A Parametric Model for Estimating Relations Between Unprecisely Located Field Measurements and Remotely Sensed Data
✍ Scribed by Raymond Salvador
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 265 KB
- Volume
- 67
- Category
- Article
- ISSN
- 0034-4257
No coin nor oath required. For personal study only.
✦ Synopsis
Mislocations in the acquisition of field measurements nal digitization processes are factors of dispersion possimay affect estimates of functional relations between field bly related to the sensor. Furthermore, atmospheric and variables and their remotely sensed radiometric reillumination effects also may have a strong influence on sponses. Under such field errors least squares (LS) estithe information in remotely sensed images (Moran et al. mators perform poorly because they present significant 1992; Pons and Sole ´-Sugranyes, 1994; Yang and Vidal, systematic biases. New statistics have been developed to 1990). In addition to the usually considered error meaachieve better estimates of parameters of the functional surements in field variables (Curran and Hay, 1986), ermodel when such errors occur. An example uses thematic rors related to inaccuracies in the spatial location of field mapper data and field measurements from a forest invensamples also frequently occur (Ardo ¨and Pilesjo ¨, 1992; tory. Bias and consistency of new statistics are analyzed . with extensive simulations, showing their higher reliabil-As a first step in building up more complex preity compared with LS statistics. Finally, the effects of nondictive models, simpler models are used to analyze the spatially and spatially related field errors are compared.