This study improves the understanding of the LSWT variations in Mongolian lakes in response to global climate change.

2022. "Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data". United States.

We applied an effective spatiotemporal gap-filled method to improve the LSWT from MODIS.•The long-term variations of the annual and seasonal mean LSWTs of ...

Nov 3, 2022 · Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data.

Bibliographic details on Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS ...

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data · List of references.

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data.

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data. Chenyu Fan ...

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data. Article. Full-text ...

11 Nov 2022. Save. Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data.