Design‐based strategies for sampling spatial units from regular grids with applications to forest surveys, land use, and land cover estimation

The purpose of this paper is to compare some spatial strategies for sampling polygons onto a grid partitioning a study area. Most of the schemes considered in the paper are aimed at avoiding the selection of neighboring polygons. When one or more auxiliary variables are similar or well correlated with the values of the survey variable, the auxiliary information is adopted at estimation level by means of the difference or the regression estimators, or at design level, using the values of auxiliary variables to determine the inclusion probabilities. Applications to large‐scale forest inventories, land use estimation, and forest cover estimation are discussed. A simulation study is performed to compare the adopted strategies in terms of bias (if present), accuracy, and accuracy estimation. The simulation is designed to mimic forest inventories and forest cover estimation, starting from some real situations. An application to plan future surveys for land use estimation in Italy is reported. Copyright © 2015 John Wiley & Sons, Ltd.

[1]  R. McRoberts,et al.  Using the regression estimator with Landsat data to estimate proportion forest cover and net proportion deforestation in Gabon , 2014 .

[2]  Piermaria Corona,et al.  Design-based diagnostics for k-NN estimators of forest resourcesThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time. , 2011 .

[3]  A. Olsen,et al.  Spatially Balanced Sampling of Natural Resources , 2004 .

[4]  Christopher A. Rodger,et al.  TWO-DIMENSIONAL BALANCED SAMPLING PLANS EXCLUDING CONTIGUOUS UNITS , 2002 .

[5]  Stephen V. Stehman,et al.  The Horvitz-Thompson Theorem as a Unifying Perspective for Probability Sampling: With Examples from Natural Resource Sampling , 1995 .

[6]  F. Breidt,et al.  Model-Assisted Estimation of Forest Resources With Generalized Additive Models , 2007 .

[7]  Anton Grafström,et al.  Spatially correlated Poisson sampling , 2012 .

[8]  Lorenzo Fattorini,et al.  Applying the Horvitz-Thompson criterion in complex designs: A computer-intensive perspective for estimating inclusion probabilities , 2006 .

[9]  R. Valentini,et al.  Land use inventory as framework for environmental accounting: an application in Italy , 2012 .

[10]  John J. Borkowski,et al.  SIMPLE LATIN SQUARE SAMPLING + 1 : A SPATIAL DESIGN USING QUADRATS , 1996 .

[11]  Piermaria Corona,et al.  Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys , 2009 .

[12]  Yves Tillé,et al.  Doubly balanced spatial sampling with spreading and restitution of auxiliary totals , 2013 .

[13]  B. N. Mandal,et al.  IPPS Sampling Plans Excluding Adjacent Units , 2008 .

[14]  Lorenzo Fattorini,et al.  Design-based methodological advances to support national forest inventories: a review of recent proposals , 2015 .

[15]  Lorenzo Fattorini,et al.  An adaptive algorithm for estimating inclusion probabilities and performing the Horvitz–Thompson criterion in complex designs , 2009, Comput. Stat..

[16]  L. Fattorini,et al.  Multi-stage cluster sampling for estimating average species richness at different spatial grains , 2007 .

[17]  Lorenzo Fattorini,et al.  Two‐phase estimation of coverages with second‐phase corrections , 2004 .

[18]  Liviu Theodor Ene,et al.  Efficient sampling strategies for forest inventories by spreading the sample in auxiliary space , 2014 .

[19]  David R. Smith,et al.  Efficiency of adaptive cluster sampling for estimating density of wintering waterfowl , 1995 .

[20]  F. Breidt,et al.  Local polynomial regresssion estimators in survey sampling , 2000 .

[21]  Niklas L. P. Lundström,et al.  Spatially Balanced Sampling through the Pivotal Method , 2012, Biometrics.

[22]  Yves Tillé,et al.  Complex national sampling design for long-term monitoring of protected dry grasslands in Switzerland , 2013, Environmental and Ecological Statistics.

[23]  P. G. D. Vries,et al.  Sampling Theory for Forest Inventory , 1986, Springer Berlin Heidelberg.

[24]  A. S. Hedayat,et al.  Sampling plans excluding contiguous units , 1988 .

[25]  Lucio Barabesi,et al.  Sampling properties of spatial total estimators under tessellation stratified designs , 2011 .

[26]  Earl F. Becker,et al.  A population estimator based on network sampling of tracks in the snow , 1998 .