Das aktuelle Vegetationshöhenmodell der Schweiz: spezifische Anwendungen im Waldbereich

2016 ◽  
Vol 167 (3) ◽  
pp. 128-135 ◽  
Author(s):  
Christian Ginzler ◽  
Martina L. Hobi
Keyword(s):  
Spatial Resolution ◽  
Forest Canopy ◽  
Current Model ◽  
Digital Terrain Model ◽  
National Forest Inventory ◽  
Aerial Images ◽  
Surface Model ◽  
Vegetation Height ◽  
Very High ◽  
Height Model

Current model of canopy heights in Switzerland: specific applications in forestry A national vegetation height model was calculated for Switzerland for the first time last year using digital aerial images. The ADS80 stereo aerial images, which were routinely gathered by the Swiss Federal Office of Topography (swisstopo), contain information about the height of vegetation in forests. We used the stereo aerial images to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using a digital terrain model (DTM) based on laser data with the buildings masked out, and to produce a vegetation height model (VHM). Such a model could be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from the years 2007 to 2012. The VHM reached almost nationwide coverage (98% of the country's surface area). Some areas, such as steep mountainsides or very bright glaciers, were problematic for calculating the model, and appear in it as gaps. Vegetation height information collected with this method is most useful for analyzing entire forest stands, but the data do not have a high enough spatial resolution for single-tree-based analyses. The VHM can be applied in a wide variety of ways. Here, we describe three of these: 1) generating forest masks, 2) extracting forest canopy gaps, and 3) detecting changes in the stocking of a forested area.

scholarly journals Photogrammetric surveying forests and woodlands with UAVs: techniques for automatic removal of vegetation and digital terrain model production for hydrological applications

2019 ◽  
Vol 7 (1) ◽  
pp. 1-20
Author(s):  
Fotis Giagkas ◽  
Petros Patias ◽  
Charalampos Georgiadis
Keyword(s):  
Vegetation Type ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Aerial Images ◽  
Surface Model ◽  
Terrain Model ◽  
Vegetation Height ◽  
Digital Terrain ◽  
Dense Point ◽  
Height Model

The purpose of this study is the photogrammetric survey of a forested area using unmanned aerial vehicles (UAV), and the estimation of the digital terrain model (DTM) of the area, based on the photogrammetrically produced digital surface model (DSM). Furthermore, through the classification of the height difference between a DSM and a DTM, a vegetation height model is estimated, and a vegetation type map is produced. Finally, the generated DTM was used in a hydrological analysis study to determine its suitability compared to the usage of the DSM. The selected study area was the forest of Seih-Sou (Thessaloniki). The DTM extraction methodology applies classification and filtering of point clouds, and aims to produce a surface model including only terrain points (DTM). The method yielded a DTM that functioned satisfactorily as a basis for the hydrological analysis. Also, by classifying the DSM–DTM difference, a vegetation height model was generated. For the photogrammetric survey, 495 aerial images were used, taken by a UAV from a height of ∼200 m. A total of 44 ground control points were measured with an accuracy of 5 cm. The accuracy of the aerial triangulation was approximately 13 cm. The produced dense point cloud, counted 146 593 725 points.

scholarly journals Mapping the Mangrove Forest Canopy Using Spectral Unmixing of Very High Spatial Resolution Satellite Images

2019 ◽  
Vol 11 (3) ◽  
pp. 367 ◽  
Author(s):  
Florent Taureau ◽  
Marc Robin ◽  
Christophe Proisy ◽  
François Fromard ◽  
Daniel Imbert ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Forest Structure ◽  
Mangrove Forest ◽  
Satellite Images ◽  
Forest Canopy ◽  
High Spatial Resolution ◽  
Spectral Unmixing ◽  
Very High Spatial Resolution ◽  
Very High ◽  
Mangrove Structure

