Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data
We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing sea...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/4/806 |
| _version_ | 1797395580423503872 |
|---|---|
| author | Liming He Rong Wang Georgy Mostovoy Jane Liu Jing M. Chen Jiali Shang Jiangui Liu Heather McNairn Jarrett Powers |
| author_facet | Liming He Rong Wang Georgy Mostovoy Jane Liu Jing M. Chen Jiali Shang Jiangui Liu Heather McNairn Jarrett Powers |
| author_sort | Liming He |
| collection | DOAJ |
| description | We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types. |
| first_indexed | 2024-03-09T00:37:34Z |
| format | Article |
| id | doaj.art-811878fa429c405e85ec681f90135c47 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T00:37:34Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-811878fa429c405e85ec681f90135c472023-12-11T18:02:47ZengMDPI AGRemote Sensing2072-42922021-02-0113480610.3390/rs13040806Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 DataLiming He0Rong Wang1Georgy Mostovoy2Jane Liu3Jing M. Chen4Jiali Shang5Jiangui Liu6Heather McNairn7Jarrett Powers8Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, CanadaDepartment of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, CanadaLaboratory of Environmental Model and Data Optima, Laurel, MD 20707, USADepartment of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, CanadaDepartment of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, CanadaOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6AAFC, CanadaOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6AAFC, CanadaOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6AAFC, CanadaScience and Technology Branch, Agriculture and Agri-Food Canada, Winnipeg, MB R3C 3G7, CanadaWe evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types.https://www.mdpi.com/2072-4292/13/4/806Sentinel-2cropbiomassmappingremote sensingManitoba |
| spellingShingle | Liming He Rong Wang Georgy Mostovoy Jane Liu Jing M. Chen Jiali Shang Jiangui Liu Heather McNairn Jarrett Powers Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data Remote Sensing Sentinel-2 crop biomass mapping remote sensing Manitoba |
| title | Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data |
| title_full | Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data |
| title_fullStr | Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data |
| title_full_unstemmed | Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data |
| title_short | Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data |
| title_sort | crop biomass mapping based on ecosystem modeling at regional scale using high resolution sentinel 2 data |
| topic | Sentinel-2 crop biomass mapping remote sensing Manitoba |
| url | https://www.mdpi.com/2072-4292/13/4/806 |
| work_keys_str_mv | AT liminghe cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT rongwang cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT georgymostovoy cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT janeliu cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT jingmchen cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT jialishang cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT jianguiliu cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT heathermcnairn cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data AT jarrettpowers cropbiomassmappingbasedonecosystemmodelingatregionalscaleusinghighresolutionsentinel2data |