Crop type mapping using remote sensing is critical for global agricultural monitoring and food ***,the complexity of crop planting patternsandspatial heterogeneity pose significant challenges to fielddata collection...
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Crop type mapping using remote sensing is critical for global agricultural monitoring and food ***,the complexity of crop planting patternsandspatial heterogeneity pose significant challenges to fielddata collection,thereby limiting the accuracy of remotely sensed crop *** study proposed a new approach forrapidly collecting field crop data by integrating unmanned aerial vehicle(UAV)images with the YOLOv3(You Only Look Once version 3)*** impacts of UAV flight altitude and the number of training samples on the accuracy of crop identification models were investigated using peanut,soybean,and maize as *** results showed that the average Fl-score for crop type detection accuracy reached 0.91 when utilizing UAV images captured at an altitude of 20 *** addition,a positive correlation was observed between identification accuracy and the number of training *** model developed in this study can rapidly and automatically identify crop types from UAV images,which significantly improves the survey efficiency and provides an innovative solution for acquiring field crop data in large areas.
In the study, a module was designed which was used to estimate yield of crop (such as lychee, banana and sugarcane etc) using spectral library of featured crops of South China. An approach combining spectral library w...
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ISBN:
(纸本)9781424445622
In the study, a module was designed which was used to estimate yield of crop (such as lychee, banana and sugarcane etc) using spectral library of featured crops of South China. An approach combining spectral library with expert system classification methods by spatialdata mining techniques is present. Being one of spatialdata mining techniques, inductive learning algorithm is used to discover knowledge of spectral library for the expert system and is designed specially for monitoring featured crops of South China. So the intelligent expert classifier can make use of spectral data, attribute data andspatialdata of spectral library to extract information of South China's featured crops. The study pre-defined some attributes of inductive learning algorithm which are in favor of featured crops mapping, for improving the efficiency of algorithm and ensuring the usability of rules. The estimation of lychee planting area of Shenzhen city in 2005 was presented as a case study. The following classification rules of lychee were acquired by running inductive learning algorithm: for example, 0.062< reflectance of TM2 <0.071, 0.47
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