Airborne Platforms Research Articles

Design of supercontinuum laser hyperspectral light detection and ranging (LiDAR) (SCLaHS LiDAR)

ABSTRACT Traditional Light Detection and Rangings (LiDARs) can quickly collect high-accuracy of three-dimensional (3D) point cloud data at a designated wavelength (i.e., cannot obtain hyperspectral data), while the passive hyperspectral imager can collect rich spectral data of ground objects, but are lack of 3D spatial data. This paper presents one innovative study on the design of airborne-oriented supercontinuum laser hyperspectral (SCLaHS) LiDAR with 50 bands covering 400 nm to 900 nm at a spectral resolution of 10 nm and ground sampling distance (GSD) of 0.5 m. The major innovations include (1) development of the high-power narrow-pulse supercontinuum laser source covering 400 nm to 900 nm with 50 bands using multi-core microstructure fibre, all-polarization maintaining fibre and ultra-long cavity structure, (2) a miniaturized aberration correction holographic concave grating spectroscopic and streak tube technique are developed for 50 bands laser echoes detection at high spectral-spatial-temporal resolution and dynamic airborne platform, and (3) the algorithm theoretic basis for SCLaHS LiDAR point cloud data 3D geodetic coordination calculation, including in-flight airborne calibration algorithm. The initial experimental results demonstrated that the designed SCLaHS LiDAR is doable, and a prototype of the (SCLaHS) LiDAR intends to be implemented.

Image‐based high‐throughput phenotyping for the estimation of persistence of perennial ryegrass (Lolium perenne L.)—A review

AbstractPerennial ryegrass (Lolium perenne L.) is considered the most important pasture species in temperate agriculture, with over six million hectares of sown area in Australia alone. However, perennial ryegrass has poor persistence in some environments because of low tolerance to a range of both abiotic and biotic stresses. To breed perennial ryegrass, cultivars with greater persistence and productivity may require evaluation of genotypes over a number of years. Persistence assessment in pasture breeding depends on manual ground cover estimation or counting the number of surviving plants or tillers in a known area. These methods are subjective and labour intensive, which may limit data collection in large‐scale breeding programs. With the rapid development of sensors and image processing algorithms, image‐based high‐throughput phenotyping (HTP) is becoming commonplace in the breeding of major food crops. Image‐based HTP approaches consist of the deployment of a wide range of sensors on ground‐based or airborne platforms and data analysed through image processing pipelines. Image‐based HTP shows high potential for use in pasture phenotyping in breeding programs and may be able to reduce timeframes for releasing new cultivars. Moreover, existing image‐based HTP approaches could be further developed to include precise tools for phenotyping pasture persistence traits such as pasture senescence, botanical composition, pathogen and pest resistance. In this study, we reviewed existing image‐based HTP approaches in precision agriculture and discussed their feasibility for perennial ryegrass persistence estimation in pasture breeding. Although the paper focuses on application in perennial ryegrass, the principles equally apply to other perennial forage species.

Monitoring the seagrass ecosystem using the unmanned aerial vehicle (UAV) in coastal water of Jepara

Seagrass ecosystem in the world were highly sensitive to environmental changes. They were also in global decline and under threat from a variety of anthropogenic factors and global climate change. There was now an urgency to establish robust monitoring methodologies so that changed in seagrass abundance and distribution in these sensitive coastal environments can be understood. Typical monitoring approaches have included remote sensing from satellites and airborne platform, ground base ecological survey. The techniques can suffer from temporal and spatial inconsistency, or were very localised, making it hard to assess seagrass meadows in a structurer manner. The aim of this research was to present the technique of using a lightweight drone and consumer grade cameras to produce very high spatial resolution mosaic of intertidal site in Bandengan, Jepara waters, Indonesia. The data collection methodologies followed by digitation method techniques to produce coverage estimates, with ground check at location, with data drone analysis. This result showed that digitation method can show between the observed and classified low coverage seagrass 7-12% (<25%) compare to middle coverage seagrass 34-48% (between 25< and <50%), also was able to detect the other biotic features, such as colonies of macroalgae, massive coral, the flat sand and coral rubble at the observation location.

