The University of Southampton
University of Southampton Institutional Repository

Assessing the ground data requirements for regional-scale remote sensing of tropical forest biophysical properties

Assessing the ground data requirements for regional-scale remote sensing of tropical forest biophysical properties
Assessing the ground data requirements for regional-scale remote sensing of tropical forest biophysical properties
The use of remotely sensed data to estimate terrestrial properties usually involves the acquisition of ground data. Remotely sensed data are being applied to ever larger areas and the acquisition and use of ground data, being so expensive, requires optimization. This paper investigates a sampling strategy that has already been used to acquire ground data in support of National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) imagery of approximately 18 000 km2 of Cameroonian forest and attempts to validate both the strategy and the use of the ground data in regression modelling. Specifically, a geostatistical approach was used to quantify the variability in the scene, the precision of the ground data, the benefits of twostage sampling and the errors associated with regression modelling and prediction.
0143-1161
2571-2587
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Boyd, D.
a9a18d6b-8f33-4025-9ba0-9de91b4924bd
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Boyd, D.
a9a18d6b-8f33-4025-9ba0-9de91b4924bd

Atkinson, P.M., Foody, G.M., Curran, P.J. and Boyd, D. (2000) Assessing the ground data requirements for regional-scale remote sensing of tropical forest biophysical properties. International Journal of Remote Sensing, 21 (13 & 14), 2571-2587. (doi:10.1080/01431160050110188).

Record type: Article

Abstract

The use of remotely sensed data to estimate terrestrial properties usually involves the acquisition of ground data. Remotely sensed data are being applied to ever larger areas and the acquisition and use of ground data, being so expensive, requires optimization. This paper investigates a sampling strategy that has already been used to acquire ground data in support of National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) imagery of approximately 18 000 km2 of Cameroonian forest and attempts to validate both the strategy and the use of the ground data in regression modelling. Specifically, a geostatistical approach was used to quantify the variability in the scene, the precision of the ground data, the benefits of twostage sampling and the errors associated with regression modelling and prediction.

Text
Atkinson_et_al_IJRS_2000.pdf - Other
Restricted to Registered users only
Download (334kB)

More information

Published date: 2000

Identifiers

Local EPrints ID: 17309
URI: http://eprints.soton.ac.uk/id/eprint/17309
ISSN: 0143-1161
PURE UUID: 14d5874e-21aa-413e-aeee-fd3adb331dad

Catalogue record

Date deposited: 23 Aug 2005
Last modified: 15 Mar 2024 05:57

Export record

Altmetrics

Contributors

Author: P.M. Atkinson
Author: G.M. Foody
Author: P.J. Curran
Author: D. Boyd

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×