Search

Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential of multi-source satellite imagery has gained increasing attention. The combination of optical and radar data is particularly promising in the context of crop type classification as it allows explaining the advantages of both sensor types with respect to e.g. vegetation structure and biochemical properties. This review article gives a comprehensive overview of studies on crop type classification using optical and radar data fusion approaches. A structured review of fusion approaches, classification strategies and potential for mapping specific crop types is provided. Finally, the partially untapped potential of radar-optical fusion approaches, research gaps and challenges for upcoming future studies are highlighted and discussed. [ABSTRACT FROM AUTHOR]

The use of the rotor equivalent wind speed for determination of power curves and annual energy production for wind turbines is advocated in the second edition of the IEC 61400‐12‐1 standard. This requires the measurements of wind speeds at different heights, for which remote sensing equipment is recommended in addition to meteorological masts. In this paper, we present a theoretical analysis that shows that the relevance of the rotor equivalent wind speed method depends on turbine dimensions and wind shear regime. For situations where the ratio of rotor diameter and hub height is smaller than 1.8, the rotor equivalent wind speed method is not needed if the wind shear coefficient at the location of the wind turbine has a constant value between −0.05 and 0.4: in these cases, the rotor equivalent wind speed and the wind speed at hub height are within 1%. For complex terrains with high wind shear deviations are larger. The effect of non‐constant wind shear exponent, ie, different wind shear coefficients for lower and upper half of the rotor swept area especially at offshore conditions is limited to also about 1%. [ABSTRACT FROM AUTHOR]

Recent advances in low-cost microprocessors and sensors have allowed for the development of low-cost spectrometers for public experimentation and education outreach. In the context of the present paper and other recent research, low-cost spectrometers are important remote sensing instruments for numerous applications in citizen science and education. We built five spectrometer designs then tested them for absorption using concentrations of fluids and reflectance using colour swatches and minerals found on Mars as well as other materials possessing a high near infra-red (NIR) reflectance. These results were then compared with a laboratory grade spectrometer. We found that while all spectrometers produced meaningful results during the fluid concentration tests, there were considerable differences in accuracies between home-made instruments during the reflectance testing. Two spectrometer designs were identified that produced useful results for a range of low-cost scientific applications. [ABSTRACT FROM AUTHOR]

Abstract: The experience of constructing a geoinformational system (GIS) of the Svetlyi Yar irrigation system (Volgograd oblast) for monitoring the status of irrigated lands is considered. The GIS was based on comprehensive information that included remote sensing materials. Analyzing and processing these materials showed that the economic pattern in the area had changed in recent years, the area of irrigated land had decreased significantly, and the irrigation volume had decreased, bringing about a drop in the groundwater level. The structure of crops had also changed, and irrigated soils had entered the desalinization and calcareous invasion stage after the salinization stage of the 1990s. [ABSTRACT FROM AUTHOR]

Detecting fires at an early stage is crucial for mitigating and extinguishing fires. The increased use of biofuels in Northern Europe has led to an increased number of fires in storage facilities. These fires are often caused by self-heating in the interior of the stored materials and slowly develop to smouldering fires. Consequently, these smouldering fires are usually detected several days or weeks after the initial smouldering fire had started. At this point, measures to extinguish the smouldering fire inside the material are difficult as the fire has grown for a long time and is located inside the material. This makes it difficult to gain a successful effect of any extinguishing agents. This paper presents a pilot study in lab scale suggesting levoglucosan as an early tracer for smouldering fires using 600 g cotton as the biomass source. The advantage of detecting levoglucosan as a fire signature is that it serves as a tracer compound for biomass burning and is produced at temperatures of 200-400°C reducing the risk of false alarms from emissions produced at lower temperatures. In this paper, levoglucosan was detected in aerosols emitted in an early stage from smouldering fires and was analyzed by ultrasonic assisted extraction followed by gas chromatographic separation and mass spectrometric detection. First detection of levoglucosan was made in the first sample, collected after 30 min when the smouldering fire was only a few cubic centimeters of the cotton package. In addition, levoglucosan was found in the solid residues of carbonized cotton after the initial smouldering process had moved through the material. The findings should be regarded as screening results to be used for the development of sensors and technology for smouldering fire detection. [ABSTRACT FROM AUTHOR]

Smoke alarms have been shown to develop sonically-deposited regions of acoustically agglomerated soot particles when they sound in smoke-filled air. These sonic depositions can be examined forensically post-fire to determine if the smoke alarm sounded during the incident. However, it is not clear how these sonic depositions are affected by common firefighting and post-fire actions. To determine the effects of post-fire forensic smoke alarm testing and environmental conditions on the persistence of the existing sonic deposition of soot on the horns of a smoke alarm, sixty (60) smoke alarms were subjected to smoke from fires of several different fuel types and common post-fire conditions or actions. Initially, each alarm was exposed to smoke in a small-scale experimental fire to develop sonic deposition around the horn. The fuel types for the fires were smoldering wood, flaming toluene-heptane, smoldering polyurethane foam, flaming polyurethane foam, and a combination of smoldering and flaming polyurethane foam. The alarms were then subjected to four common post-fire actions: pressing the test button, exposure to synthetic canned smoke, exposure to standing water, and exposure to running water. Each detector was visually inspected before and after the post-fire action. Results varied from no soot removed to almost all soot removed depending on the fuel type and post-fire test. An objective evaluation system was used to rank the degree to which soot was removed from the alarm horns: 0 (no soot removed), 1 (some soot removed), and 2 (all soot removed) based on visual inspection. The smoldering wood and smoldering polyurethane foam fires left behind a sticky resin that was essentially unaffected by any of the post-tests. The flaming foam and flaming toluene-heptane fires left powdery soot on the horn which could be easily wiped off. This soot was almost completely washed off by running water (1.067 average degree of removal) while the canned smoke and standing water post-tests removed a significant portion of the soot (0.533 and 1.000 average degrees of removal, respectively), which could lead an investigator to an errant sounding determination. Pressing the test-button appeared to make minimal impact on the amount of soot around the alarms horns regardless of the fuel type (0.067 average degree of removal). [ABSTRACT FROM AUTHOR]

