Satellite and UAV Platforms, Remote Sensing for Geographic Information Systems

Colpaert, Alfred

doi:10.3390/s22124564

Cited by 7 publications

(4 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Apart from these applications, drone-integrated GIS can also be used in wildlife monitoring, infrastructure inspection, and search and rescue operations. In wildlife monitoring, drones can be used to capture images of animals and track their movement [18,19]. In infrastructure inspection, drones can be used to inspect bridges, power lines, and other structures that are difficult to access [20,21].…”

Section: Use Cases and Applicative Scopementioning

confidence: 99%

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Quamar,

Al-Ramadan,

Khan

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Drones, also known as unmanned aerial vehicles (UAVs), have gained numerous applications due to their low cost, ease of use, vertical takeover and landing, and ability to operate in high-risk or hard-to-reach areas. The contribution of this review is that of building the bridge between drone technology and its application and advancements in the field of Geographic Information System (GIS). The integration of drones and GIS is valuable as it reduces costs and improves accessibility for geospatial data collection. Traditional methods involving aircraft for aerial photography are expensive, requiring the hiring of aircraft, pilots, and photographers. Drones equipped with advanced cameras and artificial intelligence software can replace the conventional technique and at the same time, be economical and time-efficient. The integration of drones and GIS is expected to bring revolutionary benefits in the fields of precision agriculture, urban planning, emergency health response, disaster management, the development of smart cities, food delivery, etc. In this paper, a state-of-the-art review of the deployment of drone-integrated GIS applications in different fields is presented. Numerous techniques and associated challenges related to their development, formulation, implementation, and regulation are highlighted. It has been concluded that drone-integration solutions in GIS improve efficiency and accuracy, enhance the decision-making process, and facilitate better real-time monitoring. The findings of this review paper are intended to help and benefit researchers, business developers, emergency service providers, industrialists, and policymakers.

show abstract

Section: Use Cases and Applicative Scopementioning

confidence: 99%

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Quamar,

Al-Ramadan,

Khan

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…In recent years, the emergence of the UAV remote sensing platform has brought an opportunity to solve this problem. This platform, flying at a height much lower than the satellites, can acquire images with super-spatial resolution (pixel size<10cm) ( Colpaert, 2022 ). Therefore, the UAV-based images can clearly display the structural features (shape, size, and texture) of ground objects ( Bhandari et al., 2018 ; Osco et al., 2021 ), which to a large extent overcomes the limitations of traditional remote sensing, making the extraction of tiny targets possible ( Yin et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Recognition of terminal buds of densely-planted Chinese fir seedlings using improved YOLOv5 by integrating attention mechanism

Guo

Wei

et al. 2022

Front. Plant Sci.

View full text Add to dashboard Cite

Accurate and timely information on the number of densely-planted Chinese fir seedlings is essential for their scientific cultivation and intelligent management. However, in the later stage of cultivation, the overlapping of lateral branches among individuals is too severe to identify the entire individual in the UAV image. At the same time, in the high-density planting nursery, the terminal bud of each seedling has a distinctive characteristic of growing upward, which can be used as an identification feature. Still, due to the small size and dense distribution of the terminal buds, the existing recognition algorithm will have a significant error. Therefore, in this study, we proposed a model based on the improved network structure of the latest YOLOv5 algorithm for identifying the terminal bud of Chinese fir seedlings. Firstly, the micro-scale prediction head was added to the original prediction head to enhance the model’s ability to perceive small-sized terminal buds. Secondly, a multi-attention mechanism module composed of Convolutional Block Attention Module (CBAM) and Efficient Channel Attention (ECA) was integrated into the neck of the network to enhance further the model’s ability to focus on key target objects in complex backgrounds. Finally, the methods including data augmentation, Test Time Augmentation (TTA) and Weighted Boxes Fusion (WBF) were used to improve the robustness and generalization of the model for the identification of terminal buds in different growth states. The results showed that, compared with the standard version of YOLOv5, the recognition accuracy of the improved YOLOv5 was significantly increased, with a precision of 95.55%, a recall of 95.84%, an F1-Score of 96.54%, and an mAP of 94.63%. Under the same experimental conditions, compared with other current mainstream algorithms (YOLOv3, Faster R-CNN, and PP-YOLO), the average precision and F1-Score of the improved YOLOv5 also increased by 9.51-28.19 percentage points and 15.92-32.94 percentage points, respectively. Overall, The improved YOLOv5 algorithm integrated with the attention network can accurately identify the terminal buds of densely-planted Chinese fir seedlings in UAV images and provide technical support for large-scale and automated counting and precision cultivation of Chinese fir seedlings.

show abstract

“…For LEO EO satellites, the orbit characteristics lead to limited time for satellite-to-ground data transmission [ 1 ]. Technological advancements in satellite engineering have made it feasible to develop EO satellite systems with high spatial, spectral, temporal and radiometric resolutions [ 2 , 3 , 4 , 5 ]. With the development of multifunction and high-resolution payloads, there is an obvious boost of the on-board storage and downlink transmission data volume.…”

Section: Introductionmentioning

confidence: 99%

“…However, the 375 MHz bandwidth of X-band has been saturated for higher data rate requirements. Therefore, the Ka-band with 1.5 GHz bandwidth [ 5 ] has become the development trend of data transmission [ 13 , 14 ]. The Ka-band data-transmission suffers a much greater impact of atmospheric environment, whose rain attenuation could exceed 10 dB [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Transmission Efficiency Evaluation Method of Adaptive Coding Modulation for Ka-Band Data-Transmission of LEO EO Satellites

Wang

et al. 2022

Sensors

View full text Add to dashboard Cite

Nowadays low Earth orbit (LEO) Earth observation (EO) satellites commonly use constant coding modulation (CCM) or variable coding modulation (VCM) schemes for data transmission to ground stations (G/S). Compared with CCM and VCM, the adaptive coding modulation (ACM) could further improve the data throughput of the link by making full use of link resource and the time-varying characteristics of atmospheric attenuation. In order to comprehensively study the data transmission performance, one new index which could be utilized as a quantitative index for the satellite-to-ground data transmission scheme selection, the transmission efficiency factor (TEF) of LEO satellites is proposed and defined as “the product of the link availability and the average useful data rate”. Then, the transmission efficiency of CCM, VCM and ACM at typical G/S with different weather characteristics at Ka-band is compared and analyzed. The results show that ACM is more suitable for the G/S with moderate and abundant rainfall. Compared with the CCM of MCS 28, for Beijing G/S and Sanya G/S, ACM not only improves the transmission efficiency with the TEF increased by 3.62% and 24.51%, respectively, but also improves the link availability with the outage period reduced by 82.47% and 75.18%, respectively.

show abstract

Satellite and UAV Platforms, Remote Sensing for Geographic Information Systems

Abstract: Satellite and UAV (unmanned aerial vehicle) imagery has become an important source of data for Geographic Information Systems (GISs) [...]

Cited by 7 publications

References 10 publications

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Recognition of terminal buds of densely-planted Chinese fir seedlings using improved YOLOv5 by integrating attention mechanism

A Transmission Efficiency Evaluation Method of Adaptive Coding Modulation for Ka-Band Data-Transmission of LEO EO Satellites

Contact Info

Product

Resources

About