Vegetation canopy water content (CWC) is an important parameter for monitoring natural and agricultural ecosystems.
Previous studies focused on the observation of annual or monthly variations in CWC but lacked temporal details to study
vegetation physiological activities within a diurnal cycle. This study provides an evaluation of detecting vegetation
diurnal water stress using airborne data acquired with the MASTER instrument. Concurrent with the morning and
afternoon acquisitions of MASTER data, an extensive field campaign was conducted over almond and pistachio orchards
in southern San Joaquin Valley of California to collect CWC measurements. Statistical analysis of the field
measurements indicated a significant decrease of CWC from morning to afternoon. Field measured CWC was linearly
correlated to the normalized difference infrared index (NDII) calculated with atmospherically corrected MASTER
reflectance data using either FLAASH or empirical line (EL). Our regression analysis demonstrated that both
atmospheric corrections led to a root mean square error (RMSE) of approximately 0.035 kg/m2 for the estimation of
CWC (R2=0.42 for FLAASH images and R2=0.45 for EL images). Remote detection of the subtle decline in CWC awaits
an improved prediction of CWC. Diurnal CWC maps revealed the spatial patterns of vegetation water status in response
to variations in irrigation treatment.
We assessed the capability of AVIRIS and MODIS to estimate canopy water content. Hyperspectral water retrievals with AVIRIS data, EWT, were compared to in situ leaf water content and LAI measurements at a semi-arid site in southeastern Arizona. Retrievals of EWT showed good correlation with field canopy water content measurements. Statistical analysis also suggested that EWT was significant among seven different vegetation communities. Four MODIS indexes derived from band ratios using the reflectance product and were compared to retrievals of EWT with AVIRIS at both the semi-arid site and a temperate conifer forest. Good statistical agreements were found between AVIRIS EWT and all four MODIS indexes at the semi-arid site in savanna shrub communities. Slightly poorer correlations were found at the forest site where water indexes had better correlation to AVIRIS EWT than vegetation indexes. Temporal patterns of the four indexes in all semi-arid vegetation communities except creosote bush and agriculture show distinct seasonal variation and responded to precipitation at the savanna site. Three years of net ecosystem exchange (NEE) data from eddy covariance measurements at the forest site were compared to the time series of MODIS indexes. MODIS water indexes showed similar seasonal patterns to NEE that were strongest during the period of net carbon sequestration. In contrast, the time series of MODIS vegetation indexes did not yield a good relationship to NEE.
Conference Committee Involvement (8)
Remote Sensing and Modeling of Ecosystems for Sustainability XV
22 August 2018 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability XIV
9 August 2017 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability XIII
31 August 2016 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability XII
11 August 2015 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability XI
18 August 2014 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability X
27 August 2013 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability IX
16 August 2012 | San Diego, California, United States
Remote Sensing and Modeling of Ecosystems for Sustainability VIII
23 August 2011 | San Diego, California, United States
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