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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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Demystifying field application of Critical Height sampling in estimating stand volume

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FOREST ECOSYSTEMS 2025年 13卷

作者： Lo, Hsiao-Chi Lam, Tzeng Yih Univ British Columbia Fac Forestry Dept Forest Resources Management 2045-2424 Main Mall Vancouver BC V6T 1Z4 Canada

Critical Height sampling (CHS) estimates stand volume free from any model and tree form assumptions. Despite its introduction more than four decades ago, CHS has not been widely applied in the field due to perceived challenges in measurement. The objectives of this study were to compare estimated stand volume between CHS and sampling methods that used volume or taper models, the equivalence of the sampling methods, and their relative efficiency. We established 65 field plots in planted forests of two coniferous tree species. We estimated stand volume for a range of Basal Area Factors (BAFs). Results showed that CHS produced the most similar mean stand volume across BAFs and tree species with maximum differences between BAFs of 5-18 m(3)ha(-1). Horizontal Point sampling (HPS) using volume models produced very large variability in mean stand volume across BAFs with the differences up to 126 m(3)ha(-1). However, CHS was less precise and less efficient than HPS. Furthermore, none of the sampling methods were statistically interchangeable with CHS at an allowable tolerance of <= 55 m(3)ha(-1). About 72% of critical height measurements were below crown base indicating that critical height was more accessible to measurement than expected. Our study suggests that the consistency in the mean estimates of CHS is a major advantage when planning a forest inventory. When checking against CHS, results hint that HPS estimates might contain potential model bias. These strengths of CHS could outweigh its lower precision. Our study also implies serious implications in financial terms when choosing a sampling method. Lastly, CHS could potentially benefit forest management as an alternate option of estimating stand volume when volume or taper models are lacking or are not reliable.

关键词： Angle count sampling Forest inventory Forest management probability proportional to size sampling sampling theory variable probability sampling Volume-to-basal area ratio

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Study on a soil erosion sampling survey in the Pan-Third Pole region based on higher-resolution images

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International Soil and Water Conservation Research 2020年第4期8卷 440-451页

作者： Qinke Yang Mengyang Zhu Chunmei Wang Xiaoping Zhang Baoyuan Liu Xin Wei Guowei Pang Chaozhen Du Lihua Yang College of Urban and Environment Northwest University XianShaanxi710126China Institute of Soil and Water Conservation Chinese Academic Sciences and Ministry of Water ResourcesYanglingShaanxi712100China College of Geography Beijing Normal UniversityBeijing100875China

Soil erosion is one of the most severe global environmental problems,and soil erosion surveys are the scientific basis for planning soil conservation and ecological *** improve soil erosion sampling survey methods and accurately and rapidly estimate the actual rates of soil erosion,a Pan-Third Pole region was taken as an example to study a methodology of soil erosion sampling survey based on high-spatial-resolution remote sensing *** sampling units were designed using a stratified variable probability systematic sampling *** spatiotemporal characteristics of soil erosion and conservation were taken into account,and finer-resolution freely available and accessible images in Google Earth were *** the visual interpretation of the free high-resolution remote sensing images,detailed information on land use and soil conservation measures was ***,combined with the regional soil erosion factor data products,such as rainfall-runoff erosivity factor(R),soil erodibility factor(K),and slope length and steepness factor(LS),the soil loss rates of some sampling units were *** results show that,based on these high-resolution remote sensing images,the land use and soil conservation measures of the sampling units can be quickly and accurately *** interpretation accuracy in 4 typical cross sections was more than 80%,and sampling accuracy,described by histogram similarity in 11 large sampling sites,show that the landuse of sampling uints can represent the structural characteristics of regional land *** on the interpretation of data from the sample survey and the regional soil erosion factor data products,the calculation of the soil erosion rate can be completed *** calculation results can reflect the actual conditions of soil erosion better than the potential soil erosion rates calculated by using the coarse-resolution remote sensing method.

关键词： Pan-third pole area Land use Soil conservation measures Remote sensing variable probability sampling

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Sample strategies for bias correction of regional LiDAR-assisted forest inventory Estimates on small woodlots

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ANNALS OF FOREST SCIENCE 2020年第3期77卷 75-75页

作者： Hsu, Yung-Han Chen, Yingbing Yang, Ting-Ru Kershaw, John A., Jr. Ducey, Mark J. Univ New Brunswick Fac Forestry & Environm Management POB 4400 Fredericton NB E3B 5A3 Canada Univ New Hampshire Dept Nat Resources & Environm 114 James Hall56 Coll Rd Durham NH 03824 USA

Key message This study presents an easy-to-apply variable probability sample design that is an efficient and cost-effective method to correct for local bias in regional LiDAR-assisted forest inventory estimates. This design is especially useful for small woodlot owners. Context Light detection and ranging (LiDAR)-derived forest inventory estimates are generally unbiased at landscape levels but may be biased locally. One solution to correct local bias is to use ground-based double sampling with ratio estimation where the LiDAR estimates form the large sample covariate and the ground plots are used to estimate a correction or calibration ratio. Aims Our objectives were to test the performance of different sample strategies, to correct for local bias, and to determine the most efficient and cost-effective sampling design. Methods We compared five sample selection methods and four plot types using simulation. Sample sizes and inventory costs required to achieve 5% standard error were calculated to assess sampling efficiency. Results The results showed that bias can be corrected successfully using a doubling sampling approach with ratio estimation, and that variable probability selection methods were more efficient than equal probability selection methods. A big basal area factor (BAF) plot was the most cost-effective on-the-ground plot type. Conclusion The most efficient and cost-effective sampling design was list sampling with big BAF plots. This combination can be used to calibrate LiDAR-derived forest inventory estimates for a variety of forest attributes.

