scholarly journals Long‐duration fully autonomous operation of rotorcraft unmanned aerial systems for remote‐sensing data acquisition

2019 ◽  
Vol 37 (1) ◽  
pp. 137-157 ◽  
Author(s):  
Danylo Malyuta ◽  
Christian Brommer ◽  
Daniel Hentzen ◽  
Thomas Stastny ◽  
Roland Siegwart ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Remote Sensing Data ◽  
Unmanned Aerial Systems ◽  
Sensing Data ◽  
Autonomous Operation ◽  
Long Duration ◽  
Aerial Systems

scholarly journals Remote Sensing Data Analysis for the Ecological Stability Purposes

2021 ◽  
Vol 906 (1) ◽  
pp. 012068
Author(s):  
Jakub Chromcak ◽  
Matus Farbak ◽  
Alexander Ivannikov ◽  
Robert Sasik ◽  
Jana Dibdiakova
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Remote Sensing Data ◽  
Environmental Issues ◽  
Point Of View ◽  
Environment Monitoring ◽  
Ecological Stability ◽  
Nature Protection ◽  
Stability Calculation ◽  
Sensing Data

Abstract The remote sensing offers the opportunity of miscellaneous data acquisition with various ways of their consequent analysis and application. The processed remote sensing data in the form of georeferenced orthophotoimages or orthophotomaps enable the study of the examined locality from the chosen observed feature point of view. According to periodical data acquisition, it is possible to monitor the ongoing and emerging actions in time and then prevent and predict the upcoming actions. With the increasing interest in environmental issues and nature protection, the natural environment monitoring, preservation, protection and remediation present the number one priority. From the ecological point of view, the analysis of orthophotos/orthophotomaps present the up-to-date way of ecological stability calculation and monitoring.

Study on Disaster Monitoring Satellite Remote Sensing Data Fast Acquisition Programming Technology

2011 ◽  
Vol 356-360 ◽  
pp. 2864-2869
Author(s):  
Guang Bin Ma ◽  
Wen Yi Zhang ◽  
Peng Huang
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Satellite Data ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Programming System ◽  
Sensing Data ◽  
Fast Acquisition ◽  
Disaster Area ◽  
Disaster Monitoring

This paper studies the multi-satellites data fast acquisition programming technology for disaster area, and in this paper a disaster monitoring satellite data fast acquisition programming system is established. After the disaster, the system can program the multi-satellites observation schedule for the disaster area quickly and accurately, it can provide important technical support for the satellite data acquisition of the disaster area.

scholarly journals Mapping Succession in Non-Forest Habitats by Means of Remote Sensing: Is the Data Acquisition Time Critical for Species Discrimination?

2019 ◽  
Vol 11 (22) ◽  
pp. 2629 ◽  
Author(s):  
Katarzyna Osińska-Skotak ◽  
Aleksandra Radecka ◽  
Hubert Piórkowski ◽  
Dorota Michalska-Hejduk ◽  
Dominik Kopeć ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Remote Sensing Data ◽  
Natura 2000 ◽  
Recursive Feature Elimination ◽  
Acquisition Time ◽  
Species Discrimination ◽  
Natural Habitats ◽  
Sensing Data ◽  
Data Acquisition Time

The process of secondary succession is one of the most significant threats to non-forest (natural and semi-natural open) Natura 2000 habitats in Poland; shrub and tree encroachment taking place on abandoned, low productive agricultural areas, historically used as pastures or meadows, leads to changes to the composition of species and biodiversity loss, and results in landscape transformations. There is a perceived need to create a methodology for the monitoring of vegetation succession by airborne remote sensing, both from quantitative (area, volume) and qualitative (plant species) perspectives. This is likely to become a very important issue for the effective protection of natural and semi-natural habitats and to advance conservation planning. A key variable to be established when implementing a qualitative approach is the remote sensing data acquisition date, which determines the developmental stage of trees and shrubs forming the succession process. It is essential to choose the optimal date on which the spectral and geometrical characteristics of the species are as different from each other as possible. As part of the research presented here, we compare classifications based on remote sensing data acquired during three different parts of the growing season (spring, summer and autumn) for five study areas. The remote sensing data used include high-resolution hyperspectral imagery and LiDAR (Light Detection and Ranging) data acquired simultaneously from a common aerial platform. Classifications are done using the random forest algorithm, and the set of features to be classified is determined by a recursive feature elimination procedure. The results show that the time of remote sensing data acquisition influences the possibility of differentiating succession species. This was demonstrated by significant differences in the spatial extent of species, which ranged from 33.2% to 56.2% when comparing pairs of maps, and differences in classification accuracies, which when expressed in values of Cohen’s Kappa reached ~0.2. For most of the analysed species, the spring and autumn dates turned out to be slightly more favourable than the summer one. However, the final recommendation for the data acquisition time should take into consideration the phenological cycle of deciduous species present within the research area and the abiotic conditions.

Remote Sensing Data Acquisition, Platforms and Sensor Requirements

1996 ◽  
Vol 24 (4) ◽  
pp. 207-237 ◽  
Author(s):  
R R Navalgund ◽  
V Jayaraman ◽  
A S Kiran Kumar ◽  
Tara Sharma ◽  
Kurien Mathews ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Acquisition ◽  
Remote Sensing Data ◽  
Sensing Data
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