中南林业科技大学学报

环境因子对不同生长阶段油茶冠层高光谱特征的影响

PDF下载

张超 ¹^,² , 寇幸子 ¹^,² , 苏久扬 ¹^,² , 华松杰 ¹^,² , 张研 ¹^,² , 唐雪海 ¹^,²

中南林业科技大学学报 | 林学 2026,46(10): 50-60

收起

中南林业科技大学学报 |林学 2026 , 46 (10) : 50 -60

环境因子对不同生长阶段油茶冠层高光谱特征的影响

全屏

张超¹^,², 寇幸子¹^,², 苏久扬¹^,², 华松杰¹^,², 张研¹^,², 唐雪海¹^,²

作者信息

^1.安徽农业大学　林学与园林学院，安徽　合肥　230036

^2.安徽省林木资源培育重点实验室，安徽　合肥　230036

通讯作者:

唐雪海（tangxuehai@ahau.edu.cn），副教授，博士，硕士研究生导师。

作者简介:

张超（chaozhang@stu.ahau.edu.cn），硕士研究生。

Impact of environmental factors on canopy hyperspectral characteristics of Camellia oleifera at different growth stages

Chao Zhang¹^,², Xingzi Kou¹^,², Jiuyang Su¹^,², Songjie Hua¹^,², Yan Zhang¹^,², Xuehai Tang¹^,²

Affiliations

^1.School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, Anhui, China

^2.Anhui Provincial Key Laboratory of Forest Resources Cultivation, Hefei 230036, Anhui, China

出版时间: 2026-10-25 doi: 10.14067/j.cnki.1673-923x.2026.10.004

文章导航

摘要

收起

【目的】

探讨油茶林在不同生长阶段的高光谱特征与环境因子之间的关系，以期为丘陵区油茶林磷素亏缺诊断提供光谱阈值，进而推动油茶林的精准施肥和科学管理。

【方法】

将研究区内240株油茶划分为12块样地，测定春梢期、果实膨大期和盛花期3个关键生长期的冠层高光谱数据及地形与土壤因子，并基于国家地球系统科学数据中心获取气候因子数据；选取并计算13个植被指数，结合环境因子构建结构方程模型，量化不同环境因子对油茶冠层光谱特征的影响，揭示其内在关系及空间分布特征。

【结果】

春梢期、果实膨大期和盛花期油茶冠层高光谱反射率分别为0~0.413、0~0.532和0~0.683，各时期光谱波段与土壤养分因子之间均呈显著相关性。其中，归一化植被指数（NDVI）、光化学植被指数（PRI）、增强植被指数（EVI）、优化土壤调节植被指数（OSAVI）与植物衰老反射指数（PSRI）构建的SEM模型拟合度较好，拟合指数分别为0.94、0.92、0.83、0.90和0.83。油茶冠层光谱特征主要受气候和土壤养分因子的显著直接影响，地形因子作用不显著，主要通过土壤养分因子产生间接效应；温度、降水量、蒸发量、氮素、磷素对油茶冠层光谱的影响显著。

【结论】

样地内气候、地形与土壤养分因子共同影响油茶冠层光谱特征，其中气候和土壤养分因子起核心作用，地形因子起间接作用。本研究可为油茶规模化种植与精准经营提供科学依据，为提升土壤养分利用效率与高效栽培技术推广提供实践参考。

关键词

油茶 / 高光谱 / 环境因子 / 结构方程模型

Abstract

收起

【Objective】

To investigate the impact of environmental factors on the canopy hyperspectral characteristics of Camellia oleifera at different growth stages, aiming to provide theoretical support for precise fertilization and scientific management of Camellia oleifera plantations and to promote the sustainable development of the Camellia oleifera industry.

【Method】

A total of 240 Camellia oleifera plants were divided into 12 sample plots within the study area. Canopy hyperspectral data, topographic factors, and soil factors were measured during three key growth periods: spring shoot stage, fruit expansion stage, and full bloom stage. Climate factor data were obtained from the National Earth System Science Data Center. Thirteen vegetation indices were derived from the hyperspectral bands, and a structural equation model (SEM) was constructed to quantify the impact of different environmental factors on canopy spectral characteristics and to reveal their intrinsic relationships and spatial distribution patterns.

【Result】

The canopy hyperspectral reflectance values of Camellia oleifera during the spring shoot stage, fruit expansion stage, and full bloom stage were 0-0.413, 0-0.532, and 0-0.683, respectively. Significant correlations were found between spectral bands and soil nutrient factors across all periods. The structural equation models (SEMs) constructed with the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), enhanced vegetation index (EVI), optimized soil-adjusted vegetation index (OSAVI), and plant senescence reflectance index (PSRI) had good fit indices of 0.94, 0.92, 0.83, 0.90, and 0.83, respectively. The results indicated that canopy spectral characteristics of Camellia oleifera are significantly and directly influenced by climate and soil nutrient factors, while topographic factors have an insignificant direct effect but indirectly influence canopy spectra through soil nutrients. Temperature, precipitation, evaporation, nitrogen, and phosphorus were found to have significant impacts on canopy spectral characteristics.

