Segment-based fusion of multi-sensor multi-scale satellite soil moisture retrievals

• URL: http://arxiv.org/abs/2211.15938v1
• Date: Tue, 29 Nov 2022 05:23:33 GMT
• Title: Segment-based fusion of multi-sensor multi-scale satellite soil moisture retrievals
• Authors: Reza Attarzadeh, Hossein Bagheri, Iman Khosravi, Saeid Niazmardi, Davood Akbarid
• Abstract summary: This paper proposes a segment-based image fusion framework to evaluate the possibility of preparing a multi-scale soil moisture map. The proposed methodology was able to improve soil moisture estimation in different scales up to 20% better compared to pixel-based fusion approach.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Synergetic use of sensors for soil moisture retrieval is attracting considerable interest due to the different advantages of different sensors. Active, passive, and optic data integration could be a comprehensive solution for exploiting the advantages of different sensors aimed at preparing soil moisture maps. Typically, pixel-based methods are used for multi-sensor fusion. Since, different applications need different scales of soil moisture maps, pixel-based approaches are limited for this purpose. Object-based image analysis employing an image object instead of a pixel could help us to meet this need. This paper proposes a segment-based image fusion framework to evaluate the possibility of preparing a multi-scale soil moisture map through integrated Sentinel-1, Sentinel-2, and Soil Moisture Active Passive (SMAP) data. The results confirmed that the proposed methodology was able to improve soil moisture estimation in different scales up to 20% better compared to pixel-based fusion approach.

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