Remote sensing spectrometric system for emergency response on board of unmanned helicopter

2012 ◽  
Author(s):  
Doyno Petkov ◽  
Hristo Nikolov ◽  
Denitsa Borisova
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Unmanned Helicopter ◽  
Spectrometric System

VARIABLE MANAGEMENT FOR UNIFORM POTATO YIELD USING REMOTE SENSING IMAGES WITH UNMANNED HELICOPTER

2013 ◽  
Author(s):  
Jun Yokobori ◽  
Katsuhisa Niwa ◽  
Ryo Sugiura ◽  
Noboru Noguchi ◽  
Yutaka Chiba
Keyword(s):  
Remote Sensing ◽  
Potato Yield ◽  
Unmanned Helicopter ◽  
Remote Sensing Images

Reducing the stride of the convolution kernel: a simple and effective strategy to increase the performance of CNN in building extraction from remote sensing image

2021 ◽  
Author(s):  
Meng Chen ◽  
Jianjun Wu ◽  
Feng Tian
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Learning Technology ◽  
Convolution Kernel ◽  
Building Extraction ◽  
Effective Strategy ◽  
Feature Maps ◽  
Data Set ◽  
Irregular Shapes ◽  
Deep Layers

<p>Automatically extracting buildings from remote sensing images (RSI) plays important roles in urban planning, population estimation, disaster emergency response, etc. With the development of deep learning technology, convolutional neural networks (CNN) with better performance than traditional methods have been widely used in extracting buildings from remote sensing imagery (RSI). But it still faces some problems. First of all, low-level features extracted by shallow layers and abstract features extracted by deep layers of the artificial neural network could not be fully fused. it makes building extraction is often inaccurate, especially for buildings with complex structures, irregular shapes and small sizes. Secondly, there are so many parameters that need to be trained in a network, which occupies a lot of computing resources and consumes a lot of time in the training process. By analyzing the structure of the CNN, we found that abstract features extracted by deep layers with low geospatial resolution contain more semantic information. These abstract features are conducive to determine the category of pixels while not sensitive to the boundaries of the buildings. We found the stride of the convolution kernel and pooling operation reduced the geospatial resolution of feature maps, so, this paper proposed a simple and effective strategy—reduce the stride of convolution kernel contains in one of the layers and reduced the number of convolutional kernels to alleviate the above two bottlenecks. This strategy was used to deeplabv3+net and the experimental results for both the WHU Building Dataset and Massachusetts Building Dataset. Compared with the original deeplabv3+net the result showed that this strategy has a better performance. In terms of WHU building data set, the Intersection over Union (IoU) increased by 1.4% and F1 score increased by 0.9%; in terms of Massachusetts Building Dataset, IoU increased by 3.31% and F1 score increased by 2.3%.</p>

scholarly journals Dynamic earth observation based on an urban skyline: A new remote sensing approach for urban emergency response

2020 ◽  
Vol 51 (1) ◽  
pp. 78-88
Author(s):  
ChiSheng WANG ◽  
XueQing GUO ◽  
JinCheng JIANG ◽  
YongQuan WANG ◽  
QingQuan LI ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Earth Observation

scholarly journals Tools for Improved Drought and Flood Response

Eos ◽  
2021 ◽  
Vol 102 ◽  
Author(s):  
Huan Wu ◽  
Dennis Lettenmaier ◽  
Qiuhong Tang ◽  
Philip Ward
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Global Scale ◽  
Policy Makers ◽  
Drought And Flood ◽  
Recent Advances ◽  
Droughts And Floods ◽  
Flood Response

A new book presents recent advances in the modeling and remote sensing of droughts and floods of use to emergency response organizations and policy makers on a global scale.

scholarly journals Indexes establishment and capability evaluation of space-air-ground remote sensing cooperation in geo-hazard emergency response

2020 ◽  
Author(s):  
Yahong Liu ◽  
Jin Zhang
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Evaluation Model ◽  
Collaborative Work ◽  
Service Evaluation ◽  
Task Completion ◽  
Evaluation Indexes ◽  
Service Capability ◽  
Capability Evaluation ◽  
Time Critical

Abstract. Geo-hazard emergency response is a disaster prevention and reduction action that multi-factorial, time-critical, task-intensive and socially significant. In order to improve the rationalization and standardization of space-air-ground remote sensing collaborative observation in geo-hazard emergency response, this paper comprehensively analyzes the technical resources of remote sensing sensors and the emergency service system, and establishes a database of technical and service evaluation indexes using MySQL. A method is proposed to evaluate and calculate the cooperative observation effectiveness in a specific remote sensing cooperative environment by combining TOPSIS and RSR. For the evaluation of remote sensing cooperative service capability in geo-hazard emergency response, taking earthquake as an example, establishing a remote sensing cooperative earthquake emergency response service chain, and designing a Bayesian network evaluation model. Through the evaluation of observation efficiency and service capability, the operation and task completion of remote sensing collaborative technology in geo-hazard emergency response can be effectively grasped and a basis for decision making can be provided for space-air-ground remote sensing collaborative work.

scholarly journals Emergency Response Using Volunteered Passenger Aircraft Remote Sensing Data: A Case Study on Flood Damage Mapping

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4163 ◽  
Author(s):  
Chisheng Wang ◽  
Junzhuo Ke ◽  
Wenqun Xiu ◽  
Kai Ye ◽  
Qingquan Li
Keyword(s):  
Remote Sensing ◽  
Emergency Response ◽  
Low Cost ◽  
Remote Sensing Data ◽  
Flood Damage ◽  
Sensing Data ◽  
Sensing Platform ◽  
Damage Mapping ◽  
Passenger Aircraft

Current satellite remote sensing data still have some inevitable defects, such as a low observing frequency, high cost and dense cloud cover, which limit the rapid response to ground changes and many potential applications. However, passenger aircraft may be an alternative remote sensing platform in emergency response due to the high revisit rate, dense coverage and low cost. This paper introduces a volunteered passenger aircraft remote sensing method (VPARS) for emergency response. It uses the images captured by the passenger volunteers during flight. Based on computer vision algorithms and geocoding procedures, these images can be processed into a mosaic orthoimage for rapid ground disaster mapping. Notable, due to the relatively low flight latitude, small clouds can be easily removed by stacking multi-angle tilt images in the VPARS method. A case study on the 2019 Guangdong flood monitoring validates these advantages. The frequent aircraft revisit time, intensive flight coverage, multi-angle images and low cost of the VPARS make it a potential way to complement traditional remote sensing methods in emergency response.

Precise Remote Sensing Using Unmanned Helicopter

2019 ◽  
Author(s):  
Aleksander Olejnik ◽  
Lukasz Kiszkowiak ◽  
Robert Rogolski ◽  
Grzegorz Chmaj ◽  
Michal Radomski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Helicopter
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