TY - JOUR
T1 - Monitoring spatiotemporal surface soil moisture variations during dry seasons in central america with multisensor cascade data fusion
AU - Chen, Chi Farn
AU - Valdez, Miguel Conrado
AU - Chang, Ni Bin
AU - Chang, Li Yu
AU - Yuan, Pei Yao
N1 - Publisher Copyright:
© 2008-2012 IEEE.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - Soil moisture is a critical element in the hydrological cycle, which is intimately tied to agriculture production, ecosystem integrity, and hydrological cycle. Point measurements of soil moisture samples are laborious, costly, and inefficient. Remote sensing technologies are capable of conducting soil moisture mapping at the regional scale. The advanced microwave scanning radiometer on earth observing system (AMSR-E) provides global surface soil moisture (SSM) products with the spatial resolution of 25 km which is not sufficient enough to meet the demand for various local-scale applications. This study refines AMSR-E SSM data with normalized multiband drought index (NMDI) derived from the moderate resolution imaging spectroradiometer (MODIS) data to provide fused SSM product with finer spatial resolution that can be up to 1 km. Practical implementation of this data fusion method was carried out in Central America Isthmus region to generate the SSM maps with the spatial resolution of 1 km during the dry seasons in 2010 and 2011 for various agricultural applications. The calibration and validation of the SSM maps based on the fused images of AMSR-E and MODIS yielded satisfactory agreement with in situ ground truth data pattern wise.
AB - Soil moisture is a critical element in the hydrological cycle, which is intimately tied to agriculture production, ecosystem integrity, and hydrological cycle. Point measurements of soil moisture samples are laborious, costly, and inefficient. Remote sensing technologies are capable of conducting soil moisture mapping at the regional scale. The advanced microwave scanning radiometer on earth observing system (AMSR-E) provides global surface soil moisture (SSM) products with the spatial resolution of 25 km which is not sufficient enough to meet the demand for various local-scale applications. This study refines AMSR-E SSM data with normalized multiband drought index (NMDI) derived from the moderate resolution imaging spectroradiometer (MODIS) data to provide fused SSM product with finer spatial resolution that can be up to 1 km. Practical implementation of this data fusion method was carried out in Central America Isthmus region to generate the SSM maps with the spatial resolution of 1 km during the dry seasons in 2010 and 2011 for various agricultural applications. The calibration and validation of the SSM maps based on the fused images of AMSR-E and MODIS yielded satisfactory agreement with in situ ground truth data pattern wise.
KW - Advanced microwave scanning radiometer on 26 earth observing system (AMSR-E)
KW - leaf area index (LAI)
KW - moderate resolution imaging spectroradiometer (MODIS)
KW - normalized multiband drought index (NMDI)
KW - surface soil moisture (SSM)
UR - http://www.scopus.com/inward/record.url?scp=84920983620&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2014.2347313
DO - 10.1109/JSTARS.2014.2347313
M3 - 期刊論文
AN - SCOPUS:84920983620
SN - 1939-1404
VL - 7
SP - 4340
EP - 4355
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 11
M1 - 6899629
ER -