Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model
Accurate cropland burned area estimation is crucial for air quality modeling and cropland management. However, current global burned area products have been primarily derived from coarse spatial resolution images which cannot fulfill the spatial requirement for fire monitoring at local levels. In ad...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/24/5131 |
| _version_ | 1827669864738717696 |
|---|---|
| author | Jinxiu Liu Du Wang Eduardo Eiji Maeda Petri K. E. Pellikka Janne Heiskanen |
| author_facet | Jinxiu Liu Du Wang Eduardo Eiji Maeda Petri K. E. Pellikka Janne Heiskanen |
| author_sort | Jinxiu Liu |
| collection | DOAJ |
| description | Accurate cropland burned area estimation is crucial for air quality modeling and cropland management. However, current global burned area products have been primarily derived from coarse spatial resolution images which cannot fulfill the spatial requirement for fire monitoring at local levels. In addition, there is an overall lack of accurate cropland straw burning identification approaches at high temporal and spatial resolution. In this study, we propose a novel algorithm to capture burned area in croplands using dense Landsat time series image stacks. Cropland burning shows a short-term seasonal variation and a long-term dynamic trend, so a multi-harmonic model is applied to characterize fire dynamics in cropland areas. By assessing a time series of the Burned Area Index (BAI), our algorithm detects all potential burned areas in croplands. A land cover mask is used on the primary burned area map to remove false detections, and the spatial information with a moving window based on a majority vote is employed to further reduce salt-and-pepper noise and improve the mapping accuracy. Compared with the accuracy of 67.3% of MODIS products and that of 68.5% of Global Annual Burned Area Map (GABAM) products, a superior overall accuracy of 92.9% was obtained by our algorithm using Landsat time series and multi-harmonic model. Our approach represents a flexible and robust way of detecting straw burning in complex agriculture landscapes. In future studies, the effectiveness of combining different spectral indices and satellite images can be further investigated. |
| first_indexed | 2024-03-10T03:12:03Z |
| format | Article |
| id | doaj.art-dfa4ad16d98c447fac51275a526edc26 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:12:03Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-dfa4ad16d98c447fac51275a526edc262023-11-23T10:25:14ZengMDPI AGRemote Sensing2072-42922021-12-011324513110.3390/rs13245131Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic ModelJinxiu Liu0Du Wang1Eduardo Eiji Maeda2Petri K. E. Pellikka3Janne Heiskanen4School of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Biological Sciences, Faculty of Science, University of Hong Kong, Hong Kong SAR, ChinaDepartment of Geosciences and Geography, University of Helsinki, P.O. Box 68, 00014 Helsinki, FinlandDepartment of Geosciences and Geography, University of Helsinki, P.O. Box 68, 00014 Helsinki, FinlandAccurate cropland burned area estimation is crucial for air quality modeling and cropland management. However, current global burned area products have been primarily derived from coarse spatial resolution images which cannot fulfill the spatial requirement for fire monitoring at local levels. In addition, there is an overall lack of accurate cropland straw burning identification approaches at high temporal and spatial resolution. In this study, we propose a novel algorithm to capture burned area in croplands using dense Landsat time series image stacks. Cropland burning shows a short-term seasonal variation and a long-term dynamic trend, so a multi-harmonic model is applied to characterize fire dynamics in cropland areas. By assessing a time series of the Burned Area Index (BAI), our algorithm detects all potential burned areas in croplands. A land cover mask is used on the primary burned area map to remove false detections, and the spatial information with a moving window based on a majority vote is employed to further reduce salt-and-pepper noise and improve the mapping accuracy. Compared with the accuracy of 67.3% of MODIS products and that of 68.5% of Global Annual Burned Area Map (GABAM) products, a superior overall accuracy of 92.9% was obtained by our algorithm using Landsat time series and multi-harmonic model. Our approach represents a flexible and robust way of detecting straw burning in complex agriculture landscapes. In future studies, the effectiveness of combining different spectral indices and satellite images can be further investigated.https://www.mdpi.com/2072-4292/13/24/5131cropland burned areaLandsat time seriesmulti-harmonic modelspatial information |
| spellingShingle | Jinxiu Liu Du Wang Eduardo Eiji Maeda Petri K. E. Pellikka Janne Heiskanen Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model Remote Sensing cropland burned area Landsat time series multi-harmonic model spatial information |
| title | Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model |
| title_full | Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model |
| title_fullStr | Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model |
| title_full_unstemmed | Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model |
| title_short | Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model |
| title_sort | mapping cropland burned area in northeastern china by integrating landsat time series and multi harmonic model |
| topic | cropland burned area Landsat time series multi-harmonic model spatial information |
| url | https://www.mdpi.com/2072-4292/13/24/5131 |
| work_keys_str_mv | AT jinxiuliu mappingcroplandburnedareainnortheasternchinabyintegratinglandsattimeseriesandmultiharmonicmodel AT duwang mappingcroplandburnedareainnortheasternchinabyintegratinglandsattimeseriesandmultiharmonicmodel AT eduardoeijimaeda mappingcroplandburnedareainnortheasternchinabyintegratinglandsattimeseriesandmultiharmonicmodel AT petrikepellikka mappingcroplandburnedareainnortheasternchinabyintegratinglandsattimeseriesandmultiharmonicmodel AT janneheiskanen mappingcroplandburnedareainnortheasternchinabyintegratinglandsattimeseriesandmultiharmonicmodel |