Ground Visibility Research Articles

Estimating wind turbine fatalities using integrated detection trials

ABSTRACTFatality monitoring at wind projects requires carcass detection trials to adjust fatality estimates for the proportion of fatalities not found. However, detection trials vary greatly in metric, duration, carcass monitoring schedule, species, number placed, state of decomposition, whether placed within or outside search areas, and other factors. We introduce a new approach for estimating fatalities by quantifying overall detection rates rather than separate rates for searcher detection error and carcass persistence, and by leaving placed and found fatality carcasses undisturbed throughout monitoring. We placed 2 fresh‐frozen bird carcasses weekly at random sites within fatality search areas and on randomized days Monday–Friday at Sand Hill and Santa Clara wind projects, Altamont Pass Wind Resource Area, California, USA. To estimate detection rates, we used logit regression to fit detection outcomes on body mass, which served as an axis of similitude between placed trial carcasses and fatality finds. Adjusted carcass placement rates among species detected by searchers regressed on true placement rates with a slope of 1.0 so long as sufficient numbers of trial carcasses were placed, thus validating our approach as an unbiased estimator. Our approach generally estimated lower fatality rates than did conventional approaches, the latter of which demonstrated biases in searcher detection rates and carcass persistence rates whether based on proportion of carcasses remaining or mean days to removal. Our approach also revealed detection errors that highlight the difficulty of finding and identifying the remains of dead animals, and which warrant routine reporting. Despite averaging only a 5‐day search interval on intensively grazed annual grasslands where ground visibility was usually high, our experienced fatality monitors averaged 4.3 searches/first carcass detection, failed to detect 25% of 75 species represented by placed carcasses, and misidentified carcasses to species among 44% of species detected. Estimates of time since death also suffered bias and large error. Our approach more realistically simulates carcass detection probabilities associated with fatality monitoring, is less costly, facilitates hypothesis testing, eliminates multiple sources of error and bias suspected of conventional methods, and enables quantification of errors in estimated time since death, species identifications, and false negative findings. © 2018 The Wildlife Society.

Patch-based survey methods for studying prehistoric human land-use in agriculturally modified landscapes: A case study from the Canal de Navarrés, eastern Spain

In landscapes whose surface has been modified by terracing and other agricultural land-use, the spatial and temporal patterning of prehistoric settlement can be difficult to detect using traditional, site-orientated archaeological survey methods, especially for small-scale societies. In these contexts, methods that can reveal occupational patterns at landscape scales, without the need to pinpoint specific sites of human occupation, can be especially useful. We employ a stratified, randomly selected patch-based survey strategy to examine socio-ecological dynamics from the Middle Paleolithic through Bell Beaker (Chalcolithic) periods within the Canal de Navarrés, eastern Spain. We divide the study region into survey strata according to differences in topography and vegetation communities and use a random selection of demarcated, terraced fields as data collection patches. All survey data is digitally recorded using tablets in the field, creating a streamlined and more accurate workflow, where observations of artifacts, soils, ground visibility, and photographs are georeferenced and ready for analysis in a GIS. Surface artifact densities, estimated from sampled patches, are used to generate prehistoric land-use maps and empirical Bayesian methods allow us to track shifts in occupational patterns through time. Regional reference collections of well-dated lithic artifacts provide the “prior knowledge” required to make estimates of the probability of prehistoric occupation in each sampled patch. This combination of field and analytical methods makes possible the study of regional-scale land-use dynamics in agriculturally modified landscapes.