The remote health monitoring system (RHMS) has become more real-time because the internet plus technology develops quickly. To support real-time health monitoring server, three main aspects, such as collecting, transferring and analyzing the health data, should be integrated into a system. So far, many challenges have been solved and many RHMSs have been applied in our daily lives. It is significant to use RHMS to take good care of clients who live alone, especially monitors the health data of clients in nursing home. This paper introduces a health gateway which automatically collects information of the clients. The information includes the users’ identity, vital signs, body temperature, clients’ real-time location and falling action detection. Moreover, the health gateway transmits information in WIFI relaying mode until the information is received by the background server. If the information is abnormal, the health gateway would send an alarm to the server. The server should call a doctor or caretaker and send accurate navigation based on real-time location in 3D architectural modeling to their mobile devices for finding clients quickly. [ABSTRACT FROM AUTHOR]

Submerged remote sensor systems (UWSNs) have been appeared as an encouraging innovation to screen and investigate the seas in lieu of customary undersea wireline instruments. In any case, the information get-together of UWSNs is still seriously restricted on the grounds that of the acoustic channel correspondence qualities. One approach to enhance the information gathering in UWSNs is through the plan of steering conventions thinking about the special attributes of the submerged acoustic correspondence and the profoundly unique system topology. In this paper, we propose the GEDAR directing convention for UWSNs. GEDAR is an anycast, geographic and entrepreneurial directing convention that courses information bundles from sensor hubs to different sinks at the ocean's surface. At the point when the hub is in a correspondence void locale, GEDAR changes to the recuperation mode strategy which depends on topology control through the profundity alteration of the void hubs, rather than the conventional methodologies utilizing control messages to find and keep up steering ways along void districts. Recreation comes about demonstrate that GEDAR fundamentally enhances the system execution when contrasted and the gauge arrangements, even in hard and troublesome versatile situations of extremely meagre and exceptionally thick systems and for high system movement loads. [ABSTRACT FROM AUTHOR]

Fast tracking algorithm discussed in this paper is applied to star trackers for improving the performance of star identification. Space Robotics Laboratory (SRL) in Tohoku University has developed star trackers for micro-satellites so far. Since it has only a lost-in-space algorithm for star identification, the attitude update rate is limited up to 1 Hz. It was implemented to the Philippines' 50 kg-class micro-satellite "DIWATA-1" released from the International Space Station on April 2016. Although on-orbit evaluation showed good results enough to output attitude autonomously, the performance of continuous attitude determination was worse than expected. Since quite a high access frequency of star catalog is required, timeout of the process for attitude calculation occurs frequently even if update rate is 1 Hz. Insufficient ground evaluation before launch is also one of the causes of operation failure. Tracking algorithm helps to calculate latest attitude faster than conventional methods by feeding back the previous attitude information. This algorithm includes two additional processes. First, future star positions on the image frame can be predicted according to the previous attitude and pre-identified star information. The sensor can find corresponding latest centroids compared to predicted star positions. Second, un-identified stars on the camera field of view (FOV) can be detected by referring to the star neighborhood catalog, which includes the list of some adjacent star IDs against each reference star. PC simulation shows that continuous attitude determination works effectively by keeping low catalog access frequency. The proposed algorithm is implemented to the real hardware. Then, ground evaluation is conducted using star simulator environment and satellite dynamics simulator. The result demonstrates that the processing speed in real situation becomes about 70 times faster compared to the previous method and it is successful to obtain much more stable 1 Hz attitude output. [ABSTRACT FROM AUTHOR]

A photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) probe with gold nanowires as the plasmonic material is proposed in this work. The coupling characteristics and sensing properties of the probe are numerically investigated by the finite element method. The probe is designed to detect low refractive indices between 1.27 and 1.36. The maximum spectral sensitivity and amplitude sensitivity are 6 × 103 nm/RIU and 600 RIU−1, respectively, corresponding to a resolution of 2.8 × 10−5 RIU for the overall refractive index range. Our analysis shows that the PCF-SPR probe can be used for lower refractive index detection. [ABSTRACT FROM AUTHOR]

Typical mobile agent networks, such as multi-unmanned aerial vehicle (UAV) systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e., the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as the amount of communication data, at the expense of increasing computational cost. In this paper, we aim at attaining an optimal tradeoff between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multihop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme. [ABSTRACT FROM AUTHOR]

In present time due to increase in number of crimes, Parents always worry about their children while sending them out for schools, which no one can't avoid. In a world where dangerous crime in school is a legitimate concern, arming teachers is becoming a realistic strategy for some. At the same time, what else can be done to ensure schools are more secure, visitors can be trusted, and students and teachers can efficiently stop or quickly combat an emergency situation? This paper proposes a solution for their worry using the latest enhancement in technology. Radio Frequency Identification (RFID) is one of key technologies to implement IoT applications to keep an eye on child problems. [ABSTRACT FROM AUTHOR]

