Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series

Meiling  Liu; Xiangnan Liu; A.K. Skidmore; Tiejun Wang

doi:10.1109/IGARSS.2018.8651434

Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series

Meiling Liu, Xiangnan Liu, A.K. Skidmore, Tiejun Wang

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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Abstract

The purpose of this study focused on integrating spectral indices with spatio-temporal characteristics to identify multistressor in crops. The experimental areas are located in Dongting Lake (DL), Hunan Province, China. Multitemporal Sentinel-2 (S2) images in 2016, 2017 were collected. Red-edge chlorophyll index (CIred-edge), rededge position (REP), normalized difference red-edge 2 (NDRE2) were calculated. The coefficients of spatiotemporal variation (CSTV) from spectral indices allowed us to discriminate crops exposed to pollution from heavy metal as well as environmental stressors. The results indicated that three indices were good indicators for identifying different environmental stressor in agriculture ecosystem. Crops under heavy metal stress remained stable with lower CSTV values, while crop ‘hot spots’ (with greater CSTV values) were affected by abrupt stressors (i.e., pest and disease, drought) at some growth stage. It concluded that spectral indices and spatio-temporal characteristics show promise for monitoring crops with various stressors.

Original language	English
Title of host publication	IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE
Pages	9335-9338
Number of pages	4
ISBN (Electronic)	978-1-5386-7150-4
DOIs	https://doi.org/10.1109/IGARSS.2018.8651434
Publication status	Published - 5 Nov 2018
Event	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018: Observing, Understanding and Forcasting the Dynamics of Our Planet - Feria Valencia Convention & Exhibition Center, Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Conference

Conference	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Abbreviated title	2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18
Internet address	https://www.igarss2018.org/

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10.1109/IGARSS.2018.8651434

Cite this

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title = "Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series",

abstract = "The purpose of this study focused on integrating spectral indices with spatio-temporal characteristics to identify multistressor in crops. The experimental areas are located in Dongting Lake (DL), Hunan Province, China. Multitemporal Sentinel-2 (S2) images in 2016, 2017 were collected. Red-edge chlorophyll index (CIred-edge), rededge position (REP), normalized difference red-edge 2 (NDRE2) were calculated. The coefficients of spatiotemporal variation (CSTV) from spectral indices allowed us to discriminate crops exposed to pollution from heavy metal as well as environmental stressors. The results indicated that three indices were good indicators for identifying different environmental stressor in agriculture ecosystem. Crops under heavy metal stress remained stable with lower CSTV values, while crop {\textquoteleft}hot spots{\textquoteright} (with greater CSTV values) were affected by abrupt stressors (i.e., pest and disease, drought) at some growth stage. It concluded that spectral indices and spatio-temporal characteristics show promise for monitoring crops with various stressors.",

author = "Meiling Liu and Xiangnan Liu and A.K. Skidmore and Tiejun Wang",

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Liu, M, Liu, X, Skidmore, AK & Wang, T 2018, Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series. in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, pp. 9335-9338, 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8651434

Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series. / Liu, Meiling ; Liu, Xiangnan; Skidmore, A.K. et al.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. p. 9335-9338.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

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T1 - Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series

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AU - Liu, Xiangnan

AU - Skidmore, A.K.

AU - Wang, Tiejun

N1 - Conference code: 38

PY - 2018/11/5

Y1 - 2018/11/5

N2 - The purpose of this study focused on integrating spectral indices with spatio-temporal characteristics to identify multistressor in crops. The experimental areas are located in Dongting Lake (DL), Hunan Province, China. Multitemporal Sentinel-2 (S2) images in 2016, 2017 were collected. Red-edge chlorophyll index (CIred-edge), rededge position (REP), normalized difference red-edge 2 (NDRE2) were calculated. The coefficients of spatiotemporal variation (CSTV) from spectral indices allowed us to discriminate crops exposed to pollution from heavy metal as well as environmental stressors. The results indicated that three indices were good indicators for identifying different environmental stressor in agriculture ecosystem. Crops under heavy metal stress remained stable with lower CSTV values, while crop ‘hot spots’ (with greater CSTV values) were affected by abrupt stressors (i.e., pest and disease, drought) at some growth stage. It concluded that spectral indices and spatio-temporal characteristics show promise for monitoring crops with various stressors.

AB - The purpose of this study focused on integrating spectral indices with spatio-temporal characteristics to identify multistressor in crops. The experimental areas are located in Dongting Lake (DL), Hunan Province, China. Multitemporal Sentinel-2 (S2) images in 2016, 2017 were collected. Red-edge chlorophyll index (CIred-edge), rededge position (REP), normalized difference red-edge 2 (NDRE2) were calculated. The coefficients of spatiotemporal variation (CSTV) from spectral indices allowed us to discriminate crops exposed to pollution from heavy metal as well as environmental stressors. The results indicated that three indices were good indicators for identifying different environmental stressor in agriculture ecosystem. Crops under heavy metal stress remained stable with lower CSTV values, while crop ‘hot spots’ (with greater CSTV values) were affected by abrupt stressors (i.e., pest and disease, drought) at some growth stage. It concluded that spectral indices and spatio-temporal characteristics show promise for monitoring crops with various stressors.

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Identifying multiple stressors in regional agro-ecosystems based on Sentinel-2 spectral indices time series

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