【Conclusion】

Climate, topography, and soil nutrient factors collectively influence the canopy spectral characteristics of Camellia oleifera, with climate and soil nutrients playing a core role and topography having an indirect effect. This study provides important scientific evidence for large-scale planting and precise management of Camellia oleifera, as well as practical references for improving soil nutrient use efficiency and promoting efficient cultivation techniques.

Key words

Camellia oleifera / hyperspectral / environmental factors / structural equation model

引用本文

张超, 寇幸子, 苏久扬, 华松杰, 张研, 唐雪海. 环境因子对不同生长阶段油茶冠层高光谱特征的影响. 中南林业科技大学学报, 2026 , 46 (10) : 50 -60 . DOI: 10.14067/j.cnki.1673-923x.2026.10.004

Chao Zhang, Xingzi Kou, Jiuyang Su, Songjie Hua, Yan Zhang, Xuehai Tang. Impact of environmental factors on canopy hyperspectral characteristics of Camellia oleifera at different growth stages[J]. Journal of Central South University of Forestry & Technology, 2026 , 46 (10) : 50 -60 . DOI: 10.14067/j.cnki.1673-923x.2026.10.004

基金

收起

国家自然科学基金项目(32171783; 32572046)

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

[1]

陈永忠. 我国油茶科技进展与未来核心技术[J]. 中南林业科技大学学报, 2023, 43(7): 1-22.

Chen

Y Z

. Scientific and technological progress and future core technologies of oil tea Camellia in China[J]. Journal of Central South University of Forestry & Technology, 2023, 43(7): 1-22.

[2]

Teixeira

A M

, Sousa

. A review on the biological activity of Camellia species[J]. Molecules, 2021, 26: 2178.

[3]

谭新建, 晏巢, 钟秋平, 等. 我国油茶良种选育及推广应用[J]. 世界林业研究, 2023, 36(2): 108-113.

Tan

X J

, Yan

, Zhong

Q P

, et al. Breeding, promotion and application of improved oil-tea cultivar in China[J]. World Forestry Research, 2023, 36(2): 108-113.

[4]

傅根深, 吕海燕, 燕李鹏, 等. 基于冠层高光谱特征的油茶叶片碳氮比估算模型构建[J]. 光谱学与光谱分析, 2023, 43(11): 3404-3411.

G S

, Lyu

H Y

, Yan

L P

, et al. A C/N ratio estimation model of Camellia oleifera leaves based on canopy hyperspectral characteristics[J]. Spectroscopy and Spectral Analysis, 2023, 43(11): 3404-3411.

[5]

陈泽鑫, 葛晓宁, 郭红艳, 等. 不同砧穗组合浙江红花油茶嫁接苗的生理生化特性比较[J]. 中南林业科技大学学报, 2025, 45(2): 91-100.

Chen

Z X

, Ge

X N

, Guo

H Y

, et al. Comparison of physiological and biochemical traits of grafted Camellia chekiangoleosa seedlings with various combinations of rootstocks[J]. Journal of Central South University of Forestry & Technology, 2025, 45(2): 91-100.

[6]

Lin

, Liu

, Zhang

F X

, et al. Design of multi-passband polymer multilayer film and its application in photovoltaic agriculture[J]. Chinese Optics Letters, 2021, 19(11): 112201.

[7]

倪佳颖, 丁锟奇, 黄峰, 等. 基于深度学习模型的干旱区绿洲植被时空动态预测方法—以青土湖绿洲为例[J]. 生态学报, 2025, 45(23): 11810-11820.

J Y

, Ding

K Q

, Huang

, et al. Predicting spatiotemporal dynamics of oasis vegetation in arid regions using a CNN-GRU model: a case study of Qingtu oasis[J]. Acta Ecologica Sinica, 2025, 45(23): 11810-11820.

[8]

蔡秋阳, 高翅. 园林博览园游客满意度影响因素及机理分析—基于结构方程模型的实证研究[J]. 中国园林, 2016, 32(8): 58-64.

Cai

Q Y

, Gao

. A study on the influencing factors and mechanism of tourists' satisfaction of garden expo based on structural equation model[J]. Chinese Landscape Architecture, 2016, 32(8): 58-64.

[9]

姚雪松, 冷红. 基于结构方程模型的公园游憩空间满意度研究—以长春市为例[J]. 建筑学报, 2017(增刊1): 32-37.