Multi-wavelength light-emitting diode light source radar system and near-ground atmospheric aerosol detection

Near-ground atmospheric aerosol has a direct effect on the living and production of human, and the research on its detection attracts substantial attention from engineers and scholars in the community of environment. Traditional monitoring instruments can accurately and continuously detect the aerosols above the ground, but it is difficult for them to obtain the information about vertical distribution of near-ground aerosols. As is well known, lidar can act as an efficient method to detect the aerosol's temporal and spatial distribution. However, this technique is restricted in the potential applications of the detection of aerosol at a certain wavelengths or near range. That is because it usually presents fixed wavelengths and a large blind area. In this work, a new multi-wavelength light-emitting diode (LED) light source radar system is designed and established for detecting the characteristics of atmospheric aerosol near ground. The paper is outlined as follows. Firstly, the composition and working principle of the LED light source radar system are introduced. Based on the structure of radar's transmitter and receiver, the geometric overlap factor is analyzed and calculated. The minimum detection height of the LED light source radar system is then determined to be 60 m. Secondly, the inversion method for the echo signal of LED light source radar is studied. In consideration of the suitability of near-range detection of LED light source radar, the Fernald forward integration method is used for inversing the aerosol extinction coefficient. The calibration value of aerosol extinction coefficient is further determined with the ground visibility data. Finally, by using the designed multi-wavelength LED light source radar system (475 nm, 530 nm, and 625 nm), near-ground aerosol observation at night in Xi'an city is carried out and three atmospheric conditions including light, moderate and severe pollution days are considered. The height distribution curves of atmospheric aerosol extinction coefficient of three wavelengths within a height of nearly 300 m are obtained. The characteristics of the distribution and change of near ground aerosols are accordingly discussed. The experimental results show that the multi-wavelength LED light source radar provides an efficient implementation for detecting the vertical distribution of atmospheric aerosol near the ground, and can make up for the inadequacy of lidar in near range detection.

A Comparison of Automated Object Extraction Methods for Mound and Shell-Ring Identification in Coastal South Carolina

One persistent archaeological challenge is the generation of systematic documentation for the extant archaeological record at the scale of landscapes. Often our information for landscapes is the result of haphazard and patchy surveys that stem from opportunistic and historic efforts. Consequently, overall knowledge of some regions is the product of ad hoc survey area delineation, degree of accessibility, effective ground visibility, and the fraction of areas that have survived destruction from development. These factors subsequently contribute unknown biases to our understanding of chronology, settlements patterns, interaction, and exchange. Aerial remote sensing offers one potential solution for improving our knowledge of landscapes. With sensors that include LiDAR, remote sensing can identify archaeological features that are otherwise obscured by vegetation. Object-based image analyses (OBIA) of remote sensing data hold particular promise to facilitate regional analyses thorough the automation of archaeological feature recognition. Here, we explore four OBIA algorithms for artificial mound feature detection using LiDAR from Beaufort County, South Carolina: multiresolution segmentation, inverse depression analysis, template matching, and a newly designed algorithm that combines elements of segmentation and template matching. While no single algorithm proved to be consistently superior to the others, a combination of methods is shown to be the most effective for detecting archaeological features.

Visibility-Based PM2.5 Concentrations in China: 1957-1964 and 1973-2014.

China established ground PM2.5 monitoring network in late 2012 and hence the long-term and large-scale PM2.5 data were lacking before 2013. In this work, we developed a national-scale spatiotemporal linear mixed effects model to estimate the long-term PM2.5 concentrations in China from 1957 to 1964 and from 1973 to 2014 using ground visibility monitoring data as the primary predictor. The overall model-fitting and cross-validation R2 is 0.72 and 0.71, suggesting that the model is not overfitted. Validation beyond the model year (2014) indicated that the model could accurately estimate historical PM2.5 concentrations at the monthly (R2 = 0.71) level. The historical PM2.5 estimates suggest that air pollution is not a new environmental issue that occurs in the recent decades but a problem existing in a longer time before 1980. The PM2.5 concentrations have reached 60-80 μg/m3 in the north part of North China Plain during 1950s-1960s and increased to generally higher than 90 μg/m3 during 1970s. The results also show that the entire China experienced an overall increasing trend (0.19 μg/m3/yr, P < 0.001) in PM2.5 concentrations from 1957 to 2014 with fluctuations among different periods. This paper demonstrated visibility data allow us to understand the spatiotemporal characteristics of PM2.5 pollution in China in a long-term.

