scholarly journals Measuring Tree Height with Remote Sensing—A Comparison of Photogrammetric and LiDAR Data with Different Field Measurements

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 694 ◽  
Author(s):  
Selina Ganz ◽  
Yannek Käber ◽  
Petra Adler
Keyword(s):  
Remote Sensing ◽  
Tree Height ◽  
Field Measurements ◽  
Test Site ◽  
Aerial Images ◽  
Lidar Data ◽  
Individual Tree ◽  
Indirect Measurements ◽  
Remote Sensing Techniques ◽  
Remote Sensing Methods

We contribute to a better understanding of different remote sensing techniques for tree height estimation by comparing several techniques to both direct and indirect field measurements. From these comparisons, factors influencing the accuracy of reliable tree height measurements were identified. Different remote sensing methods were applied on the same test site, varying the factors sensor type, platform, and flight parameters. We implemented light detection and ranging (LiDAR) and photogrammetric aerial images received from unmanned aerial vehicles (UAV), gyrocopter, and aircraft. Field measurements were carried out indirectly using a Vertex clinometer and directly after felling using a tape measure on tree trunks. Indirect measurements resulted in an RMSE of 1.02 m and tend to underestimate tree height with a systematic error of −0.66 m. For the derivation of tree height, the results varied from an RMSE of 0.36 m for UAV-LiDAR data to 2.89 m for photogrammetric data acquired by an aircraft. Measurements derived from LiDAR data resulted in higher tree heights, while measurements from photogrammetric data tended to be lower than field measurements. When absolute orientation was appropriate, measurements from UAV-Camera were as reliable as those from UAV-LiDAR. With low flight altitudes, small camera lens angles, and an accurate orientation, higher accuracies for the estimation of individual tree heights could be achieved. The study showed that remote sensing measurements of tree height can be more accurate than traditional triangulation techniques if the aforementioned conditions are fulfilled.

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.

Application of remote sensing methods for assessment of anthropogenic transformation of rangelands

2000 ◽  
pp. 16-25
Author(s):  
E. I. Rachkovskaya ◽  
S. S. Temirbekov ◽  
R. E. Sadvokasov
Keyword(s):  
Remote Sensing ◽  
New Technology ◽  
Field Studies ◽  
Digital Data ◽  
Aerial Images ◽  
Expert Assessment ◽  
Automated Classification ◽  
Anthropogenic Transformation ◽  
Initial Processing ◽  
Remote Sensing Methods

Capabilities of the remote sensing methods for making maps of actual and potential vegetation, and assessment of the extent of anthropogenic transformation of rangelands are presented in the paper. Study area is a large intermountain depression, which is under intensive agricultural use. Color photographs have been made by Aircraft camera Wild Heerburg RC-30 and multispectral scanner Daedalus (AMS) digital aerial data (6 bands, 3.5m resolution) have been used for analysis of distribution and assessment of the state of vegetation. Digital data were processed using specialized program ENVI 3.0. Main stages of the development of cartographic models have been described: initial processing of the aerial images and their visualization, preliminary pre-field interpretation (classification) of the images on the basis of unsupervised automated classification, field studies (geobotanical records and GPS measurements at the sites chosen at previous stage). Post-field stage had the following sub-stages: final geometric correction of the digital images, elaboration of the classification system for the main mapping subdivisions, final supervised automated classification on the basis of expert assessment. By systematizing clusters of the obtained classified image the cartographic models of the study area have been made. Application of the new technology of remote sensing allowed making qualitative and quantitative assessment of modern state of rangelands.

scholarly journals Detecting Long-Term Urban Forest Cover Change and Impacts of Natural Disasters Using High-Resolution Aerial Images and LiDAR Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1820
Author(s):  
Raoul Blackman ◽  
Fei Yuan
Keyword(s):  
Remote Sensing ◽  
Ecosystem Services ◽  
Forest Canopy ◽  
High Spatial Resolution ◽  
Urban Forest ◽  
Urban Canopy ◽  
Canopy Cover ◽  
Random Point ◽  
Aerial Images ◽  
Lidar Data

