Crop Monitoring Based on SPOT-5 Take-5 and Sentinel-1A Data for the Estimation of Crop Water Requirements

Remote Sens. 2016, 8(6), 525; doi:10.3390/rs8060525

Author

Ana Navarro ^1,* , João Rolim ²

, Irina Miguel ³

, João Catalão ¹

, Joel Silva ⁴

, Marco Painho ⁴

 and Zoltán Vekerdy ⁵

¹

IDL, Departamento de Engenharia Geográfica, Geofísica e Energia, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal

²

LEAF, Departamento de Ciências e Engenharia de Biossistemas, Instituto Superior de Agronomia, Universidade de Lisboa, 1349-017 Lisboa, Portugal

³

Departamento de Geologia, Faculdade de Ciências, Universidade Agostinho Neto, 1231 Luanda, Angola

⁴

NOVA IMS, Information Management School, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal

⁵

ITC, Department of Water Resources, Faculty of Geo-information Science and Earth Observation, University of Twente, P.O. Box 6, 7500 AA Enschede, The Netherlands

^*

Author to whom correspondence should be addressed. 

Academic Editors: Zhongbo Su, Yijian Zeng, Clement Atzberger and Prasad S. Thenkabail

Received: 31 March 2016 / Revised: 3 June 2016 / Accepted: 14 June 2016 / Published: 22 June 2016

(This article belongs to the Special Issue Land Surface Processes and Interactions—From HCMM to Sentinel Missions and beyond)

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Abstract 

Optical and microwave images have been combined for land cover monitoring in different agriculture scenarios, providing useful information on qualitative and quantitative land cover changes. This study aims to assess the complementarity and interoperability of optical (SPOT-5 Take-5) and synthetic aperture radar (SAR) (Sentinel-1A) data for crop parameter (basal crop coefficient (K_cb) values and the length of the crop’s development stages) retrieval and crop type classification, with a focus on crop water requirements, for an irrigation perimeter in Angola. SPOT-5 Take-5 images are used as a proxy of Sentinel-2 data to evaluate the potential of their enhanced temporal resolution for agricultural applications. In situ data are also used to complement the Earth Observation (EO) data. The Normalized Difference Vegetation Index (NDVI) and dual (VV + VH) polarization backscattering time series are used to compute the K_cb curve for four crop types (maize, soybean, bean and pasture) and to estimate the length of each phenological growth stage. The K_cb values are then used to compute the crop’s evapotranspiration and to subsequently estimate the crop irrigation requirements based on a soil water balance model. A significant R² correlation between NDVI and backscatter time series was observed for all crops, demonstrating that optical data can be replaced by microwave data in the presence of cloud cover. However, it was not possible to properly identify each stage of the crop cycle due to the lack of EO data for the complete growing season. View Full-Text

Keywords: agriculture;  land cover change;  SPOT-5 Take-5;  Sentinel-1A;  evapotranspiration;  TIGER initiative

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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