Modern Survey Research Articles

A stableness of resistance model for nonresponse adjustment with callback data

Abstract Nonresponse arises frequently in surveys, and follow-ups are routinely made to increase the response rate. In order to monitor the follow-up process, callback data have been used in social sciences and survey studies for decades. In modern surveys, the availability of callback data is increasing because the response rate is decreasing, and follow-ups are essential to collect maximum information. Although callback data are helpful to reduce the bias in surveys, such data have not been widely used in statistical analysis until recently. We propose a stableness of resistance assumption for nonresponse adjustment with callback data. We establish the identification and the semiparametric efficiency theory under this assumption, and propose a suite of semiparametric estimation methods including doubly robust estimators, which generalize existing parametric approaches for callback data analysis. We apply the approach to a Consumer Expenditure Survey dataset. The results suggest an association between nonresponse and high housing expenditures.

Mixed stands of black spruce (Picea mariana) and tamarack (Larix laricina) offer high secondary growth in eastern boreal forests of Canada

The Canadian boreal forest is still lacking investigation into compatible species mixtures that can lead to higher growth rates than monospecific or pure stands. The effect of species mixtures on stand productivity can vary with stem density, species proportion, site characteristics, and climate variation. We investigated mixed stands of black spruce (Picea mariana) and tamarack (Larix laricina) in eastern Canadian boreal forests. Using modern forest survey data, we analyzed stand basal area variation in 756 mature stands exclusively composed of these two species over a study area spanning 535,000 km². We generated a linear relationship between mixed stand basal area and stem density, and the residual of this relation was used as response variable named ‘residual basal area’. Positive and negative deviations of residual basal area were analysed with generalized additive models and quantile regressions with tamarack basal area, climate, and site characteristics as explanatory variables. The selected model included tamarack basal area, mean seasonal precipitation, degree days, mean annual temperature, stand age, latitude, longitude, and the type of surficial deposit. Tamarack exhibited a linear positive effect on predicted residual basal area. The most significant effect was observed from the interaction between tamarack basal area and stand age, predicting positive residual basal area of 16 m² ha−1 when stand aged was 150 years old and tamarack basal area was between 12 and 17 m² ha−1. Quantile regressions revealed that tamarack could enhance basal area while increasing black spruce stem size and density. Landscape managers may consider the establishment of mixed black spruce and tamarack stands to favor secondary growth in eastern Canadian boreal forests.

Integrating Traditional and Modern Survey Methods: A Comparative Study of East African Practices

As East Africa experiences rapid urbanization and development, the integration of traditional and modern survey methods emerges as a crucial strategy for enhancing land surveying practices. This review article explores the complementary strengths of traditional methods, rooted in local knowledge and cultural practices, and modern technologies, such as Geographic Information Systems (GIS) and drone-based surveys. The study examines the importance of integrating these approaches to improve data accuracy, cultural relevance, and community acceptance. Through comparative analysis and case studies from Kenya and Tanzania, the article highlights the benefits and challenges of combining these methodologies. The review is based on an extensive examination of existing literature and field studies to provide a comprehensive understanding of the topic. Addressing technological, financial, regulatory, and social barriers is essential for realizing the potential of this integrated approach, which can significantly enhance urban planning, infrastructure development, and sustainable land management in East Africa. Keywords: Traditional Survey Methods, Modern Survey Technologies, GIS Integration, Drone Surveys, Land Management

Probabilistic Forward Modeling of Galaxy Catalogs with Normalizing Flows

Evaluating the accuracy and calibration of the redshift posteriors produced by photometric redshift (photo-z) estimators is vital for enabling precision cosmology and extragalactic astrophysics with modern wide-field photometric surveys. Evaluating photo-z posteriors on a per-galaxy basis is difficult, however, as real galaxies have a true redshift but not a true redshift posterior. We introduce PZFlow, a Python package for the probabilistic forward modeling of galaxy catalogs with normalizing flows. For catalogs simulated with PZFlow, there is a natural notion of “true” redshift posteriors that can be used for photo-z validation. We use PZFlow to simulate a photometric galaxy catalog where each galaxy has a redshift, noisy photometry, shape information, and a true redshift posterior. We also demonstrate the use of an ensemble of normalizing flows for photo-z estimation. We discuss how PZFlow will be used to validate the photo-z estimation pipeline of the Dark Energy Science Collaboration, and the wider applicability of PZFlow for statistical modeling of any tabular data.

