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| 001 | 820871 | ||
| 005 | 20210129224630.0 | ||
| 024 | 7 | _ | |a 10.1109/TGRS.2016.2529659 |2 doi |
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| 024 | 7 | _ | |a 0196-2892 |2 ISSN |
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| 037 | _ | _ | |a FZJ-2016-06135 |
| 082 | _ | _ | |a 550 |
| 100 | 1 | _ | |a Montzka, Carsten |0 P:(DE-Juel1)129506 |b 0 |u fzj |
| 245 | _ | _ | |a Investigation of SMAP Fusion Algorithms With Airborne Active and Passive L-Band Microwave Remote Sensing |
| 260 | _ | _ | |a New York, NY |c 2016 |b IEEE |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a The objective of the NASA Soil Moisture Active Passive (SMAP) mission is to provide global measurements of soil moisture and freeze/thaw states. SMAP integrates L-band radar and radiometer instruments as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. Airborne instruments are a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment, Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer and the active L-band system F-SAR of DLR were flown simultaneously on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e., the main land cover types and all experimental monitoring sites. Here, we used the obtained data sets as a test bed for the analysis of three active-passive fusion techniques: 1) estimation of soil moisture by passive sensor data and subsequent disaggregation by active sensor backscatter data; 2) disaggregation of passive microwave brightness temperature by active microwave backscatter and subsequent inversion to soil moisture; and 3) fusion of two single-source soil moisture products from radar and radiometer. Results indicate that the regression parameters β are dependent on the radar vegetation index. The best performance was obtained by the fusion of radiometer brightness temperatures and radar backscatter, which was able to reach the same accuracy as single-source coarse-scale radiometer soil moisture retrieval but on a higher spatial resolution. |
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| 700 | 1 | _ | |a Jagdhuber, Thomas |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Horn, Ralf |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Bogena, Heye |0 P:(DE-Juel1)129440 |b 3 |u fzj |
| 700 | 1 | _ | |a Hajnsek, Irena |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Reigber, Andreas |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Vereecken, Harry |0 P:(DE-Juel1)129549 |b 6 |u fzj |
| 773 | _ | _ | |a 10.1109/TGRS.2016.2529659 |g Vol. 54, no. 7, p. 3878 - 3889 |0 PERI:(DE-600)2027520-1 |n 7 |p 3878 - 3889 |t IEEE transactions on geoscience and remote sensing |v 54 |y 2016 |x 1558-0644 |
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