Global Irrigated Areas

Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.

农业是全球第一大用水部门。据联合国粮食及农业组织（FAO）2014a报告，灌溉农田占农业生产总用地的40%。其空间分布信息对区域水资源管理与粮食安全具有重要意义。灌溉空间信息对于正迈向高效可持续农业转型的政策制定者与决策者而言至关重要。然而，灌溉农田的制图仍是土地利用分类领域的一大挑战，且现有全球数据集的结果差异显著。本研究针对现有基于统计数据的灌溉分布图展开验证，并辅以辅助数据扩展了灌溉农田范围。本研究采用多重决策树逐步处理并分析多时序归一化差分植被指数 (Normalized Difference Vegetation Index, NDVI) SPOT-VGT数据与农业适宜性数据，两类数据的空间分辨率均为30arcsec。研究时段覆盖1999年至2012年。全球尺度的结果显示，本研究估算的灌溉农田面积较现有基于统计数据的方法高出18%。与官方国家统计数据相比，差异最大的区域为亚洲，尤其是中国与印度。新增的灌溉农田主要分布在已知的灌溉密集区，其灌溉密度较此前估算值更高。通过全球及区域产品开展的验证结果表明，由于空间分辨率、研究时段、输入数据及所采用假设的不同，现有数据集在灌溉农田面积与空间分布上存在显著差异。