Estimation of rice residue cover by remote sensing based on hyperspectral and deep learning
Journal Title: Journal of Henan Agricultural University - Year 2024, Vol 58, Issue 5
Abstract
[Objective] A method for extracting rice residue cover (RRC) information in the field was designed by combining hyperspectral remote sensing, convolutional neural network and transfer learning. [Method] The work mainly includes three parts: 1) Various soil moisture content, rice residue moisture content and RRC “soil-rice straw” mixed spectrum were measured in the laboratory; 2) A rice residue cover Hyperspectral network (RRChyperNet) model was designed based on the visual geometry group network, which combined the features of deep and shallow networks to carry out RRC estimation; 3) The feasibility of using RRChyperNet model for field RRC estimation was evaluated based on laboratory and field measurements of soil-rice straw spectra. Coefficient of determination (R2) and root mean square error (RMSE) were used to evaluate the accuracy of RRC information extraction in the field. [Result] 1) The RRChyperNet can be used to estimate field RRC information with high precision (R2=0.953, RMSE=0.085); 2) The RRChyperNet based on pre-training combined with transfer learning method can achieve a highly accurate estimation of RRC in the study area (R2=0.867, RMSE=0.093) and its accuracy is significantly higher than that of the widely used random forest and support vector machine regression models (R2=0.686-0.691, RMSE=0.122-0.128); 3) This study only conducted RRChyperNet model training and performance testing based on rice residue dataset; The estimation potential of RRChyperNet for wheat, corn, and other straw types still requires further experimentation in the future. [Conclusion] RRChyperNet model can provide high-precision rice straw coverage information in the field, and provide technical support for dynamically grasping the implementation progress of farmland conservation tillage and implementing the construction of agricultural ecological environment protection.
Authors and Affiliations
Jibo YUE, Ting LI, Jie SONG, Qingjiu TIAN, Yang LIU, Haikuan FENG
Keywords
Related Articles
- EP ID EP769460
- DOI 10.16445/j.cnki.1000-2340.20240822.002
- Views 14
- Downloads 0
Meta-regression analysis of factors influencing adoption behavior of conservation tillage technologies
[Objective] To explore the degree of difference among the research results of the factors influencing the adoption behavior of conservation tillage technologies and which research characteristics can explain the differen...
Analysis of the genetic diversity and selection signals of Henan Game chicken using genome-wide SNPs
[Objective] The aim of this study is to analyze the genetic diversity and whole-genome selection signals of Henan Game chicken breeds, and to identify important genetic traits of these breeds. [Method] Affymetrix Axiom 6...
Research on parameters of the double-layer asynchronous roller screen for the larvae of black soldier fly based on chicken manure culture
[Objective] This research aims to solve the problems including difficulty to separate the caked feces produced by black soldier flies based on chicken manure culture, high loss rate of the larvae and the screening effici...
Genetic transformation of lily stress resistance gene and identification of stress resistance of transformed plants
[Objective] In order to obtain new materials of oriental lily with strong stress resistance. [Method] The stress-resistant genes LlZFHD4 and LlMYB3 cloned from Lilium lancifolium were found to be homologous to transform...
Screening and identification of a Streptomyces rochei strain LZ-7 with biocontrol potential against Fusarium pseudograminearum
[Objective] The objective of this study is to isolate and screen out the bacterial strain with inhibitory effect on Fusarium pseudograminearum from soil, and identify the strain species and analyze its biocontrol potenti...