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>

Segmenting Algorithm and Publishing Based on UVA Image

2012 ◽  
Vol 195-196 ◽  
pp. 594-598
Author(s):  
Jia Feng Wang ◽  
Xi Min Cui ◽  
De Bao Yuan ◽  
Jing Jing Jin ◽  
Ya Hui Qiu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Decision Makers ◽  
Reliable Information ◽  
Post Processing ◽  
Continuous Development ◽  
Airborne Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sensing Platforms

With the continuous development of UAV remote sensing technology, UAV remote sensing will become one of the main airborne remote sensing platforms, Image acquisition and its post-processing of the UAV remote sensing have become focus of todays study. This paper presents an idea of image segmentation and image publication of UAV remote sensing, and provides reliable information for decision makers. It possesses a certain value.

LiDAR – A new tool for forest measurements?

2006 ◽  
Vol 82 (2) ◽  
pp. 211-218 ◽  
Author(s):  
David L Evans ◽  
Scott D Roberts ◽  
Robert C Parker
Keyword(s):  
Remote Sensing ◽  
Forest Inventory ◽  
Measurement Tool ◽  
Mississippi State University ◽  
State University ◽  
Individual Tree ◽  
Sensing Technology ◽  
High Measurement ◽  
Application Potential ◽  
Forest Measurement

LiDAR (Light Detection and Ranging) is a remote sensing technology with strong application potential in forest resource management. It provides high measurement precision that can be used for tree and stand measurements. Although LiDAR has not been used widely as an operational measurement tool, there is a significant body of research and a number of projects at Mississippi State University (MSU) that illustrate the potential for this technology to be incorporated into operational forest assessments. This paper provides basic background on the capabilities of LiDAR in a forest measurement context that illustrates specific examples of LiDAR use including: 1) individual tree assessments, 2) a forest inventory protocol currently being operationally tested, 3) forest structure analysis, and 4) forest typing. Key words: LiDAR, remote sensing, tree identification, tree measurements, forest inventory, forest types

scholarly journals APPLICATION OF REMOTE SENSING BIG DATA FOR RAPID RESPOND TO LANDSLIDE LAKE DISASTER MONITOR

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 37-43
Author(s):  
H. J. Wang ◽  
Y. Zhou ◽  
S. X. Wang ◽  
F. T. Wang ◽  
Q. Zhao
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Dynamic Change ◽  
Landslide Dam ◽  
Aerial Images ◽  
Technology System ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sense ◽  
Landslide Lake

Abstract. Landslide dam, a common disaster around the world, always forms landslide lake because of blocking the river. Landslide lake is always with potentially immense hazard from rapid release of a large of water masses. Nowadays, with the development of remote sense technology, remote sensing big data has been widely applied to disaster monitor, which has broad prospect in landslide lake monitor. This study provided the processing flow of remote sensing image and flow of technology system in the landslide lake monitor based on remote sensing big data, which have been successfully applied to Baige landslide lake monitor. The result shows remote sensing technology as an objective, fleet and dynamic change of landslide lake with large monitor range and meets the requirement of all-weather dynamic monitor of landslide lake, which will provide basic information of landslide lake for decisionmaking departments to make disaster prevention and reduction. Lastly, the research points out the disadvantage of landslide lake monitor based on remote sensing big data. Drone images and aerial images will be an important supplement to remote sensing big data for landslide lake monitor.

The Application of Airborne Remote Sensing Technology in Land and Resources

2014 ◽  
Vol 644-650 ◽  
pp. 4360-4363
Author(s):  
Li Na Dong ◽  
Jing Tong ◽  
Chen Yang Wang
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Observation System ◽  
Airborne Remote Sensing ◽  
Geological Investigation ◽  
Good Efficiency ◽  
Sensing Technology ◽  
Earth Observation System ◽  
Low Altitude

Airborne and space remote sensing system are all the important parts of the earth observation system, also being good supplements to each other. Airborne remote sensing has the advantages of being high resolution, good efficiency and flexibility, which makes itself an effective method to rapidly acquire high resolution remote sensing data. Particularly, the technologies of conducting low altitude remote sensing investigation by unmanned aerial vehicles are rapidly developed with a great progress achieved, so there is no doubt that it will plays an important role in the remote sensing geological investigation.

scholarly journals LiDAR Applications to Estimate Forest Biomass at Individual Tree Scale: Opportunities, Challenges and Future Perspectives

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 550
Author(s):  
Dandan Xu ◽  
Haobin Wang ◽  
Weixin Xu ◽  
Zhaoqing Luan ◽  
Xia Xu
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Forest Biomass ◽  
Remotely Sensed ◽  
Tree Level ◽  
Biomass Estimation ◽  
Future Perspectives ◽  
Individual Tree ◽  
The Individual ◽  
Individual Trees