A modern survey method for determining live loads based on multi-source and open-access data on the Internet

A modern survey method for determining live loads based on multi-source and open-access data on the Internet

Changing bryozoan fauna in Otago Harbour reflects growing urbanisation and globalisation

ABSTRACT A comparison between historic reports dating from 1884 (78 records of 35 species) to the bryozoan fauna present today (98 colonies of 14 species) reveals considerable faunal change in Otago Harbour / Te Wai Ōtākou (45° 50'S 170° 38'E) in Dunedin, east coast of South Island, Aotearoa New Zealand. This highly-modified urban port was once a rock-edged tidal inlet surrounded by bush and grassy hills, but changes to its flora and fauna are not limited to land and the intertidal. Our modern bryozoan surveys record predominantly ‘weedy’ invasive species which colonise anthropogenic surfaces, while previously-recorded larger, slower-growing native species are now missing. This study emphasises the importance of historical data and regular monitoring in determining baselines for conservation and restoration.

Results of modern radiation-hygienic surveys of settlements of Bryansk Oblast of the Russian Federation bordering the Republic of Belarus. Part 3: Radionuclide content in agricultural food products

The third article in a series of publications devoted to the results of studying the current radiation situation in the territories of the Bryansk region bordering the Republic of Belarus presents results of studies of the content of radionuclides (137Cs and 90Sr) in samples of agricultural food products produced in the personal subsidiary plots of the population. The regularities of changing 137Cs and 90Sr content in samples of cow’s milk and potatoes depending on the level of radioactive contamination of the territory were studied; the present values of the quantities characterizing the distribution of the ratio of the activity concentration of radionuclides in agricultural food products to the density of radioactive contamination of the soil of the territory were deter -mined. The ratios of average values of 137Cs activity concentration in milk from stalled and grazing periods for cattle were analyzed. The results of the study show that some dairy product samples (less than 1%) do not meet the radiological safety criterion. Exceedances of the hygienic standards were not found in the studied samples of potatoes, vegetables, and meat of farm animals.

Every Data Point Counts: Stellar Flares as a Case Study of Atmosphere-aided Studies of Transients in the LSST Era

Due to their short timescale, stellar flares are a challenging target for the most modern synoptic sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), a project designed to collect more data than any precursor survey, is unlikely to detect flares with more than one data point in its main survey. We developed a methodology to enable LSST studies of stellar flares, with a focus on flare temperature and temperature evolution, which remain poorly constrained compared to flare morphology. By leveraging the sensitivity expected from the Rubin system, differential chromatic refraction (DCR) can be used to constrain flare temperature from a single-epoch detection, which will enable statistical studies of flare temperatures and constrain models of the physical processes behind flare emission using the unprecedentedly high volume of data produced by Rubin over the 10 yr LSST. We model the refraction effect as a function of the atmospheric column density, photometric filter, and temperature of the flare, and show that flare temperatures at or above ∼4000 K can be constrained by a single g-band observation at air mass X ≳ 1.2, given the minimum specified requirement on the single-visit relative astrometric accuracy of LSST, and that a surprisingly large number of LSST observations are in fact likely be conducted at X ≳ 1.2, in spite of image quality requirements pushing the survey to preferentially low X. Having failed to measure flare DCR in LSST precursor surveys, we make recommendations on survey design and data products that enable these studies in LSST and other future surveys.

