Browse Topic: Remote sensing
This paper solves the problem of resource and energy constraints on orbit computing for LEO satellites. By combining MADDPG reinforcement learning and Lyapunov optimization, the paper proposes a computing framework and implements an adaptive task offloading model for space flight using a multi-agent deep actor critic algorithm, MADDPG. The joint optimization mechanism is implemented by multi-agent dynamic task offloading. Through the transformation from the state with long-term constraints into optimization of the status of queue stability, the load scheduling under threshold energy in accordance with the characteristics of energy constraints was realized by introducing Lyapunov virtual queues into the process of policy evaluation of deep reinforcement learning. The experimental results show that the proposed framework enables a lightweight preliminary calculation, balanced energy consumption to reduce resource allocation, and realizes the stable queues through adaptability of tasks under energy balance conditions, which can provide high-efficiency computing assistance and support for space orbit tasks such as monitoring remote sensing of Earth.
Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field and top layers of residue, correlating this data with elevation maps to compute harvested material volume. This innovation supports operations such as baling, residue decomposition time and thereby contributing to land preparation. This technique offers benefits like reduced operational costs, labor independence, and enhanced soil nutrient planning.
The success of off-road missions for ground vehicles depends heavily on terrain traversability, which in turn requires a thorough understanding of soil characteristics a key component being soil moisture content. When large areas need to be analyzed, satellite imagery is often used, although this approach typically reduces the spatial resolution. This decrease of spatial resolution creates what are known as mixed pixels, when two or more classes or features are in a single pixel’s area, which can lead to noisier data and lower accuracy models. This paper investigates using linear spectral unmixing as a way to help clean / mitigate noisy data to yield better predictive models. Hyperspectral remote sensing from the Hyperion satellite platform and ground truth from the International Soil Moisture Network (ISMN) are used for the dataset. This study found that soil moisture content prediction, comparing the mixed multilayer perceptron (MLP) model with an unmixing approach revealed a 10–30% change in RMSE and MAE across NDVI ranges incremented by 0.1. Hence, this study demonstrates the potential use of spectral unmixing as a methodology to help enhance predictive models for terrain properties when using (lower spatial resolution / more noisy) remotely sensed datasets.
Remote sensing offers a powerful tool for environmental protection and sustainable management. While many remote sensing companies use wind or solar energy to power their platforms, California-based startup Dolphin Labs is harnessing wave energy to enable sensing networks for enhanced maritime domain awareness, improving the safety and security of offshore natural resources and critical infrastructure.
Turbulence, temperature changes, water vapor, carbon dioxide, ozone, methane, and other gases absorb, reflect, and scatter sunlight as it passes through the atmosphere, bounces off the Earth’s surface, and is collected by a sensor on a remote sensing satellite. As a result, the spectral data received at the sensor is distorted. Scientists know this and have devised several ways to account for the atmosphere’s corrupting influence on remote sensing data.
Researchers have used inkjet printing to create a compact multispectral version of a light field camera. The camera, which fits in the palm of the hand, could be useful for many applications including autonomous driving, classification of recycled materials and remote sensing.
Remember what it’s like to twirl a sparkler on a summer night? Hold it still and the fire crackles and sparks but twirl it around and the light blurs into a line tracing each whirl and jag you make.
Radio is a well-established technology. For over 100 years, it has been widely used: in communication, radar, navigation, remote control, remote sensing, and other respects. It is popular because it works; it is reliable. And yet laser has shown itself to be a superior medium of communication. Indeed, the laser-vs-radio debate is already getting old. What is new - and what will truly change the debate - are the transformations currently taking place in laser telecommunications - transformations which will drive innovation in defense. It is perhaps worth pausing to remind ourselves of what laser's existing advantages over radio are. Laser communications offer faster data transfer, and greater data capacity. And by virtue of their structure and size, lasers are almost impossible to detect, intercept, or jam. Interference is also rare. Lasers do not ‘leak’ in the same way radio does, and, as against the broad transmission style of radio, they transfer information along a very narrow beam, which cannot overlap with any other.
Radio is a well-established technology. For over 100 years, it has been widely used: in communication, radar, navigation, remote control, remote sensing, and other respects. It is popular because it works; it is reliable. And yet laser has shown itself to be a superior medium of communication. Indeed, the laser-vs-radio debate is already getting old. What is new – and what will truly change the debate – are the transformations currently taking place in laser telecommunications – transformations which will drive innovation in defense.