We report on the recent reactivation of a large rift in the Brunt Ice Shelf, East Antarctica, in December 2012 and the formation of a 50 km long new rift in October 2016. Observations from a suite of ground-based and remote sensing instruments between January 2000 and July 2017 were used to track progress of both rifts in unprecedented detail. Results reveal a steady accelerating trend in their width, in combination with alternating episodes of fast (> 600mday-1) and slow propagation of the rift tip, controlled by the heterogeneous structure of the ice shelf. A numerical ice flow model and a simple propagation algorithm based on the stress distribution in the ice shelf were successfully used to hindcast the observed trajectories and to simulate future rift progression under different assumptions. Results show a high likelihood of ice loss at the McDonald Ice Rumples, the only pinning point of the ice shelf. The nascent iceberg calving and associated reduction in pinning of the Brunt Ice Shelf may provide a uniquely monitored natural experiment of ice shelf variability and provoke a deeper understanding of similar processes elsewhere in Antarctica. [ABSTRACT FROM AUTHOR]

over the last decade, Amman's local authorities have faced challenges in meeting the needs of local populations due to unexpected rapid urbanization growth and the impact this has had on welfare and outdated urban infrastructure. Therefore, it is essential to model spatial dynamic growth to identify the land-use class of urbanized regions expansions to prepare for future urban demands. The present study addresses this need by exploring the application of the remotely- sensed data and cellular automation (CA) based SLEUTH model and its effectiveness in modelling of urban growth in highly Vibrant Metropolitan of Amman. the SLETUH model for Amman was successfully calibrated using the Optimum SLEUTH Metric (OSM) method based on archived remote sensing data from 1985 to 2015. The urban growth characteristics were determined using the urban rules derived from SLEUTH via calibration. SLEUTH's probabilistic image of future urbanized lands of historical trend-based urban growth scenario was employed as dynamic factors for urbanization suitability mapping and landscape pattern analysis of the year 2040. The SLEUTH model predicts that Amman's urban space will expand by 57km2 by 2040 (compared to 2015), resulting in a total area of 473.845 km2. Importantly, this research demonstrates that the issues experienced in Amman's urban locations today will continue into the next two decades unless steps are taken to improve urban growth strategies and increase both environmental and urban action. Findings of the present study cooperate the government's plan to demonstrate Jordan's commitment to modernisation through the creation a new administrative city for national-level civil servants and government ministries. [ABSTRACT FROM AUTHOR]

NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) satellite observes the entire sunlit Earth every 65 to 110 min from the Sun-Earth Lagrangian L1 point. This paper presents initial EPIC shortwave spectral observations of the sunlit Earth reflectance and analyses of its diurnal and seasonal variations. The results show that the reflectance depends mostly on (1) the ratio between land and ocean areas exposed to the Sun and (2) cloud spatial and temporal distributions over the sunlit side of Earth. In particular, the paper shows that (a) diurnal variations of the Earth's reflectance are determined mostly by periodic changes in the land-ocean fraction of its the sunlit side; (b) the daily reflectance displays clear seasonal variations that are significant even without including the contributions from snow and ice in the polar regions (which can enhance daily mean reflectances by up to 2 to 6% in winter and up to 1 to 4% in summer); (c) the seasonal variations of the sunlit Earth reflectance are mostly determined by the latitudinal distribution of oceanic clouds. [ABSTRACT FROM AUTHOR]

The accurate mapping of impervious surfaces is of key significance for various urban applications. Usually, traditional methods extract the proportion image of impervious surfaces from remote sensing images; however, the proportion image cannot specify where the impervious surfaces spatially distribute within a pixel. Meanwhile, impervious surfaces often locate urban areas and have a strong correlation with the relatively new big (geo)data points of interest (POIs). This study, therefore, proposed a novel impervious surfaces mapping method (super-resolution mapping of impervious surfaces, SRMIS) by combining a super-resolution mapping technique and POIs to increase the spatial resolution of impervious surfaces in proportion images and determine the accurate spatial location of impervious surfaces within each pixel. SRMIS was evaluated using a 10-m Sentinel-2 image and a 30-m Landsat 8 Operational Land Imager (OLI) image of Nanjing city, China. The experimental results show that SRMIS generated satisfactory impervious surface maps with better-classified image quality and greater accuracy than a traditional hard classifier, the two existing super-resolution mapping (SRM) methods of the subpixel-swapping algorithm, or the method using both pixel-level and subpixel-level spatial dependence. The experimental results show that the overall accuracy increase of SRMIS was from 2.34% to 5.59% compared with the hard classification method and the two SRM methods in the first experiment, while the overall accuracy of SRMIS was 1.34-3.09% greater than that of the compared methods in the second experiment. Hence, this study provides a useful solution to combining SRM techniques and the relatively new big (geo)data (i.e., POIs) to extract impervious surface maps with a higher spatial resolution than that of the input remote sensing images, and thereby supports urban research. [ABSTRACT FROM AUTHOR]