Connecting the other half: Exploring options for the 50% of the population unconnected to the internet

As of the end of 2019, 46.4% of the world's population does not have regular access to the Internet. Bringing the more than 3.5 billion individuals still unconnected online is the primary goal for multiple international organizations, including the ITU and the UN Broadband Commission. Two important barriers that restrict connectivity are the lack of infrastructure and affordability. To address these barriers, several novel concepts that involve spaceborne and airborne platforms have been proposed to provide connectivity at a lower cost (improve affordability) to a wider reach of people (extend infrastructure). We develop a techno-economic methodology to assess the potential impact of space and aerial concepts in expanding connectivity to uncovered and under-served regions. In particular, constellations of geostationary orbit (GEO) satellites, large constellations of medium Earth orbit (MEO) and low Earth orbit (LEO) satellites, and high- and low-altitude aerial platforms are studied. Results show that under the current scenario, the impact of space and aerial systems in terms of expanding connectivity would be rather modest; the current cost of satellite technology (~$200 per Mbps/month) are affordable for less than 1% of the uncovered and under-served population in the countries of interest. In a future scenario in 8–10 years, space systems have the highest potential to bring uncovered and under-served populations online, being a viable technology for 24% of the population in these countries.

Facility level measurement of offshore oil and gas installations from a medium-sized airborne platform: method development for quantification and source identification of methane emissions

Abstract. Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed, and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate &amp;amp; Clean Air Coalition (UN CCAC) objective to study and reduce short-lived climate pollutants (SLCPs), a Twin Otter aircraft was used to survey CH4 emissions from UK and Dutch offshore oil and gas installations. The aims of the surveys were to (i) identify installations that are significant CH4 emitters, (ii) separate installation emissions from other emissions using carbon-isotopic fingerprinting and other chemical proxies, (iii) estimate CH4 emission rates, and (iv) improve flux estimation (and sampling) methodologies for rapid quantification of major gas leaks. In this paper, we detail the instrument and aircraft set-up for two campaigns flown in the springs of 2018 and 2019 over the southern North Sea and describe the developments made in both the planning and sampling methodology to maximise the quality and value of the data collected. We present example data collected from both campaigns to demonstrate the challenges encountered during offshore surveys, focussing on the complex meteorology of the marine boundary layer and sampling discrete plumes from an airborne platform. The uncertainties of CH4 flux calculations from measurements under varying boundary layer conditions are considered, as well as recommendations for attribution of sources through either spot sampling for volatile organic compounds (VOCs) ∕ δ13CCH4 or using in situ instrumental data to determine C2H6–CH4 ratios. A series of recommendations for both planning and measurement techniques for future offshore work within marine boundary layers is provided.

Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) over the Middle and Lower Reaches of the Yangtze River in 2020

Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) was conducted over the middle and lower reaches of the Yangtze River during the period 16 June to 19 July 2020. This paper provides a brief overview of the IMFRE-II field campaign, including the multiple ground-based remote sensors, aircraft probes, and their corresponding measurements during the 2020 mei-yu period, as well as how to use these numerous datasets to answer scientific questions. The highlights of IMFRE-II are: (1) to the best of our knowledge, IMFRE-II is the first field campaign in China to use ground-based, airborne, and spaceborne platforms to conduct comprehensive observations over the middle and lower reaches of the Yangtze River; and (2) seven aircraft flights were successfully carried out, and the spectra of ice particles, cloud droplets, and raindrops at different altitudes were obtained. These in-situ measurements will provide a “cloud truth” to validate the ground-based and satellite-retrieved cloud and precipitation properties and quantitatively estimate their retrieval uncertainties. They are also crucial for the development of a warm (and/or cold) rain conceptual model in order to better understand the cloud-to-rain conversion and accretion processes in mei-yu precipitation events. Through an integrative analysis of ground-based, aircraft, and satellite observations and model simulations, we can significantly improve our cloud and precipitation retrieval algorithms, investigate the microphysical properties of cloud and precipitation, understand in-depth the formation and dissipation mechanisms of mei-yu frontal systems, and improve cloud microphysics parameterization schemes and model simulations.

Advances in spaceborne hyperspectral remote sensing in China

ABSTRACT With the maturation of satellite technology, Hyperspectral Remote Sensing (HRS) platforms have developed from the initial ground-based and airborne platforms into spaceborne platforms, which greatly promotes the civil application of HRS imagery in the fields of agriculture, forestry, and environmental monitoring. China is playing an important role in this evolution, especially in recent years, with the successful launch and operation of a series of civil hyperspectral spacecraft and satellites, including the Shenzhou-3 spacecraft, the Gaofen-5 satellite, the SPARK satellite, the Zhuhai-1 satellite network for environmental and resources monitoring, the FengYun series of satellites for meteorological observation, and the Chang’E series of spacecraft for planetary exploration. The Chinese spaceborne HRS platforms have various new characteristics, such as the wide swath width, high spatial resolution, wide spectral range, hyperspectral satellite networks, and microsatellites. This paper focuses on the recent progress in Chinese spaceborne HRS, from the aspects of the typical satellite systems, the data processing, and the applications. In addition, the future development trends of HRS in China are also discussed and analyzed.

