Conventional Survey Techniques Research Articles

Detecting Amphibians in Agricultural Landscapes Using Environmental DNA Reveals the Importance of Wetland Condition.

Amphibians are declining worldwide, in part because of large-scale degradation of habitat from agriculture and pervasive pathogens. Yet a common North American amphibian, the wood frog (Lithobates sylvaticus), ranges widely and persists in agricultural landscapes. Conventional survey techniques rely on visual encounters and dip-netting efforts, but detectability limits the ability to test for the effects of environmental variables on amphibian habitat suitability. We used environmental DNA to determine the presence of wood frogs and an amphibian pathogen (ranavirus) in Prairie Pothole wetlands and investigated the effects of 32 water quality, wetland habitat, and landscape-level variables on frog presence at sites representing different degrees of agricultural intensity. Several wetland variables influenced wood frog presence, the most influential being those associated with wetland productivity (i.e., nutrients), vegetation buffer width, and proportion of the surrounding landscape that is comprised of other water bodies. Wood frog presence was positively associated with higher dissolved phosphorus (>0.4 mg/L), moderate dissolved nitrogen (0.1-0.2 mg/L), lower chlorophyll a (≤15 µg/L), wider vegetation buffers (≥10 m), and more water on the landscape (≥0.25). These results highlight the effects of environmental factors at multiple scales on the presence of amphibians in this highly modified landscape-namely the importance of maintaining wetland water quality, vegetation buffers, and surrounding habitat heterogeneity. Environ Toxicol Chem 2019;38:2750-2763. © 2019 SETAC.

Detection and Monitoring of Tunneling-Induced Riverbed Deformation Using GPS and BeiDou: A Case Study

Shield tunneling under rivers often requires monitoring riverbed deformations in near real-time. However, it is challenging to measure riverbed deformation with conventional survey techniques. This study introduces a comprehensive method that uses the Global Positioning System (GPS) of the USA and the BeiDou navigation satellite system (BeiDou) of China to monitor riverbed deformation during the construction of twin tunnels beneath the Hutuo River in Shijiazhuang, China. A semi-permanent GPS network with one base station outside the river and six rover stations within the river was established for conducting near real-time and long-term monitoring. The distances between the base and the rover antennas are within two kilometers. The network was continuously operating for eight months from April to December 2018. The method is comprised of three components: (1) Monitoring the stability of the base station using precise point positioning (PPP) method, a stable regional reference frame, and a seasonal ground deformation model; (2) monitoring the relative positions of rover stations using the carrier-phase double-difference (DD) positioning method in near real-time; and (3) detecting abrupt and gradual displacements at both base and rover stations using an automated change point detection algorithm. The method is able to detect abrupt positional-changes as minor as five millimeters in near real-time and gradual positional-changes at a couple of millimeters per day within a week. The method has the flexibility of concurrent processing different GPS and BeiDou data sessions (e.g., every 15 minutes, 30 minutes, one hour, one day) for diffident monitoring purposes. This study indicates that BeiDou observations can also achieve few-millimeter-accuracy for measuring displacements. Parallel processing GPS and BeiDou observations can improve the reliability of near real-time structural deformation monitoring and minimize false alerts. The method introduced in this article can be applied to other urban areas for near real-time and long-term structural health monitoring.

Change detection of remotely sensed image using NDVI subtractive and classification methods.

Change detection is a technology ascertaining the changes ofspecific features within a certain time Interval. The use of remotelysensed image to detect changes in land use and land cover is widelypreferred over other conventional survey techniques because thismethod is very efficient for assessing the change or degrading trendsof a region. In this research two remotely sensed image of Baghdadcity gathered by landsat -7and landsat -8 ETM+ for two time period2000 and 2014 have been used to detect the most important changes.Registration and rectification the two original images are the firstpreprocessing steps was applied in this paper. Change detection usingNDVI subtractive has been computed, subtractive between the bandsof the two images and the ratio of the red to blue bands was alsocomputed. Change detection mask using minimum distanceclassification or detection after classification have be also used tocompute the changes between the resultant classes, many statisticalproperties of the original and process image have been illustrated inthis research

Accuracy of identifications of mammal species from camera trap images: A northern Australian case study

