A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery
- 30 November 1998
- journal article
- Published by Elsevier BV in Remote Sensing of Environment
- Vol. 66 (2), 153-165
- https://doi.org/10.1016/s0034-4257(98)00054-6
Abstract
No abstract availableKeywords
This publication has 27 references indexed in Scilit:
- Empirical orthogonal function analysis of sea surface temperature patterns in Delaware BayIEEE Transactions on Geoscience and Remote Sensing, 1997
- Remote sensing reflectance and its relationship to optical properties of natural watersInternational Journal of Remote Sensing, 1996
- A neural network as a nonlinear transfer function model for retrieving surface wind speeds from the special sensor microwave imagerPublished by American Geophysical Union (AGU) ,1995
- The spectral responses of algal chlorophyll in water with varying levels of suspended sedimentInternational Journal of Remote Sensing, 1994
- The axial salinity distribution in the delaware estuary and its weak response to river dischargeEstuarine, Coastal and Shelf Science, 1992
- Satellite Monitoring of Optically-Active Components of Inland Waters: An Essential Input to Regional Climate Change Impact StudiesJournal of Great Lakes Research, 1991
- Chlorophyll-a estimation in New Jersey's coastal waters using Thematic Mapper dataInternational Journal of Remote Sensing, 1990
- A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methodsBiometrika, 1989
- Optical Properties, Suspended Sediments, and Chemistry Associated with the Turbidity Maxima of the Delaware EstuaryCanadian Journal of Fisheries and Aquatic Sciences, 1983
- Phytoplankton pigment concentrations in the Middle Atlantic Bight: comparison of ship determinations and CZCS estimatesApplied Optics, 1983