Time Tracking of Different Cropping Patterns Using Landsat Images under Different Agricultural Systems during 1990–2050 in Cold China
| dc.contributor.author | Pan, Tao | |
| dc.contributor.author | Zhang, Chi | |
| dc.contributor.author | Kuang, Wenhui | |
| dc.contributor.author | De Maeyer, Philippe | |
| dc.contributor.author | Kurban, Alishir | |
| dc.contributor.author | Hamdi, Rafiq | |
| dc.contributor.author | Du, Guoming | |
| dc.date | 2018-12-01 | |
| dc.date.accessioned | 2019-05-16T09:44:22Z | |
| dc.date.available | 2019-05-16T09:44:22Z | |
| dc.identifier.citation | Pan, T.; Zhang, C.; Kuang, W.; De Maeyer, P.; Kurban, A.; Hamdi, R.; Du, G. Time Tracking of Different Cropping Patterns Using Landsat Images under Different Agricultural Systems during 1990–2050 in Cold China. Remote Sens. 2018, 10, 2011. | en_US |
| dc.identifier.uri | https://orfeo.belnet.be/handle/internal/7261 | |
| dc.description | Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and associated environmental effects. The Cold China contains different agricultural systems (state and private farming), and such systems could lead to different cropping patterns. So far, such changes have not been revealed yet. Based on the Landsat images, this study tracked cropping information in five-year increments (1990–1995, 1995–2000, 2000–2005, 2005–2010, and 2010–2015) and predicted future patterns for the period of 2020–2050 under different agricultural systems using developed method for determining cropland patterns. The following results were obtained: The available time series of Landsat images in Cold China met the requirements for long-term cropping pattern studies, and the developed method exhibited high accuracy (over 91%) and obtained precise spatial information. A new satellite evidence was observed that cropping patterns significantly differed between the two farm types, with paddy field in state farming expanding at a faster rate (from 2.66 to 68.56%) than those in private farming (from 10.12 to 34.98%). More than 70% of paddy expansion was attributed to the transformation of upland crop in each period at the pixel level, which led to a greater loss of upland crop in state farming than private farming (9505.66 km2 vs. 2840.29 km2) during 1990–2015. Rapid cropland reclamation is projected to stagnate in 2020, while paddy expansion will continue until 2040 primarily in private farming in Cold China. This study provides new evidence for different land use change pattern mechanisms between different agricultural systems, and the results have significant implications for understanding and guiding agricultural system development. | en_US |
| dc.language | eng | en_US |
| dc.publisher | www.mdpi.com | en_US |
| dc.title | Time Tracking of Different Cropping Patterns Using Landsat Images under Different Agricultural Systems during 1990–2050 in Cold China | en_US |
| dc.type | Article | en_US |
| dc.subject.frascati | Earth and related Environmental sciences | en_US |
| dc.audience | Scientific | en_US |
| dc.source.title | Remote Sensing | en_US |
| dc.source.volume | 12 | en_US |
| dc.source.issue | 10 | en_US |
| Orfeo.peerreviewed | Yes | en_US |
| dc.identifier.doi | https://doi.org/10.3390/rs10122011 |
