Evaluation of approaches for forest cover estimation in the Pacific Northwest, USA, using remote sensing

Applied Geography

Volumn 22, Issue 4, 2002, Pages 375-392

  Boyd, D S ^a   Foody, G M ^b   Ripple, W J ^c  

^a KINGSTON UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c OREGON STATE UNIVERSITY   (United States)

Author keywords

Conferous forest cover; Land cover transformation; Multiple regression; Neural networks; Pacific Northwest; Remote sensing; Vegetation indices

Indexed keywords

CONIFEROUS FOREST; FOREST COVER; LAND COVER; REMOTE SENSING;

UNITED STATES;

EID: 0036812380     PISSN: 01436228     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0143-6228(02)00048-6     Document Type: Article

References (56)

1. A review of vegetation indices
2. Use of reflectance spectral variation to retrieve canopy biophysical characteristics
3. Quantifying chlorophylls and carotenoids from leaf to canopy scales: An evaluation of some hyper-spectral approaches
4. Effects of land use on the climate of the United States
5. Vegetation indices
6. Consequences of changing biodiversity
7. Retrieving leaf area index of boreal conifer forests using Landsat TM images
8. Artificial neural network for land cover classification and mapping
9. Factors affecting the remotely sensed response of coniferous forest plantations
10. Global land cover characterisation from satellite data: From research to operational implementation?
11. Subpixel forest cover in central Africa from multisensor, multitemporal data
12. Carbon pools and flux of global forest ecosystems
13. Improvements on the global biospheric record from the Advanced Very High Resolution Radiometer
14. Computational neural networks a new paradigm for spatial analysis
15. Image classification with a neural network: From completely-crisp to fully-fuzzy situations
16. Detection of partial land cover change with ecotone movement
17. Mapping the biomass of Bornean tropical forests
18. Classification of remotely sensed data by an artificial neural network: Issues related to training data characteristics
19. Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas
20. Integrated analysis of spatial data from multiple sources: Using evidential reasoning and artificial neural network techniques for geological mapping
21. Land transformation
22. Land-use change and climate
23. The annual net flux of carbon to the atmosphere from changes in land use 1850- 1990
24. Deforestation in Mwanza district, Malawi, from 1981-1992, as determined from Landsat MSS imagery
25. Predictive modelling of coniferous forest age using statistical and artificial neural network approaches applied to remote sensor data
26. 2 concentration
27. Comparisons among vegetation indices and bandwise regression in a highly disturbed, heterogeneous landscape: Mount St. Helens, Washington
28. A global 1×1 degree NDVI data set for climate studies derived from the GIMMS continental NDVI data
29. Candidate high spectral resolution infrared indices for crop cover
30. Investigation of the utility of spectral vegetation indices for determining information on coniferous forests
31. Landsat MSS-derived land-cover map of northern Alaska: Extrapolation methods and a comparison with photo-interpreted and AVHRR-derived maps
32. The interpretation of spectral vegetation indexes
33. Nitrogen deposition makes a minor contribution to carbon sequestration in temperate forests
34. Effect of thinning cutting on boreal forest reflectance, a comparison of simulations and Landsat TM estimates
35. The sustainability debate
36. Towards a quantitative interpretation of vegetation indices Part 1: Biophysical canopy properties and classical indices
37. Vegetation spectral reflectance along a north south vegetation gradient in Northern Australia
38. Determining coniferous forest cover and forest fragmentation with NOAA-9 Advanced Very High Resolution Radiometer
39. Analysis of effective radiant temperature in a Pacific Northwestern forest using a thermal infrared multispectral scanner
40. The role of science in the preservation of forest biodiversity
41. Data on global land-cover change: Acquisition, assessment and analysis
42. LAI inversion using a back-propagation neural network trained with a multiple scattering model
43. An application of artificial neural networks to the prediction of surface ozone concentration in the United Kingdom
44. Dynamics and pattern of a managed coniferous forest landscape
45. 2 budget
46. Effects of spectral, spatial and radiometric characteristics on remote sensing vegetation indices of forested regions
47. Evaluation of narrow and broadband vegetation indices for determining optimal hyperspectral wavebands for agricultural crop characterisation
48. Integrating Landsat-TM data with environmental data for classifying forest cover types and estimating their biomass
49. Potential and limitations of information extraction on the terrestrial biosphere from satellite remote sensing