AbstractCamera traps are a powerful and increasingly popular tool for mammal research, but like all survey methods, they have limitations. Identifying animal species from images is a critical component of camera trap studies, yet while researchers recognize constraints with experimental design or camera technology, image misidentification is still not well understood. We evaluated the effects of a species’ attributes (body mass and distinctiveness) and individual observer variables (experience and confidence) on the accuracy of mammal identifications from camera trap images. We conducted an Internet‐based survey containing 20 questions about observer experience and 60 camera trap images to identify. Images were sourced from surveys in northern Australia and included 25 species, ranging in body mass from the delicate mouse (Pseudomys delicatulus, 10 g) to the agile wallaby (Macropus agilis, >10 kg). There was a weak relationship between the accuracy of mammal identifications and observer experience. However, accuracy was highest (100%) for distinctive species (e.g. Short‐beaked echidna [Tachyglossus aculeatus]) and lowest (36%) for superficially non‐distinctive mammals (e.g. rodents like the Pale field‐rat [Rattus tunneyi]). There was a positive relationship between the accuracy of identifications and body mass. Participant confidence was highest for large and distinctive mammals, but was not related to participant experience level. Identifications made with greater confidence were more likely to be accurate. Unreliability in identifications of mammal species is a significant limitation to camera trap studies, particularly where small mammals are the focus, or where similar‐looking species co‐occur. Integration of camera traps with conventional survey techniques (e.g. live‐trapping), use of a reference library or computer‐automated programs are likely to aid positive identifications, while employing a confidence rating system and/or multiple observers may lead to a collection of more robust data. Although our study focussed on Australian species, our findings apply to camera trap studies globally.

Using Google’s Passive Data and Machine Learning for Origin-Destination Demand Estimation

Origin-destination (OD) data collection methods are steadily attempting to move from conventional survey techniques (roadside interview, license plate, etc.) toward using passively collected big data sources such as those based on global positioning system (GPS) and cell phone call detail records (CDR). In this study, a new passive data source, Google’s Aggregated and Anonymized Trips (AAT), was used to derive hourly OD demand matrices for the San Francisco Bay Area. Since the AAT dataset contains relative flows or weights as opposed to absolute trips, machine learning techniques were applied to convert them with the help of observed OD flows from expanded household travel survey. Several machine learning models were trained to perform quite well for both training and test data. However, it was found that the multi-layer perceptron (MLP), a neural networks approach, resulted in the best performing model for the conversion. Additionally, all models were used for predictions in a hypothetical application context where input AAT data were scaled by different growth factors. This exercise showed that, even though the trip predictions of all models were close to each other initially, they varied widely for different magnitudes of OD markets and growth factors.

Sampling effort determination in bird surveys: do current norms meet best-practice recommendations?

A critical design component of studies measuring diversity is sampling effort. Allocation of sampling effort dictates how many sites can be sampled within a particular time-frame or budget, as well as sample duration, frequency and intensity, thereby determining the resolution and reliability of emergent inferences. Conventional survey techniques use fixed-effort methods that assume invariant detectabilities among sites and species. Several approaches have been developed in the past decade that account for variable detectability by using alternative sampling methods or by adjusting standard counts before analysis, but it is unclear how widely adopted these techniques have been or how current bird surveying norms compare with best-practice recommendations. I conducted a systematic search of the primary literature to ascertain how sampling effort is determined, how much effort is devoted to sampling each site and how variation in detectability is dealt with. Of 225 empirical studies of bird diversity published between 2004 and 2016, five used results-based stopping rules (each derived independently), 54 used proportional sampling, and 159 (71%) used implicit effort-based stopping rules (fixed effort). Effort varied widely, but 61% of studies used samples of 10min or less and 62% of studies expended total effort per datum of 2h or less, with 78% providing no justification for sampling efforts used and just 15% explicitly accounting for estimated detectability. Given known variation in detectability, relying on short-duration fixed-effort approaches without validation or post hoc correction means that most bird diversity studies necessarily under-sample some sites and/or species. Having identified current bird surveying norms and highlighted their shortcomings, I provide five practical solutions to improve sampling effort determination, urging contributors and consumers of empirical ecological literature to consider survey data in terms of sample completeness.

Lithological Profiling of Rocky Slopes using GeoReader Software Based on the Results of Ground Penetrating Radar Method

The paper presents the Ground Penetrating Radar (GPR) technique for the survey of deforming rocky slopes of the railway subgrades. The developed software GeoReader allows the delineation of the boundaries in soils, which compose the slope, and definition of the possible slip surface. We have summarized the results of the use of the technique in certain sections of the Far Eastern Railway.The current level of development in the sphere of geo-survey does not allow for the complete abandonment of costly and labor-intensive conventional survey techniques, such as boring. Nevertheless, in the near future geophysical methods will be able to provide complete information on the object of investigation.