Dramatic Rebrightening of the Type-changing Stripped-envelope Supernova SN 2023aew

Multipeaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility. Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (−17.4 mag) and long (∼100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew’s spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak’s photospheric phase, before Hα resurfaces again during the nebular phase. The nebular lines ([O i], [Ca ii], Mg i], Hα) exhibit a double-peaked structure that hints toward a clumpy or nonspherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than that of normal SESNe as well as requiring a very high 56Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak and also powers the second peak of the light curve through interaction of the SN with the circumstellar medium.

National-scale mapping of soil-thickness probability in hilly and mountainous areas of Japan using legacy and modern soil survey

Soil thickness is a crucial parameter for local, regional and globalscale assessments, including those related to carbon cycles, water retention capacity, and landslide risk in the context of biogeochemical, soil physical, and slope stability models. This study had two primary objectives: 1) to predict maps depicting the probability of the A-horizon thickness exceeding 15 cm (AT15) and the A and B-horizon thickness exceeding 75 cm (soil thickness, ST75), across the expansive mountainous regions of Japan. 2) To evaluate the enhancement of model performance through the preselection of the maximum value and implementation of enhanced modeling using gridded modern soil survey data to utilize geographically clustered data. Initially, the study modeled the SOC, bulk density, and coarse fraction proportion using data from a modern soil survey of 0–30 cm. Subsequently, we employed a random forest model for AT15 and ST75 using a dataset of geographically clustered legacy soil profiles as training data, and topographic, vegetation, climatic, and volcanic attributes, and the predicted soil organic carbon and related properties as explanatory variables. We reduced the number of legacy soil profiles in the densely sampled areas by selecting the maximum soil thickness before modeling. The study assessed the final model performance at the national scale, with the accuracy and F1 scores reaching 0.691 and 0.754 for AT15 and 0.600 and 0.511 for ST75, respectively. Maximum value selection proved effective for modeling ST75 but not AT15. Although an enhanced model incorporating data from legacy and modern surveys did not improve accuracy at the national level, it did improve recall in sparsely sampled areas, for ST75. The resulting spatial pattern of the predicted ST75 effectively captured variations in soil thickness associated with topography, geology, and tephra deposition. However, ST75, representing pedological soil thickness, tended to be strongly underestimated compared to geotechnical soil thickness, including the C-horizon, especially in areas affected by tephra deposition. This study represents a significant contribution as it delivers Japan's first national-scale soil thickness map and an approach for utilizing clustered legacy data. It is expected to find practical applications in estimating water storage capacity for forest management and other relevant purposes.

Observational Tests of Active Galactic Nuclei Feedback: An Overview of Approaches and Interpretation

Growing supermassive black holes (Active Galactic Nuclei; AGN) release energy with the potential to alter their host galaxies and larger-scale environment; a process named “AGN feedback”. Feedback is a required component of galaxy formation models and simulations to explain the observed properties of galaxy populations. We provide a broad overview of observational approaches that are designed to establish the physical processes that couple AGN energy to the multi-phase gas, or to find evidence that AGN impact upon galaxy evolution. The orders-of-magnitude range in spatial, temporal, and temperature scales, requires a diverse set of observational studies. For example, studying individual targets in detail sheds light on coupling mechanisms; however, evidence for the long-term impact of AGN is better established within galaxy populations that are not necessarily currently active. We emphasise how modern surveys have revealed the importance of radio emission for identifying and characterising feedback mechanisms. At the achieved sensitivities, the detected radio emission can trace a range of processes, including a shocked interstellar medium caused by AGN outflows (driven by various mechanisms including radiation pressure, accretion disc winds, and jets). We also describe how interpreting observations in the context of theoretical work can be challenging, in part, due to some of the adopted terminology.

Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness

Modern surveys with large sample sizes and growing mixed-type questionnaires require robust and scalable analysis methods. In this work, we consider recovering a mixed dataframe matrix, obtained by complex survey sampling, with entries following different canonical exponential distributions and subject to heterogeneous missingness. To tackle this challenging task, we propose a two-stage procedure: in the first stage, we model the entry-wise missing mechanism by logistic regression, and in the second stage, we complete the target parameter matrix by maximizing a weighted log-likelihood with a low-rank constraint. We propose a fast and scalable estimation algorithm that achieves sublinear convergence, and the upper bound for the estimation error of the proposed method is rigorously derived. Experimental results support our theoretical claims, and the proposed estimator shows its merits compared to other existing methods. The proposed method is applied to analyze the National Health and Nutrition Examination Survey data. Supplementary materials for this article are available online.

Reconstruction of cropland cover in topographically complex areas: The case of Sichuan Province, China, from 1671 to 2019

Accurately reconstructing cropland cover in topographically complex areas has long been challenging for historical anthropogenic land cover change (ALCC) datasets. Sichuan Province, one of the most topographically complex areas in China, was chosen as a case study. This study integrated historical gazetteers and modern cropland statistics and survey data to examine and correct the prefecture-level cropland area of Sichuan Province. Subsequently, a novel cropland reconstruction model was proposed based on the order of cropland reclamation. Using this model, cropland changes in Sichuan Province from 1671 to 2019 were reconstructed with a spatial resolution of 5′ × 5′. The main findings were as follows: (1) The cropland reconstruction model designed in this study can well reproduce with the cropland cover in Sichuan Province. Compared with the prevailing ALCC datasets, our reconstructions were more consistent with descriptions of cropland changes in Sichuan Province in the literature. (2) The cropland cover in Sichuan Province expanded from northeastern and southern Sichuan to the Chengdu Plain and the hills north of the Yangtze River and then to the mountainous areas in the center and periphery of the basin from 1671 to 1985, after which it shrank in mountainous and urban areas. (3) The changes in cropland cover in Sichuan Province over the past 350 years were shaped by multiple factors such as war, famine, migration, agricultural policies and urbanization. The reconstructions in this study captured the spatial differences in cropland distribution in Sichuan Province, but their accuracy was limited by the cropland estimation method and the satellite-based cropland data used in the reconstruction model.

Denoising of Geochemical Data using Deep Learning–Implications for Regional Surveys

Regional geochemical surveys generate large amounts of data that can be used for a number of purposes such as to guide mineral exploration. Modern surveys are typically designed to permit quantification of data uncertainty through data quality metrics by using quality assurance and quality control (QA/QC) methods. However, these metrics, such as data accuracy and precision, are obtained through the data generation phase. Consequently, it is unclear how residual uncertainty in geochemical data can be minimized (denoised). This is a limitation to propagating uncertainty through downstream activities, particularly through complex models, which can result from the usage of artificial intelligence-based methods. This study aims to develop a deep learning-based method to examine and quantify uncertainty contained in geochemical survey data. Specifically, we demonstrate that: (1) autoencoders can reduce or modulate geochemical data uncertainty; (2) a reduction in uncertainty is observable in the spatial domain as a decrease of the nugget; and (3) a clear data reconstruction regime of the autoencoder can be identified that is strongly associated with data denoising, as opposed to the removal of useful events in data, such as meaningful geochemical anomalies. Our method to post-hoc denoising of geochemical data using deep learning is simple, clear and consistent, with the amount of denoising guided by highly interpretable metrics and existing frameworks of scientific data quality. Consequently, variably denoised data, as well as the original data, could be fed into a single downstream workflow (e.g., mapping, general data analysis or mineral prospectivity mapping), and the differences in the outcome can be subsequently quantified to propagate data uncertainty.

