Titlebook: Sampling Spatial Units for Agricultural Surveys; Roberto Benedetti,Federica Piersimoni,Paolo Postig Book 2015 Springer-Verlag Berlin Heide

爭(zhēng)論

Advances in Sampling Estimation,surveys cannot be only performed on list frames (farms, households, or other legal bodies), or only on spatially defined frames, but also using a combination of these two types of frames..This chapter discusses these different advanced topics in sampling estimation.

fastness

Overview and Brief History, the use of spatial reference frames has become more attractive for defining the sampling design. This approach appears to be suited to the analysis of agricultural data, which are often geographically distributed. In this chapter, we outline some survey examples that make effective use of spatial reference frames.

Osmosis

Setting Up the Frame,onal access to the finite population of interest (S?rndal et al. 1992). The sampling frame has significant implications on the cost and the quality of any agricultural or non-agricultural survey..This chapter is devoted to the description of the main strengths and weaknesses of the different statistical frames.

有其法作用

Sampling Designs,ped to minimize the survey cost, while controlling the uncertainty associated with the estimates..Each scheme has advantages and disadvantages, but generally a combination can achieve stable and acceptable results in any field of statistical research..In this chapter, we review the main basic sampling designs.

流動(dòng)性

Spatial Sampling Designs,ay be present. The presence of this spatial effect may be inherent to the phenomenon under investigation, so it is desirable and appropriate that we consider this information in the sampling design..In this chapter we discuss the main spatial sampling designs, also with applications, that have been recently introduced in literature.

啞劇

LEERY

Book 2015erformed with the open-source software R,?readers will learn about the different phases of spatial data collection. The agricultural data analyzed in this book help policymakers and market stakeholders to monitor the production of agricultural goods and its effects on environment and food safety.

古老

Kinetic

An Introduction to Remotely Sensed Data Analysis,rage of a field, and can be used as a proxy for measuring crop and soil attributes. In this chapter, we discuss some statistical techniques for improving and interpreting the remotely sensed images with particular reference to their use in agriculture.

ADORN

Small Area Estimation,ch as a type of crop or a particular economic activity, or a subgroup of people with the same sex, race, or other characteristics..In this chapter, we describe the problems and main methodologies of small area estimation, with applications to artificial and agricultural data.