Radar, Lidar and Vegetation Structure

Greg Asner TED Talk

Vegetation structural information, particularly in forests Land cover mapping – used with spectral data or direct use of radar polarimetry Agricultural mapping Tropical vegetation studies under cloudy skies Deriving information on soil water content

Radar can penetrate into plant canopies (pass through leaves, etc.) and reflect off of various parts of the plant Longer wavelengths penetrate more deeply into the canopy than shorter wavelengths By looking at the timing and intensity of radar backscatter from vegetation, can get information on the configuration of leaves, twigs, and trunks

The type of vegetation Growth stage Condition and health Crop yields Agricultural practices Soil characteristics Disturbance type and intensity Many others…

Radar can be designed to transmit and receive EMR that is polarized Characteristics of materials on the ground can change the polarization of radar signals (or not) If you measure the amount of change in polarization, you can infer information about the materials on the surface

Different incident angles for radar change the amount of backscatter (reflectance) By flying multiple passes of the same target but with different incidence angles, you can sometimes identify materials that otherwise would not be distinct.

Materials have a property called their dielectric constant that affects the amount of radar return Water has a very high dielectric constant By measuring the intensity of radar return you can sometimes infer the water content of a material because of the effect of high dielectric constant on the radar signal

In general radar is useful for vegetation because… 1. It can “see” through the canopy and give us information on structure of plants 2. It can be used to help identify plants that are spectrally similar 3. It can give us an idea of surface properties of soils (e.g., water availability) which are related to vegetation 4. It can see through clouds in tropical areas Combining radar remote sensing with optical remote sensing expands the possibilities for gathering information

Can characterize structural feature of vegetation using Lidar Tree or shrub height Leaf Area Index (LAI) Vegetation biomass Canopy structure Fuel loads Coarse woody debris

Multiple Lidar returns can give information about vegetation height and structure

Forest metrics

Biomass distribution in rain forest canopy. La Selva, Costa Rica

Map of canopy height and density in NE Utah – warm colors = trees, cool colors = brush

Lidar data are useful for creating high resolution surfaces Surface of top of plant canopy Bare earth surface Vegetation height by subtracting bare earth from top of canopy surface Detailed topography maps are useful for modeling vegetation distribution Lidar is so high resolution that you can often see individual trees and/or shrubs – can calculate things like vegetation density.