Dynamic spatial fusion of cloud top phase from PARASOL, CALIPSO, cloudsat satellite data

Chen, Zhenting; Sun, Xiaobing

doi:10.1016/j.jqsrt.2018.11.010

Cited by 3 publications

(1 citation statement)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Random Forest classification algorithm has the advantages of no worry about over-fitting, suitable for large data sets and a large number of unknown features, autonomous estimation of optimal feature sets, direct processing of high-dimensional feature input samples without dimensionality reduction, strong resistance to fabrication, easy to understand the algorithm content and the possibility of merging processing, etc. [17,18].…”

Section: Random Forestmentioning

confidence: 99%

A Study of Forest Swamp Mapping in Hani Wetland Integrating Sentinel-1 and Sentinel-2 Satellite Images

Wang

2021

Proceedings of CECNet 2021

View full text Add to dashboard Cite

As a unique wetland type, forest swamps play an important role in regional carbon cycling and biodiversity conservation. Taking Hani wetland in Jilin province as the research object, we integrated the application of Sentinel-1 radar and Sentinel-2 multispectral images, fully exploited the potential of Sentinel-1 multi-polarization band features and Sentinel-2 red edge index for forest swamp remote sensing identification, and applied the random forest method to realize the extraction of forest swamp distribution information of Hani wetland. The results show that when the optimal number of decision trees for forest swamp information extraction is 1200, the fusion of Sentinel-1VV and VH backscattering coefficient radar band features and Sentinel-2 red-edge band features can significantly improve the extraction accuracy of forest swamp distribution information, and the overall accuracy and Kappa coefficient of forest swamp information extraction in protected areas are as high as 89% and 0.85, respectively. The overall accuracy and Kappa coefficient of forest swamp information extraction in the protected area were 89% and 0.85, respectively. The landscape types of Hani Wetlands of International Importance are diversified, with natural wetlands, artificial wetlands and non-wetland landscape types co-existing. Among the natural wetland types, the forest swamp has the largest area of 27.1 km2, accounting for 11.2% of the total area of the reserve; the river has the smallest area of 0.7 km2, accounting for 0.3% of the total area of the reserve. The forest swamp extraction method provides data support for the sustainable management of Hani wetlands and case guidance for forest swamp mapping in other regions.

show abstract

Section: Random Forestmentioning

confidence: 99%

A Study of Forest Swamp Mapping in Hani Wetland Integrating Sentinel-1 and Sentinel-2 Satellite Images

Wang

2021

Proceedings of CECNet 2021

View full text Add to dashboard Cite

show abstract

Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm

Hu¹,

Zhu²,

Lu³

et al. 2021

Atmospheric Research

View full text Add to dashboard Cite

Dynamic Spatial Fusion of Cloud Vertical Phase from CALIPSO and CloudSat Satellite Data

Chen¹,

Wang²,

Gao³

et al. 2021

photogramm eng remote sensing

View full text Add to dashboard Cite

Cloud phase is a core parameter of inversion of cloud characteristics. The accuracy of cloud phase affects the results of cloud optical and microphysical characteristics. In this study, we obtain the cloud vertical phase (CVP ) products of CALIPSO and CloudSat satellites, then we put forward a dynamic spatial fusion algorithm for the fusion of the two products. A series of spatial optimal CVP fusion rules are presented for dual-source data, and we realize CVP fusion using these rules. We took Typhoon Lupit in the Pacific Ocean as an experimental object. The results show that the total cloud pixel amount increased by 124.09% and 10.54%, respectively, compared to those of CALIPSO and CloudSat. The recognition of different CVP is 7.97% and 1.37%. The results show that this method can improve the accuracy of multi-source CVP inversion effectively, and provide new ways for the synergy of multi-sensor satellites.

show abstract

Dynamic spatial fusion of cloud top phase from PARASOL, CALIPSO, cloudsat satellite data

Cited by 3 publications

References 28 publications

A Study of Forest Swamp Mapping in Hani Wetland Integrating Sentinel-1 and Sentinel-2 Satellite Images

A Study of Forest Swamp Mapping in Hani Wetland Integrating Sentinel-1 and Sentinel-2 Satellite Images

Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm

Dynamic Spatial Fusion of Cloud Vertical Phase from CALIPSO and CloudSat Satellite Data

Contact Info

Product

Resources

About