Despite the low tree diversity and scarcity of the understory vegetation, the high morphological plasticity of mangrove trees induces, at the stand level, a very large variability of forest structures that need to be mapped for assessing the functioning of such complex ecosystems. Fully constrained linear spectral unmixing (FCLSU) of very high spatial resolution (VHSR) multispectral images was tested to fine-scale map mangrove zonations in terms of horizontal variation of forest structure. The study was carried out on three Pleiades-1A satellite images covering French island territories located in the Atlantic, Indian, and Pacific Oceans, namely Guadeloupe, Mayotte, and New Caledonia archipelagos. In each image, FCLSU was trained from the delineation of areas exclusively related to four components including either pure vegetation, soil (ferns included), water, or shadows. It was then applied to the whole mangrove cover imaged for each island and yielded the respective contributions of those four components for each image pixel. On the forest stand scale, the results interestingly indicated a close correlation between FCLSU-derived vegetation fractions and canopy closure estimated from hemispherical photographs (R2 = 0.95) and a weak relation with the Normalized Difference Vegetation Index (R2 = 0.29). Classification of these fractions also offered the opportunity to detect and map horizontal patterns of mangrove structure in a given site. K-means classifications of fraction indeed showed a global view of mangrove structure organization in the three sites, complementary to the outputs obtained from spectral data analysis. Our findings suggest that the pixel intensity decomposition applied to VHSR multispectral satellite images can be a simple but valuable approach for (i) mangrove canopy monitoring and (ii) mangrove forest structure analysis in the perspective of assessing mangrove dynamics and productivity. As with Lidar-based surveys, these potential new mapping capabilities deserve further physically based interpretation of sunlight scattering mechanisms within forest canopy.

scholarly journals Application of the global SRTM and AW3D30 digital elevation models to mapping folds at cave sites

2021 ◽  
Vol 50 (1) ◽  
pp. 75-89
Author(s):  
Mark Abolins ◽  
Albert Ogden
Keyword(s):  
Cell Size ◽  
Forest Canopy ◽  
Digital Elevation Models ◽  
Digital Terrain Model ◽  
Surface Model ◽  
M Cell ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
The Mean

A novel method to map and quantitatively describe very gentle folds (limb dip <5°) at cratonic cave sites was evaluated at Snail Shell and Nanna caves, central Tennessee, USA. Elevations from the global SRTM digital terrain model (DTM) were assigned to points on late Ordovician geologic contacts, and the elevations of the points were used to interpolate 28 m cell size natural neighbor digital elevation models (DEM’s) of the contacts. The global Forest Canopy Height Dataset was subtracted from the global 28 m cell size AW3D30 digital surface model (DSM) to create a DTM, and that DTM was applied in the same way. Comparison of mean and modal strikes of the interpolated surfaces with mean and modal cave passage trend shows that many passages are sub-parallel to the trend of an anticline. WithiSn 500 m of the caves, the SRTM- and AW3D30-based interpolated surfaces have mean strikes within 8° of the mean strike of an interpolated reference surface created with a high resolution (~0.76 m cell size and 10 cm RMSE) Tennessee, USA LiDAR DTM. This evaluation shows that the SRTM- and AW3D30-based method has the potential to reveal a relationship between the trend of a fold, on one hand, and cave passages, on the other, at sites where a geologic contact varies in elevation by >35 m within an area of <12.4 km2 and the mean dip of bedding is >0.9°.

scholarly journals Deteksi Tinggi Vegetasi di Delta Mahakam dengan Penginderaan Jauh

2019 ◽  
Vol 4 (3) ◽  
pp. 175
Author(s):  
Nanin Anggraini ◽  
Atriyon Julzarika
Keyword(s):  
Remote Sensing ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Remote Sensing Data ◽  
Surface Model ◽  
Geoid Model ◽  
Alos Palsar ◽  
Vegetation Height ◽  
Vertical Accuracy ◽  
Mahakam Delta