Accurate forest biomass estimation at the individual tree scale is the foundation of timber industry and forest management. It plays an important role in explaining ecological issues and small-scale processes. Remotely sensed images, across a range of spatial and temporal resolutions, with their advantages of non-destructive monitoring, are widely applied in forest biomass monitoring at global, ecoregion or community scales. However, the development of remote sensing applications for forest biomass at the individual tree scale has been relatively slow due to the constraints of spatial resolution and evaluation accuracy of remotely sensed data. With the improvements in platforms and spatial resolutions, as well as the development of remote sensing techniques, the potential for forest biomass estimation at the single tree level has been demonstrated. However, a comprehensive review of remote sensing of forest biomass scaled at individual trees has not been done. This review highlights the theoretical bases, challenges and future perspectives for Light Detection and Ranging (LiDAR) applications of individual trees scaled to whole forests. We summarize research on estimating individual tree volume and aboveground biomass (AGB) using Terrestrial Laser Scanning (TLS), Airborne Laser Scanning (ALS), Unmanned Aerial Vehicle Laser Scanning (UAV-LS) and Mobile Laser Scanning (MLS, including Vehicle-borne Laser Scanning (VLS) and Backpack Laser Scanning (BLS)) data.

scholarly journals On the Use of Low-Cost RGB-D Sensors for Autonomous Pothole Detection with Spatial Fuzzy c-Means Segmentation

2020 ◽  
Author(s):  
Yashon Ombado Ouma
Keyword(s):  
Remote Sensing ◽  
Spatial Information ◽  
Low Cost ◽  
Complex Structure ◽  
Pavement Distress ◽  
Fuzzy C Means ◽  
Sensing Technology ◽  
Efficiency And Effectiveness ◽  
The Individual ◽  
Pothole Detection

The automated detection of pavement distress from remote sensing imagery is a promising but challenging task due to the complex structure of pavement surfaces, in addition to the intensity of non-uniformity, and the presence of artifacts and noise. Even though imaging and sensing systems such as high-resolution RGB cameras, stereovision imaging, LiDAR and terrestrial laser scanning can now be combined to collect pavement condition data, the data obtained by these sensors are expensive and require specially equipped vehicles and processing. This hinders the utilization of the potential efficiency and effectiveness of such sensor systems. This chapter presents the potentials of the use of the Kinect v2.0 RGB-D sensor, as a low-cost approach for the efficient and accurate pothole detection on asphalt pavements. By using spatial fuzzy c-means (SFCM) clustering, so as to incorporate the pothole neighborhood spatial information into the membership function for clustering, the RGB data are segmented into pothole and non-pothole objects. The results demonstrate the advantage of complementary processing of low-cost multisensor data, through channeling data streams and linking data processing according to the merits of the individual sensors, for autonomous cost-effective assessment of road-surface conditions using remote sensing technology.

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.

SIOS’s airborne remote sensing campaigns in Svalbard 

2021 ◽  
Author(s):  
Shridhar Jawak ◽  
Agnar Sivertsen ◽  
Veijo Pohjola ◽  
Małgorzata Błaszczyk ◽  
Jack Kohler ◽  
...  
Keyword(s):  
Remote Sensing ◽  
3D Models ◽  
Hyperspectral Data ◽  
Aerial Images ◽  
Airborne Remote Sensing ◽  
Aerial Photos ◽  
Travel Restrictions ◽  
Field Campaigns ◽  
Local Company ◽  
Hyperspectral Sensor

&lt;p&gt;Svalbard Integrated Arctic Earth Observing System (SIOS) is an international collaboration of 24 research institutions from 9 countries studying the environment and climate in and around Svalbard. The global pandemic of Coronavirus disease (Covid-19) has affected the Svalbard research in a number of ways due to nationwide lockdown in many countries, strict travel restrictions in Svalbard, and quarantine regulations. Many field campaigns to Svalbard were cancelled in 2020 and campaigns in 2021 are still uncertain. In response to this challenge, we conducted practical activities to support the Svalbard science community in filling gaps in scientific observations. One of our activities involved conducting airborne remote sensing campaigns in Svalbard to support scientific projects. In 2020, SIOS supported 10 scientific projects by conducting 25 hours of aircraft and unmanned aerial vehicle (UAV)-based data collection in Svalbard. This is one of the finest ways to fill the data gap in the current situation as it is practically possible to conduct field campaigns using airborne platforms in spite of travel restrictions. We are using the aerial camera and hyperspectral sensor installed onboard the Dornier DO228 aircraft operated by the local company Lufttransport to acquire aerial images and hyperspectral data from various locations in Svalbard. The hyperspectral sensor image the ground in 186 spectral bands covering the range 400-1000 nm. Hyperspectral data can be used to map and characterise earth, ice and ocean surface features, such as minerals, vegetation, glaciers and snow cover, colour and pollutants. Further, it can be used to make 3D models of the terrain as well as searching for the presence of animals (e.g. counting seals). In addition, aerial photos are particularly useful tool to follow the seasonal dynamic changes and extent in sea ice cover, tracking icebergs, ocean productivity (Chlorophyll a) and river runoff (turbidity). Data collected from the SIOS funded airborne missions will not only help to fill a few of the data gaps resulting from the lockdown but also will be used by glaciologists, biologists, hydrologists, and other Earth system scientists to understand the state of the environment of Svalbard during these times. In 2021, we are continuing this activity by conducting more airborne campaigns in Svalbard. In this presentation, we will specifically focus on the overview of projects supported by airborne remote sensing campaigns.&lt;/p&gt;

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