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Simulation studies to examine bias and precision of some estimators that use auxiliary information in design-based sampling in forest inventory

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NEW ZEALAND JOURNAL OF FORESTRY SCIENCE 2017年第1期47卷 1页

作者： West, P. W. Southern Cross Univ Sch Environm Sci & Engn Forest Res Ctr Lismore NSW 2480 Australia

Background: Various double sampling methods using both target and auxiliary variables have been developed over many years for use in natural resource inventory. Methods: Simulations of inventory were carried out using four different ratio estimators and model-assisted estimation in each of five rather different example forest populations. Estimates of population means and their standard errors from each of these methods were compared with those obtained using simple random sampling. Results: With all five double sampling estimators, bias in estimates of means and standard errors (the latter estimated analytically or through bootstrapping) was generally small and consistent with theoretical expectations. Their efficiency increased as either the first- or second-phase sample sizes increased. All were more efficient than estimates obtained using simple random sampling as long as there was some positive level of correlation between the target and auxiliary variable. However, none of the double sampling estimators was more efficient than any of the others. Conclusions: For many forest inventory tasks, users may well be able to use whichever of the estimators is most convenient to their purpose. However, model-assisted estimation has application in a wider range of circumstances than the other methods, which perhaps recommends it for general use.

关键词： Inventory design-based sampling Ratio estimators Model-assisted estimation

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A simple two-step method for spatio-temporal design-based balanced sampling

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2018年第2期32卷 457-468页

作者： Khavarzadeh, Ramin Mohammadzadeh, Mohsen Mateu, Jorge Tarbiat Modares Univ Dept Stat Tehran Iran Univ Jaume 1 Dept Math Castellon de La Plana Spain

We introduce a two-step method to perform spatio-temporal balanced sampling in a design-based approach. For populations with spatio-temporal trends and with anisotropic effects in the variable of interest, the prediction can be further improved by selecting samples that are well spread over the entire population in space and time. We control the spread of the sample over the population by using the volume of the corresponding three-dimensional Voronoi tessellation. Indeed, spatio-temporal design-based balanced sampling is even more efficient under the presence of a trend and anisotropic effects. We present an intensive simulation study comparing our method to other available methods for spatio-temporal sampling. Finally, we analyze real data by sampling from a population of temperature stations over six European countries.

关键词： Balanced sampling design-based sampling Spatio-temporal sampling

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Locally correlated Poisson sampling

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ENVIRONMETRICS 2024年第2期35卷 e2832-e2832页

作者： Prentius, Wilmer Swedish Univ Agr Sci Dept Forest Resource Management SE-90183 Umea Sweden

designs that produces spatially balanced, or well-spread, samples are desirable as they increase the probability of obtaining a sample highly representative of the population. Spatially correlated Poisson sampling (SCPS) is a method for selecting well-spread samples. In the SCPS method, the sampling outcomes (inclusion or exclusion of units) are decided sequentially. After each decision, the inclusion probabilities of surrounding units are updated. A specific order for deciding the sampling outcomes is not enforced for SCPS, that is, the order can be chosen randomly or be fixed. A new modified method called locally correlated Poisson sampling (LCPS) is suggested. In this new method, the order of the decisions makes sure the inclusion probabilities are updated (more) locally. As a result, a stronger negative correlation between inclusion indicators of nearby units is achieved. Simulations on various data sets show that the resulting samples from LCPS, in general, are more spatially balanced and produce lower variance than samples from SCPS and the local pivotal method.

关键词： auxiliary variables design-based sampling environmental monitoring local pivotal method spatially correlated Poisson sampling unequal probability sampling

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Integrating rapid assessment, variable probability sampling, and machine learning to improve accuracy and consistency in mapping local spatial distribution of plant species richness

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Forestry 2024年第2期97卷 282-294页

