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首页> 外文期刊>European Journal of Agronomy >A simple model of regional wheat yield based on NDVI data.
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A simple model of regional wheat yield based on NDVI data.

机译:基于NDVI数据的区域小麦单产简单模型。

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The application of crop simulation models to yield estimation on a regional scale is generally constrained by the lack of spatially distributed information on major environmental and agronomic factors affecting crop conditions. The use of remote sensing data can circumvent this problem by providing actual estimates of these conditions with various spatial and temporal resolutions. The current paper presents the development and testing of a methodological framework which utilizes NDVI data taken from satellite platforms and a simulation model (CROPSYST) to estimate wheat yield. This operation relies on two main steps, the first being the computation of wheat above-ground biomass obtained through the use of NDVI-derived FAPAR estimates. The second step consists of the final repartition of the estimated biomass into crop yield, which is obtained through the use of an harvest index computed by integrating the CROPSYST development sub-model and NDVI data. The proposed methodology was applied in two Italian provinces where wheat is widely grown (Grosseto and Foggia). In both cases, attention was first devoted to the production of multi-year NDVI data sets descriptive of wheat conditions. Next, the current methodology was applied to estimate wheat yield. The results obtained showed the high accuracy of the method in estimating wheat yield at the provincial level. Correlation coefficients equal to 0.77-0.73 were obtained between measured and simulated crop yield, with corresponding root mean square errors (RSME) of 0.47 and 0.44 Mg/ha for Grosseto and Foggia, respectively..
机译:由于缺乏影响作物状况的主要环境和农艺因素的空间分布信息,通常限制了作物模拟模型在区域规模上的产量估算的应用。通过提供具有各种空间和时间分辨率的这些条件的实际估计值,遥感数据的使用可以避免此问题。本文介绍了一种方法框架的开发和测试,该框架利用从卫星平台获取的NDVI数据和模拟模型(CROPSYST)来估算小麦产量。此操作依赖于两个主要步骤,第一步是通过使用NDVI得出的FAPAR估计值来计算小麦地上生物量。第二步包括将估计的生物量最终重新分配为作物产量,这是通过使用收获指数获得的,该收获指数是通过将CROPSYST开发子模型和NDVI数据进行整合而得出的。所建议的方法已在两个小麦普遍种植的意大利省(格罗塞托和福贾)得到应用。在这两种情况下,首先都将注意力放在描述小麦状况的多年NDVI数据集上。接下来,将当前的方法应用于估算小麦产量。所得结果表明,该方法在省级水平上估算小麦单产的准确性很高。在实测和模拟作物产量之间获得的相关系数等于0.77-0.73,格罗塞托和福贾的相对均方根误差(RSME)分别为0.47和0.44 Mg / ha。

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