文献类型： 会议论文

第一作者： Rizza Lorena P. Espenido

作者： Rizza Lorena P. Espenido ¹ ; Ronaldo B, Saludes ² ; Moises A, Dorado ² ; Pompe C. Sta. Cruz ³ ;

作者机构： 1.Graduate School, UPLB

2.Agrometeorology and Farm Structures Division, IAE, CEAT, UPLB

3.Institute of Crop Science, CAFS, UPLB

关键词： Corn;UAV;vegetation indices

会议名称： Asian conference on remote sensing

主办单位：

页码： 340-349

摘要： The study focused on establishing relationships between remotely-sensed vegetation indices and selected agronomic parameters for corn, namely: leaf area index (LAI), leaf chlorophyll content (LCC), and yield. Four varieties of corn plants (UPLB Var 6 and 11, USM Var 10 and CSC Var 1) were planted following a split-plot arrangement in a randomized complete block design. These varieties were subjected to four different fertilizer treatments: F0 — no fertilizer, Fl — 100% commercial fertilizer, F2 - 100% organic fertilizer and F3 - 50% commercial, 50% organic fertilizer. Aerial images were acquired every 15 days starting at 30 days after sowing (DAS), until 75 DAS using a multispectral digital camera mounted in an unmanned aerial vehicle (UAV). Vegetation indices (VI), namely: GNDVI, BNDVI and ENDVI, were computed using the spectral bands (NIR, Green and Blue) from the multispectral images. Regression analysis revealed that GNDVI had the highest coefficient of multiple determination (R~2) for corn LAI, LCC, and yield at different growth stages. The relationship between GNDVI and LCC; and GNDVI and Yield both generated highest R~2 values of 0.66 and 0.47, respectively, at 45 DAS. Also, the relationship between GNDVI and LAI yielded highest R~2 of 0.44 at 75 DAS. Results of the study showed that remotely-sensed vegetation indices can be used for rapid and non-destructive monitoring com growth parameters as early as vegetation stage for LCC and yield and reproductive stage for LAI.

分类号： tp7