Urban forests provide ecosystem services; tree canopy cover is the basic quantification of ecosystem services. Ground assessment of the urban forest is limited; with continued refinement, remote sensing can become an essential tool for analyzing the urban forest. This study addresses three research questions that are essential for urban forest management using remote sensing: (1) Can object-based image analysis (OBIA) and non-image classification methods (such as random point-based evaluation) accurately determine urban canopy coverage using high-spatial-resolution aerial images? (2) Is it possible to assess the impact of natural disturbances in addition to other factors (such as urban development) on urban canopy changes in the classification map created by OBIA? (3) How can we use Light Detection and Ranging (LiDAR) data and technology to extract urban canopy metrics accurately and effectively? The urban forest canopy area and location within the City of St Peter, Minnesota (MN) boundary between 1938 and 2019 were defined using both OBIA and random-point-based methods with high-spatial-resolution aerial images. Impacts of natural disasters, such as the 1998 tornado and tree diseases, on the urban canopy cover area, were examined. Finally, LiDAR data was used to determine the height, density, crown area, diameter, and volume of the urban forest canopy. Both OBIA and random-point methods gave accurate results of canopy coverages. The OBIA is relatively more time-consuming and requires specialist knowledge, whereas the random-point-based method only shows the total coverage of the classes without locational information. Canopy change caused by tornado was discernible in the canopy OBIA-based classification maps while the change due to diseases was undetectable. To accurately exact urban canopy metrics besides tree locations, dense LiDAR point cloud data collected at the leaf-on season as well as algorithms or software developed specifically for urban forest analysis using LiDAR data are needed.

scholarly journals Acquisition of Forest Attributes for Decision Support at the Forest Enterprise Level Using Remote-Sensing Techniques—A Review

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 273 ◽  
Author(s):  
Peter Surový ◽  
Karel Kuželka
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Forest Cover ◽  
Forest Health ◽  
Basal Area ◽  
Tree Height ◽  
Radar Sensors ◽  
Tree Number ◽  
Remote Sensing Techniques ◽  
New Sensors

In recent decades, remote sensing techniques and the associated hardware and software have made substantial improvements. With satellite images that can obtain sub-meter spatial resolution, and new hardware, particularly unmanned aerial vehicles and systems, there are many emerging opportunities for improved data acquisition, including variable temporal and spectral resolutions. Combined with the evolution of techniques for aerial remote sensing, such as full wave laser scanners, hyperspectral scanners, and aerial radar sensors, the potential to incorporate this new data in forest management is enormous. Here we provide an overview of the current state-of-the-art remote sensing techniques for large forest areas thousands or tens of thousands of hectares. We examined modern remote sensing techniques used to obtain forest data that are directly applicable to decision making issues, and we provided a general overview of the types of data that can be obtained using remote sensing. The most easily accessible forest variable described in many works is stand or tree height, followed by other inventory variables like basal area, tree number, diameters, and volume, which are crucial in decision making process, especially for thinning and harvest planning, and timber transport optimization. Information about zonation and species composition are often described as more difficult to assess; however, this information usually is not required on annual basis. Counts of studies on forest health show an increasing trend in the last years, mostly in context of availability of new sensors as well as increased forest vulnerability caused by climate change; by virtue to modern sensors interesting methods were developed for detection of stressed or damaged trees. Unexpectedly few works focus on regeneration and seedlings evaluation; though regenerated stands should be regularly monitored in order to maintain forest cover sustainability.

scholarly journals A novel technique for extracting clouds base height using ground based imaging

2010 ◽  
Vol 3 (5) ◽  
pp. 4231-4260 ◽  
Author(s):  
E. Hirsch ◽  
E. Agassi ◽  
I. Koren
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Thermal Imaging ◽  
Field Measurements ◽  
Cloud Base ◽  
Convective Clouds ◽  
Boundary Layer Clouds ◽  
Remote Sensing Techniques ◽  
Power Needs ◽  
Cloud Base Height

