热带地理 ›› 2019, Vol. 39 ›› Issue (4): 562-570.doi: 10.13284/j.cnki.rddl.003160
• 专刊:无人机在生态学和地理学中的应用 • 上一篇 下一篇
周 慧1,2,苏有勇1,王重洋2,陈金月2,赵 晶1,2,姜 浩2,陈水森2,李 丹2
出版日期:
2019-07-10
发布日期:
2019-07-10
通讯作者:
李丹(1985—),女,河南通许人,副研究员,研究方向为农业遥感,(E-mail)lidan@gdas.ac.cn。
作者简介:
周慧(1995—),女,湖南郴州人,硕士研究生,研究方向为农业遥感,(E-mail)1540206331@qq.com;
基金资助:
广东省科学院发展专项资金项目(2019GDASYL-0503001,2018GDASCX-0905);广东省农业厅省级农业科技创新及推广项目(2019KJ02)
Zhou Hui1,2, Su Youyong1, Wang Chongyang2, Chen Jinyue2, Zhao Jing1,2, Jiang hao2, Chen Shuisen2 and Li Dan2
Online:
2019-07-10
Published:
2019-07-10
摘要:
以花芽分化期荔枝为例,分析了荔枝冠层叶片养分质量分数的空间分布差异;选用18种光谱变量,研究了荔枝不同冠层叶片养分质量分数与光谱变量的关系及其对无人机多光谱遥感监测模型的影响。结果表明:荔枝不同冠层叶片的氮、钾质量分数随冠层高度降低而明显提高;冠层中、上层叶片氮质量分数与无人机正射数据计算的类胡萝卜素反射指数(CRI)相关性最高(r=0.86,p<0.01);冠层中、下层叶片钾质量分数与无人机正射数据的光谱变量显著相关,且与标准绿波段(NG)指数的相关程度最高(r=-0.83,p<0.01)。荔枝冠层叶片养分质量分数空间变化对基于垂直观测遥感数据建立的叶片养分质量分数估算模型精度有影响,无人机多光谱数据具有估算荔枝叶片氮、钾质量分数变化的潜力,但估算精度与冠层高度有关。
周慧,苏有勇,王重洋,陈金月,赵晶,姜浩,陈水森,李丹. 利用无人机的多光谱参数预测荔枝叶片养分质量分数[J]. 热带地理, 2019, 39(4): 562-570.
Zhou Hui, Su Youyong, Wang Chongyang, Chen Jinyue, Zhao Jing, Jiang hao, Chen Shuisen and Li Dan. Prediction of Nutrient Content in Litchi Leaves by UAV Multispectral Parameters[J]. TROPICAL GEOGRAPHY, 2019, 39(4): 562-570.
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