The correlation coefficient (CC) was substantiated as a simple, yet robust statistical tool in the quality assessment of hyperspectral imaging (HSI) data. The sensitivity of the metric was also characterized with respect to artificially-induced errors. The CC was found to be sensitive to spectral shifts and single feature modifications in hyperspectral ground data despite the high, artificially-induced, signal-to-noise ratio (SNR) of 100:1. The study evaluated eight airborne hyperspectral images that varied in acquisition spectrometer, acquisition date and processing methodology. For each image, we identified a uniform ground target region of interest (ROI) that was comprised of a single asphalt road pixel from each column within the sensor field-of-view (FOV). A CC was calculated between the spectra from each of the pixels in the ROI and the data from the center pixel. Potential errors were located by reductions in the CCs below a designated threshold, which was derived from the results of the sensitivity tests. The spectral range associated with each error was established using a windowing technique where the CCs were recalculated after removing the spectral data within various windows. Errors were isolated in the spectral window that removed the previously-identified reductions in the CCs. Finer errors were detected by calculating the CCs across the ROI in the spectral range surrounding various atmospheric absorption features. Despite only observing deviations in the CCs from the 3rd-6th decimal places, non-trivial errors were detected in the imagery. An error was detected within a single band of the shortwave infrared imagery. Errors were also observed throughout the visible-near-infrared imagery, especially in the blue end. With this methodology, it was possible to immediately gauge the spectral consistency of the HSI data across the FOV. Consequently, the effectiveness of various processing methodologies and the spectral consistency of the imaging spectrometers themselves could be studied. Overall, the research highlights the utility of the CC as a simple, low monetary cost, analytical tool for the localization of errors in spectroscopic imaging data. [ABSTRACT FROM AUTHOR]

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. [ABSTRACT FROM AUTHOR]

In-situ measurements using Unmanned Aerial Vehicles (UAVs) and remote sensing observations can independently provide dense vertically-resolved measurements of atmospheric aerosols; information which is highly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from Light Detection And Ranging (lidar) observations and in-situ measurements using an Optical Particle Counter (OPC) onboard a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse-mode (i.e., particles having radii > 0.5 µm) where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of the aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models. [ABSTRACT FROM AUTHOR]

Field experiment in South China was undertaken to improve understanding of cloud and precipitation properties. Measurements of the vertical structures of non-precipitating and precipitating clouds were obtained using passive and active remote sensing equipment: a Ka-band cloud radar (CR) system, a C-band frequency modulated continuous wave vertical pointing radar (CVPR), a microwave radiometer and a laser ceilometer (CEIL). CR plays a key role in high-level cloud observation, whereas CVPR is important for observing low- and mid-level clouds and heavy precipitation. CEIL helps us diminish the effects of "clear-sky" in the planetary boundary layer. The experiment took place in Longmen, Guangdong Province, China from May to September of 2016. This study focuses on evaluating the ability of the two radars to deliver consistent observation data and develops an algorithm to merge the CR, CVPR and CEIL data. Cloud echo base, thickness, frequency of observed cloud types and reflectivity vertical distributions are analyzed in the radar data. Comparisons between the collocated data sets show that reflectivity biases between the CR three operating modes are less than 2 dB. The averaged difference between CR and CVPR reflectivity can be reduced with attenuation correction to 3.57 dB from the original 4.82 dB. No systemic biases were observed between velocity data collected in the three CR modes and CVPR. The corrected CR reflectivity and velocity data were then merged with the CVPR data and CEIL data to fill in the gaps during the heavy precipitation periods and reduce the effects of Bragg scattering and fog on cloud observations in the boundary layer. Meanwhile, the merging of velocity data with different Nyquist velocities and resolutions diminishes velocity folding to provide fine-grain information about cloud and precipitation dynamics. The three daily periods in which low-level clouds tended to occur were at sunrise, noon and sunset and large differences in the average reflectivity values were observed. Mid- and high-level clouds tended to occur at 1400 and 1800 BT. Few clouds were found between a height of 3 and 5 km. [ABSTRACT FROM AUTHOR]

The Colour and Stereo Surface Imaging System (CaSSIS) is the main imaging system onboard the European Space Agency's ExoMars Trace Gas Orbiter (TGO) which was launched on 14 March 2016. CaSSIS is intended to acquire moderately high resolution (4.6 m/pixel) targeted images of Mars at a rate of 10-20 images per day from a roughly circular orbit 400 km above the surface. Each image can be acquired in up to four colours and stereo capability is foreseen by the use of a novel rotation mechanism. A typical product from one image acquisition will be a $9.5~\mbox{km} \times {\sim}45~\mbox{km}$ swath in full colour and stereo in one over-flight of the target thereby reducing atmospheric influences inherent in stereo and colour products from previous high resolution imagers. This paper describes the instrument including several novel technical solutions required to achieve the scientific requirements. [ABSTRACT FROM AUTHOR]

In this study, we showed that the multi-angle satellite remote sensing product, MISR L2 Land Surface (MIL2ASLS), which has a scale of 1.1 km, could be suitable for improving land-cover studies. Using seven images from this product, captured by the multi-angle imaging spectroradiometer sensor (MISR), we explored the values reached by the three parameters (ρ0, Θ, and k) of the Rahman-Pinty-Verstraete model, which was modified by Martonchick (MRPV). Thereafter, we compared the values and behaviors shown in seven Co-ordination of Information on the Environment (CORINE) land cover categories, in the red and near infrared (NIR) bands, over the seven MISR orbits captured in 2006 for Mainland Spain. Furthermore, we used Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR) ancillary data and the illumination angles from the same pixels, which made up the images. These ancillary data were also provided by the MISR products. An inferential statistic test was performed to evaluate the relationship between each parameter-band combination, and the land cover in every MISR orbit used. The results suggested that the ρ0 parameters of this product seemed to be the most related to photosynthetic activity, and it should be comparable with the widely-used NDVI. On the other hand, the k and Θ parameter values were not related, or at least not entirely related, to the phenology of land coverage. These seemed to be more influenced by the anisotropy behavior of the studied land cover pixels. Additionally, we observed, by constructing analysis of variance, how the mean of each MRPV parameter-band differed statistically (p < 0.01) by land covers and orbits. This study suggested that the MISR MRPV model parameter data product has great potential to be used to improve land cover applications. [ABSTRACT FROM AUTHOR]

