Agricultural Survey Methods

Due to the widespread use of surveys in agricultural resources estimation there is a broad and recognizable interest in methods and techniques to collect and process agricultural data.
This book brings together the knowledge of academics and experts to increase the dissemination of the latest developments in agricultural statistics. Conducting a census, setting up frames and registers and using administrative data for statistical purposes are covered and issues arising from sample design and estimation, use of remote sensing, management of data quality and dissemination and analysis of survey data are explored.
Key features:
Brings together high quality research on agricultural statistics from experts in this field.Provides a thorough and much needed overview of developments within agricultural statistics.Contains summaries for each chapter, providing a valuable reference framework for those new to the field.Based upon a selection of key methodological papers presented at the ICAS conference series, updated and expanded to address current issues.Covers traditional statistical methodologies including sampling and weighting.
This book provides a much needed guide to conducting surveys of land use and to the latest developments in agricultural statistics. Statisticians interested in agricultural statistics, agricultural statisticians in national statistics offices and statisticians and researchers using survey methodology will benefit from this book.

Spis treści:
1 The Present state of agricultural statistics in developed countries, situation and
challenges
1.1 Introduction
1.2 Current State and Political and Methodological Context
1.3 Governance and Horizontal Issues
1.4 Development in Demands for Agricultural Statistics and Challenges
1.5 Conclusions
Part One Census, frames, registers and administrative data
2 Using Administrative Registers for Agricultural Statistics
2.1 Introduction
2.2 Registers, Register Systems and Methodological Issues
2.3 Using Registers for Agricultural Statistics
2.4 Creating a Farm Register–the Population
2.5 Creating a Farm Register–the Statistical Units
2.6 Creating a Farm Register–the Variables
2.7 Conclusions
Bibliography
3 Alternative Sampling Frames and Administrative Data. Which is the Best Data
Source for Agricultural Statistics?
3.1 Introduction
3.2 Administrative Data
3.3 Administrative Data versus Sample Surveys
3.4 Direct Tabulation of Administrative Data
3.5 Errors in administrative registers
3.6 Errors in Administrative Data
3.7 Alternatives to Direct Tabulation  
3.8 Calibration and Small Area Estimators
3.9 Combined Use of Different Frames
3.10 Area Frames
3.11 Conclusions
Bibliography
4 Statistical Aspects of a Census
4.1 Introduction
4.2 Frame
4.3 Sampling
4.4 Non–sampling Error
4.5 Post Collection Processing
4.6 Weighting
4.7 Modeling
4.8 Disclosure Avoidance
4.9 Dissemination
4.10 Conclusions
Bibliography
5 Using Administrative Data for Census Coverage
5.1 Introduction
5.2 Statistics Canada’s Agriculture Statistics Program
5.3 1996 Census
5.4 Strategy to Add Farms to the Farm Register
5.5 2001 Census
5.6 2006 Census
5.7 Towards the 2011 Census
5.8 Conclusions
Bibliography
Part Two Sample design, weighting, and estimation
6 Area Sampling for Small–Scale Economic Units
6.1 Introduction
6.2 Similarities and Differences from Household Survey Design
6.3 Description of the Basic Design
6.4 Evaluation Criterion: the Effect of Weights on Sampling Precision
6.5 Constructing and Using ‘Strata of Concentration’ (StrCon)
6.6 Numerical Illustrations and More Flexible Models
6.7 Conclusions
Bibliography
7 On th e Use of Auxiliary Variables in Agricultural Surveys Design
7.1 Introduction
7.2 Stratification
7.3 Probability Proportional to Size Sampling
7.4 Balanced Sampling
7.5 Calibration weighting
7.6 Combining ex ante and ex post auxiliary information: a simulated approach
7.7 Conclusions
Bibliography
8 Estimation with Inadequate Frames
8.1 Introduction
8.2 Estimation Procedure
Bibliography
9 Small Area Estimation with Applications to Agriculture
9.1 Introduction
9.2 Design Issues
9.3 Synthetic and Composite Estimates
9.4 Area Level Models
9.5 Unit Level Models
9.6 Conclusions
Bibliography
Part Three GIS and remote sensing
10 The European Land Use and Cover Area–Frame Statistical Survey (LUCAS)
10.1 Introduction
10.2 Integrating Agricultural and Environmental Information with LUCAS
10.3 LUCAS 2001–2003: Target Region, Sample Design and Results
10.4 The Transect Survey in LUCAS 2001–2003
10.5 LUCAS 2006: A Two–phase Sampling Plan of Unclustered Points
10.6 Stratified Systematic Sampling with a Common Pattern of Replicates
10.7 GroundWork and Check Survey
10.8 Variance Estimation and Some Results in LUCAS 2006
10.9 Relative Efficiency of the LUCAS 2006 Sampling Plan
10.10 Expected Accuracy of Area Estimates with the LUCAS 2006 Scheme
10.11 Non–sampling Errors in LUCAS 2006
10.12 Conclusions
Bibliography
11 Area Frame Design for Agricultural Surveys
11.1 Introduction
11.2 Pre–Construction Analysis
11.3 Land–Use Stratification
11.4 Sub–Stratification
11.5 Replicated Sampling
