-resolution digital surface model along a 215-m long section of the 34-m tall vertical rock wall that included the failure zone.</p><p>A Structure-from-Motion (SfM)-based methodology was selected to achieve the desired resolution on the rock wall face, as well as below the foot and above the head of the wall. Due to the proximity of the wall face to the remaining open lanes of traffic, it was not possible to survey the face of the wall using a remotely piloted aircraft system (RPAS). Therefore, a combined platform photogrammetric surveying technique was employed to ensure optimal photographic coverage and to generate the best possible model. Ground control points (GCP) were distributed and surveyed along the bottom and top of the wall and an RPAS was flown manually over the head of the wall to capture downward facing (nadir) images. A lift crane was also employed to capture images from elevations varying between 20–30 meters with a standoff distance of 15 meters from the wall. Finally, ground-based images were captured using a camera equipped with real-time GNSS from the top of the opposite rock wall (across the highway) with standoff distance of approximately 65 meters.</p><p>In total, over 800 images were ingested into a commercial SfM software package. The bundle adjustments were assisted by the GNSS-equipped camera locations and the surveyed GCP were imported to georeference the resulting model. The dense point cloud product was exported to a separate meshing software package for comparison with a second dense surface model that was derived from pre-existing images of the as-built condition of same rock wall face (prior to failure). By subtracting the post-failure model from the pre-failure model, a volume estimate of the material, that was mobilized during the failure, was determined.</p><p>The utility of the multi-platform survey technique was demonstrated. The combination of aerial and ground-based photographic surveying techniques provided optimal photographic coverage of the entire length of the rock wall to successfully derive high-resolution surface models and volume estimates.</p><p> </p><p><strong> </strong></p><p><strong>Keywords</strong>: Structure-from-Motion, photogrammetry, digital surface model, natural hazards, ground control.</p><p> </p><p><strong>*</strong>Helge C. Smebye, E-mail: [email protected]</p>


Author(s):  
K. M. Kim

Traditional field methods for measuring tree heights are often too costly and time consuming. An alternative remote sensing approach is to measure tree heights from digital stereo photographs which is more practical for forest managers and less expensive than LiDAR or synthetic aperture radar. This work proposes an estimation of stand height and forest volume(m<sup>3</sup>/ha) using normalized digital surface model (nDSM) from high resolution stereo photography (25cm resolution) and forest type map. The study area was located in Mt. Maehwa model forest in Hong Chun-Gun, South Korea. The forest type map has four attributes such as major species, age class, DBH class and crown density class by stand. Overlapping aerial photos were taken in September 2013 and digital surface model (DSM) was created by photogrammetric methods(aerial triangulation, digital image matching). Then, digital terrain model (DTM) was created by filtering DSM and subtracted DTM from DSM pixel by pixel, resulting in nDSM which represents object heights (buildings, trees, etc.). Two independent variables from nDSM were used to estimate forest stand volume: crown density (%) and stand height (m). First, crown density was calculated using canopy segmentation method considering live crown ratio. Next, stand height was produced by averaging individual tree heights in a stand using Esri’s ArcGIS and the USDA Forest Service’s FUSION software. Finally, stand volume was estimated and mapped using aerial photo stand volume equations by species which have two independent variables, crown density and stand height. South Korea has a historical imagery archive which can show forest change in 40 years of successful forest rehabilitation. For a future study, forest volume change map (1970s&ndash;present) will be produced using this stand volume estimation method and a historical imagery archive.


2014 ◽  
Vol 875-877 ◽  
pp. 440-444
Author(s):  
Mauro Lo Brutto ◽  
Donatella Termini

Natural rivers are characterized by continuous variations in bed topography, especially along curved reaches. High resolution topographic data are necessary to analyze the mutual interactions between the downstream flow and the cross-stream flow, which determine the distribution of the bed-shear stress along the channel. Because of the difficulty in acquiring good and accurate data in rivers, the major part of studies have been conducted in laboratory flumes. This paper reports on a laboratory study in which the automatic digital photogrammetric survey was applied to derive the high-resolution Digital Surface Model (DSM) of the bed topography in a large amplitude meandering flume. In order to assess the advantages of the procedure, the bed profiles obtained by the DSM have been compared with those obtained using a servo-controlled vertical profiler (PV09) has been operated and discussed.