作者： Perng, Bo-Hao Lam, Tzeng Yih Su, Sheng-Hsin Bin Md Sabri, Mohamad Danial Burslem, David Cardenas, Dairon Duque, Álvaro Ediriweera, Sisira Gunatilleke, Nimal Novotny, Vojtech O’Brien, Michael J. Reynolds, Glen School of Forestry and Resource Conservation National Taiwan University Taipei 10617 Taiwan Fushan Research Center Taiwan Forestry Research Institute Yilan 264013 Taiwan Forestry and Environment Division Forest Research Institute Malaysia Selangor Kepong 52109 Malaysia The School of Biological Sciences University of Aberdeen Aberdeen AB24 3FX United Kingdom Instituto Amazónico de Investigaciones Científicas SINCHI Amazonas Leticia Colombia Department of Forest Sciences National University of Colombia Medellín 050034 Colombia Faculty of Applied Sciences Uva Wellassa University Badulla 90000 Sri Lanka University of Peradeniya Peradeniya 20400 Sri Lanka Biology Centre Institute of Entomology the Czech Academy of Sciences České Budějovice 37005 Czech Republic Faculty of Sciences University of South Bohemia České Budějovice 37011 Czech Republic Estación Experimental de Zonas Áridas Consejo Superior de Investigaciones Científicas Almería 04120 Spain Danum Valley Field Centre South East Asia Rainforest Research Partnership (SEARRP) Sabah Lahad Datu 91112 Malaysia

Conserving plant diversity is integral to sustainable forest management. This study aims at diversifying tools to map spatial distribution of species richness. We develop a sampling strategy of using rapid assessments by local communities to gather prior information on species richness distribution to drive census cell selection by sampling with covariate designs. An artificial neural network model is built to predict the spatial patterns. Accuracy and consistency of rapid assessment factors, sample selection methods, and sampling intensity of census cells were tested in a simulation study with seven 25–50-ha census plots in the tropics and subtropics. Results showed that identifying more plant individuals in a rapid assessment improved accuracy and consistency, while transect was comparable to or slightly better than nearest-neighbor assessment, but knowing more species had little effects. Results of sampling with covariate designs depended on covariates. The covariate I_freq, inverse of the frequency of the rapidly assessed species richness strata, was the best choice. List sampling and local pivotal method with I_freq increased accuracy by 0.7%–1.6% and consistency by 7.6%–12.0% for 5% to 20% sampling intensity. This study recommends a rapid assessment method of selecting 20 individuals at every 20-m interval along a transect. Knowing at least half of the species in a forest that are abundant is sufficient. Local pivotal method is recommended at 5% sampling intensity or less. This study presents a methodology to directly involve local communities in probability-based forest resource assessment to support decision-making in forest management. © The Author(s) 2023. Published by Oxford University Press on behalf of Institute of Chartered Foresters. All rights reserved.

关键词： biodiversity conservation design-based sampling forest inventory rapid biodiversity assessment species diversity variable probability sampling

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Two-phase adaptive cluster sampling with circular field plots

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ENVIRONMETRICS 2022年第5期33卷 e2729-e2729页

作者： Prentius, Wilmer Grafstrom, Anton Swedish Univ Agr Sci Dept Forest Resource Management SE-90183 Umea Sweden

Adaptive cluster sampling (ACS) is extended to the case when the primary sampling units consist of circular field plots. When conducting field work for environmental monitoring, circular field plots are often preferred as they are easily set up by field workers. ACS was developed by tessellating the area frame into square plots. By using a two-phase sampling procedure, a first-phase sample of circular field plots can be established as the primary sampling units, from which ACS can be performed. However, the two-phase approach introduces some additional complexity in estimation. We derive estimators and conservative variance estimators for two-phase ACS using circular field plots. For some populations, ACS may produce a highly variable sample size. To deal with this issue, we provide a way to reduce the maximal possible sample size. By using simulated populations, we compare the efficiencies of two-phase methods with ordinary simple random sampling. The simulations show that the two-phase approach is a competitive alternative to regular ACS, and that adding a restriction to the maximal possible sample size makes ACS a viable alternative for a larger set of populations.