<strong>Detection of Vegetation Height in Mahakam Delta Using Remote Sensing. </strong>The vegetation height is a vertical distance between top of the vegetation to ground surface. Vegetation height is one of the parameters for vegetation growth. There are various methods to measure vegetation height; one of them is the use of remote sensing technology. This study aims to map vegetation height in Mahakam Delta by using height models derived from remote sensing data. Such models are Digital Surface Model (DSM) and Digital Terrain Model (DTM). DSM was generated using a combination of interferometric processing of ALOS PALSAR interferometry, X-SAR, Shuttle Radar Topography Mission (SRTM), and geodetic height of Icesat/GLAS satellite imagery. This integration technique incorporated the Digital Elevation Model (DEM) method. The geoid model used in this study was EGM 2008. The following step was the correction of height errors of DSM. Terrain correction was undertaken to convert DSM into DTM, while vegetation heights were obtained from subtraction of DSM and DTM. Vertical accuracy verification refers to a tolerance of 1.96σ (95%) or ~80 cm. In DSM, a vertical accuracy value of 60.4 cm was obtained so that the DSM is feasible for mapping with scale of 1: 10,000, while the DTM was 37 cm so it is also applicable for mapping with such scale. Based on the subtraction of DSM and DTM, the vegetation heights in Mahakam Delta varied between 0 and 64 m.

scholarly journals AUTOMATIC VEHICLE RECOGNITION FOR URBAN TRAFFIC MANAGEMENT

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 741-744
Author(s):  
M. Mohammadi ◽  
F. Tabib Mahmoudi ◽  
M. Hedayatifard
Keyword(s):  
Land Use ◽  
Spatial Resolution ◽  
Traffic Management ◽  
Decision Fusion ◽  
Image Resolution ◽  
Urban Traffic ◽  
Aerial Images ◽  
Fusion Algorithm ◽  
Vehicle Recognition ◽  
Very High

Abstract. Automatic vehicle recognition has an important role for many applications such as supervision, traffic management and rescue tasks. The ability of online supervision on the distribution of vehicles in urban environments prevents traffic, which in turn reduces air pollution and noise. However, this is extremely challenging due to the small size of vehicles, their different types and orientations, and the visual similarity to some other objects in very high resolution images. In this paper, an automatic vehicle recognition algorithm is proposed based on very high spatial resolution aerial images. In the first step of the proposed method, by generating the image pyramid, the candidate regions of the vehicles are recognized. Then, performing reverse pyramid, decision level fusion of the vehicle candidates and the land use/cover classification results of the original image resolution are performed in order to modify recognized vehicle regions. For evaluating the performance of the proposed method in this study, Ultracam aerial imagery with spatial resolution of 11 cm and 3 spectral bands have been used. Comparing the obtained vehicle recognition results from the proposed decision fusion algorithm with some manually selected vehicle regions confirm the accuracy of about %80. Moreover, the %78.87 and 0.71 are respectively the values for overall accuracy and Kappa coefficient of the obtained land use/cover classification map from decision fusion algorithm.

Countrywide surface models from historical panchromatic and true color stereo imagery – a retrospective analysis of forest structures in Switzerland

2020 ◽  
Author(s):  
Christian Ginzler ◽  
Mauro Marty ◽  
Lars T. Waser
Keyword(s):  
Forest Inventory ◽  
Digital Terrain Model ◽  
National Forest Inventory ◽  
Aerial Images ◽  
National Forest ◽  
Terrain Model ◽  
Digital Terrain ◽  
Surface Models ◽  
Stereo Imagery ◽  
True Color