Author(s):  
J. Susaki ◽  
H. Kishimoto

In this paper, we present a method to improve the accuracy of a digital surface model (DSM) by utilizing multi-temporal triplet images. The Advanced Land Observing Satellite (ALOS) / Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) measures triplet images in the forward, nadir, and backward view directions, and a DSM is generated from the obtained set of triplet images. To generate a certain period of DSM, multiple DSMs generated from individual triplet images are compared, and outliers are removed. Our proposed method uses a traditional surveying approach to increase observations and solves multiple observation equations from all triplet images via the bias-corrected rational polynomial coefficient (RPC) model. Experimental results from using five sets of PRISM triplet images taken of the area around Saitama, north of Tokyo, Japan, showed that the average planimetric and height errors in the coordinates estimated from multi-temporal triplet images were 3.26 m and 2.71 m, respectively, and that they were smaller than those generated by using each set of triplet images individually. As a result, we conclude that the proposed method is effective for stably generating accurate DSMs from multi-temporal triplet images.


Author(s):  
K. M. Kim

Traditional field methods for measuring tree heights are often too costly and time consuming. An alternative remote sensing approach is to measure tree heights from digital stereo photographs which is more practical for forest managers and less expensive than LiDAR or synthetic aperture radar. This work proposes an estimation of stand height and forest volume(m&lt;sup&gt;3&lt;/sup&gt;/ha) using normalized digital surface model (nDSM) from high resolution stereo photography (25cm resolution) and forest type map. The study area was located in Mt. Maehwa model forest in Hong Chun-Gun, South Korea. The forest type map has four attributes such as major species, age class, DBH class and crown density class by stand. Overlapping aerial photos were taken in September 2013 and digital surface model (DSM) was created by photogrammetric methods(aerial triangulation, digital image matching). Then, digital terrain model (DTM) was created by filtering DSM and subtracted DTM from DSM pixel by pixel, resulting in nDSM which represents object heights (buildings, trees, etc.). Two independent variables from nDSM were used to estimate forest stand volume: crown density (%) and stand height (m). First, crown density was calculated using canopy segmentation method considering live crown ratio. Next, stand height was produced by averaging individual tree heights in a stand using Esri’s ArcGIS and the USDA Forest Service’s FUSION software. Finally, stand volume was estimated and mapped using aerial photo stand volume equations by species which have two independent variables, crown density and stand height. South Korea has a historical imagery archive which can show forest change in 40 years of successful forest rehabilitation. For a future study, forest volume change map (1970s&ndash;present) will be produced using this stand volume estimation method and a historical imagery archive.


UKaRsT ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 49
Author(s):  
Dian Wahyu Khaulan ◽  
Entin Hidayah ◽  
Gusfan Halik

The Digital Surface Model (DSM) is commonly used in studies on flood map modeling. The lack of accurate, high-resolution topography data has hindered flood modeling. The use of the Unmanned Aerial Vehicle (UAV) can help data acquisition with sufficient accuracy. This research aims to provide high-resolution DSM-generated maps by Ground Control Points (GCPs) settings. Improvement of the model's accuracy was pursued by distributing 20 GCPs along the edges of the study area. Agrisoft software was used to generate the DSM. The generated DSM can be used for various planning purposes. The model's accuracy is measured in Root Mean Square Error (RMSE) based on the generated DSM. The RMSE values are 0.488 m for x-coordinates and y-coordinates (horizontal direction) and 0.161 m for z-coordinates (vertical direction).


Sign in / Sign up

Export Citation Format

Share Document