Taming Big Data

Social media websites such as Facebook and Twitter provide an unprecedented amount of qualitative data about organizations and collective behavior. Yet these new data sources lack critical information about the broader social context of collective behavior—or protect it behind strict privacy barriers. In this article, I introduce social media survey apps (SMSAs) that adjoin computational social science methods with conventional survey techniques in order to enable more comprehensive analysis of collective behavior online. SMSAs (1) request large amounts of public and non-public data from organizations that maintain social media pages, (2) survey these organizations to collect additional data of interest to a researcher, and (3) return the results of a scholarly analysis back to these organizations as incentive for them to participate in social science research. SMSAs thus provide a highly efficient, cost-effective, and secure method for extracting detailed data from very large samples of organizations that use social media sites. This article describes how to design and implement SMSAs and discusses an application of this new method to study how nonprofit organizations attract public attention to their cause on Facebook. I conclude by evaluating the quality of the sample derived from this application of SMSAs and discussing the potential of this new method to study non-organizational populations on social media sites as well.

Improving understanding of the spatial dimensions of biophysical change in atoll island countries and implications for island communities: A Marshall Islands’ case study

Using coarse-scale approaches, existing national assessments of vulnerability and adaptation highlight physical land instability as a major threat to atoll island nationhood. However, such evaluations are bereft of detailed, ground-truthed analyses of the physical impacts of climatic change on reef islands, treating islands as homogenous in both biophysical and social characteristics. The distinct geomorphic context of two proximate reef islands (Jeh and Jabat) in the Marshall Islands was examined through conventional land survey techniques. A template documenting the nuances in island topography was used to evaluate simple inundation scenarios, reflecting current and future sea-level changes under storm surge conditions. The variations in local scale community exposure to inundation were discernible. The study highlights the importance of treating coarse-scale assessments with caution and underscores the need for continued commitment to resolving variations in community experiences to environmental change. Notions of risk and exposure are complex and embedded in both the biophysical and social contexts of each island community. Despite a number of targeted urban vulnerability studies in the Pacific there remains a need for efforts to document localised differences in experience to better inform contemporary adaptation efforts.

UTILIZING UNDERWATER THREE-DIMENSIONAL MODELING TO ENHANCE ECOLOGICAL AND BIOLOGICAL STUDIES OF CORAL REEFS

Abstract. The structural complexity of coral reefs profoundly affects the biodiversity, productivity, and overall functionality of reef ecosystems. Conventional survey techniques utilize 2-dimensional metrics that are inadequate for accurately capturing and quantifying the intricate structural complexity of scleractinian corals. A 3-dimensional (3D) approach improves the capacity to accurately measure architectural complexity, topography, rugosity, volume, and other structural characteristics that play a significant role in habitat facilitation and ecosystem processes. This study utilized Structure-from-Motion (SfM) photogrammetry techniques to create 3D mesh models for several Hawaiian corals that represent distinct morphological phenotypes. The orthophotos and digital elevation models generated from the SfM process were imported into geospatial analysis software in order to quantify several metrics pertaining to 3D complexity that are known to affect ecosystem biodiversity and productivity. The 3D structural properties of the reconstructed coral colonies were statistically analyzed to determine if the each species represents a unique morpho-functional group. The SfM reconstruction techniques described in this paper can be utilized for an array of research purposes to improve our understanding of how changes in coral composition affect habitat structure and ecological processes in coral reef ecosystems.

Structural monitoring for the rail industry using conventional survey, laser scanning and photogrammetry

Monitoring the movement of structures on railway projects in the UK typically involves the fixing of targets (e.g. prisms) or sensors onto the structures being monitored and their surroundings. Whilst this provides discrete point measurement capability across the structure, it is highly intrusive and expensive to setup in a railway environment. Terrestrial laser scanning (TLS) has become an invaluable method of data capture within the surveying industry including applications such as deformation monitoring. The main advantages of TLS, as opposed to other surveying techniques, are the ability to capture large volumes of 3D data at high speed, remotely and with a reasonably high accuracy. A complimentary technique, close-range photogrammetry (CRP), has been traditionally applied to structural monitoring, but is not routinely considered by the railway monitoring community. This technique has the advantage of rapid data capture from a mobile camera with the capability to monitor single points or to generate a point cloud, with an equipment cost approximately twenty times cheaper than a TLS system and at about one tenth the cost of a single instrument total station approach. This paper describes the application of TLS and CRP, along with conventional survey techniques, to the monitoring of a set of masonry arches during a major station refurbishment. Firstly, it investigates the capabilities of using TLS compared to traditional survey methods and encompasses a case where significant movements occur over an extended period of time. Inter-epoch comparison demonstrates a capability to detect change but highlights a requirement to understand the structure and data quality in making valid interpretations. Secondly, the paper compares TLS and CRP techniques as monitoring tools for creating point cloud data on the same set of masonry arches. These investigations generate significant volumes of data conferring the additional challenge of how to visualise observed changes and communicate those changes and their significance to the engineers who must make informed decisions from the data in a timely fashion.