Real-Time SAR Imaging Based on Reconfigurable Computing

Real-time synthetic aperture radar (SAR) image-processing systems on airborne or spaceborne platforms have constraints in terms of their power consumption, volume, and weight. In order to meet the requirements of these platforms and increase the flexibility of system application, this paper presents a SAR real-time imaging technology based on field-programmable gate array (FPGA) dynamic-reconfiguration technology. First, this technology is used to optimize the algorithm. The entire process flow is then classified into dynamic and static parts. The dynamic part implements numerical calculations, and the static part involves process control, data storage, and peripheral interface. Then, based on dynamic reconfiguration, the processing system is designed, including data interface, data storage, process control, and data operation. Finally, using flight data based on an unmanned aerial vehicle, the performance of the system is verified. The results indicate that the system needs to be run at a 200 MHz frequency for 85.9 s to process data with a size of 65536 ×65536. The system uses approximately 31.4% less resources and consumes 20% less power compared to the traditional method. These experimental results prove the effectiveness of the technology, laying the foundation for the design of high-performance real-time image-processing systems on airborne or spaceborne platforms.

Spatial-Resolution Independent Object Detection Framework for Aerial Imagery

Earth surveillance through aerial images allows more accurate identification and characterization of objects present on the surface from space and airborne platforms. The progression of deep learning and computer vision methods and the availability of heterogeneous multispectral remote sensing data make the field more fertile for research. With the evolution of optical sensors, aerial images are becoming more precise and larger, which leads to a new kind of problem for object detection algorithms. This paper proposes the “Sliding Region-based Convolutional Neural Network (SRCNN),” which is an extension of the Faster Region-based Convolutional Neural Network (RCNN) object detection framework to make it independent of the image’s spatial resolution and size. The sliding box strategy is used in the proposed model to segment the image while detecting. The proposed framework outperforms the state-of-the-art Faster RCNN model while processing images with significantly different spatial resolution values. The SRCNN is also capable of detecting objects in images of any size.

A Remote Carrier Synchronization Technique for Coherent Distributed Remote Sensing Systems

Phase, frequency, and time synchronization are crucial requirements for many applications, such as multistatic remote sensing and communication systems. Moreover, the synchronization solution becomes even more challenging when the nodes are orbiting or flying on airborne or spaceborne platforms. This article compares the available technologies used for the synchronization and coordination of nodes in distributed remote sensing applications. Additionally, this article proposes a general system model and identifies preliminary guidelines and critical elements for implementing the synchronization mechanisms exploiting the intersatellite communication link. The distributed phase synchronization loop introduced in this work deals with the self-interference in a full-duplex point to point scenario by transmitting two carriers at each node. All carriers appear with different frequency offsets around a central frequency, called the application central-frequency or the beamforming frequency. This article includes a detailed analysis of the proposed algorithm and the required simulations to verify its performance for different phase noise, additive white Gaussian noise, and Doppler shift scenarios.

Airborne GNSS-R: A Key Enabling Technology for Environmental Monitoring

Weather forecast using GNSS-R relies, to a large extent, on data acquired by airborne and spaceborne platforms due to the extended coverage that can be achieved. GEO satellites can retrieve measurements over large areas but with spatial resolutions on the order of thousands of meters per pixel. LEO satellites with polar orbits can provide measurements over the entire world, but they cannot provide good spatial or high temporal resolutions by themselves. LEO constellations of small satellites have the same coverage with improved spatial resolution and revisit times by using data fusion techniques. High-altitude pseudo-satellites offer an excellent temporal and spatial resolution but only over limited areas. In this article, the potential of using hosted GNSS-R payloads on commercial aircraft is explored as an alternative and cost-effective means to achieve a very high resolution and a very low revisit time for regional environmental applications. Finally, a case study of soil moisture monitoring over Europe is presented, including an analysis of the expected performance.