Networked observational devices have proliferated in recent years, contributing to voluminous data streams from a variety of sources and problem domains. These streams often have a spatiotemporal component and include multidimensional features of interest. Processing such data in an offline fashion using batch systems or data warehouses is costly from both a storage and computational standpoint, and in many situations the insights derived from the data streams are useful only if they are timely. In this study, we propose Synopsis, an online, distributed sketch that is constructed from voluminous spatiotemporal data streams. The sketch summarizes feature values and inter-feature relationships in memory to facilitate real-time query evaluations and to serve as input to computations expressed using analytical engines. As the data streams evolve, Synopsis performs targeted dynamic scaling to ensure high accuracy and effective resource utilization. We evaluate our system in the context of two real-world spatiotemporal datasets and demonstrate its efficacy in both scalability and query evaluations. [ABSTRACT FROM PUBLISHER]

The main goal of this study was to evaluate four major remote sensing soil moisture (SM) products over the state of Texas. These remote sensing products are: (i) the Advanced Microwave Scanning Radiometer--Earth Observing System (AMSR-E) (2002-September 2011); (ii) the Soil Moisture Ocean Salinity system (SMOS, 2010-present); (iii) AMSR2 (2012-present); and (iv) the Soil Moisture Active Passive system (SMAP, 2015-present). The quality of the generated SM data is influenced by the accuracy and precision of the sensors and the retrieval algorithms used in processing raw data. Therefore, it is important to evaluate the quality of these satellite SM products using in situ measurements and/or by inter-comparing their data during overlapping periods. In this study, these two approaches were used where we compared each satellite SM product to in situ soil moisture measurements and we also conducted an inter-comparison of the four satellite SM products at 15 different locations in Texas over six major land cover types (cropland, shrub, grassland, forest, pasture and developed) and eight climate zones along with in situ SM data from 15 Mesonet, USCRN and USDA-NRCS Scan stations. Results show that SM data from SMAP had the best correlation coefficients range from 0.37 to 0.92 with in situ measurements among the four tested satellite surface SM products. On the other hand, SM data from SMOS, AMSR2 and AMSR-E had moderate to low correlation coefficients ranges with in situ data, respectively, from 0.24-0.78, 0.07-0.62 and 0.05-0.52. During the overlapping periods, average root mean square errors (RMSEs) of the correlations between in situ and each satellite data were 0.13 (AMSR-E) and 0.13 (SMOS) cm³/cm³ (2010-2011), 0.16 (AMSR2) and 0.14 (SMOS) cm³/cm³ (2012-2016) and 0.13, 0.16, 0.14 (SMAP, AMSR2, SMOS) cm³/cm³ (2015-2016), respectively. Despite the coarser spatial resolution of all four satellite products (25-36 km), their SM measurements are considered reasonable and can be effectively used for different applications, e.g., flood forecasting, and drought prediction; however, further evaluation of each satellite product is recommended prior to its use in practical applications. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Spectral radiance measurements collected in nadir and sideward viewing directions by two airborne passive solar remote sensing instruments, the Spectral Modular Airborne Radiation measurement sysTem (SMART) and the Differential Optical Absorption Spectrometer (mini-DOAS), are used to compare the remote sensing results of cirrus optical thickness τ. The comparison is based on a sensitivity study using radiative transfer simulations (RTS) and on data obtained during three airborne field campaigns: the North Atlantic Rainfall VALidation (NARVAL) mission, the Mid-Latitude Cirrus Experiment (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems (ACRIDICON) campaign. Radiative transfer simulations are used to quantify the sensitivity of measured upward radiance I with respect to τ, ice crystal effective radius reff, viewing angle of the sensor θV, spectral surface albedo α, and ice crystal shape. From the calculations it is concluded that sideward viewing measurements are generally better suited than radiance data from the nadir direction to retrieve τ of optically thin cirrus, especially at wavelengths larger than λ = 900 nm. Using sideward instead of nadir-directed spectral radiance measurements significantly improves the sensitivity and accuracy in retrieving τ, in particular for optically thin cirrus of τ ≤ 2. The comparison of retrievals of τ based on nadir and sideward viewing radiance measurements from SMART, mini-DOAS and independent estimates of τ from an additional active remote sensing instrument, the Water Vapor Lidar Experiment in Space (WALES), shows general agreement within the range of measurement uncertainties. For the selected example a mean τ of 0.54 ± 0.2 is derived from SMART, and 0.49 ± 0.2 by mini-DOAS nadir channels, while WALES obtained a mean value of τ = 0.32 ± 0.02 at 532 nm wavelength, respectively. The mean of τ derived from the sideward viewing mini-DOAS channels is 0.26 ± 0.2. For the few simultaneous measurements, the mini-DOAS sideward channel measurements systematically underestimate (-17.6%) the nadir observations from SMART and mini-DOAS. The agreement between mini-DOAS sideward viewing channels and WALES is better, showing the advantage of using sideward viewing measurements for cloud remote sensing for τ ≤ 1. Therefore, we suggest sideward viewing measurements for retrievals of τ of thin cirrus because of the significantly enhanced capability of sideward viewing compared to nadir measurements. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Geology / Gongcheng Dizhi Xuebao is the property of Journal of Engineering Geology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Illumination of nocturnal environments is increasing steadily worldwide. While there are some benefits for mankind, light at night affects animals, plants, and human health by blurring the natural distinction between day and night. International regulations exist to protect the environment for the maintenance of human health but nocturnal darkness is not considered. In Germany, cities and communities labeled as Climatic Health Resorts provide for high standards in air quality. However, their degree of nocturnal darkness is unexplored so far. In our study, we examined the degree of nocturnal darkness in German Climatic Health Resorts by two datasets based on georeferenced remote sensing data. The majority of Climatic Health Resorts (93.1 %) are able to offer a relative respite (≥ 20 mag/arcsec) from a degraded nocturnal environment, while only 3.4 % are able to offer a dark, if by no means pristine, night environment (≥ 21 mag/arcsec). Climatic Health Resorts emit less light as well as are less affected by night sky brightness compared to the average of non-classified communities. In combination with daytime requirements, the resorts provide conditions for a more distinct day-and-night-cycle than non-classified communities. [ABSTRACT FROM AUTHOR]

