2026-10-15T00:04:40Z https://www.scidb.cn/oai

10.57760/sciencedb.IGA.001d1 2026-08-31T11:24:07Z

2026-08-31 XDA28100502 - Crop Growth Monitoring Technology Patent doi:10.57760/sciencedb.iga.001d1 en This dataset is based on Vegetation Indices (VIs) and uses a combination of feature importance assessment and correlation analysis to estimate the influence of different features on the model (IMP). According to the IMP values, iterative analysis is performed to select the optimal feature set, and then a crop leaf nitrogen concentration estimation model is constructed. The dataset uses Python to build a random forest model for estimation, and generates two raster datasets in TIFF format, with a total size of 1.06 GB. Crop growth monitoring; Vegetation indices; Leaf nitrogen concentration; Random forest model; Agricultural remote sensing 叶回春 PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank