Cloud detection and removal is a well-known critical issue for land remote sensing in the optical domain. Despite the vast literature on the subject, uncertainties still remain on the used cloud detection approaches that can have significant impact for a wide range of applications.
In the case of Proba-V cloud detection is particularly challenging, considering the limited number of spectral bands (Blue, Red, NIR and SWIR) and the lack of TIR channels or dedicated cirrus band (as the 1.38 micron band). The legacy approach for Proba-V cloud detection was inherited from SPOT-VGT [RD-1] and based on static thresholds on the Blue and SWIR channels. The main drawback of such threshold method is that its performances are strongly dependent on the amount of contrast in radiometry between the clouds and the underlying surface.
Recent improvements were proposed for both SPOT-VGT [RD-2] and Proba-V [RD-3], using climatology of reflectances to define a dynamic threshold on the Blue band, which depends on the surface cover and on vegetation conditions. Additional improvements could be obtained using statistically-sound approaches, such as Neural Network, allowing to optimally use all the information from the four Proba-V channels.
In order to inter-compare the performances of different cloud detection algorithms for Proba-V, ESA and the Belgian Science Policy Office (BELSPO) decided to organise a dedicated Round Robin exercise.
This Proba-V Cloud Detection Round Robin (PV-CDRR) will be open to any interested algorithm provider. The main goal is to learn advantages and drawbacks of the different approaches for various cloud and surface conditions. As an outcome of the study recommendations will be provided to ESA on the potential new cloud detection algorithm for the operational processing chain.
The PV-CDRR project is part of the Instrument Characterisation and Algorithm Studies. Maintenance and improvements of instrument characterisation and algorithm definition are crucial activities to guarantee that the requirements formulated in the Mission Requirement Document. These activities are nominally managed within the Quality Working Group (QWG), though some complementary studies are funded by ESA for supporting ad-hoc recalibration and reprocessing campaigns as well as for developing advanced scientific processors and innovative geophysical products.
[RD-1] Lisens, G., P. Kempeneers, F. Fierens, and J. Van Rensbergen. Development of Cloud, Snow, and Shadow Masking Algorithms for VEGETATION Imagery. Proceedings of Geoscience and Remote Sensing Symposium, IGARSS 2000, Honolulu, HI 2: 834–836.
[RD-2] Wolters, E., Swinnen, E., I. Benhadj, Dierckx, W., PROBA-V cloud detection evaluation and proposed modification, QWG Technical Note, 17/7/2015
[RD-3] Hagolle, O., et al. Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 and 2 images. Remote Sensing of Environment 94.2 (2005): 172-186.
Round Robin Registration
The benefits in participating in the Proba-V Cloud Detection Round Robin include:
- The opportunity of considering your algorithm for implementation in the future Proba-V operational processing chain and to be considered for other ESA optical missions
- The opportunity to be a co-author on a peer-reviewed paper summarising the outcomes of the Round Robin exercise
- The opportunity to compare your cloud detection algorithm with other leading algorithms and identify strengths and weaknesses. Results of the inter-comparison will be discussed in a dedicated workshop in ESRIN and summarised in a final report
- Contribution to reducing one of the largest sources of uncertainty in remote sensing of land geophysical parameters
Note that a dedicated fixed price reward is allocated to each participant, allowing to cover the effort spent for algorithm development, testing and running. Access to the reward is granted to each participant upon contribution to the Round Robin with an original algorithm and provision of the required deliverables.
As a participant in the PV-CDRR you are committing to the following:
- Providing a cloud mask generated using your algorithm for each of the selection scenes (details on the round robin process and data submission format will be provided in the Round Robin Protocols). Data must be provided in the specified format and by the submission deadline.
- Providing a description of your cloud-clearing algorithm including reference to peer-reviewed documents where available. The size and nature of both static and dynamic auxiliary files used should be stated along with the main steps of the algorithm indicating where significant processing is required or external models are used.
- Providing a Technical Note on the Computing Resource required by your software and the potential for further development of the algorithm used in the round robin submission with focus on operational implementation in the Ground Segment processing chain.
- Registering my intent to participate using the form below.
Note that the working environment will be provided by ESA, through the RSS Cloud Toolbox service. Thanks to this tool, the participant will have access to a remote virtual machine with all needed input data, some relevant tools and the required computing resources, the virtual machine can be tailored to the user needs in terms of available SW, as well as CPU and RAM.
Algorithm providers, register to the Round Robin.
Please provide in the Registration Form your users name, email and affiliation, as well as information on the type of algorithm you are going to use for cloud detection, e.g., Neural Network, Bayesian.
If you have any questions about this project, contact:
Address: ESA/ESRIN, Via Galileo Galilei, 00044 Frascati, Italy Tel: +39-06-941-88387
Rosario Quirino Iannone
Address: Serco S.p.A., 00044 Frascati (RM), Italy
Tel:+39 06-98354 473
Organisation: Serco S.p.A.
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