The author reflects on the contributions of the "Journal of the American Water Resources Association" for improved water resources management. Topics discussed include an early spreadsheet model for modeling nonpoint source pollution presented by J. F. Walker et al in 1989, the journal's effort to bridge the gap between fundamental research and application needs, and growth in both spatial information and remote-sensing technologies from 1985-1994.

Snow contributes to regional and global water budgets, and is of critical importance to water resources management and our society. Along with advancement in remote sensing tools and techniques to retrieve snowfall, verification and refinement of these estimates need to be performed using ground-validation datasets. A comprehensive evaluation of the Multi-Radar/Multi-Sensor (MRMS) snowfall products and Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) precipitation products is conducted using the Snow Telemetry (SNOTEL) daily precipitation and Snow Water Equivalent (SWE) datasets. Severe underestimations are found in both radar and satellite products. Comparisons are conducted as functions of air temperature, snowfall intensity, and radar beam height, in hopes of resolving the discrepancies between measurements by remote sensing and gauge, and finally developing better snowfall retrieval algorithms in the future. [ABSTRACT FROM AUTHOR]

The vocalization source level distributions and pulse compression gains are estimated for four distinct baleen whale species in the Gulf of Maine: fin, sei, minke and an unidentified baleen whale species. The vocalizations were received on a large-aperture densely-sampled coherent hydrophone array system useful for monitoring marine mammals over instantaneous wide areas via the passive ocean acoustic waveguide remote sensing technique. For each baleen whale species, between 125 and over 1400 measured vocalizations with significantly high Signal-to-Noise Ratios (SNR > 10 dB) after coherent beamforming and localized with high accuracies (<10% localization errors) over ranges spanning roughly 1 km-30 km are included in the analysis. The whale vocalization received pressure levels are corrected for broadband transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for a random range-dependent ocean waveguide. The whale vocalization source level distributions are characterized by the following means and standard deviations, in units of dB re 1 μ Pa at 1 m: 181.9 ± 5.2 for fin whale 20-Hz pulses, 173.5 ± 3.2 for sei whale downsweep chirps, 177.7 ± 5.4 for minke whale pulse trains and 169.6 ± 3.5 for the unidentified baleen whale species downsweep calls. The broadband vocalization equivalent pulse-compression gains are found to be 2.5 ± 1.1 for fin whale 20-Hz pulses, 24 ± 10 for the unidentified baleen whale species downsweep calls and 69 ± 23 for sei whale downsweep chirps. These pulse compression gains are found to be roughly proportional to the inter-pulse intervals of the vocalizations, which are 11 ± 5 s for fin whale 20-Hz pulses, 29 ± 18 for the unidentified baleen whale species downsweep calls and 52 ± 33 for sei whale downsweep chirps. The source level distributions and pulse compression gains are essential for determining signal-to-noise ratios and hence detection regions for baleen whale vocalizations received passively on underwater acoustic sensing systems, as well as for assessing communication ranges in baleen whales. [ABSTRACT FROM AUTHOR]

Altitude-resolved aerosol detection in the upper troposphere and lower stratosphere (UTLS) is a challenging task for remote sensing instruments. Infrared limb emission measurements provide vertically resolved global measurements at day- and nighttime in the UTLS. For high-spectralresolution infrared limb instruments we present here a new method to detect aerosol and separate between ice and nonice particles. The method is based on an improved aerosol-cloud index that identifies infrared limb emission spectra affected by non-ice aerosol or ice clouds. For the discrimination between non-ice aerosol and ice clouds we employed brightness temperature difference correlations. The discrimination thresholds for this method were derived from radiative transfer simulations (including scattering) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)/Envisat measurements obtained in 2011. We demonstrate the value of this approach for observations of volcanic ash and sulfate aerosol originating from the Grímsvötn (Iceland, 64° N), Puyehue-Cordón Caulle (Chile, 40° S), and Nabro (Eritrea, 13° N) eruptions in May and June 2011 by comparing the MIPAS volcanic aerosol detections with Atmospheric Infrared Sounder (AIRS) volcanic ash and SO2 measurements. [ABSTRACT FROM AUTHOR]