Abstract. The height of a cloud in the atmospheric column is a key parameter in its characterization. Several remote sensing techniques (passive and active, either ground-based or on space-borne platforms) and in-situ measurements are routinely used in order to estimate top and base heights of clouds. In this article we present a novel method that combines thermal imaging from the ground and sounded wind profile in order to derive the cloud base height. This method is independent of cloud types, making it efficient for both low boundary layer and high clouds. In addition, using thermal imaging ensures extraction of clouds' features during daytime as well as at nighttime. The proposed technique was validated by comparison to active sounding by ceilometers (which is a standard ground based method), to lifted condensation level (LCL) calculations, and to MODIS products obtained from space. As all passive remote sensing techniques, the proposed method extracts only the height of the lowest cloud layer, thus upper cloud layers are not detected. Nevertheless, the information derived from this method can be complementary to space-borne cloud top measurements when deep-convective clouds are present. Unlike techniques such as LCL, this method is not limited to boundary layer clouds, and can extract the cloud base height at any level, as long as sufficient thermal contrast exists between the radiative temperatures of the cloud and its surrounding air parcel. Another advantage of the proposed method is its simplicity and modest power needs, making it particularly suitable for field measurements and deployment at remote locations. Our method can be further simplified for use with visible CCD or CMOS camera (although nighttime clouds will not be observed).

scholarly journals Remote Sensing

2017 ◽  
Vol 58 ◽  
pp. 10.1-10.21 ◽  
Author(s):  
J. Bühl ◽  
S. Alexander ◽  
S. Crewell ◽  
A. Heymsfield ◽  
H. Kalesse ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Ice Formation ◽  
Literature Study ◽  
Passive Remote Sensing ◽  
Level Information ◽  
Formation And Evolution ◽  
Remote Sensing Techniques ◽  
Remote Sensing Methods

Abstract State-of-the-art remote sensing techniques applicable to the investigation of ice formation and evolution are described. Ground-based and spaceborne measurements with lidar, radar, and radiometric techniques are discussed together with a global view on past and ongoing remote sensing measurement campaigns concerned with the study of ice formation and evolution. This chapter has the intention of a literature study and should illustrate the major efforts that are currently taken in the field of remote sensing of atmospheric ice. Since other chapters of this monograph mainly focus on aircraft in situ measurements, special emphasis is put on active remote sensing instruments and synergies between aircraft in situ measurements and passive remote sensing methods. The chapter concentrates on homogeneous and heterogeneous ice formation in the troposphere because this is a major topic of this monograph. Furthermore, methods that deliver direct, process-level information about ice formation are elaborated with a special emphasis on active remote sensing methods. Passive remote sensing methods are also dealt with but only in the context of synergy with aircraft in situ measurements.

Application of sky-view factor for the visualisation of historic landscape features in lidar-derived relief models

Antiquity ◽  
2011 ◽  
Vol 85 (327) ◽  
pp. 263-273 ◽  
Author(s):  
Žiga Kokalj ◽  
Klemen Zakšek ◽  
Krištof Oštir
Keyword(s):  
Remote Sensing ◽  
Point Source ◽  
Test Site ◽  
Lidar Data ◽  
View Factor ◽  
Diffuse Light ◽  
Sky View Factor ◽  
Usual Form ◽  
Aerial Mapping ◽  
Historic Landscape

Aerial mapping and remote sensing takes another step forward with this method of modelling lidar data. The usual form of presentation, hill shade, uses a point source to show up surface features. Sky-view factor simulates diffuse light by computing how much of the sky is visible from each point. The result is a greatly improved visibility — as shown here by its use on a test site of known topography in Slovenia.

scholarly journals AIRBORNE TECHNOLOGIES FOR DISASTER MANAGEMENT

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 387-393
Author(s):  
J. Schulz
Keyword(s):  
Remote Sensing ◽  
Water Masses ◽  
Aerial Images ◽  
Airborne Remote Sensing ◽  
Optimal Method ◽  
Individual Tree ◽  
Flood Peak ◽  
Sensing Technology ◽  
Aircraft System ◽  
The Individual