Assessing visibility and geomorphological biases in regional field surveys: The case of Roman Aesernia

AbstractArchaeological field survey data can be biased by many factors, such as ground visibility conditions (e.g. vegetation, plowing) and geomorphological processes (erosion, deposition). Both visibility and geomorphological factors need, therefore, to be assessed when patterns of settlement and location preferences are inferred from survey data. Although both factors have been taken into account in a variety of fieldwork projects and studies, their combined effects remain hard to predict. In this paper, we aim to address this issue by presenting a visualization method that helps in evaluating in combination the possible visibility and geomorphological effects in regional, site‐oriented field surveys. Capitalizing on first‐hand data on both archaeology and soil types produced by the recent Leiden University field survey project in the area of Isernia (Roman Aesernia, Central‐Southern Italy), we propose a combined application of statistical tests and geo‐pedological analysis to assess the extent and scale of the main biases possibly affecting the interpretation of the ancient settlement organization. Translating both sets of biases into GIS maps, we indicate the likelihood that negative field survey observations (absence of sites), in specific parts of the landscape, are genuine or rather distorted by biasing factors. The resulting “archaeological detectability” maps allow researchers to formally highlight critical surveyed zones where the recording of evidence is likely unreliable, and thus provide a filter through which archaeologists can calibrate their interpretations of field survey datasets.

Assessing the Value of UAV Photogrammetry for Characterizing Terrain in Complex Peatlands

Microtopographic variability in peatlands has a strong influence on greenhouse gas fluxes, but we lack the ability to characterize terrain in these environments efficiently over large areas. To address this, we assessed the capacity of photogrammetric data acquired from an unmanned aerial vehicle (UAV or drone) to reproduce ground elevations measured in the field. In particular, we set out to evaluate the role of (i) vegetation/surface complexity and (ii) supplementary LiDAR data on results. We compared remote-sensing observations to reference measurements acquired with survey grade GPS equipment at 678 sample points, distributed across a 61-hectare treed bog in northwestern Alberta, Canada. UAV photogrammetric data were found to capture elevation with accuracies, by root mean squares error, ranging from 14–42 cm, depending on the state of vegetation/surface complexity. We judge the technology to perform well under all but the most-complex conditions, where ground visibility is hindered by thick vegetation. Supplementary LiDAR data did not improve results significantly, nor did it perform well as a stand-alone technology at the low densities typically available to researchers.

Observation and analysis of the temperature inversion layer by Raman lidar up to the lower stratosphere.

The vibration-rotational Raman lidar system built in Xi'an, China (34.233°N, 108.911°E) was used to simultaneously detect atmospheric temperature, water vapor, and aerosols under different weather conditions. Temperature measurement examples showed good agreement with radiosonde data in terms of the lapse rates and heights of the inversion layer under the lower stratosphere. The statistical temperature error due to the signal-to-noise ratio is less than 1 K up to a height of 15 km, and is estimated to be less than 3 K below a height of 22 km. High-quality temperature data were collected from 70 nighttime observations from October 2013 to May 2014, and were used to analyze the temperature inversion characteristics at Xi'an, which is a typical city in the northwest of China. The tropopause height over the Xi'an area was almost 17-18 km, and the inversion layer often formed above the cloud layer. In the winter at night, inversions within the boundary layer can easily form with a high occurrence of ∼60% based on 47 nights from 01 November 2013 to 21 January 2014. Continuous observation of atmospheric temperature, water vapor (relative humidity), and aerosols was carried out during one night, and the relevant changes were analyzed in the boundary layer via the joint observation of atmospheric visibility, PM2.5 and PM10 from a ground visibility meter and from a monitoring site, which revealed that the temperature inversion layer has a great influence on the formation of fog and haze during the winter night and early morning.