A comparison of two snapshot studies half a century apart suggests stability in a Pacific Northwest winter forest bird community

Populations of many North American bird species have declined throughout the past half century. The majority of studies quantifying these declines have analyzed counts of birds taken during spring and summer, not during the season of scarcity, winter. We re-surveyed seven large study plots in Douglas fir (Pseudotsuga menziesii) forests initially surveyed in winter during the late 1960s in the Oregon Coast Range, USA. We compared density estimates, observed species richness and vegetation structure within plots, and inspected aerial photography to describe changes in landscape-level landcover. To assess potential drivers of change, we reviewed historical climate data and explored patterns of abundance associated with forest age. Observed species richness was greater in the modern surveys. Abundances of four of the six most common bird species appeared to be similar to or slightly lower than 50 years ago as the historical point estimates usually fell within or above 95% confidence intervals generated from our analyses. We found no clear associations with changes in bird communities and forest structure, climate, or forest age. The historical data are unique in providing point estimates of abundance for the entire bird community on each study plot. Yet, some uncertainties in accuracy of the historic counting methods could still influence interpretation of multi-decadal changes in apparent abundance. We conclude that this Pacific Northwest bird community was relatively stable in its abundances of the most common forest-dwelling species and that largely the communities are still intact. Additional production of precisely repeatable surveys of winter bird communities are needed in all habitats to adequately characterize long-term population dynamics during the season of scarcity.

Minute-Cadence Observations of the LAMOST Fields with the TMTS: V. Machine Learning Classification of TMTS Catalogues of Periodic Variable Stars

Abstract Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variable stars has experienced substantial growth for several decades, which significantly deepened our comprehension of stellar structure and binary evolution. The Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) has started to monitor the LAMOST sky areas since 2020, with a cadence of 1 minute. During the period from 2020 to 2022, this survey has resulted in densely sampled light curves for ~30,000 variables of the maximum powers in the Lomb-Scargle periodogram above the 5σ threshold. In this paper, we classified 11,638 variable stars into 6 main types using XGBoost and Random Forest classifiers with accuracies of 98.83% and 98.73%, respectively. Among them, 5301 (45.55%) variables are newly discovered, primarily consisting of δ Scuti stars, demonstrating the capability of TMTS in searching for short-period variables. We cross-matched the catalogue with Gaia’s second Data Release (DR2) and LAMOST’s seventh Data Release (DR7) to obtain important physical parameters of the variables. We identified 5504 δ Scuti stars (including 4876 typical δ Scuti stars and 628 high-amplitude δ Scuti stars), 5899 eclipsing binaries (including EA-, EB- and EW-type) and 226 candidates of RS Canum Venaticorum. Leveraging the metal abundance data provided by LAMOST and the Galactic latitude, we discovered 8 candidates of SX Phe stars within the class of ”δ Scuti stars”. Moreover, with the help of Gaia color-magnitude diagram, we identified 9 ZZ ceti stars.

Accurate Fourier-space statistics for line intensity mapping: Cartesian grid sampling without aliased power

ABSTRACT Estimators for n-point clustering statistics in Fourier-space demand that modern surveys of large-scale structure be transformed to Cartesian coordinates to perform Fast Fourier Transforms (FFTs). In this work, we explore this transformation in the context of pixelized line intensity maps (LIM), highlighting potential biasing effects on power-spectrum measurements. Current analyses often avoid a complete resampling of the data by approximating survey geometry as rectangular in Cartesian space, an increasingly inaccurate assumption for modern wide-sky surveys. Our simulations of a $20\, {\times }\, 20\, \text{deg}^2$ 21 cm LIM survey at $0.34\, {\lt }\, z\, {\lt }\, 0.54$ show this assumption biases power-spectrum measurements by ${\gt }\, 20~{{\ \rm per\ cent}}$ across all scales. We therefore present a more robust framework for regridding the voxel intensities on to a 3D FFT field by coordinate transforming large numbers of Monte-Carlo sampling particles. Whilst this unbiases power-spectrum measurements on large scales, smaller scale discrepancies remain, caused by structure smoothing and aliasing from separations unresolved by the grid. To correct these effects, we introduce modelling techniques, higher order particle assignments, and interlaced FFT grids to suppress the aliased power. Using a piecewise cubic spline (PCS) particle assignment and an interlaced FFT field, we achieve sub-per cent accuracy up to 80 per cent of the Nyquist frequency for our 21 cm LIM simulations. We find a more subtle hierarchical improvement in results for higher order assignment schemes, relative to the gains made for galaxy surveys, which we attribute to the extra complexity in LIM from additional discretizing steps. python code accompanying this paper is available at github.com/stevecunnington/gridimp.