The prevailing mission-based paradigm for ocean color remote sensing typically involves high-cost satellite platforms launched and operated by government agencies such as NASA, NOAA, ESA, and JAXA. These platforms host state-of-the-art ocean-viewing radiometers with design and sensitivity specifications appropriate for delineating a comparatively weak water-leaving radiance from the total radiant signal detected at the top of the atmosphere. The current suite of such operational ocean color sensors includes NASA’s Moderate Resolution Imaging Spectroradi-ometer (MODIS; Aqua satellite), NOAA’s VIIRS (SNPP and NOAA-20 satellites), the Ocean and Land Color Instrument (OLCI; Sentinel-3 A/B satellites), and the Second-Generation Global Imager (SGLI) onboard the GCOM-C satellite. All of these sensors provide multi-spectral band sets (visible, near-infrared (NIR), and shortwave infrared (SWIR)) with daily coverage at approximately kilometer-scale spatial resolution. However, even kilometer-scale spatial resolution may be unable to resolve finer-scale features near rivers and estuaries that are critical for scientific and environmental resource management applications.
The ability to control light using a semiconductor device could allow low-power, relatively inexpensive sources like LEDs or flashlight bulbs to replace more powerful laser beams in new technologies such as holograms, remote sensing, self-driving cars, and high-speed communication.
Light from an object contains continuous various colors, the spectrum of light, that result from the interaction between light and the object. Spectral measurement is thus the basis of remote sensing, allowing for highly accurate material analysis and image recognition. Although the world is full of colors, human being and standard color cameras receive light through their eyes/sensors and perceive it as only three primary colors of red (R), green (G), and blue (B). Hyperspectral (HS) imaging is a technology that splits and detects light into more colors than humans and color cameras can. The richer spectral information of HS image is promising for machine vision to provide more information than human eyes or color cameras in visual inspection of foods, industrial products, and so on.
A research team co-led by Qiang Lin, a professor of electrical and computer engineering at the University of Rochester, has set new milestones in addressing this challenge, with the first multi-color integrated Pockels laser that:
Stratospheric balloons are routinely used for Earth imaging and environmental monitoring in the upper atmosphere. The balloons are often enormous in size — several hundred feet —and when inflated could engulf an entire football stadium. Urban Sky, a Denver-based stratospheric technology and remote sensing startup, has miniaturized the technology for collecting images and data of the Earth by developing small stratospheric balloons.
The concept of remote sensing, which is defined as sensing information of an object or objects from far away, has been a major endeavor from the very beginning of space exploration. With this exploration from outer space came a myriad of opportunities that not only answered questions about other worlds, but also allowed us to explore our own world. This includes a better understanding of the earth’s surface: land, water, and atmosphere.
Innovators at the NASA Langley Research Center have designed a Pulsed 2-Micron Laser Transmitter for Coherent 3-D Doppler Wind LiDAR Systems. The design produces a compact, efficient, long-lifetime laser transmitter as needed for use in space, while also having potential applications as an airborne or ground-based wind measurement tool.
Coastal and riverine shorelines are dynamic landscapes that change continually in response to environmental forces. The combination of static infrastructure with dynamic and diverse landscapes creates management challenges for navigation, storm damage reduction, and ecosystem health that are exacerbated during natural disasters. The U.S. Army Corps of Engineers (USACE) flood risk management (FRM) mission strives to reduce the nation's flood risk and increase resilience to disasters. FRM is inherently interdisciplinary, requiring accurate identification of environmental, physical, and infrastructure features that can reduce risk from flood and coastal storm disasters.
Weak optical signals are common in many science and technology applications. However, they are difficult to detect or process due to the incoherent noise that is inherently present in any system. PhD student Benjamin Crockett and colleagues, working under the supervision of Professor José Azaña of the Institut national de la recherche scientifique (INRS), have conceived a technique for the recovery of weak, noise-dominated optical signals. Their research was published in the journal Optica.
Soldier modernization programs take on new urgency as funding priorities shift and operational demands increase. There are many challenges posed by resource constraints and changing operational environments. Defense connectivity solutions offer new capabilities and innovative, economical approaches to help soldiers and commanders at every level make better decisions faster – when observing, orienting, deciding and acting (OODA) in unforgiving operational environments.
Soldier modernization programs take on new urgency as funding priorities shift and operational demands increase. There are many challenges posed by resource constraints and changing operational environments. Defense connectivity solutions offer new capabilities and innovative, economical approaches to help soldiers and commanders at every level make better decisions faster - when observing, orienting, deciding and acting (OODA) in unforgiving operational environments. There is no doubt that military forces worldwide are adapting their equipment and operating models to new levels of operational intensity. As the US Army Vision describes, forces are refocusing on “high-intensity conflict […] in dense urban terrain, in electronically degraded environments and under constant surveillance.”1
A new device known as MC-TENG — short for multilayered cylindrical triboelectric nanogenerator — generates electrical power by harvesting energy from the sporadic movement of the tree branches from which it hangs. The self-powered sensing system could continuously monitor the fire and environmental conditions without requiring maintenance after deployment.
A new technology that can allow for better light control without requiring large, difficult-to-integrate materials and structures has been developed. The photonic integrated chip could allow for many advances in the optical field and industry, ranging from improvements in virtual-reality glasses to optical remote sensing.