11.6 Sample Allocation
11.7 Selection Probabilities
11.8 Sample Selection
11.9 Sample Rotation
11.10 Sample Estimation
11.11 Conclusions
Bibliography
12 Accuracy, Objectivity and Efficiency of Remote Sensing for Agricultural
Statistics
12.1 Introduction12.2 Satellites and Sensors
12.3 Accuracy, objectivity and cost–efficiency
12.4 Main approaches to use EO for crop area estimation
12.5 Bias and subjectivity in pixel counting
12.6 Simple correction of bias with a confusion matrix
12.7 Calibration and regression estimators
12.8 Some examples of Crop area estimation with remote sensing in large regions
12.9 The GEOSS best practices document on EO for crop area estimation
12.10 Sub–pixel analysis
12.11 Accuracy assessment of classified images and land cover maps
12.12 General data and methods for yield estimation
12.13 Forecasting yields
12.14 Satellite images and vegetation indices for yield monitoring
12.15 Some examples of Crop yield estimation / forecasting with remote sensing
Bibliography
13 Estimation of Land Cover ParametersWhen Some Covariates Are Missing
13.1 Introduction
13.2 The AGRIT Survey
13.3 Imputation of the Missing Auxiliary Variables
13.4 Analysis of the 2006 AGRIT data
13.5 Conclusions
Bibliography
Part Four Data editing and quality assurance
14 A Generalized Edit and Analysis System for Agricultural Data
14.1 Introduction
14.2 The System Development
14.3 Analysis
14.4 Development Status
14.5 Conclusions
Bibliography
15 Statistical Data Editing for Agricultural Surveys
15.1 Introduction
15.2 Edit Rules
15.3 The Role of Automatic Editing in the Editing Process
15.4 Selective Editing
15.5 An Overview of Automatic Editing
15.6 Automatic Editing of Systematic Errors
15.7 The Fellegi–Holt Paradigm
15.8 Algorithms for Automatic Error Localization of Random Errors
15.9 Conclusions
Bibliography
16 Quality in Agricultural Statistics
16.1 Introduction
16.2 Changing Concepts of Quality
16.3 Assuring Quality
16.4 Conclusions
Bibliography
17 Statistics Canada’s Quality Assurance Framework Applied to Agricultu ral
Statistics
17.1 Introduction
17.2 Evolution of Agriculture Industry Structure and User Needs
17.3 Agriculture Statistics – A Centralized Approach
17.4 Quality Assurance Framework
17.5 Managing Quality
17.6 Quality Management Assessment
17.7 Conclusions
Bibliography
Part Five Data dissemination and survey data analysis
18 The DataWarehouse: A Modern System forManaging Data
18.1 Introduction
18.2 The Data Situation in NASS
18.3 What is a Data Warehouse?
18.4 How Does it Work?
18.5 What We Learned
18.6 What is in Store for the Future?
18.7 Conclusions
19 Data Access and Dissemination: Some Experiments During the First
Agricultural Census in China
19.1 Introduction
19.2 Data Access and Dissemination
19.3 SDA General Characteristics
19.4 A Sample Session Using SDA
19.5 Conclusions
Bibliography
20 Analysis of Economic Data Collected in Farm Surveys
20.1 Introduction
20.2 Requirements of Sample Surveys for Economic Analysis
20.3 Typical Contents of a Farm Economic Survey
20.4 Issues in Statistical Analysis of Farm Survey Data
20.5 Issues in EconomicModelling Using Farm Survey Data
20.6 Case Studies
Bibliography
21 Measuring Household Resilience To Food Insecurity: Application To Palestinian
Households
21.1 Introduction
21.2 The Concept of Resilience and its Relation to Household Food Security
21.3 From Concept to Measurement
21.4 Empirical Strategy
21.5 Testing Resilience Measurement
21.6 Conclusions
Bibliography
22 Spatial Prediction of Agricultural Crop Yield
22.1 Introduction
22.2 The Proposed Approach
22.3 Case Study: the Province of Foggia
22.4 Conclusions
Bibliography


Okładka tylna:
Due to the widespread use of surveys in agricultural resources estimation there is a broad and recognizable interest in methods and techniqu es to collect and process agricultural data.
This book brings together the knowledge of academics and experts to increase the dissemination of the latest developments in agricultural statistics. Conducting a census, setting up frames and registers and using administrative data for statistical purposes are covered and issues arising from sample design and estimation, use of remote sensing, management of data quality and dissemination and analysis of survey data are explored.
Key features:
Brings together high quality research on agricultural statistics from experts in this field.Provides a thorough and much needed overview of developments within agricultural statistics.Contains summaries for each chapter, providing a valuable reference framework for those new to the field.Based upon a selection of key methodological papers presented at the ICAS conference series, updated and expanded to address current issues.Covers traditional statistical methodologies including sampling and weighting.
This book provides a much needed guide to conducting surveys of land use and to the latest developments in agricultural statistics. Statisticians interested in agricultural statistics, agricultural statisticians in national statistics offices and statisticians and researchers using survey methodology will benefit from this book.