建立具有准确空间属性的历史时期土地覆被数据集有助于更好地模拟土地覆被变化的过程及其效应。本文基于我国过去300年耕地面积总体呈持续增加的特点,提出了历史时期耕地分布范围未超出现代耕地范围的合理假设,并以地表高程和坡度为影响土地宜垦程度的主导因子,评估了MODIS土地覆被产品中现代耕地分布区域的宜垦程度,再按宜垦程度从高到低的顺序,将依据历史文献资料订正的以行政单元为统计单位的耕地面积分配至网格。利用这一方法,重建了清代云南省1671年和1827年两个时间断面空间分辨率为90m的耕地空间分布格局。结果表明:该方法可有效地将历史耕地统计数据转化为具有较高空间分辨率的网格数据,其结果基本能够反映历史耕地空间格局的变化情况。
Highly precise Land Use and Cover Change (LUCC) dataset plays a key role in improving simulations of effects of LUCC on climate and ecosystem. Historical LUCC usually has no precise spatial location information. This shortage limited usage of historical LUCC dataset in the global environmental changes simulations. So, it is needed to develop an effective way to reconstruct historical cropland spatial distribution with grid-boxes. In this study, we develop a new way in which the spatial distribution of historical cropland was reconstructed effectively. This approach was built on a reasonable hypothesis that historical cropland was located in the domain of present cropland area. This hypothesis was derived from a feature that cropland area increased all the time generally in the past 300 years. This approach includes two steps: (1) estimating the easiness for reclamation one pixel by one pixel within the cropland domain determined by MODIS land cover product; (2) by descending order of easiness for reclamation, filling in the pixels with cropland from historical inventories; it would not stop until the total area of cropland pixels was equal to inventory cropland area. As a case study, we reconstructed the spatial distribution with a 90-m resolution of cropland in the Yunnan Province in 1671 and 1827 by using this approach. The results show this approach could reconstruct the historical cropland spatial distribution with high resolution