Title of article
Satellite passive microwave remote sensing for monitoring global land surface phenology
Author/Authors
Jones، نويسنده , , Matthew O. and Jones، نويسنده , , Lucas A. and Kimball، نويسنده , , John S. and McDonald، نويسنده , , Kyle C.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
13
From page
1102
To page
1114
Abstract
Vegetation phenology characterizes seasonal life-cycle events that influence the carbon cycle and land–atmosphere water and energy exchange. We analyzed global phenology cycles over a six year record (2003–2008) using satellite passive microwave remote sensing based Vegetation Optical Depth (VOD) retrievals derived from daily time series brightness temperature (Tb) measurements from the Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and other ancillary data inputs. The VOD parameter derives vegetation canopy attenuation at a given microwave frequency (18.7 GHz) and varies with canopy height, density, structure and water content. An error sensitivity analysis indicates that the retrieval algorithm can resolve the VOD seasonal cycle over a majority of global vegetated land areas. The VOD results corresponded favorably (p < 0.01) with vegetation indices (VIs) and leaf area index (LAI) information from satellite optical-infrared (MODIS) remote sensing, and phenology cycles determined from a simple bioclimatic growing season index (GSI) for over 82% of the global domain. Lower biomass land cover classes (e.g. savannas) show the highest correlations (R = 0.66), with reduced correspondence at higher biomass levels (0.03 < R < 0.51) and higher correlations for homogeneous land cover areas (0.41 < R < 0.83). The VOD results display a unique end-of-season signal relative to VI and LAI series, and may reflect microwave sensitivity to the timing of vegetation biomass depletion (e.g. leaf abscission) and associated changes in canopy water content (e.g. dormancy preparation). The VOD parameter is independent of and synergistic with optical-infrared remote sensing based vegetation metrics, and contributes to a more comprehensive view of land surface phenology.
Keywords
AMSR-E , phenology , Optical depth , Vegetation index , EVI , NDVI , LAI , growing season , MODIS
Journal title
Remote Sensing of Environment
Serial Year
2011
Journal title
Remote Sensing of Environment
Record number
1630606
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