Spotting East African mammals in open savannah from space.

Knowledge of population dynamics is essential for managing and conserving wildlife. Traditional methods of counting wild animals such as aerial survey or ground counts not only disturb animals, but also can be labour intensive and costly. New, commercially available very high-resolution satellite images offer great potential for accurate estimates of animal abundance over large open areas. However, little research has been conducted in the area of satellite-aided wildlife census, although computer processing speeds and image analysis algorithms have vastly improved. This paper explores the possibility of detecting large animals in the open savannah of Maasai Mara National Reserve, Kenya from very high-resolution GeoEye-1 satellite images. A hybrid image classification method was employed for this specific purpose by incorporating the advantages of both pixel-based and object-based image classification approaches. This was performed in two steps: firstly, a pixel-based image classification method, i.e., artificial neural network was applied to classify potential targets with similar spectral reflectance at pixel level; and then an object-based image classification method was used to further differentiate animal targets from the surrounding landscapes through the applications of expert knowledge. As a result, the large animals in two pilot study areas were successfully detected with an average count error of 8.2%, omission error of 6.6% and commission error of 13.7%. The results of the study show for the first time that it is feasible to perform automated detection and counting of large wild animals in open savannahs from space, and therefore provide a complementary and alternative approach to the conventional wildlife survey techniques.

Measurement of glacier velocity at Pik Lenin, Tajikistan, by feature tracking

Abstract. Glaciers, especially in mountain area are sensitive indicators of climate fluctuations and also contribute to present rates of sea level rise. In Central Asia, these glaciers are the primary resource for fresh water. Understanding the seasonal behavior of these glaciers would help to make efficient use of the available water reservoir. Different methods have been employed to study glacier displacements in past. The conventional survey techniques are very cost-intensive and highly depend on accessibility to high mountain glaciers also directs us to look for new ways to study these areas. Here remote sensing comes in handy with freely available data and a good coverage with high spatial and temporal resolution. Optical satellite imagery, available free can be effectively used for research purpose. The glacier in this region fed lake Karakul (380 km2), the largest Lake in Tajikistan. The objective is to study the displacement tendency of the Glacier in Pik Lenin area using Landsat 7 dataset. Normalized cross correlation algorithm has been implemented via CIAS to estimate the motion of glacier surface. A number of combination of reference block and search area size were tested for 30 m resolution dataset. As a result the specifications: reference block size of 15 pixels and search area size of 10 pixels was found out as the best set of parameters and considered for further processing. The study derives a reliable set of data depicting the velocities in the glacier which after post processing shows peak velocity of 121 m/y of the glacier.

Integrating Undergraduate Fieldwork into the Study of Human Mobility

ABSTRACTFieldwork has long been fundamental to human geography; however, increasingly unreceptive institutional environments have led to a decline in fieldwork in undergraduate human geography programs. We argue that mobility research presents an opportunity to reinvigorate the undergraduate field trip in human geography. We report on a second-year field course to Noosa, Australia, that blends new technologies with conventional survey techniques to capture data on a spectrum of human spatial behaviour. Over the course of a single weekend, students collect GPS traces of tourist mobility, survey businesses on the journey to work, collect residential migration histories and trace population dynamics on Noosa beach. Over the three years the course has been running, students have constructed a large repository of data on this Australian mobility hotspot, of which we report highlights. Results from standardised student course evaluations confirm the pedagogical value of these initiatives for human geography undergraduates.

Influence of elevation modelling on hydrodynamic simulations of a tidally-dominated estuary

Summary Hydrodynamic simulation of estuaries requires a single digital elevation model (DEM) resulting from merging of both topographic and bathymetric data. These two datasets are usually produced using different technologies, co-ordinate systems and datums. Intertidal data in particular are often lacking due to the difficulty of data acquisition using conventional survey techniques. This paper presents a fast, accurate and low-cost methodology to fill this gap and highlights the effect of the digital elevation model characteristics, such as the interpolation method and spatial resolution, on modelled water levels and flooded areas. The Lima river estuary, located in North-western Portugal, is used as a case study. Validation tests for commonly available spatial interpolators showed ordinary kriging to be the most adequate interpolator. Digital elevation models with regular grids of 5 m and 50 m resolution were used, together with the original (not interpolated) elevation dataset, as input to a finite element hydrodynamic model for astronomic tide simulation. Results indicate that the larger differences between using different elevation models occur at low tide during spring tide, marginally impacting the flood modelling. The effect of a vertical offset of the chart datum with respect to a part of the digital elevation model was finally investigated, showing a limited influence in the determination of the water levels.

