Measuring Vegetation Characteristics Going beyond land cover

Vegetation characteristics Some commonly measured characteristics: Vegetation structure Phenology Primary productivity Leaf area index Vegetation health/vigor Research is ongoing to improve existing indices and create new ones and to tie these assorted indices to useful environmental/ecological processes Some indices are created in a production environment on a global scale and others are created on a case-by-case bases Measurement of these indices is based on the fact the reflectance, transmittance, and scattering of energy in a canopy is greatly affected by vegetation structure and how vegetation components (leaves, branches, trunk) interact with the wavelength(s) of energy used by a particular instrument

Vegetation indices Uses the fundamental principle that chlorophyll in green healthy vegetation largely absorbs red and blue wavelengths of light and strongly reflects near-infrared wavelengths Closely related to primary productivity Dozens of vegetation indices have been developed Often composited for periods ranging form 8 days to one month Often used to monitor changes in productivity over time

Band 3 (Red) Band 4 (near-IR) RGB image NDVI

Popular vegetation indices Normalized Difference Vegetation Index (NDVI) NDVI = (NIR – Red) / (NIR + Red) Most common vegetation index Value is always between +1 and -1 with green vegetation closer to +1 and no vegetation close to 0 Negative values are possible for non-vegetated features Somewhat sensitive to radiometric contaminants

Popular vegetation indices Enhanced Vegetation Index (EVI) Developed to improve upon NDVI Output as a standard MODIS product EVI = G*[(NIR-Red)/NIR+C1*Red-C2*Blue+L)] where G, C1, C2, and L are coefficients: G = Gain factor (2.5 for MODIS) L = Canopy background adjustment (1 for MODIS) C2 = Atmospheric aerosol resistance (6 for MODIS) C2 = Atmospheric aerosol resistance (7.5 for MODIS) These coefficients reduces atmospheric effects in the red band and compensates for the different ways in which near-IR and red light behaves inside and below a canopy thereby reducing the effect of soil type, soil moisture, surface litter, and snow cover. EVI is more sensitive to canopy structure than NDVI

Continuous fields data Each pixel provides a proportional estimate of woody vegetation (needleleaf or broadleaf and evergreen or deciduous), herbaceous vegetation, and bare ground A standard MODIS product available for the globe (except the poles) at a resolution of 500 meters Initial reports are quite positive on the utility of this layer for species distribution models

Use of active sensors to measure vegetation characteristics Radar and lidar are used to measure vegetation structure characteristics such as: Height Density Timber volume Canopy volume Biomass This is an area of active research and additional indices will certainly be developed and more sophisticated instruments will be developed during the next several years