关键词： adaptive sampling area frame sampling design-based sampling environmental monitoring spatially clustered populations

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How to find the best sampling design: A new measure of spatial balance

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ENVIRONMETRICS 2024年第7期35卷

作者： Prentius, Wilmer Grafstrom, Anton Swedish Univ Agr Sci Dept Forest Resource Management SE-90183 Umea Sweden

We present a novel measure to assess the spatial balance of a sample by utilizing the balancing equation, which captures the balance between the sample units and their neighbours. Spatially balanced samples are desirable as they may reduce the variance of an estimator of a population parameter. If the auxiliary variables we employ to spread the sample possess high explanatory power for the variable(s) of interest, the resulting reduction in variance can be substantial. An advantageous aspect of using auxiliary variables is that their availability is not contingent upon the sampling effort. Therefore, we can assess and compare sampling designs before committing resources to full-scale surveys. By comparing the proposed measure with commonly used measures of spatial balance, we ascertain that our measure consistently yields meaningful insights regarding the spatial balance of samples. Consequently, our measure can effectively differentiate between various designs when planning a survey, evaluate the potential gains from replacing an existing sample, and determine which non-responding units would contribute the most to enhancing the set of responding units.

关键词： auxiliary variables design-based sampling spatial balance spatial sampling statistical measure

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design-based spatial sampling: Theory and implementation

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ENVIRONMENTAL MODELLING & SOFTWARE 2013年 40卷 280-288页

作者： Wang, Jin-Feng Jiang, Cheng-Sheng Hu, Mao-Gui Cao, Zhi-Dong Guo, Yan-Sha Li, Lian-Fa Liu, Tie-Jun Meng, Bin Chinese Acad Sci Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing 100101 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Various sampling techniques are widely used in environmental, social and resource surveys. Spatial sampling techniques are more efficient than conventional sampling when surveying spatially distributed targets such as CO2 emissions, soil pollution, a population distribution, disaster distribution, and disease incidence, where spatial autocorrelation and heterogeneity are prevalent. However, despite decades of development in theory and practice, there are few computer programs for spatial sampling. We investigated the three-fold relationship between targets, sampling strategies and statistical methods in spatial contexture. Accordingly, the information flow of the spatial sampling process was reconstructed and optimized. SSsampling, a computer program for design-based spatial sampling, has been developed from the theoretical basis. Three typical applications of the software, namely sampling design, optimal statistical inference and precision assessment, are demonstrated as case studies. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Spatial sampling sampling trinity relationship Prior knowledge design-based sampling

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Ex-vessel price monitoring design in small-scale fisheries: An application in Chilean fisheries

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FISHERIES RESEARCH 2020年 230卷 105591-105591页

作者： Young, Zaida Robotham, Hugo Torres, Camilo Palta, Elizabeth Inst Fomento Pesquero Blanco 839 Valparaiso Chile Univ Diego Portales Fac Ingn & Ciencias Inst Ciencias Basicas Ave Ejercito 441 Santiago Chile

Small-scale fishery monitoring programs can provide valuable information about ex-vessel prices, which are essential for economic analyses and fisheries management. Ex-vessel prices obtained without adequate statistical support can generate inconsistent data and imprecise estimates that do not comply with quality standards that guarantee their usefulness in decision-making. We propose methodological approach for monitoring of ex-vessel prices across a wide range species and coves. In this study, an ex-vessel prices monitoring design was applied to small-scale fisheries in Chile. Our proposal includes: i) development of a sample frame, ii) adoption of a sampling design and estimators for the mean ex-vessel prices and their variance;and iii) determination of sample sizes. A sample frame of 40 species and 54 coves were selected to be monitored, representing close to 94 % of the small-scale landings. We proposed a stratified two-stage sampling design. Sample sizes of 2-5 days/month per species in each cove are suggested, with minimum limits between 3 and 10 transactions/day, in accordance with price variability. In coves where catch is transferred directly from fisher to consumer (shortened trade chains), higher and more variable prices were verified. In contrast, coves that destined their catch only to processing plants, ex-vessel prices remained relatively constant. The precision in mean ex-vessel price estimate depend largely on the number of days sampled. Data collection system used should be updated periodically, in order to capture the dynamics of the seafood trade at the landing sites and ensure precise and accurate estimates of mean ex-vessel prices. The methodological approach for price monitoring developed in this study can be used to implement or improve other ex-vessel price monitoring designs in small-scale fisheries.