<p><strong>Abstract.</strong> Currently, satellite-based systems and UAVs are very popular in the investigation of natural disasters. Both systems have their justification and advantages &amp;ndash; but one should not forget the airborne remote sensing technology. The presentation shows with three examples very clearly how airborne remote sensing is still making great progress and in many cases represents the optimal method of data acquisition.</p> <p>The airborne detection of forest damages (especially currently the bark beetle in spruce stands) can determine the pest attack using CIR aerial images in combination with ALS and hyperspectral systems &amp;ndash; down to the individual tree. Large forest areas of 100 sqkm and more can be recorded from planes on one day (100 sqkm with 10cm GSD on one day).</p> <p>Flood events &amp;ndash; such as on the Elbe in 2013 &amp;ndash; were recorded by many satellites. However, many evaluations require highresolution data (GSD 10cm), e.g. to clarify insurance claims. Here the aircraft system, which was able to fly below the cloud cover and was constantly flying at the height level of the flood peak, proved to be unbeatable.</p> <p>The phenomenon of urban flash floods is one of the consequences of climate change. Cities are not in a position to cope with the water masses of extreme rain events and so are confronted with major damages. In Germany, a number of cities are already preparing to manage short-term but extreme water masses. The complicated hydrographic and hydraulic calculations and simulations require above all one thing &amp;ndash; a precise data basis. This involves, for example, the height of kerbstones and the recording of every gully and every obstacle. Such city-wide data can only be collected effectively by photogrammetric analysis of aerial photography (GSD 5 to 10cm).</p>

scholarly journals Application of Remote Sensing to the Investigation of Rock Slopes: Experience Gained and Lessons Learned

2019 ◽  
Vol 8 (7) ◽  
pp. 296 ◽  
Author(s):  
Doug Stead ◽  
Davide Donati ◽  
Andrea Wolter ◽  
Matthieu Sturzenegger
Keyword(s):  
Remote Sensing ◽  
Lessons Learned ◽  
Rock Slopes ◽  
Field Methods ◽  
Potential Applications ◽  
Remote Sensing Techniques ◽  
The Stability ◽  
Difficult Terrain ◽  
Remote Sensing Methods

The stability and deformation behavior of high rock slopes depends on many factors, including geological structures, lithology, geomorphic processes, stress distribution, and groundwater regime. A comprehensive mapping program is, therefore, required to investigate and assess the stability of high rock slopes. However, slope steepness, rockfalls and ongoing instability, difficult terrain, and other safety concerns may prevent the collection of data by means of traditional field techniques. Therefore, remote sensing methods are often critical to perform an effective investigation. In this paper, we describe the application of field and remote sensing approaches for the characterization of rock slopes at various scale and distances. Based on over 15 years of the experience gained by the Engineering Geology and Resource Geotechnics Research Group at Simon Fraser University (Vancouver, Canada), we provide a summary of the potential applications, advantages, and limitations of varied remote sensing techniques for comprehensive characterization of rock slopes. We illustrate how remote sensing methods have been critical in performing rock slope investigations. However, we observe that traditional field methods still remain indispensable to collect important intact rock and discontinuity condition data.

scholarly journals Using volunteered geographical information to map the November 2012 floods in Slovenia

2013 ◽  
Vol 13 (11) ◽  
pp. 2753-2762 ◽  
Author(s):  
M. Triglav-Čekada ◽  
D. Radovan
Keyword(s):  
Remote Sensing ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Web Search ◽  
Aerial Images ◽  
Geographical Information ◽  
Flood Mapping ◽  
Remote Sensing Methods ◽  
Flooded Areas ◽  
Complete Account

Abstract. Volunteered geographical information represents a promising field in the monitoring and mapping of natural disasters. The contributors of volunteered geographical information have the advantage that they are at the location of the natural disaster at exactly the time when the disaster happened. Therefore, they can provide the most complete account of the extent of the damage. This is not always possible when applying photogrammetric or remote-sensing methods, as prior to the data acquisition an order to carry out the measurements has to be made. On 5 and 6 November 2012 almost half of Slovenia was badly affected by floods. The gathering of volunteered geographical information in the form of images and videos of these floods is presented. Two strategies were used: (1) a public call for volunteered contributions and (2) a web search for useful images and their authors. The authorship of these images was verified with every contributor. In total, 15 contributors provided 102 terrestrial and aerial images and one aerial video, with 45% classified as potentially useful. For actual flood mapping 22 images and 12 sequences from video were used. With the help of the volunteered images 12% of the most severely affected river sections were mapped. Altogether, 1195.3 ha of flooded areas outside of the usual river beds along a total river length of 48 km were mapped. The results are compared with those from satellite mapping of the same floods, which successfully covered 18% of the most affected river sections.

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