Multi-UAV Surveillance over Forested Regions

S-UAVs (Small-Unmanned Aerial Vehicles) have emerged as low-cost alternatives for aerial surveillance over forests. However, they provide limited coverage owing to their low altitudes and short endurance. Therefore, a quick and effective surveillance necessitates optimal flying paths, maximizing ground visibility. Even though the occlusion of ground points due to vegetation is significant in forests, it is generally neglected. This paper proposes a probabilistic sensing model that incorporates both occlusions due to terrain and vegetation, in the visibility computations and presents a two-step approach to determine near-optimal flight paths: (a) waypoints are strategically deployed to enhance visibility, using centroidal Voronoi tessellation, and (b) flyable paths are designed using a clustered spiral-alternating algorithm. Simulation studies conducted on synthetic terrains and a reconstructed terrain, from satellite data of tree-cover and a Digital Elevation Model (DEM), show the effectiveness of the proposed method in improving the terrain visibility as compared to commonly used grid-based waypoints.

A vertical sounding of severe haze process in Guangzhou area

We detected a severe haze process in Guangzhou area with lidar and microwave radiometer, performed an inversion to get boundary layer height by wavelet covariance transform, and analyzed the correlation between meteorological factors of boundary layer and visibility from the perspective of dynamical and thermodynamic structures. Our results indicate that the boundary layer height shows significant daily changes, consistent with ground visibility variation. During the cleaning process, the boundary layer height exceeded 1 km; during severe haze, the height was only 500 m. Temperature gradient of 50–100 m, which was 30 h lag, was remarkably correlated with visibility, with the correlation coefficient of 0.77. High layer visibility (255 m) and low layer stability were significantly anticorrelation, and the maximum anticorrelation coefficient was up to −0.76 in cleaning days and −0.49 in haze days. In the related boundary layer meteorological factors, surface ventilation coefficient was linearly correlated with ground visibility, with the greatest correlation coefficient of 0.88. The correlation coefficients of boundary layer height, ground wind velocity, relative humidity and ground visibility were 0.76, 0.67, and −0.77, respectively. There was a strong correlation between different meteorological factors. The dominant meteorological factor during this haze process was surface ventilation coefficient. In the area without boundary layer height sounding, ground visibility and wind velocity could be used to estimate boundary layer height.

An analysis of the fog distribution in Beijing for the 2001–2005 period using NOAA and FY data

Based on the various fog remote sensing information products abstracted from the polar orbit meteorological satellite data (NOAA and FY), this paper analyzes the characteristics of the frequency and distribution that dense fogs have taken place in the Beijing district from 2001 to 2005. Among those information products, the statistical graph of the foggy days in Beijing from 2001 to 2005 by means of satellite remote-sensing reflects the frequency that dense fog has occurred in the different regions in Beijing; and the statistical graph of the foggy days of each season by satellite remote-sensing shows the characteristics of the temporal and spatial change of the fog distribution in Beijing in different seasons; the fog degree index(like pixel-level spatial measurement) by satellite remote-sensing reflects the fog frequency difference on unit area in different counties of Beijing. Meanwhile, based on the satellite remote-sensing pictures, data on the main meteorological elements that contribute to the formation of fog, geographic information, and DEM data, this paper makes an analysis in 3 areas, the traits of the fog distribution in the different regions of Beijing in different seasons; meteorological causes for temporal and spatial changes of the main fog types (advection fog, radiation fog). This paper also gave a brief introduction of the general principles of meteorological satellite remote sensing fog, fog information extraction method, as well as the process of satellite orbit selecting according to the ground visibility, data processing and product generation.

Development of High-Power Ka/Q Dual-Band and Communications/Radar Dual-Function Helix-TWT

Future military communication systems on mobile satellite uplink platforms such as ground-based high-mobility vehicles and unmanned aerial vehicles (UAVs) and aircraft have strict constraints in size, weight, and power. Despite these constraints, these platforms also require ever-increasing data rate and bandwidth for video/imagery transmissions from small aperture terminals. In addition to the communications requirements, more UAV platforms, as an important part of current and future military operations, desire radar capabilities for ground mapping and visibility through poor weather conditions. In 2007, as part of an ongoing effort to meet these demands, L-3 Communications Electron Technologies, Inc. successfully developed a Ka/Q dual-band helix-traveling-wave tube, i.e., the 8923H, that produces 315 W minimum output power at Ka-band (30-31 GHz) and 200 W minimum output power at Q-band (43.5-45.5 GHz). The device was primarily developed to satisfy the Ka/Q dual-band communications requirements with power goals of 300 W minimum at Ka-band and 175 W at Q-band, but in addition, the device can also dual-function as a radar source in the Ka-radar-band (33-36 GHz) with peak power up to 400 W and duty demonstrated up to 50%, all from a single device.

