Detection and mapping of irrigated farmland in Canterbury, New Zealand
Detection and mapping of irrigated farmland in Canterbury, New Zealand
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新西兰坎特伯雷灌溉农田的检测和绘图
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
S. McNeill
中科院分区：
文献类型：
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作者：
D. Pairman;S. Belliss;James A. Cuff;S. McNeill
灌溉农田的识别对于各种环境模型至关重要。对于这项工作，需要模拟灌溉对地下水质量和流量的影响。由于许多土地利用的地被覆盖外观非常动态，我们采用多时相遥感方法，如果每个位置在任何阶段出现灌溉，则将其分类为可能已灌溉。我们的模型还使用地形分析来确定灌溉可行的地方。然后，无论是可见基础设施的存在，还是高于降雨数据预期的 NDVI 值，都可以用作灌溉土地的证据。现场工作确定的灌溉围场的正确分类率为 75.6%，牧场子集的正确分类率为 88.9%。事实证明，种植农田更加困难，因为它们的 NDVI 还取决于其生长阶段和具体作物类型。
Identification of irrigated farm land is critical to a variety of environmental models. For this work, it is needed to model the impacts of irrigation on groundwater quality and flow rates. As the ground cover appearance for many land uses is quite dynamic, we take a multi-temporal remote sensing approach and classify each location as likely irrigated if it appears irrigated at any stage. Our model also uses a landform analysis to determine where irrigation is feasible. Either the presence of visible infrastructure or NDVI values higher than expected from rainfall data are then used as evidence for irrigated land. Paddocks identified by fieldwork as irrigated were 75.6% correctly classified, rising to 88.9% for a pasture subset. Cropping fields have proved more difficult as their NDVI also depends on their growth stage and the specific crop type.