&lt;p&gt;&lt;strong&gt;Countrywide surface models from historical panchromatic and true color stereo imagery &amp;#8211; a retrospective analysis of forest structures in Switzerland&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Mauro Marty&lt;sup&gt;1&lt;/sup&gt;, Lars T. Waser&lt;sup&gt;1&lt;/sup&gt;, Christian Ginzler&lt;sup&gt;1&lt;/sup&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Swiss Federal Institute for Forest, Snow and Landscape Research WSL, &lt;br&gt;Z&amp;#252;rcherstrasse 111, CH - 8903 Birmensdorf, Switzerland&lt;/p&gt;&lt;p&gt;Remote sensing methods allow the acquisition of 3D structures of forests over large areas. Active systems, such as Airborne Laser Scanning (ALS) and Synthetic Aperture Radar (SAR) and passive systems, such as multispectral sensors, have been established to acquire 3D and 2.5D data of the earth's surface. Nationwide calculations of surface models with photogrammetric methods from digital stereo aerial images or ALS data are already in operation in some countries (e.g. Switzerland, Austria, some German states).&lt;/p&gt;&lt;p&gt;The availability of historical stereo aerial images allows the calculation of digital surface models from the past using photogrammetric methods. We present a workflow with which we have calculated nationwide surface models for Switzerland for the 1980s, 1990s and 2000s. Current surface models are available from the National Forest Inventory (LFI) Switzerland.&lt;/p&gt;&lt;p&gt;In the context of the Swiss land use and land cover statistics, the Federal Office of Topography (swisstopo) scanned and oriented the analogue black and white stereo aerial photographs with a mean scale of ~1:30'000 of the nationwide flights of 1979 - 84 and1993 - 1997 with 14 &amp;#181;m. The true colour image data from 1998 &amp;#8211; 2007 were scanned for the production of the orthoimages swissimage by swisstopo. All these data &amp;#8211; the scanned images and the orientation parameters - are also available to the National Forest Inventory (NFI). Within the framework of the NFI, we developed a highly automated workflow to generate digital surface models (DSMs) from many thousands of overlapping frame images covering the whole country. In total, more than 25'000 individual stereo models were processed to nationwide surface models. For their normalization, the digital terrain model of Switzerland 'swissAlti3D' was used. As the image orientation in some areas showed high vertical inaccuracies, corrections had to be made. Data from the Swiss land use and land cover statistics were used for this purpose. At places with constant surface cover since the 1980s (e.g. grassland), correction grids were calculated using the digital terrain model and applied to the surface models.&lt;/p&gt;&lt;p&gt;The results are new data sets on the 2.5D surface of Switzerland from the 1980s, 1990s and 2000s with a high spatial resolution of 1 m. It can be stated that the completeness of the image correlation in forested areas was quite satisfactory. In open areas with agricultural land, however, the matching points were often reduced to the road network, as the meadows and fields in the scanned SW stereo aerial images had very little texture.&lt;/p&gt;&lt;p&gt;This new historical, nationwide data on the horizontal and vertical structure in forests now allows their analysis of changes over the last 40 years.&lt;/p&gt;

New Opportunities for Highly Automated Countrywide Assessment of Trees Outside Forests in Switzerland

2020 ◽  
Author(s):  
Eylul Malkoc ◽  
Lars T. Waser
Keyword(s):  
Remote Sensing ◽  
Forest Tree ◽  
National Forest Inventory ◽  
National Forest ◽  
Data Sets ◽  
Tree Line ◽  
Trees Outside Forests ◽  
Vegetation Height ◽  
Surface Models ◽  
Height Model

