EurekaMag.com logo
+ Site Statistics
References:
52,725,316
Abstracts:
28,411,598
+ Search Articles
+ Subscribe to Site Feeds
EurekaMag Most Shared ContentMost Shared
EurekaMag PDF Full Text ContentPDF Full Text
+ PDF Full Text
Request PDF Full TextRequest PDF Full Text
+ Follow Us
Follow on FacebookFollow on Facebook
Follow on TwitterFollow on Twitter
Follow on Google+Follow on Google+
Follow on LinkedInFollow on LinkedIn

+ Translate

Differences in vegetation indices for simulated landsat 5 mss and tm noaa 9 avhrr and spot 1 sensor systems


Remote Sensing of Environment 23(3): 439-452
Differences in vegetation indices for simulated landsat 5 mss and tm noaa 9 avhrr and spot 1 sensor systems
The objective of this study was to evaluate the effects of the different wavelength bands of the Landsat-5 MSS and TM, NOAA-9 AVHRR, and SPOT-1 sensors on two vegetation indices, the normalized difference (ND) and near IR to red ratio (RATIO). The study also demonstrates how vegetation indices for the Landsat-5 MSS and TM, and SPOT-1 systems may be estimated with NOAA-9 AVHRR data. Agronomic and spectral reflectance measurements of corn (Zea mays L.) canopies were acquired with an Exotech 20C spectroradiometer in field experiments at Purdue University (W. Lafayette, IN) [USA]. The reflectance factor data were averaged into 10 nm bands over the 400-2400 nm wavelength interval. Each experiment included four rates of nitrogen fertilization (0, 67, 134 and 202 kg/ha) and three replicates. The vegetation indices were computed i) for ground-based sensors by integrating the reflectance factor data over the visible and near-IR bands of the four sensors and ii) for simulated satellite-based sensors by modifying the reflectance factors with the filter response of each sensor, atmospheric transmittance, and solar irradiance at the Earth's surface in each 10 nm waveband. Variability in the RATIO between the four sensor systems was greatest during mid-season when maximum amounts of green vegetation were present. Variability in ND for the four sensors was considerably less than for the RATIO and nearly constant for most of the growing season. Comparisons of predicted agronomic variables indicated that AVHRR data can estimate both of the vegetation indices of the MSS, and subsequently, agronomic variables as effectively as direct use of the vegetation indices of the MSS. The vegetation indices of all four systems were associated with similar amounts of variation in the examined agronomic variables. Thus, under similar viewing conditions, the AVHRR may complement measurements of the other sensor systems for monitoring surface features of the Earth. Studies are encouraged that address the effects of the dissimilar viewing conditions (orbital characteristics, spatial resolution, off nadir views, etc.) of these sensor systems on their respective vegetation indices.


Accession: 005151729



Related references

An integrative classification of vegetation in China based on NOAA AVHRR and vegetation-climate indices of the Holdridge life zone. International Journal of Remote Sensing 24(5): 1009-1027, 2003

Obtaining spatial and temporal vegetation data from Landsat MSS and AVHRR/NOAA satellite images for a hydrologic model. PEandRS, Photogrammetric Engineering and Remote Sensing 63(1): 69-77, 1997

NOAA/AVHRR vegetation indices and agriculture-meteorology processes. Advances in Space Research 12(7): 87-90, 1992

Monitoring crop yield using NOAA/AVHRR-based vegetation indices. Transactions of the Chinese Society of Agricultural Engineering 21(4): 104-108, 2005

Deriving stand age distribution in boreal forests using SPOT VEGETATION and NOAA AVHRR imagery. Remote Sensing of Environment 91(3/4): 405-418, 2004

District level noaa avhrr vegetation indices and scan angle effects. International Journal of Remote Sensing 13(4): 715-735, 1992

Comparison of vegetation indices derived from noaa avhrr data for sahelian crop assessments. Agricultural & Forest Meteorology 46(1-2): 23-40, 1989

Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India. International Journal of Remote Sensing 24(22): 4393-4402, 20 November, 2003

Monitoring Brazilian soybean production using NOAA/AVHRR based vegetation condition indices. International Journal of Remote Sensing 23(6): 1161-1179, 20 March, 2002

Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study. Photogrammetric engineering and remote sensing 54(4): 485-490, 1988