关键词： LiDAR-assisted inventory variable probability sampling Big BAF sampling Ratio estimation sampling with covariates sampling to correct

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On the Estimation of the Distribution Function of a Finite Population Under High Entropy sampling Designs, with Applications

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SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS 2014年第2期76卷 234-259页

作者： Conti, Pier Luigi Sapienza Univ Roma Dipartimento Sci Stat Ple A Moro 5 I-00185 Rome Italy

The estimation of the distribution function of a population is an important problem in sampling finite populations. The existing literature focuses on the problem of estimating the population distribution function (p.f.d.) at a single point, or at a finite number of points. In this paper the main interest consists in estimating the whole p.d.f.. In many respects, the starting point is close to classical nonparametric statistics, although the approach to inference is based on sampling design. It is shown here that the Hajek estimator of the p.d.f., if properly centered and scaled, converges weakly to a Gaussian process with covariance kernel proportional to that of a Brownian bridge. The proportionality factor essentially depends on the sample design. Applications to (i) construction of a confidence band for the p.d.f., (ii) comparison of the p.d.f.s of two populations, and (iii) testing for independence of two characters are provided.

关键词： Finite populations variable probability sampling distribution function

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A distance limited method for sampling downed coarse woody debris

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FOREST ECOLOGY AND MANAGEMENT 2012年 282卷 53-62页

作者： Gove, Jeffrey H. Ducey, Mark J. Valentine, Harry T. Williams, Michael S. USDA Forest Service No Res Stn Durham NH 03829 USA Univ New Hampshire Dept Nat Resources & Environm Durham NH 03824 USA US Food Safety & Inspect Serv Risk Assessment & Residue Div Ft Collins CO 80526 USA

A new sampling method for down coarse woody debris is proposed based on limiting the perpendicular distance from individual pieces to a randomly chosen sample point. Two approaches are presented that allow different protocols to be used to determine field measurements;estimators for each protocol are also developed. Both protocols are compared via simulation against existing sampling methods that are closely related in terms of theory and field implementation. The new method performed well in comparison to both fixed-area plot and perpendicular distance sampling, and may provide some simplifications in operational field use. Published by Elsevier B.V.

关键词： Dead wood Ecological inventory Forest inventory variable probability sampling

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Asymptotic properties of weighted M-estimators for variable probability samples

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ECONOMETRICA 1999年第6期67卷 1385-1406页

作者： Wooldridge, JM Michigan State Univ Dept Econ E Lansing MI 48824 USA

I provide a systematic treatment of the asymptotic properties of weighted M-estimators under variable probability stratified sampling. The characterization of the sampling scheme and representation of the objective function allow for a straightforward analysis. Simple, consistent asymptotic variance matrix estimators are proposed for a large class of problems. When stratification is based on exogenous variables, I show that the unweighted M-estimator is more efficient than the weighted estimator under a generalized conditional information matrix equality. When population frequencies are known, a more efficient weighting is possible. I also show how the results carry over to multinomial sampling.

关键词： stratified sampling variable probability sampling multinomial sampling exogenous sampling weighted M-estimator weighted least squares

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THE HORVITZ-THOMPSON THEOREM AS A UNIFYING PERSPECTIVE FOR probability-sampling - WITH EXAMPLES FROM NATURAL-RESOURCE sampling

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AMERICAN STATISTICIAN 1995年第3期49卷 261-268页

作者： OVERTON, WS STEHMAN, SV SUNY COLL ENVIRONM SCI & FORESTRY SYRACUSENY 13210

Courses in sampling often lack a coherent structure because many related sampling designs, estimators, variances, and variance estimators are presented as separate cases. The Horvitz-Thompson theorem offers a needed integrating perspective for teaching the methods and fundamental concepts of probability sampling. Development of basic concepts in sampling via this approach provides the student with tools to solve more complicated problems, and helps to avoid some common stumbling blocks of beginning students, Examples from natural resource sampling are provided to illustrate applications and insight gained from this approach.

关键词： BITTERLICH sampling ENVIRONMENTAL sampling INCLUSION probability SYSTEMATIC sampling variable probability sampling

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Variance estimation in the EMAP strategy for sampling discrete ecological resources

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ENVIRONMENTAL AND ECOLOGICAL STATISTICS 1994年第2期1卷 133-149页

作者： Overton, W. S. Stehman, S. V. Oregon State Univ Dept Stat Corvallis OR 97331 USA SUNY Coll Environm Sci & Forestry Syracuse NY 13210 USA

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) is designed to describe status, trends and spatial pattern of indicators of condition of the nation's ecological resources. The proposed sampling design for EMAP is based on a triangular systematic grid and employs both variable probability and double sampling. The Horvitz-Thompson estimator provides the foundation of the design-based estimation strategy used in EMAP. However, special features of EMAP designed to accommodate the complexity of sampling environmental resources on a national scale require modifications of standard variance estimation procedures as well as development of new techniques. An overview of variance estimation methods proposed for application to EMAP's sampling strategy for discrete resources is presented.

关键词： double sampling EMAP Horvitz-Thompson estimator systematic sampling variable probability sampling

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