&lt;p&gt;Although various ways of defining forests exist, non of them is eligible on assessing every tree -growing outside forest- on the landscape. In the last decades, forestry and land management sectors have become increasingly aware that Trees Outside Forests (TOF) are critical non-forest tree resources to ensure environmental, economic, social and cultural services and functions. The importance of TOF varies in international, national and local levels. Recently, international programmes have been established to strengthen the services and functions of TOF: sustainable land management, carbon capturing and storage on climate change mitigation and improving local economies. Therefore, in the past years countries have started to take action for assesing their TOF resources on different scales. &amp;#160;&lt;/p&gt;&lt;p&gt;Only little research has been conducted on TOF in Switzerland, yet the explicit spatial distribution of TOF in the landscape is poorly understood and their extent and tree biomass are unknown. Nowadays, remote sensing technologies have opened new opportunities to fill this knowledge gap, and countrywide data sets of TOF have become more feasible.&amp;#160;&lt;/p&gt;&lt;p&gt;The present research aims to introduce a highly automated method to derive extent, spatial distribution and biomass of TOF in different land use classes: Agriculture, Urban, and Non- Agriculture/Urban for the whole of Switzerland.&amp;#160;&lt;/p&gt;&lt;p&gt;The entire process of identifying TOF is done in Python using routinely acquired countrywide remote sensing data, i.e. Vegetation Height Model (Ginzler and Hobi 2015), CORINE Land Cover/Use map and the Forest Mask of Switzerland (Waser et al. 2015) and based on the decision tree algorithm developed by FAO-FRA (Foresta et.al., 2013). The primarily applied criterias are the Presence of Trees on the land, Land Use, and Spatial pattern of Trees. After the application of primary criterias, a set of thresholds were applied as following: the minimum canopy cover threshold: 5% (if trees only), 10% if combined cover is trees and shrubs, minimum area 0.05 ha., tree line lenght 25 m, and tree line width 3 m.&amp;#160;&lt;/p&gt;&lt;p&gt;The present study aims to complement forest data obtained from the Swiss National Forest Inventory and enables to derived relevant TOF parameters such as tree species distribution, biomass and carbon sequestration potential. Moreover, the proposed method is relevant to help other countries to create their own data sets on non-forest tree resources as an input to energy, environment, forest policy making, and wood industry decision making and to contribute to better cope with the challenges of changing climate and environment. Currently, the potential of Sentinel-2 imagery is being tested.&lt;/p&gt;&lt;p&gt;Keywords: Trees Outside Forest, Wall-to-wall, Vegetation Height Model&lt;/p&gt;&lt;p&gt;Reference: Hubert de Foresta, Eduardo Somarriba, August Temu, D&amp;#233;sir&amp;#233;e Boulanger, H&amp;#233;l&amp;#232;ne Feuilly and Michelle Gauthier. 2013. Towards the Assessment of Trees Outside Forests. Resources Assessment Working Paper 183. FAO Rome.&lt;br&gt;Ginzler, C., Hobi, M.L., 2015. Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory. Remote Sensing, 7, 4343-4370.&lt;br&gt;Waser, L.T., Fischer, C., Wang, Z., Ginzler, C., 2015. Wall-to-Wall Forest Mapping Based on Digital Surface Models from Image-Based Point Clouds and a NFI Forest Definition. Forests, 6, 4510-4528.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Assessing the impact of soil surface characteristics on vineyard erosion from very high spatial resolution aerial images (Côte de Beaune, Burgundy, France)

CATENA ◽  
2014 ◽  
Vol 116 ◽  
pp. 163-172 ◽  
Author(s):  
Amélie Quiquerez ◽  
Emmanuel Chevigny ◽  
Pascal Allemand ◽  
Pierre Curmi ◽  
Christophe Petit ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Soil Surface ◽  
Surface Characteristics ◽  
Aerial Images ◽  
Very High Spatial Resolution ◽  
The Impact ◽  
Very High

UAV-Based Canopy Height Modeling under Leaf-on and Leaf-off Conditions for Determining Tree Height and Crown Diameter (Case study: Hyrcanian mixed Forest)

2021 ◽  
Author(s):  
Vahid Nasiri ◽  
Ali.A. Darvishsefat ◽  
Hossein Arefi ◽  
Marc Pierrot-Deseilligny ◽  
Manochehr Namiranian ◽  
...  
Keyword(s):  
Mixed Forest ◽  
Digital Terrain Model ◽  
Local Maximum ◽  
Tree Height ◽  
Field Measurements ◽  
Canopy Height ◽  
Aerial Images ◽  
Surface Model ◽  
Individual Tree ◽  
Crown Diameter

