关键词: 水稻, 无人机, 差异数字表面模型, 氮、磷含量, 生长速率假说

Abstract: Unmanned aerial vehicle (UAV) has the advantages of convenience and lower cost in agricultural remote sensing monitoring. Remote sensing data of three developmental periods of rice in the study area were collected by using DJI Elf 4Pro, and the N and P contents of rice leaves in two periods were measured. The digital surface model (DSM) constructed from the UAV images was used to obtain a differential digital surface model (DDSM) capable of reflecting rice growth height by performing differential operations. The decision coefficient R2 of the fit analysis between the measured plant height and the DDSMextracted plant height was 0.814, indicating that the DDSMextracted plant height had high accuracy. The N and P contents in the leaves were analyzed with the growth rate extracted by DDSM, and the results showed that three days after fertilization, the N and P contents were 4.787% and 0.291%, and the N and P content ratio was 16.481, and the growth rate was 4.971 cm/d. 20 days after fertilization, the N and P contents were 3.750% and 0.211%, and the N and P content ratio was 17.892 growth, and the growth rate was 2.564 cm/d. The results indicate that rice growth is consistent with the growth rate hypothesis and the period of higher growth rate has higher N and P content and lower N and P content ratio.

Key words: rice, UAV, differential digital surface model, nitrogen and phosphorus content, growth rate hypothesis