Active remote-sensing instruments, such as ceilometers, have been shown to be potentially useful for the investigation of the behavior of the atmospheric mixing layer height (MLH). For the first time ever, high-resolution measurements of backscatter intensity, taken from two CL31 ceilometers situated inland and onshore of Israel, have enabled evaluation of the mean diurnal cycle of the MLH in the eastern Mediterranean region. Although the Israeli summer synoptic conditions are considered to be quite stable, results for the summer season (July-August 2014) showed the inland MLH to be about 200m higher than the MLH at the onshore site, situated only 7.5 km away. The prevailing influence of the sea breeze front (SBF), as it progresses inland, is presented by the ceilometer plots. Complementing results were found between the radiosonde profiles and the adjacent ceilometer at the inland site of Beit Dagan. In contrast to the expected regularity of clear skies during the Israeli summer, the ceilometers revealed significant cloud cover throughout the day, with higher presence onshore. Assessment of cloud thickness in further research would serve to improve the evaluation of the MLH evolution. [ABSTRACT FROM AUTHOR]

In this new era of remote-sensing based hydrology, a major unanswered question is how to incorporate the impact of land-surface based heterogeneity on soil moisture dynamics at remote sensing scales. The answer to this question is complicated since (1) soil moisture dynamics that vary with support, extent, and spacing scales are dependent on land-surface based heterogeneity and (2) land-surface based heterogeneity itself is scale-specific and varies with hydroclimates. Land-surface factors such as soil, vegetation, and topography affect soil moisture dynamics by redistributing the available soil moisture on the ground. In this study, we determined the contribution of these biophysical factors to redistribution of near-surface soil moisture across a range of remote sensing scales varying from an (airborne) remote sensor footprint (1.6 km) to a (satellite) footprint scale (25.6 km). Two-dimensional nondecimated wavelet transform was used to extract the support scale information from the spatial signals of the land-surface and soil moisture variables. The study was conducted in three hydroclimates: humid (Iowa), subhumid (Oklahoma), and semiarid (Arizona). The dominance of soil on soil moisture dynamics typically decreased from airborne to satellite footprint scales whereas the influence of topography and vegetation increased with increasing support scale for all three hydroclimates. The distinct effect of hydroclimate was identifiable in the soil attributes dominating the soil moisture dynamics. The near-surface soil moisture dynamics in Arizona (semiarid) can be attributed more to the clay content which is an effective limiting parameter for evaporation whereas in Oklahoma (humid), sand content (limiting parameter for drainage) was the dominant soil attribute. The findings from this study can provide a deeper understanding of the impact of heterogeneity on soil moisture dynamics and the potential improvement of hydrological models operating at footprints' scales. [ABSTRACT FROM AUTHOR]

Recent discharge observations are lacking for most rivers globally. Discharge can be estimated from remotely sensed floodplain and channel inundation area, but there is currently no method that can be automatically extended to many rivers. We examined whether automated monitoring is feasible by statistically relating inundation estimates from moderate to coarse (>0.05°) resolution remote sensing to monthly station discharge records. Inundation extents were derived from optical MODIS data and passive microwave sensors, and compared to monthly discharge records from over 8000 gauging stations and satellite altimetry observations for 442 reaches of large rivers. An automated statistical method selected grid cells to construct 'satellite gauging reaches' (SGRs). MODIS SGRs were generally more accurate than passive microwave SGRs, but there were complementary strengths. The rivers widely varied in size, regime, and morphology. As expected performance was low ( R < 0.7) for many (86%), often small or regulated, rivers, but 1263 successful SGRs remained. High monthly discharge variability enhanced performance: a standard deviation of 100-1000 m3 s−1 yielded ca. 50% chance of R > 0.6. The best results ( R > 0.9) were obtained for large unregulated lowland rivers, particularly in tropical and boreal regions. Relatively poor results were obtained in arid regions, where flow pulses are few and recede rapidly, and in temperate regions, where many rivers are modified and contained. Provided discharge variations produce clear changes in inundated area and gauge records are available for part of the satellite record, SGRs can retrieve monthly river discharge values back to around 1998 and up to present. [ABSTRACT FROM AUTHOR]

The abundance of NO2 in the boundary layer relates to air quality and pollution sources monitoring. Observing the spatio-temporal distribution of NO2 above well-delimited (flue gas stacks, volcanoes, ships) or more extended sources (cities) allows for several applications: monitoring emission fluxes or studying the plume dynamic chemistry and its transport. So far, most attempts to map the NO2 field from the ground have been made with visible-light scanning spectrometers. Benefiting from a high retrieval accuracy, they only achieve a relatively low temporal resolution that hampers the detection of dynamic features. We present a new type of passive remote sensing instrument aiming at the measurement of the 2-D distributions of NO2 slant column densities (SCD) with a high spatio-temporal resolution. The measurement principle has strong similarities with the popular filter-based SO2 camera as it relies on spectral images taken at wavelengths where the molecule absorption cross-section is different. Contrary to the SO2 camera, the spectral selection is performed by an acousto-optical tunable filter (AOTF) capable of resolving the target molecule's spectral features. The NO2 camera capabilities are demonstrated by imaging the NO2 abundance in the plume of a coal-fired power plant. During this experiment, the 2-D distribution of the NO2 SCD was retrieved with a temporal resolution of 3 minutes and a spatial sampling of 50 cm (over a 250 x 250 m² area). The detection limit was close to 5 x 1016 molecules cm-2, with a maximum detected SCD of 4 x 1017 molecules cm-2. Illustrating the added-value of the NO2 camera measurements, the data reveal the dynamics of the NO to NO2 conversion in the early plume with an unprecedent resolution: from its release in the air, and for 100 m upwards, the observed NO2 plume concentration increased at a rate of 0.75-1.25 g s-1. In joint campaigns with SO2 cameras, the NO2 camera could also help in removing the bias introduced by the NO2 interference in the SO2 measurements. [ABSTRACT FROM AUTHOR]

