Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China
Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vu...
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ftmdpi:oai:mdpi.com:/2072-4292/11/13/1628/ 2023-08-20T04:04:53+02:00 Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China Jing Zhao Shengzhi Huang Qiang Huang Hao Wang Guoyong Leng Jian Peng Haixia Dong agris 2019-07-09 application/pdf https://doi.org/10.3390/rs11131628 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs11131628 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 11; Issue 13; Pages: 1628 copula-based method NDVI and precipitation/temperature change points teleconnection factors double cumulative curve method Text 2019 ftmdpi https://doi.org/10.3390/rs11131628 2023-07-31T22:25:19Z Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems. Text Arctic MDPI Open Access Publishing Arctic Pacific Remote Sensing 11 13 1628 |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
copula-based method NDVI and precipitation/temperature change points teleconnection factors double cumulative curve method |
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copula-based method NDVI and precipitation/temperature change points teleconnection factors double cumulative curve method Jing Zhao Shengzhi Huang Qiang Huang Hao Wang Guoyong Leng Jian Peng Haixia Dong Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
topic_facet |
copula-based method NDVI and precipitation/temperature change points teleconnection factors double cumulative curve method |
description |
Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems. |
format |
Text |
author |
Jing Zhao Shengzhi Huang Qiang Huang Hao Wang Guoyong Leng Jian Peng Haixia Dong |
author_facet |
Jing Zhao Shengzhi Huang Qiang Huang Hao Wang Guoyong Leng Jian Peng Haixia Dong |
author_sort |
Jing Zhao |
title |
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
title_short |
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
title_full |
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
title_fullStr |
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
title_full_unstemmed |
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China |
title_sort |
copula-based abrupt variations detection in the relationship of seasonal vegetation-climate in the jing river basin, china |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11131628 |
op_coverage |
agris |
geographic |
Arctic Pacific |
geographic_facet |
Arctic Pacific |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Remote Sensing; Volume 11; Issue 13; Pages: 1628 |
op_relation |
https://dx.doi.org/10.3390/rs11131628 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs11131628 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
13 |
container_start_page |
1628 |
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1774715306945544192 |