Good Practices In Sample Based Area Estimation

Reducing Emissions from Deforestation and Forest Degradation, and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+), as well as greenhouse gas reporting for the agriculture, forestry and other land use sector, requires land use changes to be characterized to estimate the associated greenhouse gas emissions or absorptions. It is becoming increasingly common to generate these estimates using sample-based area estimation (SBAE). This technique has been widely used in recent years in the generation of activity data – particularly for estimating areas of deforestation – for REDD+ measuring, reporting and verification. However, implementing countries and agencies have repeatedly highlighted the lack of guidance on how to address certain frequently encountered issues with this approach. This paper seeks to enable donors, academia, and countries that currently use or want to use SBAE for generating activity data for REDD+ or for other national or international reporting purposes, to delve into current good practice and existing literature, as well as gain a better understanding of the most pressing research needs in the area. The paper moreover will give non-experts an overview of area estimation, as well as its applications and limitations. Published by FAO with the collaborative support of several partners in the Global Forest Observations Initiative (GFOI), the World Bank and the Department for Energy Security and Net Zero of the United Kingdom of Great Britain and Northern Ireland, the paper is expected to contribute to improved forest data.

This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?rst C- pion Fellow (2000–2002). For the Fellowship I proposed these two topics as areas in which the academic statistics could contribute to the development of government statistics, in exchange for access to the operational details and background that would inform the direction and sharpen the focus of a- demic research. After a few years of involvement, I have come to realise that the separation of ‘academic’ and ‘industrial’ statistics is not well suited to either party, and their integration is the key to progress in both branches. Most of the work on this monograph was done while I was a visiting l- turer at Massey University, Palmerston North, New Zealand. The hospitality and stimulating academic environment of their Institute of Information S- ence and Technology is gratefully acknowledged. I could not name all those who commented on my lecture notes and on the presentations themselves; apart from them, I want to thank the organisers and silent attendees of all the events, and, with a modicum of reluctance, the ‘grey ?gures’ who kept inquiring whether I was any nearer the completion of whatever stage I had been foolish enough to attach a date.

This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.

Designed to aid readers in gathering the most reliable quantitative information on forests for the least cost. Thoroughly explains the interrelationships between sampling strategies; discusses forestry techniques of efficient tactics; examines new developments in statistics having immediate applications in forestry and describes related developments that should have relevance in the future. Includes practical methods for dealing with forest data such as tree number, height, diameter and marketable wood. Also contains problem sets.

An accessible introduction to indirect estimation methods, both traditional and model-based. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation. Uses a basic area-level linear model to illustrate the methods Presents the various extensions including binary response data through generalized linear models and time series data through linear models that combine cross-sectional and time series features Provides recent applications of SAE including several in U.S. Federal programs Offers a comprehensive discussion of the design issues that impact SAE

Comprehensive Remote Sensing covers all aspects of the topic, with each volume edited by well-known scientists and contributed to by frontier researchers. It is a comprehensive resource that will benefit both students and researchers who want to further their understanding in this discipline. The field of remote sensing has quadrupled in size in the past two decades, and increasingly draws in individuals working in a diverse set of disciplines ranging from geographers, oceanographers, and meteorologists, to physicists and computer scientists. Researchers from a variety of backgrounds are now accessing remote sensing data, creating an urgent need for a one-stop reference work that can comprehensively document the development of remote sensing, from the basic principles, modeling and practical algorithms, to various applications. Fully comprehensive coverage of this rapidly growing discipline, giving readers a detailed overview of all aspects of Remote Sensing principles and applications Contains ‘Layered content’, with each article beginning with the basics and then moving on to more complex concepts Ideal for advanced undergraduates and academic researchers Includes case studies that illustrate the practical application of remote sensing principles, further enhancing understanding

This Research Topic will coincide with an international Blue Carbon Conference at the Royal Society of Edinburgh in November 2021, during the UNFCCC COP26 climate negotiations; we seek to showcase Blue Carbon as a Nature-based Solution for Climate Change, People and Biodiversity. The conference theme identifies the growing climate mitigation opportunities presented by Blue Carbon, yet also seeks to highlight the emergent research that points to the wider climate mitigation services of carbon in the marine environment - what we are calling "beyond the inventory". We welcome contributions that address the science and policy dimensions of Blue Carbon, particularly where these highlight opportunities and mechanisms for the protection, restoration and creation of Blue Carbon habitats. We also welcome case-study examples that highlight successful partnerships in a wide range of international settings and would particularly encourage contributions that show-case legal, policy or investment opportunities.

ADVANCES IN BUSINESS STATISTICS, METHODS AND DATA COLLECTION Advances in Business Statistics, Methods and Data Collection delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include: Practical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector. Comprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization. Detailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic. In-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata. Methodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods. Providing a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, Advances in Business Statistics, Methods and Data Collection will also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.