Experimental Study on Photodiode Array Sensor Aided MEMS Fine Steering Mirror Control for Laser Communication Platforms

Line-of-sight laser communication application scenarios are numerous including land, mobile, maritime, airborne and space platforms for conventional and tactical utilization. However, beam pointing and stabilization are complicated in dynamic systems such as orbiting satellite to ground receiver, drones, aircrafts and metropolitan free-space optical links vulnerable to natural and artificial disturbances. Small Satellite platforms such as CubeSats are even more challenging due to their limited size and on-board resources. This paper presents an experimental study on a feedback photodiode array sensor assisted control of a one-axis micro-electromechanical (MEMS) fine steering mirror stabilizing a laser communication link on an optical bench in the laboratory. Disturbance profiles similar to vibrations on dynamic platforms are induced into the setup using an electrodynamic vibration machine to test the efficacy of the MEMS fine steering control mechanism. The Photodiode Array (PDA) sensor collocated with an Avalanche Photodiode at the receiving section provides sustained information about the transmitter's movements and beam displacements while the received optical signal strength is continuously monitored. The feedback signals are transmitted to the FSM controller via a radio link. We demonstrate the capacity to stabilize a laser beam transmission in the presence of external disturbances and platform movements using a PDA sensor assisted control.

Target echo denoising algorithm of airborne platform multi pulse laser rangefinder under low SNR

Target echo denoising algorithm of airborne platform multi pulse laser rangefinder under low SNR

The role of a suburban forest in controlling vertical trace gas and OH reactivity distributions - a case study for the Seoul metropolitan area.

We present trace gas vertical profiles observed by instruments on the NASA DC-8 and at a ground site during the Korea-US air quality study (KORUS) field campaign in May to June 2016. We focus on the region near the Seoul metropolitan area and its surroundings where both anthropogenic and natural emission sources play an important role in local photochemistry. Integrating ground and airborne observations is the major research goal of many atmospheric chemistry field campaigns. Although airborne platforms typically aim to sample from near surface to the free troposphere, it is difficult to fly very close to the surface especially in environments with complex terrain or a populated area. A detailed analysis integrating ground and airborne observations associated with specific concentration footprints indicates that reactive trace gases are quickly oxidized below an altitude of 700 m. The total OH reactivity profile has a rapid decay in the lower part of troposphere from surface to the lowest altitude (700 m) sampled by the NASA DC-8. The decay rate is close to that of very reactive biogenic volatile organic compounds such as monoterpenes. Therefore, we argue that photochemical processes in the bottom of the boundary layer, below the typical altitude of aircraft sampling, should be thoroughly investigated to properly assess ozone and secondary aerosol formation.

Research on echo filtering algorithm of multi pulse laser range extended target in dynamic clutter background of airborne platform

Research on echo filtering algorithm of multi pulse laser range extended target in dynamic clutter background of airborne platform

A Compact, Reconfigurable, Multi-UWB Radar for Snow Thickness Evaluation and Altimetry: Development and Field Trials

We developed a portable ultra-wideband radar system capable of reconfigurable operation in multiple frequency bands (separate or simultaneous) spanning from microwaves through millimeter waves. The instrument provides a compact solution for fine-resolution measurements of elevation changes and superficial snow/firn thickness from low-altitude, mid-sized airborne platforms. In this article, we provide an overview of the radar system design and its performance during laboratory testing. We demonstrate its application in aerial surveys of snow layer thickness at S/C bands, dual-band airborne altimetry at Ku-/Ka-bands, and present first-order comparisons with coincident airborne lidar data.

Spatial validation of submerged fluvial topographic models by mesohabitat units

ABSTRACT Mapping the streambed morphology is crucial for understanding fluvial forms and processes, for advancing both our knowledge and best management practice of riverine systems. It is often done by wading streams but recently topobathymetric Light Detection and Ranging (LiDAR) and imagery captured from airborne platforms are becoming promising and effective surveying methodologies. The recent use of remotely piloted aerial systems (RPAS) combined with structure-from-motion (SfM) photogrammetric processing provides a novel, high-resolution approach to modelling fluvial morphology. Nevertheless, a complicating factor of such data acquisition in fluvial settings is linked to water bodies, whose presence introduces errors and distortions because of light reflection and refraction at the air–water interface. Although proof-of-concept research has shown it is possible to reduce the effects of refraction in certain settings (e.g., clear waters, unbroken surfaces), corresponding validation methods remain limited to point-based assessments of error, these being typically limited to accessible parts of the channel. Here, we provide the first high-resolution, spatially continuous validation of a stream reach bathymetry surveyed with SfM and corrected with an advanced refraction method. This method required only the camera co-ordinates and is available as open source, coded in C++. We used RPAS imagery from a regulated reach of the Palancia River, Spain, where a diversion structure fully dewatered the reach and let us obtain the entire streambed topography, which we used as spatially continuous control topography to compare the bathymetry surveyed from imagery during normal flow conditions. We compared this method with the small angle refraction correction (SARC), which has less data requirements, and analysed the error distribution across habitat types (i.e. pools and riffles). These results showed that our approach had smaller errors than SARC in both habitat types, especially in the riffle. By analysing the relationship between error and channel roughness obtained from our dry-bed model, we found that the greatest errors arise in the peripheral zones of the water surface and in its areas where streambed roughness generates more turbulence. Quantitative validation confirmed the reliability of our method as a relatively low-cost tool for the modelling and management of geomorphology and habitat within small – to medium-sized streams.

