The rapid growth of the global population has resulted in a continuous increase in cropland intensity and a shortening of the fallow period as part of the cropland rotation cycle.Yet,there is a lack of systematic know...The rapid growth of the global population has resulted in a continuous increase in cropland intensity and a shortening of the fallow period as part of the cropland rotation cycle.Yet,there is a lack of systematic knowledge on the extent of fallow lands,particularly in complex landscapes,such as the mountainous regions of China.To fill this knowledge gap,taking Yuanyang County(YYC),Yunnan Province,China,as a case study,we tested a method to identify the spatial-temporal distribution of fallow land by mapping cropland with Landsat data.The overall accuracy of land cover classification,including cropland,ranged between 90.1%and 95.8%from 1998 to 2019.The average accuracy of fallow plots was 75.7%from 2001 to 2019.The annual fallow rate varied between 8.3%and 54.3%,with an average of 20.7%.Kernel density estimated with the probability density function showed that fallow varied between 5 and 13 blocks per km2,gradually decreasing from the central area to the periphery.Increasing elevation,the low value of regional domestic products,and the increased distance to rural settlements were closely related to the higher proportions of fallow land.The approach presented here can be applied to map fallow land in other regions.展开更多
基金supported by the National Natural Science Foundation of China[grant number 42071233]the Strategic Priority Research Program of Chinese Academy of Sciences[grant number XDA20040201]and the Second Tibetan Plateau Scientific Expedition and Research Program[grant number 2019QZKK0603].
文摘The rapid growth of the global population has resulted in a continuous increase in cropland intensity and a shortening of the fallow period as part of the cropland rotation cycle.Yet,there is a lack of systematic knowledge on the extent of fallow lands,particularly in complex landscapes,such as the mountainous regions of China.To fill this knowledge gap,taking Yuanyang County(YYC),Yunnan Province,China,as a case study,we tested a method to identify the spatial-temporal distribution of fallow land by mapping cropland with Landsat data.The overall accuracy of land cover classification,including cropland,ranged between 90.1%and 95.8%from 1998 to 2019.The average accuracy of fallow plots was 75.7%from 2001 to 2019.The annual fallow rate varied between 8.3%and 54.3%,with an average of 20.7%.Kernel density estimated with the probability density function showed that fallow varied between 5 and 13 blocks per km2,gradually decreasing from the central area to the periphery.Increasing elevation,the low value of regional domestic products,and the increased distance to rural settlements were closely related to the higher proportions of fallow land.The approach presented here can be applied to map fallow land in other regions.