Parallel Archaeological and Visibility Survey in the Western Lower Papaloapan Basin, Veracruz, Mexico

We evaluate a relatively intensive Gulf lowland survey in Mesoamerica to assess the effects of topographic and ground visibility as well as vegetation types on the archaeological information recovered. Surveys conducted between 1986 and 1989 and between 1998 and 2002 in the Western Lower Papaloapan Basin, Veracruz, Mexico, focused on individual archaeological features rather than sites. The features are predominantly residential earthen mounds, but monumental earthen architecture occurs intermittently. We discuss variation in feature densities according to topographic visibility, ground visibility, and the nature of the vegetation cover, and we estimate the number of features that that the survey crew failed to detect due to variable visibility conditions. Although 3690 features were recorded, our more reliable estimates indicate that a substantial number (between 1056 and 1327 features) may have gone undetected due to a variety of vegetation and visibility conditions.

General Aviation Pilot Takeoff into Adverse Weather: The “Go/No-Go” Equation

This exploratory study assessed pilot takeoff behavior into adverse weather. Sixty general aviation pilots were presented with three levels of simulated ground visibility (1, 3, 5 sm), two levels of cloud ceiling (1000′, 2000′), and two levels of real financial incentive (straight salary, salary + bonus for takeoff). Trends were found in regression analysis for a number of environmental predictors of takeoff, though not for personality or demographic predictors. Methodological and analytical concerns inherent to this type of study were encountered and identified.

Conjugate observations of electromagnetic ion cyclotron waves

We compare electromagnetic ion cyclotron (EMIC) waves observed by the electric field instrument on Polar to simultaneous Pc1 pulsations detected at the subauroral Sodankylä station. We studied 44 passes where Polar was within ±1.5 hours in magnetic local time (MLT) from Sodankylä during a Pc1 pulsation event. In 70% of these passes a matching EMIC wave was observed in space. This shows that ground Pc1s indeed originate at high altitudes in the magnetosphere and have their source field line within a rather limited (±1–1.5 hours) MLT range. It also limits horizontal ducting of waves in the longitude direction to less than ∼1000–1500 km, and it gives a lower limit of ∼3 hours on the MLT extent of a typical EMIC wave band in space. Out of 69 EMIC events, 75% were observed at Sodankylä. This restricts the scale of ionospheric modification on the amplitude and frequency of waves. In several passes, two or three EMIC waves corresponding to different frequency branches were observed simultaneously. We discuss the location, frequency, amplitude, and ground visibility of the EMIC waves of these three branches separately. The results emphasize the high‐latitude dayside as a source of EMIC waves observed on the ground.

Atmospheric correction of satellite data using multi-wavelength lidar data with MODTRAN3 code

Standard atmospheric models are employed in radiative transfer codes such as MODTRAN3. The actual atmospheric conditions, especially those due to aerosol particles, change both spatially and temporally. For the atmospheric correction of satellite data it is highly desirable to use the data measured simultaneously with the satellite overflight. Lidars are quite useful to obtain the aerosol information. The Atmospheric Data Correction Lidar, a multi-wavelength lidar system at CEReS, Chiba University, has been applied for that purpose. Lidar signals are collected on June 27, 1997 and December 15, 1997, and analyzed to obtain the aerosol extinction profile. The extinction at 550 nm is interpolated from lidarderived data and substituted into MODTRAN3 as user-defined 26 layers. To compare this with the result using standard atmospheric model (urban spring/summer and urban fall/winter), the meteorological ground visibility for the latter is adjusted to give the optical thickness the same as the lidar data. The atmospheric correction to NOAA AVHRR data (channel 1 and 2) is performed with two step correction, the first step removing the atmospheric scattering contributions. The second correction, on the other hand, deals with the adjacency effect. This algorithm gives rise to appropriate albedo values in the range of 0.1 to 0.3 for land surfaces and 0.01 to 0.03 for sea surfaces. Although the effect of atmospheric correction is significant, the difference between the results based on lidar data and the standard model is found to be relatively small.

