English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Frequent cloud cover leads to significant problems in estimating snow distribution based on remote-sensing observations, especially in mountainous regions. Supported by Google Earth Engine (GEE), a cloud-gap filling framework using the cubic spline interpolation method was proposed to generate cloud-free data based on the MODIS snow cover dataset. The framework is validated in the Chinese Tien Shan region with in-site snow depth observations, demonstrating good agreement. Subsequently, the spatio-temporal patterns and trends of snow cover in Chinese Tien Shan for nearly 20 years were identified using temporal interpolated snow cover data. The results show that (1) the interpolated images generated by the framework effectively fill the invalid value caused by cloud cover and have significant consistency with the snow depth data from gauges (with the Snow Cover Days (SCD) score of 0.89 and the correlation coefficient (CC) of 0.80); (2) compared with linear interpolation, the interpolated snow cover images generated based on cubic spline method have higher CC with snow depth data from gauges, reflecting higher data reliability; and (3) the snow cover over Chinese Tien Shan demonstrated remarkable periodicity and different spatial distribution, and it had an apparent decreasing trend in the southeastern region of Chinese Tien Shan.

Spatio-temporal patterns of snow cover in the Tien Shan, China from 2000 to 2019 based on cloud-free data supported by Google Earth Engine