Remote Sensing for Sustainable Forest ManagementAs remote sensing data and methods have become increasingly complex and varied - and increasingly reliable - so have their uses in forest management. New algorithms have been developed in virtually every aspect of image analysis, from classification to enhancements to estimating parameters. Remote Sensing for Sustainable Forest Management reviews t |
Contents
| 1 | |
2 Sustainable Forest Management | 39 |
3 Acquisition of Imagery | 85 |
4 Image Calibration and Processing | 121 |
5 Forest Modeling and GIS | 177 |
6 Forest Classification | 205 |
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Common terms and phrases
aerial photographs airborne algorithms approach assessment bands biodiversity biomass canopy change detection classes classification accuracy climate complex components conifer considered crown closure deciduous defoliation density ecological ecological land classification estimates example field forest conditions forest covertypes forest ecosystems forest inventory forest stands forest types forestry forestry applications Franklin growth habitat high spatial hyperspectral image analysis image data image processing image processing systems increased interpretation land Landsat TM landscape leaf area leaf area index lidar Lillesand mapping measurements methods metrics models monitoring multispectral NDVI patch photointerpretation photosynthesis pixel predicted radar radiometric reflectance relationship remote sensing applications remote sensing data remote sensing imagery satellite imagery satellite remote sensing scale sensor soil spatial detail spatial resolution species composition spectral response structure studies sustainable forest management texture topographic tree crown typically understanding understory users variables vegetation