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A Weekly Indicator of Surface Moisture Status from Satellite Data for Operational Monitoring of Crop Conditions.

Authors :
Nutini F
Stroppiana D
Busetto L
Bellingeri D
Corbari C
Mancini M
Zini E
Brivio PA
Boschetti M
Source :
Sensors (Basel, Switzerland) [Sensors (Basel)] 2017 Jun 09; Vol. 17 (6). Date of Electronic Publication: 2017 Jun 09.
Publication Year :
2017

Abstract

The triangle method has been applied to derive a weekly indicator of evaporative fraction on vegetated areas in a temperate region in Northern Italy. Daily MODIS Aqua Land Surface Temperature (MYD11A1) data has been combined with air temperature maps and 8-day composite MODIS NDVI (MOD13Q1/MYD13Q1) data to estimate the Evaporative Fraction ( EF ) at 1 km resolution, on a daily basis. Measurements at two eddy covariance towers located within the study area have been exploited to assess the reliability of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator ( EF <subscript>w</subscript> ) were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EF <subscript>w</subscript> showed a temporal behavior consistent with growing cycles and agro-practices of the main crops cultivated in the study area (rice, forages and corn). Comparison with official regional corn yield data showed that variations in EF <subscript>w</subscript> cumulated over summer are related with crop production shortages induced by water scarcity. These results suggest that weekly-averaged EF estimated from MODIS data is sensible to water stress conditions and can be used as an indicator of crops' moisture conditions at agronomical district level. Advantages and disadvantages of the proposed approach to provide information useful to issue operational near real time bulletins on crop conditions at regional scale are discussed.<br />Competing Interests: The authors declare no conflict of interest.

Details

Language :
English
ISSN :
1424-8220
Volume :
17
Issue :
6
Database :
MEDLINE
Journal :
Sensors (Basel, Switzerland)
Publication Type :
Academic Journal
Accession number :
28598399
Full Text :
https://doi.org/10.3390/s17061338