Effects of Delineation Errors in Forest Stand Boundaries on Estimated Area and Timber Volumes

A 717 ha forest area dominated by Norway spruce [Picea abies (L.) Karst.] and Scots pine [Pinus sylvestris L.] was used to assess the effects of photointerpreter errors in the placement of stand boundaries on the estimated area of different groups of forest stands (strata) and other land use classes, and on the total timber volume estimate of the forest. The boundaries between thinning phase stands and clearcuts were classified into three different groups according to the length of the tree shadows hindering ground visibility in the aerial photographs. Different distributions of errors in stand boundaries were assigned to the three groups of boundaries. By means of Monte Carlo simulations of errors in each boundary, the placement of each boundary was altered according to a normally distributed random deviate. In total, 125 independent estimates of total timber volume and area of different land use classes were produced. For thinning phase forest, the difference between the mean area of the simulations and true area was –2.0% of true area. The corresponding difference for total timber volume of all stands was –2.1%. For individual simulations, the minimum and maximum biases in timber volume were –4.8% and 3.1%, respectively

Neural network for emulation of an inverse model operational derivation of Case II water properties from MERIS data

An algorithm was developed to derive the concentrations of phytoplankton pigment, suspended matter and gelbstoff, and the aerosol path radiance from 'Rayleigh corrected' top-of-atmosphere reflectances over turbid coastal waters. The procedure is designed for MERIS, the Medium Resolution Imaging Spectrometer, which will be flown onboard the Earth observation satellite Envisat of the European Space Agency (ESA). The algorithm is a neural network (NN) which is used to parameterize the inverse of a radiative transfer model. It is used in this study as a multiple nonlinear regression technique. The NN is a feedforward backpropagation model with two hidden layers. The NN was trained with computed reflectances covering the range of 0.5-50mugl-1 phytoplankton pigment, 1-100mgl-1 suspended matter, gelbstoff absorption at 420nm of 0.02-2m-1 and a horizontal visibility of 2-50km. Inputs to the NN are the reflectances of the 16 spectral channels which were under discussion for MERIS. The outputs are the three water constituent concentrations and the aerosol concentration, here expressed as the horizontal ground visibility. Tests with simulated reflectances show: (1) that concentations are correctly retrieved for a wide range covering oligotrophic Case I and turbid Case II water; (2) that the atmospheric correction can be performed even over very turbid water where the reflectance of the water cannot be neglected for the atmospheric correction channels in the near-infrared spectral range; and (3) that the algorithm is robust against errors in the input data. Although the training of the NN is time consuming, the utilization of the NN algorithm is extremely fast and can be applied routinely for satellite data mass production.

Positional accuracy of boundaries between clearcuts and mature forest stands delineated by means of aerial photointerpretation

Four skilled interpreters delineated 48 boundaries between mature forest stands and clear-felled or nonproductive areas using black and white and color infrared aerial photographs. The positions of the boundaries were compared with ground-truth points located along the boundaries. On average, the interpreters located the boundaries 1.22-2.44 m inside the mature forest stands. Film type, focal length, location of the boundaries within different parts of the stereo models, and the height of the trees along the boundaries did not affect the interpretations significantly. Shadows caused by the trees, which is a hinderance to ground visibility, seriously affected the interpretation. The interpreters placed the boundaries 0.62 m farther inside the mature stands for boundaries covered by shadow than for boundaries without shadows.

The 1984 Chillagoe surveys

The results of a systematic archaeological survey at Chillagoe (north Queensland) are presented. Observations are made concerning site location and the effects of ground visibility on site patterning. This paper concludes with a working model of site patterning at Chillagoe during recent prehistory.