@book{JRC40569,
	editor = {},
	address = {AA Enschede (The Netherlands)},
	year = {2007},
	author = {Gallego Pinilla F},
	isbn = {},
	abstract = {We analyse the different ways satellite images can be used for crop area estimation. We can group the methods into three categories: 
		- Pixel counting or similar approaches, including sub-pixel analysis : Estimates coming essentially from remote sensing. Ground data have a secondary role: training data for image classification, or sub-pixel analysis. In general this type of approaches should not be used unless there is no reasonable alternative. The statistical justification for this type of methods is very weak and there is a very high risk that the final estimates come essentially from the a priori belief of the analyst.  
		- Methods combining exhaustive but inaccurate information (from satellite images) with accurate information on a sample (most often ground surveys): Main types of methods in this category are regression, calibration and small area estimators. This is often the soundest way to use remote sensing for area estimation. 
		- Satellite images are used as support to build area frame surveys: to define sampling units, for stratification; as graphic documents for the ground survey, or for quality control.   
		Cost-efficiency is discussed: Operational use of remote sensing had reached the cost-efficiency threshold in some types of landscapes (large fields and few crop types) with Landsat TM images. New assessments are needed now for other image types. Some comments are made on the reason why many administrations are reluctant to integrate remote sensing in the production of area statistics.
		The specific experience of the MARS Project on area estimation is reported here with more detail on three activities: 
		- Regional crop inventories (1988-1993), that combined ground surveys and satellite images with a statistically consistent regression estimator. The remote sensing part that did not reach the cost-efficiency threshold at that time. 
		- Rapid Crop Area Change Estimates (Action 4 or Activity B). This was an attempt to provide area estimates without ground surveys. The reasons for the failure of this activity are briefly analysed. 
		- Eurostat¿s LUCAS 2006 survey: the main contribution of remote sensing was a stratification of a large pre-sample of points by photo-interpretation on aerial orthophotos.  
		},
	title = {Review of the Main Remote Sensing Methods for Crop Area Estimates},
	url = {http://agrifish.jrc.it/marsstat/meetings/STRESA_papers/Gallego_ISPRS_2006.pdf},
	volume = {},
	number = {},
	journal = {},
	pages = {1-6},
	issn = {},
	publisher = {International Society for Photogrammetry and Remote Sensing  - ISPRS},
	doi = {}