A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses
The soil freeze/thaw (FT) state has emerged as a critical role in the ecosystem, hydrological, and biogeochemical processes, but obtaining representative soil FT state datasets with a long time sequence, fine spatial resolution, and high accuracy remains challenging. Therefore, we propose a decision...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2024
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs16060950 https://doaj.org/article/38fdd18d079c4411b9473e23a98e0a5b |
id |
ftdoajarticles:oai:doaj.org/article:38fdd18d079c4411b9473e23a98e0a5b |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:38fdd18d079c4411b9473e23a98e0a5b 2024-09-15T18:30:11+00:00 A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses Hongjing Cui Linna Chai Heng Li Shaojie Zhao Xiaoyan Li Shaomin Liu 2024-03-01T00:00:00Z https://doi.org/10.3390/rs16060950 https://doaj.org/article/38fdd18d079c4411b9473e23a98e0a5b EN eng MDPI AG https://www.mdpi.com/2072-4292/16/6/950 https://doaj.org/toc/2072-4292 doi:10.3390/rs16060950 2072-4292 https://doaj.org/article/38fdd18d079c4411b9473e23a98e0a5b Remote Sensing, Vol 16, Iss 6, p 950 (2024) soil freeze/thaw product temporal expanding SMAP long time series spatiotemporal fusion ConvLSTM Science Q article 2024 ftdoajarticles https://doi.org/10.3390/rs16060950 2024-08-05T17:49:44Z The soil freeze/thaw (FT) state has emerged as a critical role in the ecosystem, hydrological, and biogeochemical processes, but obtaining representative soil FT state datasets with a long time sequence, fine spatial resolution, and high accuracy remains challenging. Therefore, we propose a decision-level spatiotemporal data fusion algorithm based on Convolutional Long Short-Term Memory networks (ConvLSTM) to expand the SMAP-enhanced L3 landscape freeze/thaw product (SMAP_E_FT) temporally. In the algorithm, the Freeze/Thaw Earth System Data Record product (ESDR_FT) is sucked in the ConvLSTM and fused with SMAP_E_FT at the decision level. Eight predictor datasets, i.e., soil temperature, snow depth, soil moisture, precipitation, terrain complexity index, area of open water data, latitude and longitude, are used to train the ConvLSTM. Direct validation using six dense observation networks located in the Genhe, Maqu, Naqu, Pali, Saihanba, and Shandian river shows that the fusion product (ConvLSTM_FT) effectively absorbs the high accuracy characteristics of ESDR_FT and expands SMAP_E_FT with an overall average improvement of 2.44% relative to SMAP_E_FT, especially in frozen seasons (averagely improved by 7.03%). The result from indirect validation based on categorical triple collocation also shows that ConvLSTM_FT performs stable regardless of land cover types, climate types, and terrain complexity. The findings, drawn from preliminary analyses on ConvLSTM_FT from 1980 to 2020 over China, suggest that with global warming, most parts of China suffer from different degrees of shortening of the frozen period. Moreover, in the Qinghai–Tibet region, the higher the permafrost thermal stability, the faster the degradation rate. Article in Journal/Newspaper permafrost Directory of Open Access Journals: DOAJ Articles Remote Sensing 16 6 950 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
soil freeze/thaw product temporal expanding SMAP long time series spatiotemporal fusion ConvLSTM Science Q |
spellingShingle |
soil freeze/thaw product temporal expanding SMAP long time series spatiotemporal fusion ConvLSTM Science Q Hongjing Cui Linna Chai Heng Li Shaojie Zhao Xiaoyan Li Shaomin Liu A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
topic_facet |
soil freeze/thaw product temporal expanding SMAP long time series spatiotemporal fusion ConvLSTM Science Q |
description |
The soil freeze/thaw (FT) state has emerged as a critical role in the ecosystem, hydrological, and biogeochemical processes, but obtaining representative soil FT state datasets with a long time sequence, fine spatial resolution, and high accuracy remains challenging. Therefore, we propose a decision-level spatiotemporal data fusion algorithm based on Convolutional Long Short-Term Memory networks (ConvLSTM) to expand the SMAP-enhanced L3 landscape freeze/thaw product (SMAP_E_FT) temporally. In the algorithm, the Freeze/Thaw Earth System Data Record product (ESDR_FT) is sucked in the ConvLSTM and fused with SMAP_E_FT at the decision level. Eight predictor datasets, i.e., soil temperature, snow depth, soil moisture, precipitation, terrain complexity index, area of open water data, latitude and longitude, are used to train the ConvLSTM. Direct validation using six dense observation networks located in the Genhe, Maqu, Naqu, Pali, Saihanba, and Shandian river shows that the fusion product (ConvLSTM_FT) effectively absorbs the high accuracy characteristics of ESDR_FT and expands SMAP_E_FT with an overall average improvement of 2.44% relative to SMAP_E_FT, especially in frozen seasons (averagely improved by 7.03%). The result from indirect validation based on categorical triple collocation also shows that ConvLSTM_FT performs stable regardless of land cover types, climate types, and terrain complexity. The findings, drawn from preliminary analyses on ConvLSTM_FT from 1980 to 2020 over China, suggest that with global warming, most parts of China suffer from different degrees of shortening of the frozen period. Moreover, in the Qinghai–Tibet region, the higher the permafrost thermal stability, the faster the degradation rate. |
format |
Article in Journal/Newspaper |
author |
Hongjing Cui Linna Chai Heng Li Shaojie Zhao Xiaoyan Li Shaomin Liu |
author_facet |
Hongjing Cui Linna Chai Heng Li Shaojie Zhao Xiaoyan Li Shaomin Liu |
author_sort |
Hongjing Cui |
title |
A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
title_short |
A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
title_full |
A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
title_fullStr |
A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
title_full_unstemmed |
A Spatiotemporal Enhanced SMAP Freeze/Thaw Product (1980–2020) over China and Its Preliminary Analyses |
title_sort |
spatiotemporal enhanced smap freeze/thaw product (1980–2020) over china and its preliminary analyses |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/rs16060950 https://doaj.org/article/38fdd18d079c4411b9473e23a98e0a5b |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Remote Sensing, Vol 16, Iss 6, p 950 (2024) |
op_relation |
https://www.mdpi.com/2072-4292/16/6/950 https://doaj.org/toc/2072-4292 doi:10.3390/rs16060950 2072-4292 https://doaj.org/article/38fdd18d079c4411b9473e23a98e0a5b |
op_doi |
https://doi.org/10.3390/rs16060950 |
container_title |
Remote Sensing |
container_volume |
16 |
container_issue |
6 |
container_start_page |
950 |
_version_ |
1810471656625274880 |