Gulden Yespolova

Relevance. The relevance of the study is that in the primary grades, science is most demanding for pupils, due to a lack of interest in the subjects. Stimulating curiosity for scientific knowledge and enhancing students' competence is possible through the professional training of teachers. Purpose. The purpose of the study is to explore and examine the concept of research competence of primary school students in the content of renewed education to enhance the quality of learning activities through the implementation of innovative forms of learning. Methodology. The study utilized modern scientific methods, including sociological, functional, and survey approaches to examine the impact of the renewed education system on the younger generation and the formation of research competence in it. Results. Although innovation education is now at its height, its popularity in the Republic of Kazakhstan is still relatively new and gaining in significance. While state-provided resources support the development of research competence, educators play a pivotal role in advancing modern teaching methods. Project-based learning, practical exercises, and collaborative activities are integral components of the program, aligning with the trend towards open learning. However, challenges persist as some educators perceive curiosity as obstructive, and variations in student attitudes influence the development of research competence. By cultivating emotional engagement and employing activating methods, educators enhance student motivation and interest, facilitating the acquisition of research skills. Conclusions. The practical significance consists of overcoming the difficulties of the learning process by implementing research competence in the content of the renewed education through classroom and extracurricular activities, experiments and appropriate cognitive methods during the educational process. Keywords: research competence; innovative technologies; primary grades; renewed education; pupils

Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey.

Handwritten Text Recognition (HTR) is essential for digitizing historical documents in different kinds of archives. In this study, we introduce a hybrid form archive written in French: the Belfort civil registers of births. The digitization of these historical documents is challenging due to their unique characteristics such as writing style variations, overlapped characters and words, and marginal annotations. The objective of this survey paper is to summarize research on handwritten text documents and provide research directions toward effectively transcribing this French dataset. To achieve this goal, we presented a brief survey of several modern and historical HTR offline systems of different international languages, and the top state-of-the-art contributions reported of the French language specifically. The survey classifies the HTR systems based on techniques employed, datasets used, publication years, and the level of recognition. Furthermore, an analysis of the systems' accuracies is presented, highlighting the best-performing approach. We have also showcased the performance of some HTR commercial systems. In addition, this paper presents a summarization of the HTR datasets that publicly available, especially those identified as benchmark datasets in the International Conference on Document Analysis and Recognition (ICDAR) and the International Conference on Frontiers in Handwriting Recognition (ICFHR) competitions. This paper, therefore, presents updated state-of-the-art research in HTR and highlights new directions in the research field.

Application of modern survey and cartographic methods for documenting and presenting existing and historical workings of the UNESCO heritage site: Silver mine in Tarnowskie Góry

In this article, contemporary survey and cartographic methods were employed to document and present both the existing and historical workings of the UNESCO World Heritage Site, the Silver Mine in Tarnowskie Góry. Terrestrial laser scanning was utilized to capture detailed point clouds, which were then processed for advanced 3D applications. Due to the mine’s limited man-made roof supports, traditional vectorization methods were found to be impractical. Instead, ContexCapture Bentley software was used to create a detailed mesh model, overcoming the limitations of standard mesh algorithms in capturing intricate interior details. The project also integrated historical and current maps, orthophotos, and a digital terrain model to enrich the dataset. For georeferencing, fixed church locations were used, and vector layers were developed to map shafts, adits, water tunnels, and narrow-gauge railways, with each layer annotated with historical and geometric attributes. This approach not only preserves the mine’s complex features but also enhances its usability for future analysis and educational purposes. The resulting data offers a comprehensive, interactive representation of the mine, providing valuable insights into its historical importance and its ongoing role in the region’s mining heritage.