Simultaneous measurement of cloud microphysical parameters based on digital holographic interferometry

Investigation of cloud microphysical is of great significance in deepening the understanding of the radiation energy budget, water cycle process, and precipitation mechanism, and improving the scientificity and effectiveness of artificial precipitation. Especially under the action of turbulence, in addition to shear and inertia, the turbulence in the cloud will accelerate the collision of cloud droplets through vortex superposition. The above process will further complicate the cloud microphysical characters. At present, the methods of measuring cloud microphysical parameters based on light scattering, collision and imaging theories encounter bottlenecks: the inversion process needs to make the assumptions about cloud droplet spectrum and particle characteristics, the impact process will destroy particle characteristics, and the three-dimensional characteristics of cloud particles cannot be obtained. Because of its many advantages, such as fast, real-time, non-destructive, non-invasive, high-resolution, full-field optical measurement, etc., in-line digital holographic interferometry is considered as a new potential tool for the dynamical measurement of cloud microphysical property. In particular, the mutual interference between the particle image and twin image is small under far-field recording conditions. In this paper, the measurement method of the on-line digital holographic interferometry based on interference theory, combining optical information processing, depth of field compression, and gray gradient variance technology of fusion holograms, is investigated. This method, with a &lt;i&gt;z&lt;/i&gt;-axis position accuracy of 0.01 mm and system resolution of 2 μm, is employed for simultaneously and finely detecting the cloud droplet spectrum, cloud particle diameter, and number concentration. In the experiment, the liquid droplet with a median diameter of 3.9 μm, produced by the ultrasonic atomizer, is used as an example of the cloud particle. The measurement results are consistent with realistic scenario. By using a high speed charge coupled device or complementary metal oxide semiconductor camera, this method can solve the technical bottleneck of three-dimensional fine characteristics of cloud particle in airborne measurement by using cloud droplet spectrometer. It can provide effective support for the research of liquid water in the cloud, entrainment, condensation, collision, and temporal and spatial evolution laws. In addition, it has reference significance for the study of particle dynamics. Simultaneously, this method provides a feasible solution for the measurement of cloud in land-based and airborne platforms.

Coastal Sand Dunes Monitoring by Low Vegetation Cover Classification and Digital Elevation Model Improvement Using Synchronized Hyperspectral and Full-Waveform LiDAR Remote Sensing

Due to the coastal morphodynamic being impacted by climate change there is a need for systematic and large-scale monitoring. The monitoring of sandy dunes in Pays-de-la-Loire (France) requires a simultaneous mapping of (i) its morphology, allowing to assess the sedimentary stocks and (ii) its low vegetation cover, which constitutes a significant proxy of the dune dynamics. The synchronization of hyperspectral imaging (HSI) with full-waveform (FWF) LiDAR is possible with an airborne platform. For a more intimate combination, we aligned the 1064 nm laser beam of a bi-spectral Titan FWF LiDAR with 401 bands and the 15 cm range resolution on the Hyspex VNIR camera with 160 bands and a 4.2 nm spectral resolution, making both types of data follow the same emergence angle. A ray tracing procedure permits to associate the data while keeping the acquisition angles. Stacking multiple shifted FWFs, which are linked to the same pixel, enables reaching a 5 cm range resolution grid. The objectives are (i) to improve the accuracy of the digital terrain models (DTM) obtained from an FWF analysis by calibrating it on dGPS field measurements and correcting it from local deviations induced by vegetation and (ii) in combination with airborne reflectances obtained with PARGE and ATCOR-4 corrections, to implement a supervised hierarchic classification of the main foredune vegetation proxies independently of the acquisition year and the physiological state. The normalization of the FWF LiDAR range to a dry sand reference waveform and the centering on their top canopy echoes allows to isolate Ammophilia arenaria from other vegetation types using two FWF indices, without confusion with slope effects. Fourteen HSI reflectance indices and 19 HSI Spectral Angle Mapping (SAM) indices based on 2017 spectral field measurements performed with the same Hyspex VNIR camera were stacked with both FWF indices into a single co-image for each acquisition year. A simple straightforward hierarchical classification of all 35 pre-classified co-image bands was successfully applied along 20 km, out of the 250 km of coastline acquired from 2017 to 2019, prefiguring its systematic application to the whole 250 km every year.

Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland

Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands.