Continuous Innovation of the Quality Control of Remote Sensing Data for Territory Management

Elisabetta Carfagna () and Johnny Marzialetti ()
Additional contact information
Elisabetta Carfagna: University of Bologna, Department of Statistical Sciences
Johnny Marzialetti: University of Bologna, Department of Statistical Sciences

Chapter Chapter 8 in Statistics for Innovation, 2009, pp 145-160 from Springer

Abstract: Abstract This chapter deals with the problem of assessing the quality of land-cover databases, since only high-quality products are useful for gaining knowledge about and managing territory. After a brief analysis of the main aspects of quality control and validation of land-cover databases, the main concepts of statistical quality control methods are recalled in order to show how some quality control procedures for land-cover databases can be formalized and improved by taking advantage of statistical quality control methods. Then, sequential and two-step adaptive procedures with various quality indices are proposed that continuously improve the quality of land-cover databases during the production process, in order to satisfy the user’s needs.

Keywords: Sample Unit; Adaptive Sampling; Remote Sensing Data; European Environment Agency; Global Land Cover (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-88-470-0815-1_8

Ordering information: This item can be ordered from
http://www.springer.com/9788847008151

DOI: 10.1007/978-88-470-0815-1_8

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().