NASA Ames developed a novel remote sensing instrument with advanced scientific capabilities for Multispectral Imaging, Detection and Active Reflectance (MiDAR). The MiDAR transmitter and receiver demonstrate a cost-effective solution for simultaneous high-frame-rate, high signal-to-noise ratio (SNR) multispectral imaging, with hyperspectral potential, high-bandwidth simplex communication, and in-phase radiometric calibration. The use of computational imaging further allows for multispectral data to be fused using Structure from Motion (SfM) and fluid lensing algorithms to produce 3D multi-spectral scenes and high-resolution underwater imagery of benthic systems as part of future scientific airborne field campaigns.
A new technology that can allow for better light control without requiring large, difficult-to-integrate materials and structures has been developed. The photonic integrated chip could allow for many advances in the optical field and industry, ranging from improvements in virtual-reality glasses to optical remote sensing.
An analysis of shoreline change, dune volume, beach volume, beach slope, and cumulative elevation change along the northern Outer Banks of North Carolina near the CHL Field Research Facility over a 6-year study period. Army Engineer Research and Development Center, Vicksburg, Mississippi The dynamic nature of the nation's coastlines necessitates frequent shoreline monitoring and mapping. The U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), has collected datasets on the nearshore zone's changing conditions for over 40 years. During the course of these efforts, CHL has continued to develop different technologies to refine shoreline monitoring techniques, with a particular focus on the application of remote sensing technology to coastal monitoring. Light detection and ranging (lidar) scanners have proven useful for the CHL coastal measurement efforts, providing highly detailed data of coastal change and hydrodynamic processes. Lidar is frequently collected from stationary ground-based platforms, which provide fine detail (100s to 1000s of points per meter) in one location or mobile airborne sampling approaches that provide coverage over large areas but at lower resolution (1 to 10s of points per meter). The U.S. Army Corps of Engineers (USACE), U.S. Naval Oceanographic Office, and National Oceanic and Atmospheric Administration (NOAA) formed the Joint Airborne Lidar Bathymetry Technical Center of eXpertise in 1998 to support coastal mapping requirements and committed to surveying the U.S. coastline every 5 years with airborne lidar. As a result of these and other efforts, coastal monitoring with airborne lidar data has provided a range of insights into coastal change since the late 1990s.
The dynamic nature of the nation’s coastlines necessitates frequent shoreline monitoring and mapping. The U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), has collected datasets on the nearshore zone’s changing conditions for over 40 years. During the course of these efforts, CHL has continued to develop different technologies to refine shoreline monitoring techniques, with a particular focus on the application of remote sensing technology to coastal monitoring. Light detection and ranging (lidar) scanners have proven useful for the CHL coastal measurement efforts, providing highly detailed data of coastal change and hydro-dynamic processes.
Currently, the dominant method to generate ultrafast laser pulses passively is to use semiconductor saturable absorber mirrors (SESAMs). This type of passive mode locker produces exceptional results but is difficult to fabricate, expensive, and limited in bandwidth. In contrast, a graphene-based saturable absorber is easier to produce and has the advantages of much wider bandwidth, lower saturation intensity, tunable modulation depth, ultrafast recovery time, and much higher optical damage threshold, thus producing higher energies.
There is a need for rad-hard crystal stabilized clock sources with at least 300 krad of total ionizing dose (TID) immunity. A common solution has been to spot-shield a commercial off-the-shelf part or enclose it in a vault. Rad-hard clock sources are needed for main electronics boards (MEBs) and readout electronics that need to operate in hazardous space environments. Remote sensing and telemetry require that the readout circuits be co-located with the sensors, which can be separated by an arbitrary distance from the data processing electronics.
Using advanced machine learning, drones could be used to detect dangerous “butterfly” landmines in remote regions of post-conflict countries. Researchers had previously developed a method that allowed for highly accurate detection of butterfly landmines using low-cost commercial drones equipped with infrared cameras. New research focuses on automated detection of landmines using convolutional neural networks, the standard machine learning method for object detection and classification in the field of remote sensing.
For remote sensing spectrometers, wavelength-scanned laser emissions are used to capture the absorption spectrum of targets to perform measurement of soil and/or gas. Previous techniques to accomplish these measurements have involved combining multiple fixed-wavelength lasers to detect a single species, limiting the scope and effectiveness of the instruments.
Acoustic waves propagating in the atmosphere may undergo many effects including refraction by temperature and wind velocity gradients, scattering by atmospheric turbulence, absorption by the atmosphere (fluid), diffraction by terrain features, and absorption and reflection by a porous ground. As a result, there may be insonification in acoustic shadow zones, amplitude and phase fluctuations of the propagating sound signals, loss of signal coherence, changes in the interference maxima and minima of the direct ground reflected waves, and multipath effects. Understanding these effects is important for a variety of military applications, such as acoustic source localization and classification, noise propagation in the atmosphere, and the development of new remote sensing techniques of the atmosphere.
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