Agriculture Reference
In-Depth Information
The semivariogram is a very important tool for planning a spatial design. It
provides information on the structure of the population. This can be used in
exploratory mode, and also to partition the observed region into zones that
optimize the sampling design.
Several issues remain open for future research. They are generally related
to the theoretical derivation of the
π kl s, which would result in a wide range of
advantages. A theoretical framework is, of course, important, and allows us to
study the properties of each design
References
Arbia G (1993) The use of GIS in spatial statistical surveys. Int Stat Rev 61:339-359
Barabesi L, Franceschi S (2011) Sampling properties of spatial total estimators under tessellation
stratified designs. Environmetrics 22:271-278
Bee M, Benedetti R, Espa G, Piersimoni F (2010) On the use of auxiliary variables in agricultural
surveys design. In: Benedetti R, Bee M, Espa G, Piersimoni F (eds) Agricultural survey
methods. Wiley, Chichester, pp 107-132
Benedetti R, Palma D (1995) Optimal
sampling designs
for dependent
spatial units.
Environmetrics 6:101-114
Benedetti R, Piersimoni F, Postiglione P (2015) Sampling spatial units: a comparison between
different designs
Berger YG (2004) A simple variance estimator for unequal probability sampling without replace-
ment. J Appl Stat 31:305-315
Bondesson L, Grafstr¨m A (2011) An extension of Sampford
s method for unequal probability
'
sampling. Scand J Stat 38:377-392
Bondesson L, Thorburn D (2008) A list sequential sampling method suitable for real-time
sampling. Scand J Stat 35:466-483
Breidt FJ, Chauvet G (2012) Penalized balanced sampling. Biometrika 99:945-958
Chauvet G (2009) Stratified balanced sampling. Surv Methodol 35:115-119
Chauvet G, Till´ Y (2006) A fast algorithm of balanced sampling. Comput Stat 21:53-62
Chauvet G, Bonn´ry D, Deville JC (2011) Optimal inclusion probabilities for balanced sampling.
J Stat Plan Inference 141:984-994
Christman MC (2000) A review of quadrat-based sampling of rare, geographically clustered
populations. J Agric Biol Environ Stat 5:168-201
Colbourn CJ, Ling ACH (1998) A class of partial triple systems with applications in survey
sampling. Commun Stat Theory Methods 27:1009-1018
Colbourn CJ, Ling ACH (1999) Balanced sampling plans with block size four excluding contig-
uous units. Aust J Comb 20:37-46
Cordy C (1993) An extension of the Horvitz-Thompson theorem to point sampling from a
continuous universe. Stat Probab Lett 18:353-362
Cressie N (1993) Statistics for spatial data. Wiley, New York
Dalenius T, H ´ jek J, Zubrzycki S (1961) On plane sampling and related geometrical problems. In:
Proceedings of the 4th Berkeley symposium on probability and mathematical statistics,
vol 1, pp 125-150
Das AC (1950) Two-dimensional systematic sampling and the associated stratified and random
sampling. Sankhya 10:95-108
Delmelle EM (2013) Spatial sampling. In: Fischer MM, Nijkamp P (eds) Handbook of regional
science. Springer, Berlin, pp 1385-1399
 
Search WWH ::




Custom Search