- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Histogram-Based Autoadaptive Filter for Destriping NDVI Imagery Acquired by UAV-Loaded Multispectral Camera
摘要： Combinations of unmanned aerial vehicles (UAVs) and multispectral sensors provide low-cost approaches for detailed spatiotemporal vegetation studies. However, the resulting vegetation index images such as normalized difference vegetation index (NDVI) have unignorable stripe noise and seriously disturb the extraction of vegetation information. In this letter, the similar frequency phenomena caused by stripe noise were observed in the gray-scale histogram and the Fourier spectrum of a striped NDVI image. Thus, we tried establishing the empirical quantitative relationship between them, and then designed an autoadaptive ?lter for stripe noise removal in Fourier spectrum according to the characteristics including the dominant peak and troughs of the histogram curve of the raw NDVI image. Applying this autoadaptive ?lter to the corresponding Fourier spectrum image, we achieved automatic and effective stripe noise removal without any manual interference. Based on visual judgment and quantitative evaluation, the proposed autoadaptive ?lter demonstrated by far the better performance in retaining image ?delity and intelligibility than the improved high-pass ?lter and 2-D Weiner ?lter.
关键词： Agricultural multispectral camera (ADC) lite,auto-adaptive ?lter,stripe noise,image histogram,unmanned aerial vehicles (UAV),Fourier spectrum,normalized difference vegetation index (NDVI)
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - The Integration of Uavand Backpack Lidar Systems for Forest Inventory
摘要： Light detection and ranging (Lidar) has been demonstrated with strong capability in capturing three-dimensional (3D) forest structures. The reducing cost and weight of lidar sensors and the development of positioning systems make light-weighted near-surface lidar platforms, such as unmanned aerial vehicle (UAV) and backpack, become possible. These light-weighted lidar platforms have great potentials to be used as complimentary tools to improve both the accuracy and efficiency of forest inventory. In this study, we presented our self-developed low-cost UAV lidar system and backpack lidar system. A kinetic calibration algorithm and an improved 3D simultaneous localization and mapping algorithm were used to improve the positioning accuracy of the UAV lidar system and backpack lidar system, respectively. We then explored the possibility to automatically register backpack lidar data with UAV lidar data in a conifer forest using a two-step method based on segmented individual tree locations and the iterative closest point algorithm. The results of this study can provide guidance for a systematic lidar solution in forest inventory.
关键词： UAV,forest,inventory,backpack,Lidar
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Implementation of UAV-Based Lidar for High Throughput Phenotyping
摘要： High throughput phenotyping is rapidly gaining widespread popularity due to its ability to non-destructively extract plant traits, such as plant height, canopy density, leaf and plant structure, and so on. In this study, we focus on developing a UAV-based LiDAR system to acquire accurate time-series 3D point clouds for monitoring two specific plant traits – plant height and canopy cover – which are integral for enhancing crop genetic improvement to meet the needs of future generations. Furthermore, the obtained estimates are validated by comparing the results with those obtained from wheel-based LiDAR data.
关键词： High throughput phenotyping,UAV,plant height,canopy cover,LiDAR system
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Development and Preliminary Results of Small-Size Uav-Borne Fmcw Sar
摘要： The small-size unmanned aerial vehicle (UAV) is being used widely in many fields, especially in surveying, mapping and remote sensing. Due to the platform’s size and load ability, its payload is strictly limited. Synthetic aperture radar(SAR) is a kind of microwave imaging instrument with high performance under all weather, day and night conditions. Highly miniaturized SAR can satisfy the requirement of observation on small UAV. Frequency modulation continuous wave (FMCW) technology provides a way for small volume, low cost, high reliability and high resolution SAR. FMCW SAR transmits frequency modulated signal continuously. This reduces the peak power, which is the important factor determining the size and cost of SAR. Meanwhile, due to transmitting and receiving signals simultaneously, increasing the isolation between the transmitter and receiver becomes associated problem. Two separated antennas solve the problem partly. There is another problem in processing algorithm. Long duration of signal makes the assumption of stop and go model ineffective. Frequency scaling algorithm has to be chosen to correct the phase variation during one period of frequency sweep. Procedure of development for prototype and practical systems and verification experiments are shown in this paper. The results of experiments with such radars prove the expected performance.
