水保所知识产出(1956---)知识库

作物系数 K c 快速获取是大田作物蒸散量(Evapotranspiration，ET)估算的关键，为研究无人机多光谱遥感估算
玉米作物系数的可行性和适用性，以 2017 年内蒙古达拉特旗昭君镇实验站大田玉米、土壤、气象等数据为基础，采
用经气象因子和作物覆盖度校正后的双作物系数法计算不同生长时期与不同水分胁迫玉米的作物系数，并使用自
主研发的无人机多光谱系统航拍玉米的冠层多光谱(蓝、绿、红、红边、近红外，475 ～840 nm)影像，研究了不同生长
时期(快速生长期、生长中期和生长后期)玉米的 6 种常用植被指数(Vegetation indices，VIs):归一化差值植被指数
(NDVI)、土壤调节植被指数(SAVI)、增强型植被指数(EVI)、比值植被指数(SＲ)、绿度归一化植被指数(GNDVI)
和抗大气指数(VAＲI)，与作物系数 K c 的关系模型及水分胁迫对其的影响。结果表明:玉米生长时期和水分胁迫是
影响玉米 VIs-K c 模型相关性的两个重要因素。不同生长时期玉米植被指数和 K c 相关性不同:充分灌溉情况下，快
速生长期玉米 VIs-K c 模型的相关性(Ｒ 2 为 0. 731 2 ～0. 940 1，p ＜0. 05，n =25)与生长中期至生长后期 VIs-K c 模型的
相关性(Ｒ 2 为 0. 276 5 ～0. 373 2，p ＜0. 05，n =40)不同;水分胁迫情况下，快速生长期玉米 VIs-K
c 模型的相关性(Ｒ
2
为 0. 0002 ～0. 0830，p ＜0. 05，n =25)与生长中期至生长后期 VIs-K c 模型的相关性(Ｒ 2 为0. 366 2 ～0. 848 7，p ＜0. 05，
n =40)不同。水分胁迫对 VIs-K c 模型的相关性影响较大:快速生长期，充分灌溉玉米 VIs-K c 模型的相关性(Ｒ 2 最大
为 0. 940 1)比水分胁迫玉米 VIs-K c 模型的相关性(Ｒ 2 最大为 0. 083 0)强;生长中期至生长后期，充分灌溉玉米 VIs-
K c 模型的相关性(Ｒ 2 最大为 0. 373 2)比水分胁迫玉米 VIs-K c 模型的相关性(Ｒ 2 最大为 0. 848 7)弱。部分植被指数
和作物系数相关性较强;快速生长期充分灌溉玉米的 VIs-K c 模型的相关性由大到小依次为:SＲ、EVI、VAＲI 、
GNDVI、SAVI、NDVI;生长中期至生长后期水分胁迫玉米的 VIs-K c 模型的相关性由大到小依次为:SＲ、GNDVI、
VAＲI、NDVI、SAVI、EVI;其中比值植被指数 SＲ 与作物系数 K c 的相关性最好。结果表明采用无人机多光谱技术估
算 K c 具有一定的可行性。

 Ｒapid acquisition of crop coefficient K c is the key to estimation of field evapotranspiration
(ET)，in order to study the feasibility and applicability of unmanned aerial vehicle (UAV) multispectral
remote sensing in estimation of maize crop coefficient，based on the data of field maize in experimental
station，soil and meteorology in Zhaojun Town，Dalate Qi，Inner Mongolia in 2017，by using
meteorological factors and crop canopy cover to correct dual crop coefficient method at different growth
stages and different water stresses． The multi-spectral (blue，green，red，red edge，near IＲ，475 ～
840 nm) images from UAV were used to calculate vegetation indices (normalized difference vegetationindex (NDVI)，soil adjusted vegetation index (SAVI)，enhanced vegetation index (EVI)，simple ratio
(SＲ) and green normalized difference vegetation index (GNDVI)，visible atmospherically resistant index
(VAＲI)) of maize in different growth stages (rapid growth stage，mid-growth stage and late growth
stage)． Thus the model relation of VIs and crop coefficient K c could be established，and the effect of
water stress on it was studied． Ｒesults demonstrated that maize growth period and water stress were two
important factors influencing the VIs-K c model． The correlation between VIs and K c in different growth
stages was different: under full irrigation condition，the correlation of VIs-K c model in the rapid growth
stage (Ｒ 2 was 0. 731 2 ～0. 940 1，p ＜0. 05，n =25) was different with the correlation of VIs-K c model
from mid to late growth stage (Ｒ 2 was 0. 276 5 ～ 0. 373 2，p ＜ 0. 05，n = 40); under water stress
condition，the correlation of VIs-K c model in the rapid growth stage (Ｒ 2 was 0. 000 2 ～ 0. 083 0，p ＜
0. 05，n =25) was different with the correlation of VIs-K c model from mid to late growth stage (Ｒ 2 was
0. 336 2 ～0. 848 7，p ＜0. 05，n =40)． Water stress had a significant effect on the correlation of VIs-K c
model: in the rapid growth stage，the correlation of VIs-K c model for full irrigation maize (the maximum
value of Ｒ 2 was 0. 940 1) was better than the correlation for water stress maize (the maximum value of Ｒ 2
was 0. 0830); from mid to late growth stage，the correlation of VIs-K c model for full irrigation maize (the
maximum value of Ｒ 2 was 0. 373 2) was worse than the correlation for water stress maize (the maximum
value of Ｒ 2 was 0. 8487)． The correlation of part of VIs and crop coefficient K c was good; the descending
order of correlation of VIs-K c model for full irrigated maize in the rapid growth stage was SＲ，EVI，
VAＲI，GNDVI and SAVI; the descending order of correlation of the VIs-K c model for water stress maize
from mid to late growth stage was SＲ，GNDVI，VAＲI，NDVI，SAVI and EVI; the correlation of SＲ and
crop coefficient K c was the best． Estimation of K c based on UAV multispectral technology was feasible．