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Remote Sens. 2016, 8(3), 219; doi:10.3390/rs8030219

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

1
Universidade de Brasília, Campus Universitário Darcy Ribeiro, Pós-graduação em Transportes, Anexo SG-12, 1° andar, CEP 70910-900 Brasilia, Brazil
2
Instituto Nacional de Pesquisas Espaciais (INPE), Divisão de Sensoriamento Remoto (DSR), Avenida dos Astronautas 1.758, 12227-010 São José dos Campos, Brazil
3
Universidade Federal de Pelotas—UFPel, Campus Universitário S/N, Caixa postal 354, 96001-970 Pelotas-RS, Brazil
4
Institute of Surveying, Remote Sensing and Land Information (IVFL), University of Natural Resources and Life Sciences, Vienna (BOKU), Peter Jordan Strasse 82, 1190 Vienna, Austria
5
The Boeing Company, Boeing Research and Technology Brazil, 12247-016 São José dos Campos-SP, Brazil
6
Agricultural Research and Rural Extension Company of Santa Catarina–Epagri, Santa Catarina State Information Center on Environmental and Hydrometeorological Resource-CIRAM. Rod. Admar Gonzaga, Itacorubi 1.347, Caixa Postal 502, 88034-901 Florianópolis-SC, Brazil
7
Embrapa Environment, Caixa Postal 69, 13820-000 Jaguariúna-SP, Brazil
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Richard Gloaguen and Prasad S. Thenkabail
Received: 5 November 2015 / Revised: 24 February 2016 / Accepted: 1 March 2016 / Published: 8 March 2016
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Abstract

The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information. View Full-Text
Keywords: clear sky coverage; agriculture monitoring; crop classification; MODIS clear sky coverage; agriculture monitoring; crop classification; MODIS
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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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MDPI and ACS Style

Eberhardt, I.D.R.; Schultz, B.; Rizzi, R.; Sanches, I.D.; Formaggio, A.R.; Atzberger, C.; Mello, M.P.; Immitzer, M.; Trabaquini, K.; Foschiera, W.; José Barreto Luiz, A. Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas. Remote Sens. 2016, 8, 219.

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