Tree height and crown diameter are two common individual tree attributes that can be estimated from Unmanned Aerial Vehicles (UAVs) images thanks to photogrammetry and structure from motion. This research investigates the potential of low-cost UAV aerial images to estimate tree height and crown diameter. Two successful flights were carried out in two different seasons corresponding to leaf-off and leaf-on conditions to generate Digital Terrain Model (DTM) and Digital Surface Model (DSM), which were further employed in calculation of a Canopy Height Model (CHM). The CHM was used to estimate tree height using low pass and local maximum filters, and crown diameter was estimated based on an Invert Watershed Segmentation (IWS) algorithm. UAV-based tree height and crown diameter estimates were validated against field measurements and resulted in 3.22 m (10.1%) and 0.81 m (7.02%) RMSE, respectively. The results showed high agreement between our estimates and field measurements, with R2=0.808 for tree height and R2=0.923 for crown diameter. Generally, the accuracy of the results was considered acceptable and confirmed the usefulness of this approach for estimating tree heights and crown diameter.

Reference Data and Methods for Validation of Very High Resolution Optical Data Within ESA / EDAP Project

2021 ◽  
Author(s):  
Sébastien Saunier
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Spatial Resolution ◽  
Reference Data ◽  
Test Site ◽  
Optical Data ◽  
Surface Model ◽  
Landsat 8 ◽  
Validation Process ◽  
Very High

&lt;p&gt;In this paper, the authors propose to describe the methodologies developed for the validation of Very High-Resolution (VHR) optical missions within the Earthnet Data Assessment Pilot (EDAP) Framework.&amp;#160; The use of surface-based, drone, airborne, and/or space-based observations to build calibration reference is playing a fundamental role in the validation process. A rigorous validation process must compare mission data products with independent reference data suitable for the satellite measurements. As a consequence, one background activity within EDAP is the collection, the consolidation of reference data of various nature depending on the validation methodology.&lt;/p&gt;&lt;p&gt;The validation methodologies are conventionally divided into three categories; i.e. validations of the measurement, the geometry and the image quality. The validation of the measurement requires an absolute calibration reference. This latter on is built up by using either in situ measurements collected with RadCalNet[1] stations or by using space based observations performed with &amp;#8220;gold&amp;#8221; mission (Sentinel-2, Landsat-8) over Pseudo Invariant Calibration Site (PICS). For the geometric validation, several test sites have been set up. A test site is equipped with data from different reference sources. The full usability of a test site is not systematic. It depends on the validation metrics and the specifications of the sensor, particularly the spatial resolution and image acquisition geometry. Some existing geometric sites are equipped with Ground Control Point (GCP) set surveyed by using Global Navigation Satellite System (GNSS) devices in the field.&amp;#160; In some cases, the GCP set comes in support to the refinement of an image observed with drones in order to produce a raster reference, subsequently used to validate the internal geometry of images under assessment. Besides, a limiting factor in the usage of VHR optical ortho-rectified data is the accuracy of the Digital Surface Model (DSM) / Digital Terrain Model (DTM). In order to separate errors due to terrain elevation and error due to the sensor itself, some test sites are also equipped with very accurate Light Detection and Ranging (LIDAR) data.&lt;/p&gt;&lt;p&gt;The validation of image quality address all aspect related to the spatial resolution and is strongly linked to both the measurement and the geometry. The image quality assessments are performed with both qualitative and quantitative approaches. The quantitative approach relies on the analysis of artificial ground target images and lead to the estimate of Modulation Transfer Function (MTF) together with additional image quality parameters such as Signal to Noise Ratio (SNR). On the other hand, the qualitative approach assesses the interpretability of input images and leads to a rating scaling[2] which is strongly related to the sensor Ground Resolution Distance (GRD). This visual inspection task required a database including very detailed image of man-made objects. This database is considered within EDAP as a reference.&lt;/p&gt;&lt;div&gt; &lt;div&gt; &lt;p&gt;[1] https://www.radcalnet.org&lt;/p&gt; &lt;/div&gt; &lt;div&gt; &lt;p&gt;[2] https://fas.org/irp/imint/niirs.htm&lt;/p&gt; &lt;/div&gt; &lt;/div&gt;

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