关键词： UAV,Synthetic Aperture Radar,FMCW,SAR/ISAR
更新于2025-09-09 09:28:46
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Criteria for the optimal selection of remote sensing images to map event landslides
摘要： We executed an experiment to determine the effects of image characteristics on event landslide mapping. In the experiment, we compared eight maps of the same landslide, the Assignano landslide, in Umbria, central Italy. Six maps were obtained through the expert visual interpretation of monoscopic and pseudo-stereoscopic (2.5D), ultra-resolution (3 × 3 cm) images taken on 14 April 2014 by a Canon EOS M photographic camera flown by an CarbonCore 950 hexacopter over the landslide, and of monoscopic and stereoscopic, true-colour and false-colour-composite, 1.84 × 1.84 m resolution images taken by the WorldView-2 satellite also on 14 April 2014. The seventh map was prepared through a reconnaissance field survey aided by a pre-event satellite image taken on 8 July 2013, available on Goggle Earth?, and by colour photographs taken in the field with a hand-held camera. The images were interpreted visually by an expert geomorphologist using the StereoMirror? hardware technology combined with the ERDAS IMAGINE? and Leica Photogrammetry Suite (LPS) software. The eighth map, which we considered our reference showing the “ground truth”, was obtained through a Real Time Kinematic differential GPS survey conducted by walking a GPS receiver along the landslide perimeter to capture geographic coordinates every about 5 m, with centimetre accuracy. The eight maps of the Assignano landslide were stored in a GIS, and compared adopting a pairwise approach. Results of the comparisons, quantified by the error index E, revealed that where the landslide signature was primarily photographical (in the landslide source and transport area) the best mapping results were obtained using the higher resolution images, and where the landslide signature was mainly morphometric (in the landslide deposit) the best results were obtained using the stereoscopic images. The ultra-resolution image proved very effective to map the landslide, with results comparable to those obtained using the stereoscopic satellite image. Conversely, the field-based reconnaissance mapping provided the poorest results, measured by large mapping errors, and confirmed the difficulty in preparing accurate landslide maps in the field. Albeit conducted on a single landslide, we maintain that our results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.
关键词： remote sensing,landslide mapping,UAV,GIS,image interpretation,WorldView-2 satellite
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - GPU Acceleration of UAV Image Splicing Using Oriented Fast and Rotated Brief Combined with PCA
摘要： In this study, an accelerating method of oriented FAST and rotated BRIEF combined with principal component analysis (ORB/PCA) is proposed for splicing detection of unmanned aerial vehicle (UAV) images. Compared to traditional scale-invariant feature transform (SIFT) and speeded up robust features (SURF) methods, the proposed ORB/PCA can not only be faster but also produce more accurate. Moreover, in order for the proposed ORB to be effective for image stitching process in near real-time, the Compute Unified Device Architecture (CUDA) application programming interface of graphics processing unit (GPU) is cooperated to speed up the proposed method. Experimental results show that the proposed GPU based ORB/PCA framework is suitable for splicing detection of UAV images in Earth remote sensing. It can improve the image stitching process both in time and accuracy compared to conventional methods.
