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首页> 外文期刊>International journal of applied earth observation and geoinformation >Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data
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Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data

机译:全球雨养,灌溉和稻田:从遥感,作物清单和气候数据得出的新高分辨率地图

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Irrigation accounts for 70% of global water use by humans and 33-40% of global food production comes from irrigated croplands. Accurate and timely information related to global irrigation is therefore needed to manage increasingly scarce water resources and to improve food security in the face of yield gaps, climate change and extreme events such as droughts, floods, and heat waves. Unfortunately, this information is not available for many regions of the world. This study aims to improve characterization of global rain-fed, irrigated and paddy croplands by integrating information from national and sub-national surveys, remote sensing, and gridded climate data sets. To achieve this goal, we used supervised classification of remote sensing, climate, and agricultural inventory data to generate a global map of irrigated, rainfed, and paddy croplands. We estimate that 314 million hectares (Mha) worldwide were irrigated circa 2005. This includes 66 Mha of irrigated paddy cropland and 249 Mha of irrigated non-paddy cropland. Additionally, we estimate that 1047 Mha of cropland are managed under rain-fed conditions, including 63 Mha of rain-fed paddy cropland and 985 Mha of rain-fed non-paddy cropland. More generally, our results show that global mapping of irrigated, rain-fed, and paddy croplands is possible by combining information from multiple data sources. However, regions with rapidly changing irrigation or complex mixtures of irrigated and non-irrigated crops present significant challenges and require more and better data to support high quality mapping of irrigation. (C) 2015 Elsevier B.V. All rights reserved.
机译:灌溉占人类用水的70%,全球粮食产量的33-40%来自灌溉农田。因此,需要面对与全球灌溉有关的准确和及时的信息,以应对日益短缺的水资源,并在面对产量差距,气候变化和干旱,洪水和热浪等极端事件时改善粮食安全。不幸的是,该信息不适用于世界上许多地区。这项研究旨在通过整合来自国家和地方以下调查,遥感和网格化气候数据集的信息来改善全球雨养,灌溉和水稻田的特征。为了实现这一目标,我们使用了遥感,气候和农业库存数据的监督分类来生成灌溉,雨养和水稻田的全球地图。我们估计,到2005年左右,全球灌溉面积为3.14亿公顷(Mha)。其中包括66 Mha的灌溉稻田和249 Mha的灌溉非稻田。此外,我们估计在雨养条件下管理1047 Mha的农田,包括63 Mha的雨养稻田和985 Mha的雨养非稻田。更广泛地说,我们的结果表明,通过结合来自多个数据源的信息,可以对灌溉,雨养和水稻田进行全球制图。但是,灌溉快速变化的地区或灌溉和非灌溉作物的复杂混合物构成了严峻的挑战,需要更多更好的数据来支持高质量的灌溉图。 (C)2015 Elsevier B.V.保留所有权利。

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