Agriculture is an important economic sector in China, employing over 300 million of farmers. During the last two decades, scientific literature focusing on agricultural applications of Synthetic Aperture Radar (SAR) has shown great developments and promising results in mapping crop cultivation and monitoring crop growth, providing valuable information in a timely and reliable fashion. During our work, we investigated the capabilities of X-band SAR data, and in particular of COSMO-SkyMed (CSK), in providing reliable and physically based information on different features two globally spread summer crops, maize and rice. To this aim, 22 COSMO-SkyMed Stripmap PingPong HH-VV pol. descending pass. scenes have been programmed and acquired from June to September 2016 on two Chinese test sites: Baima lake farm (33°24' N, 119°06' E), located in Jiangsu province and typically cultivated with a succession of winter wheat and paddy rice, and Yixian county (39°16' N, 115°36' E), located in Hebei province and typically cultivated with a succession of winter wheat and maize. In situ measurement campaigns were conducted in both areas for collecting data on morphological (leaf area index, biomass) and phenological parameters of maize and rice fields. Crop parameters collected in situ were used for assessing CSK temporal copular backscatter evolution during the growing season of monitored crops. Results show a good sensitivity of X-band backscatter in HH, VV and in the polarizations and HH/VV ratio to vegetation growth. This is especially evident during the early crop phenological stages, due to the weak X-band microwave penetration in dense vegetation layer. This experiment demonstrates with reference to actual crop morphology and phenology measured on the field that multi-temporal series of dual pol. backscatter from COSMO-SkyMed Stripmap PingPong data could be exploited for rice and maize crop monitoring.

COSMO-BIOPAR: MULTITEMPORAL MONITORING OF MAIZE AND RICE GROWTH USING X-BAND COSMO-SKYMED BACKSCATTER

Paolo Villa;Giacomo Fontanelli
2017

Abstract

Agriculture is an important economic sector in China, employing over 300 million of farmers. During the last two decades, scientific literature focusing on agricultural applications of Synthetic Aperture Radar (SAR) has shown great developments and promising results in mapping crop cultivation and monitoring crop growth, providing valuable information in a timely and reliable fashion. During our work, we investigated the capabilities of X-band SAR data, and in particular of COSMO-SkyMed (CSK), in providing reliable and physically based information on different features two globally spread summer crops, maize and rice. To this aim, 22 COSMO-SkyMed Stripmap PingPong HH-VV pol. descending pass. scenes have been programmed and acquired from June to September 2016 on two Chinese test sites: Baima lake farm (33°24' N, 119°06' E), located in Jiangsu province and typically cultivated with a succession of winter wheat and paddy rice, and Yixian county (39°16' N, 115°36' E), located in Hebei province and typically cultivated with a succession of winter wheat and maize. In situ measurement campaigns were conducted in both areas for collecting data on morphological (leaf area index, biomass) and phenological parameters of maize and rice fields. Crop parameters collected in situ were used for assessing CSK temporal copular backscatter evolution during the growing season of monitored crops. Results show a good sensitivity of X-band backscatter in HH, VV and in the polarizations and HH/VV ratio to vegetation growth. This is especially evident during the early crop phenological stages, due to the weak X-band microwave penetration in dense vegetation layer. This experiment demonstrates with reference to actual crop morphology and phenology measured on the field that multi-temporal series of dual pol. backscatter from COSMO-SkyMed Stripmap PingPong data could be exploited for rice and maize crop monitoring.
2017
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
Maize
COSMO-SkyMed
Rice
Crop monitoring
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/338187
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