关键词： Monitoring Ex-vessel price design-based sampling Two-stage sampling Small-scale fisheries Chilean fisheries

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Baseline estimates of soil organic carbon by proximal sensing: Comparing design-based, model-assisted and model-based inference

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GEODERMA 2016年 265卷 152-163页

作者： Rossel, R. A. Viscarra Brus, D. J. Lobsey, C. Shi, Z. McLachlan, G. CSIRO Land & Water Bruce E Butler Lab POB 1666 Canberra ACT 2601 Australia Alterra Univ Wageningen & Res Ctr Environm Sci Grp Wageningen Netherlands Zhejiang Univ Coll Environm & Resource Sci Inst Appl Remote Sensing & Informat Technol 866 Yuhangtang Rd Hangzhou 310058 Zhejiang Peoples R China CSIRO Agr Flagship Bruce E Butler Lab POB 1666 Canberra ACT 2601 Australia

For baselining and to assess changes in soil organic carbon (C) we need efficient soil sampling designs and methods for measuring C stocks. Conventional analytical methods are time-consuming, expensive and impractical, particularly for measuring at depth. Here we demonstrate the use of proximal soil sensors for estimating the total soil organic C stocks and their accuracies in the 0-10 cm, 0-30 cm and 0-100 cm layers, and for mapping the stocks in each of the three depth layers across 2837 ha of grazing land. sampling locations were selected by probability sampling, which allowed design-based, model-assisted and model-based estimation of the total organic C stock in the study area. We show that spectroscopic and gamma attenuation sensors can produce accurate measures of soil organic C and bulk density at the sampling locations, in this case every 5 cm to a depth of 1 m. Interpolated data from a mobile multisensor platform were used as covariates in Cubist to map soil organic C. The Cubist map was subsequently used as a covariate in the model-assisted and model-based estimation of the total organic C stock. The design-based, model-assisted and model-based estimates of the total organic C stocks in the study area were similar. However, the variances of the model-assisted and model-based estimates were smaller compared to those of the design-based method. The model-based method produced the smallest variances for all three depth layers. Maps helped to assess variability in the C stock of the study area. The contribution of the spectroscopic model prediction error to our uncertainty about the total soil organic C stocks was relatively small. We found that in soil under unimproved pastures, remnant vegetation and forests there is good rationale for measuring soil organic C beyond the commonly recommended depth of 0-30 cm. Crown Copyright (C) 2015 Published by Elsevier B.V.

关键词： Proximal soil sensing Soil organic carbon stocks Visible-near Infrared spectroscopy design-based sampling Regression estimator Model-based inference

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Estimation of a partially linear additive model for data from an outcome-dependent sampling design with a continuous outcome

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BIOSTATISTICS 2016年第4期17卷 663-676页

作者： Tan, Ziwen Qin, Guoyou Zhou, Haibo Fudan Univ Sch Publ Hlth Dept Biostat Shanghai 200032 Peoples R China Fudan Univ Key Lab Publ Hlth Safety Dept Biostat Shanghai 200032 Peoples R China Univ North Carolina Chapel Hill Dept Biostat Chapel Hill NC 27599 USA

Outcome-dependent sampling (ODS) designs have been well recognized as a cost-effective way to enhance study efficiency in both statistical literature and biomedical and epidemiologic studies. A partially linear additive model (PLAM) is widely applied in real problems because it allows for a flexible specification of the dependence of the response on some covariates in a linear fashion and other covariates in a nonlinear non-parametric fashion. Motivated by an epidemiological study investigating the effect of prenatal polychlorinated biphenyls exposure on children's intelligence quotient (IQ) at age 7 years, we propose a PLAM in this article to investigate a more flexible non-parametric inference on the relationships among the response and covariates under the ODS scheme. We propose the estimation method and establish the asymptotic properties of the proposed estimator. Simulation studies are conducted to show the improved efficiency of the proposed ODS estimator for PLAM compared with that from a traditional simple random sampling design with the same sample size. The data of the above-mentioned study is analyzed to illustrate the proposed method.

关键词： design-based sampling Empirical likelihood Polychlorinated biphenyls Semi-parametric model

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