Estimating historical changes in global land cover: Croplands from 1700 to 1992
Estimating historical changes in global land cover: Croplands from 1700 to 1992
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DOI：
10.1029/1999gb900046
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发表时间：
1999-12-01
影响因子：
5.2
通讯作者：
Foley, JA
中科院分区：
文献类型：
--
作者：
Ramankutty, N;Foley, JA
过去三个世纪的人类活动，主要是通过将自然生态系统转变为农业，大大改变了地球的环境。这项研究提出了一种简单的方法来推导1700年至1992年全球农田的地理明确变化。通过校准一个遥感土地覆盖分类数据集对耕地清查数据，我们得出了一个全球性的永久性耕地在1992年，在5分钟的空间分辨率[Ramankutty和Foley，1998年]。为了重建历史耕地，我们首先从各种来源在国家和次国家一级编制了一个广泛的历史耕地清查数据库。然后，我们使用我们的1992年耕地数据在一个简单的土地覆盖变化模型，沿着与历史库存数据，重建全球5分钟分辨率的永久耕地面积从1992年到1700年的数据。历史耕地的重建变化与人类居住历史和经济发展模式相一致。通过将我们的历史农田数据集覆盖在新获得的潜在植被数据集上，我们分析了不同自然植被类型转化为农业的程度。我们进一步研究了世界不同地区农田被遗弃的程度。我们的数据集可用于全球气候模型和全球生态系统模型，以了解土地覆盖变化对气候以及碳和水循环的影响。这样的分析是一个至关重要的帮助，以提高我们对可持续未来的思考。
Human activities over the last three centuries have significantly transformed the Earth's environment, primarily through the conversion of natural ecosystems to agriculture. This study presents a simple approach to derive geographically explicit changes in global croplands from 1700 to 1992. By calibrating a remotely sensed land cover classification data set against cropland inventory data, we derived a global representation of permanent croplands in 1992, at 5 min spatial resolution [Ramankutty and Foley, 1998]. To reconstruct historical croplands, we first compile an extensive database of historical cropland inventory data, at the national and subnational level, from a variety of sources. Then we use our 1992 cropland data within a simple land cover change model, along with the historical inventory data, to reconstruct global 5 min resolution data on permanent cropland areas from 1992 back to 1700. The reconstructed changes in historical croplands are consistent with the history of human settlement and patterns of economic development. By overlaying our historical cropland data set over a newly derived potential vegetation data set, we analyze our results in terms of the extent to which different natural vegetation types have been converted for agriculture. We further examine the extent to which croplands have been abandoned in different parts of the world. Our data sets could be used within global climate models and global ecosystem models to understand the impacts of land cover change on climate and on the cycling of carbon and water. Such an analysis is a crucial aid to sharpen our thinking about a sustainable future.