关键词： oriented FAST and rotated BRIEF (ORB),principal component analysis (PCA),unmanned aerial vehicle (UAV),graphics processing unit (GPU)
更新于2025-09-09 09:28:46
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Dynamic Optimization of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints
摘要： This paper demonstrates the use of nonlinear dynamic optimization to calculate energy-optimal trajectories for a high-altitude, solar-powered unmanned aerial vehicle (UAV). The objective is to maximize the total energy in the system while staying within a 3 km mission radius and meeting other system constraints. Solar energy capture is modeled using the vehicle orientation and solar position, and energy is stored both in batteries and in potential energy through elevation gain. Energy capture is maximized by optimally adjusting the angle of the aircraft surface relative to the sun. The UAV flight and energy system dynamics are optimized over a 24 h period at an 8 s time resolution using nonlinear model predictive control. Results of the simulated flights are presented for all four seasons, showing an 8.2% increase in end-of-day battery energy for the most limiting flight condition of the winter solstice.
关键词： solar-powered UAV,energy-optimal trajectories,nonlinear model predictive control,nonlinear dynamic optimization,high-altitude long-endurance
更新于2025-09-09 09:28:46
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[IEEE 2018 37th Chinese Control Conference (CCC) - Wuhan (2018.7.25-2018.7.27)] 2018 37th Chinese Control Conference (CCC) - Wheat Drought Assessment by Remote Sensing Imagery Using Unmanned Aerial Vehicle
摘要： This work aims at evaluating the usability of remote sensing RGB imagery by an Unmanned Aerial Vehicle (UAV) in assessing wheat drought status. A UAV survey is conducted to collect high-resolution RGB imageries by using DJI S1000 for the experimental wheat ?elds of Gucheng town, Heibei Province, China. The soil moisture for different plots of the experimental ?led is kept at an approximately constant level for the whole growing season in a well controlled environment, where ?eld measurements are performed just after the UAV survey to obtain the soil water content for each plot. A machine learning based wheat drought assessment framework is proposed in this work. In the proposed framework, wheat pixels are ?rst segmented from the soil background using the classical normalized excess green index (NExG). Rather than using pixel-wise classi?cation, a pixel square of appropriate dimension is de?ned as the samples, based on which various features are extracted for the wheat pixels including statistical features and spectral index features. Different classi?cation algorithms are experimented to identify a suitable one in terms of classi?cation accuracy and computation time. It is discovered that Support Vector Machine with Gaussian kernel can obtain an accuracy over 90%, which demonstrates the usefulness of RGB imagery in wheat drought assessment.
关键词： UAV imagery,Wheat drought,Remote sensing,Classi?cation
更新于2025-09-09 09:28:46
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A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications
摘要： This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative ?ying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological ?ltering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational ef?ciency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting ?ight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments.
关键词： autonomous navigation,morphological ?ltering,visual detection,unmanned aerial vehicles,visual tracking,template matching,cooperative UAV applications
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Investigating Forest Photosynthetic Response to Elevated CO<inf>2</inf> Using Uav-Based Measurements of Solar Induced Fluorescence
摘要： The response of ecosystems to increasing atmospheric CO2 will have significant, but still uncertain, impacts on the global carbon and water cycles. A lot of information has been gained from Free Air CO2 Enrichment (FACE) experiments, but the response of mature forest ecosystems remains a significant knowledge gap. One of the challenges in FACE studies is obtaining an integrated measure of canopy photosynthesis at the scale of the treatment ring. A new remote sensing approach for measuring photosynthetic activity is based on Solar Induced Fluorescence (SIF), which is emitted by plants during photosynthesis, and is closely linked to the rates and regulation of photosynthesis. We proposed that UAV-based SIF measurements, that enable the spectrometer field of view to be targeted to the treatment ring, provide a unique opportunity for investigating the dynamics of photosynthetic responses to elevated CO2. We have successfully tested this approach in a new FACE site, located in a mature oak forest in the UK. We flew a series of flights across the experiment arrays, collecting a number of spectra. We combined these with ground-based physiological and optical measurements, and see great promise in the use of UAV-based SIF measurements in FACE and other global change experiments.
关键词： Piccolo Doppio,photosynthesis,Solar Induced Fluorescence,UAV,global change
更新于2025-09-09 09:28:46