Appendix B

Appendix B

Data fusion using aerial photographs and satellite images for detailed landslide assessment

Hong Kong is one of the world's mountainous international cities, and landslides are a constant threat to human life and property. Monitoring landslides in Hong Kong is important and this is always done by field surveying. However, although conventional survey techniques provide accurate landslide information, they are limited to small areas and physical contact with the slope may be dangerous. Remote sensing techniques can provide an alternative for collecting information about landslide causes and occurrences, and they may assist in the prediction of future landslide occurrences. This article demonstrates the use of monoscopic and stereoscopic aerial photographs, along with satellite images from the IKONOS very high resolution (VHR) sensor for detailed landslide hazard assessment over Hong Kong. For monoscopic aerial photographs, a fusion technique for generating pseudo true colour images from false colour aerial photographs was demonstrated. The pseudo true colour image is useful for better visual analysis in the photogrammetric model. For monoscopic IKONOS image, a set of image fusion techniques was applied in order to improve landslide interpretation, and the results were examined visually and statistically. The Pan-sharpening method among all the image fusion techniques has been demonstrated to have superior performance for identifying both landslide trails and crowns. Stereoscopic viewing using a stereoscopic pair of aerial photographs and stereoscopic IKONOS images was employed for more detailed landslide investigation such as landscape positional relationships (e.g. streams and ridges). Digital elevation models (DEM) were generated from aerial photographs and IKONOS stereoscopic images, and they were compared with digital contour data with 2 m contour interval. The DEMs generated from digital photogrammetric model and IKONOS stereoscopic images are consistently more accurate than an existing DEM, and are sensitive to micro-scale terrain features. The Hong Kong Civil Engineering Department may use the derived monoscopic fused images, stereoscopic images, DEM and anaglyph as objective measures for a detailed landslide study within Hong Kong.

Comparison of survey methods for monitoring Clark's Nutcrackers and predicting dispersal of whitebark pine seeds

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Researching creative companies: lessons learned from a risk in design project

Five small creative companies were studied in detail over extended periods of the New Product Development (NPD) life cycle. Design was a key aspect of company activity and central to the NPD process. A novel participatory methodology was developed and employed to identify perceived risks at the outset of NPD and to track risk thereafter. The methods used were partly determined by the nature of the companies, their work pattern and ethos and activities, though all companies shared a process by which objectives were agreed upon at the outset and reviewed regularly. Novel participatory research identified key data themes reflecting human-centred risk processes in small companies. It is unlikely that these themes would be captured using conventional survey techniques.

Production of giant marine diatoms and their export at oceanic frontal zones: Implications for Si and C flux from stratified oceans

From a synthesis of recent oceanic observations and paleo‐data it is evident that certain species of giant diatoms includingRhizosoleniaspp.Thalassiothrixspp. andEthmodiscus rexmay become concentrated at oceanic frontal zones and subsequently form episodes of mass flux to the sediment. Within the nutrient bearing waters advecting towards frontal boundaries, these species are generally not dominant, but they appear selectively segregated at fronts, and thus may dominate the export flux. AncientThalassiothrixdiatom mat deposits in the eastern equatorial Pacific and beneath the Polar Front in the Southern Ocean record the highest open ocean sedimentation rates ever documented and represent vast sinks of silica and carbon. Several of the species involved are adapted to a stratified water column and may thrive in Deep Chlorophyll Maxima. Thus in oceanic regions and/or at times prone to enhanced surface water stratification (e.g., during meltwater pulses) they provide a mechanism for generating substantial biomass at depth and its subsequent export with concomitant implications for Si export and C drawdown. This ecology has important implications for ocean biogeochemical models suggesting that more than one diatom “functional type” should be used. In spite of the importance of these giant diatoms for biogeochemical cycling, their large size coupled with the constraints of conventional oceanographic survey schemes and techniques means that they are undersampled. An improved insight into these key species will be an important prerequisite for enhancing our understanding of marine biogeochemical cycling and for assessing the impacts of climate change on ocean export production.