Title | ALOS PALSAR L-band polarimetric SAR data and in-situ measurements for leaf area index assessment |
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Author | Canisius, F; Fernandes, R |
Source | Canadian Journal of Remote Sensing vol. 3, no. 3, 2011 p. 221-229, https://doi.org/10.1080/01431161.2011.559288 |
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Year | 2011 |
Alt Series | Earth Sciences Sector, Contribution Series 20110318 |
Publisher | Informa UK Limited |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Province | Ontario |
NTS | 31G/05 |
Area | Nepean |
Lat/Long WENS | -76.0000 -75.5000 45.5000 45.2500 |
Subjects | remote sensing; satellite imagery; vegetation; radar imagery; radar methods; soil moisture; soils; infrared surveys |
Illustrations | satellite images; location maps; bar graphs; graphs |
Program | Groundwater Geoscience Aquifer Assessment &
support to mapping |
Released | 2012 05 01 |
Abstract | Leaf Area Index (LAI), a key parameter controlling crop growth and yield models, has been widely estimated using optical satellite measurements. The estimation of LAI from high resolution optical
satellite data is limited by cloudy conditions especially when systematic monitoring during the growing season is required. Synthetic Aperture Radar (SAR) data are less susceptible to atmospheric effects than optical data and L-Band SAR data has
been related to standing biomass over a number of landscapes. Here we quantify the relationship between LAI and both ALOS PALSAR L-band data and ENVISAT ASAR data under relatively uniform soil moisture conditions. In-situ LAI values of large corn,
soybean and pasture fields and forest plots were estimated using digital hemispherical photography, processed using the CANEYE software, between July 4th and 21st, 2006. PALSAR L band polarimetric radar backscatter of crop (corn and soybean) fields
and forest plots were in good agreement with measured LAI values but the C-Band ASAR imagery showed weak relationships. The study shows that PALSAR L band polarimetric data has the potential to provide useful estimates of LAI, especially in the case
of loss of optical data due to cloud. However, additional work is required to characterize the temporal variability of the relationship between PALSAR backscatter and LAI over varying soil moisture and soil surface conditions. |
GEOSCAN ID | 289692 |
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