Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine
The Tibetan Plateau (TP), known as “The Roof of World”, has expansive alpine grasslands and is a hotspot for climate change studies. However, cropland expansion and increasing anthropogenic activities have been poorly documented, let alone the effects of agricultural activities on food security and...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/12/2289 |
| _version_ | 1797530487931011072 |
|---|---|
| author | Yuanyuan Di Geli Zhang Nanshan You Tong Yang Qiang Zhang Ruoqi Liu Russell B. Doughty Yangjian Zhang |
| author_facet | Yuanyuan Di Geli Zhang Nanshan You Tong Yang Qiang Zhang Ruoqi Liu Russell B. Doughty Yangjian Zhang |
| author_sort | Yuanyuan Di |
| collection | DOAJ |
| description | The Tibetan Plateau (TP), known as “The Roof of World”, has expansive alpine grasslands and is a hotspot for climate change studies. However, cropland expansion and increasing anthropogenic activities have been poorly documented, let alone the effects of agricultural activities on food security and environmental change in the TP. The existing cropland mapping products do not depict the spatiotemporal characteristics of the TP due to low accuracies and inconsistent cropland distribution, which is affected by complicated topography and impedes our understanding of cropland expansion and its associated environmental impacts. One of the biggest challenges of cropland mapping in the TP is the diverse crop phenology across a wide range of elevations. To decrease the classification errors due to elevational differences in crop phenology, we developed two pixel- and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth Engine platform along the Brahmaputra River and its two tributaries (BRTT) in the Tibet Autonomous Region, also known as the granary of TP, in 2015–2019. Our first phenology-based cropland mapping algorithm (PCM1) used different thresholds of land surface water index (LSWI) by considering varied crop phenology along different elevations. The second algorithm (PCM2) further offsets the phenological discrepancy along elevational gradients by considering the length and peak of the growing season. We found that PCM2 had a higher accuracy with fewer images compared with PCM1. The number of images for PCM2 was 279 less than PCM1, and the Matthews correlation coefficient for PCM2 was 0.036 higher than PCM1. We also found that the cropland area in BRTT was estimated to be 1979 ± 52 km<sup>2</sup> in the late 2010s. Croplands were mainly distributed in the BRTT basins with elevations of 3800–4000 m asl. Our phenology-based methods were effective for mapping croplands in mountainous areas. The spatially explicit information on cropland area and distribution in the TP aid future research into the effects of cropland expansion on food security and environmental change in the TP. |
| first_indexed | 2024-03-10T10:30:43Z |
| format | Article |
| id | doaj.art-d7e57c742db6499abdc03b5369d80809 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:30:43Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d7e57c742db6499abdc03b5369d808092023-11-21T23:44:09ZengMDPI AGRemote Sensing2072-42922021-06-011312228910.3390/rs13122289Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth EngineYuanyuan Di0Geli Zhang1Nanshan You2Tong Yang3Qiang Zhang4Ruoqi Liu5Russell B. Doughty6Yangjian Zhang7College of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaDivision of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USAKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThe Tibetan Plateau (TP), known as “The Roof of World”, has expansive alpine grasslands and is a hotspot for climate change studies. However, cropland expansion and increasing anthropogenic activities have been poorly documented, let alone the effects of agricultural activities on food security and environmental change in the TP. The existing cropland mapping products do not depict the spatiotemporal characteristics of the TP due to low accuracies and inconsistent cropland distribution, which is affected by complicated topography and impedes our understanding of cropland expansion and its associated environmental impacts. One of the biggest challenges of cropland mapping in the TP is the diverse crop phenology across a wide range of elevations. To decrease the classification errors due to elevational differences in crop phenology, we developed two pixel- and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth Engine platform along the Brahmaputra River and its two tributaries (BRTT) in the Tibet Autonomous Region, also known as the granary of TP, in 2015–2019. Our first phenology-based cropland mapping algorithm (PCM1) used different thresholds of land surface water index (LSWI) by considering varied crop phenology along different elevations. The second algorithm (PCM2) further offsets the phenological discrepancy along elevational gradients by considering the length and peak of the growing season. We found that PCM2 had a higher accuracy with fewer images compared with PCM1. The number of images for PCM2 was 279 less than PCM1, and the Matthews correlation coefficient for PCM2 was 0.036 higher than PCM1. We also found that the cropland area in BRTT was estimated to be 1979 ± 52 km<sup>2</sup> in the late 2010s. Croplands were mainly distributed in the BRTT basins with elevations of 3800–4000 m asl. Our phenology-based methods were effective for mapping croplands in mountainous areas. The spatially explicit information on cropland area and distribution in the TP aid future research into the effects of cropland expansion on food security and environmental change in the TP.https://www.mdpi.com/2072-4292/13/12/2289croplandTibetan Plateaupixel- and phenology-based algorithmGoogle Earth EngineLandsat |
| spellingShingle | Yuanyuan Di Geli Zhang Nanshan You Tong Yang Qiang Zhang Ruoqi Liu Russell B. Doughty Yangjian Zhang Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine Remote Sensing cropland Tibetan Plateau pixel- and phenology-based algorithm Google Earth Engine Landsat |
| title | Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine |
| title_full | Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine |
| title_fullStr | Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine |
| title_full_unstemmed | Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine |
| title_short | Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine |
| title_sort | mapping croplands in the granary of the tibetan plateau using all available landsat imagery a phenology based approach and google earth engine |
| topic | cropland Tibetan Plateau pixel- and phenology-based algorithm Google Earth Engine Landsat |
| url | https://www.mdpi.com/2072-4292/13/12/2289 |
| work_keys_str_mv | AT yuanyuandi mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT gelizhang mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT nanshanyou mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT tongyang mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT qiangzhang mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT ruoqiliu mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT russellbdoughty mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine AT yangjianzhang mappingcroplandsinthegranaryofthetibetanplateauusingallavailablelandsatimageryaphenologybasedapproachandgoogleearthengine |