The process of rapid urbanization in China features two opposing trends: declining rural population and increasing rural residential land, especially in southern hilly areas. The extraction and analysis of residential land in rural China represents an important application for remote sensing technology. The study aimed to discover rural residential land information using RapidEye satellite imagery, taking Taihe County as the research area in the hilly region of southern China. Based on multiple experiments, classification was conducted with an optimal image segmentation scale set to 200. The object-oriented classification rule set was constructed using the customized parameters NDVI, NDWI, brightness, and length/width. The areas of residential land and other land use types were interpreted by varying the parameter values for classification rule sets. Finally, validation and accuracy evaluations were carried out. The overall accuracy of residential land interpretation is 78.40%, and producer's accuracy and user's accuracy are 68.75% and 77.33%, respectively. The results indicate that RapidEye provides a suitable data source for extraction of rural residential land using an object-oriented approach. Compared with the second national land survey of China, the classification gave an absolute difference of 93.67 ha residential land within the study area. Recognition errors occurred mainly in regions adjacent to the boundaries between residential land and other types of land. [ABSTRACT FROM AUTHOR]

Remote sensors such as Doppler radars are providing novel insights into the migrations of diverse animal taxa, but limits in scope and sensitivity can hamper the utility of these tools. For example, studies investigating whether songbirds compensate effectively for wind displacement during nocturnal migration have been challenged by the need to assess behavior on a large scale. In addition, these studies typically overlook the potential role low-altitude diurnal flights play in dealing with unfavorable winds. In such cases, a combination of approaches—new and traditional—may be necessary to understand behavior more completely. Here, we unite ground-based visual observations with a new radar analysis method to investigate how songbirds deal with crosswinds over the northeast United States. We find that nocturnally migrating birds experienced significant wind drift, even though they often flew at 90° or more to the wind direction. Significantly, more birds undertook reoriented diurnal flights after nocturnal wind drift, and wind influence, nocturnal migration intensity, and time of season together explained the majority of variation in counts of these "morning flights." This study shows that bird behavior during migration can be strongly shaped by the danger of wind drift and that some songbird species respond to drift with reoriented diurnal migratory flights. Knowledge of birds' interactions with wind is essential for successfully modeling migratory behavior and assessing the risks associated with changing habitats and meteorological patterns. Furthermore, an understanding of the degree to which drift defines migratory behaviors may have value across animal taxa. [ABSTRACT FROM AUTHOR]

The launch of the MinION Access Program has caused much activity within the scientific community. MinION represents a keenly anticipated, novel addition to the current melange of commercial sequencers. Driven by the nanopore sequencing mechanism that requires minimal sample manipulation, the device is capable of generating long sequence reads in sizes (up to or exceeding 50 kb) that surpass those of all other platforms. One notable advantage of this feature is that long-range haplotypes can be more accurately resolved; such advantage is particularly pertinent to the genotyping of complex loci such as genes encoding the human leukocyte antigens, which are pivotal determinants of drug hypersensitivity. With this timely, albeit brief, review, we set out to examine the applications on which MinION has been tested thus far, the bioinformatics workflow tailored to the unique characteristics of its extended sequence reads, the device's potential utility in the detection of genetic markers for drug hypersensitivity, and how it may eventually evolve to become fit for diagnostic purposes in the clinical setting. [ABSTRACT FROM AUTHOR]

An all-spherical catadioptic telescope with the angular field of view of several tens of degrees in diameter and spherical focal surface is proposed for the monitoring of large sky areas. We provide a few examples of such a system with the apertures up to 800 mm and the field of view 30° and 40° in diameter. The curvature of the focal surface is repaid by high performance of the telescope. In particular, the diameter of a circle that includes 80% of energy in the polychromatic image of a star is in the range 1.″4-1.″9 across the field of 30° size and 2.″2-2.″9 for the field of 40° size. Some ways of working with curved focal surfaces are discussed. (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

This study investigated the upper limit of suspended sediment concentration (SSC) with respect to the relationship between SSC and reflectance to develop an SSC remote-sensing model for the highly turbid Yellow River. An SSC quantification model was generated by using the spectral mixing index of sediments in water and sediment mixtures. In this study, laboratory experiments were made to measure the spectral curves of sediment-laden water with a high-resolution spectroradiometer. River-bed deposited sediments from two sites, one on the Yellow River at Huayuankou (HYK) and the other on the Wei River at Yangling (YL), and their sand, silt and clay particle groups were used for laboratory experiments to measure the spectral responses of sediment-laden water. The correlation analysis depicted stable correlation between SSC and reflectance at wavelengths ranging from 450 to 1000 nm, in which Spearman rank correlation coefficient (rs) for all sediments was above 0.7 while rs for the HYK natural sediment exceeded 0.9. Experimental results revealed the curves of the relationship between SSC and reflectance, up to 40 g l-1. A physical-based exponential model (> R2 0.9) at each simulated Landsat band effectively interpreted the relationship between SSC and reflectance. The highest upper limit SSCs at 21 and 15 g l-1 in natural YL and HYK sediments, respectively, were observed in Landsat Band 4. A spectral mixing algorithm was used to build the model and estimate the SSC from reflectance at correlated wavelength bands. The spectral mixing algorithm can generate a uniform model that disregards the effects of sediment type by adopting the reflectance curve at the upper-limit SSC to represent the standard reflectance of sediment. This study is useful in understanding the spectral characteristic of high SSC in water and in applying remote-sensing techniques to monitor SSC in the Yellow River. [ABSTRACT FROM AUTHOR]

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, . . . , 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. [ABSTRACT FROM AUTHOR]