Yao

X S

, Leng

. Study on satisfaction of park recreation space based on structural equation model: a case study of Changchun[J]. Architectural Journal, 2017(S1): 32-37.

[10]

吴金霏, 张文元, 殷佑斗, 等. 28-高芸苔素内酯对油茶果实经济性状及营养品质的影响[J]. 经济林研究, 2023, 41(3): 197-205.

J F

, Zhang

W Y

, Yin

Y D

, et al. Effects of 28-homobrassinolide on economic characters and nutritional quality of Camellia oleifera fruit[J]. Nonwood Forest Research, 2023, 41(3): 197-205.

[11]

董灵波, 田栋元, 陈莹, 等. 基于结构方程模型的兴安落叶松天然林更新影响因素[J]. 应用生态学报, 2021, 32(8): 2763-2772.

Dong

L B

, Tian

D Y

, Chen

, et al. Clarifying the factors affecting Larix gmelinii forest regeneration based on structural equation model[J]. Chinese Journal of Applied Ecology, 2021, 32(8): 2763-2772.

[12]

郭凌曜, 蒋元华, 李茂松, 等. 油茶丰产气候指标体系构建与区划—以湖南普通油茶为例[J]. 中国油料作物学报, 2023, 45(5): 1042-1052.

Guo

L Y

, Jiang

Y H

, Li

M S

, et al. Construction and zoning of climatic index system for Camellia abundance: example of ordinary Camellia in Hunan[J]. Chinese Journal of Oil Crop Sciences, 2023, 45(5): 1042-1052.

[13]

龚家国, 常紫倩, 赫晓慧, 等. 结合光谱分解与空间吸引模型的中低分辨率影像山区河流水体提取[J]. 地球信息科学学报, 2025, 27(8): 1936-1951.

Gong

J G

, Chang

Z Q

, He

X H

, et al. Mountain river waterbody extraction from medium and low-resolution imagery using spectral unmixing and spatial attraction modeling[J]. Journal of Geo-information Science, 2025, 27(8): 1936-1951.

[14]

吴锦成, 于坤霞, 李雪, 等. 黄河流域植被时空变化及驱动因素[J]. 环境科学, 2026, 47(4): 2307-2317.

J C

, Yu

K X

, Li

, et al. Spatio-temporal changes and driving factors of vegetation in the Yellow River basin[J]. Environmental Science, 2026, 47(4): 2307-2317.

[15]

闫子岳, 杜敏, 孙文义, 等. 1986—2023年中国四大沙地扩张与萎缩的动态变化[J]. 水土保持研究, 2026, 33(1): 205-215.

Yan

Z Y

, Du

, Sun

W Y

, et al. Dynamic changes of expansion and shrinkage of the four major sandy lands of China from 1986 to 2023[J]. Research of Soil and Water Conservation, 2026, 33(1): 205-215.

[16]

顾亚, 张亚, 段海川, 等. 基于OSAVI-Albedo特征空间的香格里拉市土地荒漠化时空动态监测[J]. 生态学报, 2025, 45(13): 6524-6543.

, Zhang

, Duan

H C

, et al. Spatio-temporal dynamic monitoring of land desertification in Shangri-La City based on OSAVI-Albedo feature space[J]. Acta Ecologica Sinica, 2025, 45(13): 6524-6543.

[17]

许政勇, 孙斌, 张王菲, 等. 基于优化三角形植被指数(TVI)的灌丛化草原植被地上生物量遥感估测方法研究[J]. 草业学报, 2023, 32(10): 1-14.

Z Y

, Sun

, Zhang

W F

, et al. An evaluation of a remote sensing method based on optimized triangular vegetation index (TVI) for aboveground shrub biomass estimation in shrub-encroached grassland[J]. Acta Prataculturae Sinica, 2023, 32(10): 1-14.

[18]

陈聪, 于啸, 宫琪. 基于改进残差网络的苹果叶片病害识别研究[J]. 河南农业科学, 2023, 52(4): 152-161.

Chen

, Yu

, Gong

. Apple leaf diseases identification based on improved residual networks[J]. Journal of Henan Agriculture Sciences, 2023, 52(4): 152-161.

[19]

林秋云, 谢振宇, 胡伟, 等. 水稻亮绿叶突变体bgl-2的表型特征与遗传分析[J]. 热带作物学报, 2023, 44(6): 1091-1096.

Lin

Q Y

, Xie

Z Y

, Hu

, et al. Phenotypic characteristics and genetic analysis of bgl-2, a bright green leaf mutant Oryza sativa L.[J]. Chinese Journal of Tropical Crops, 2023, 44(6): 1091-1096.

[20]

胡志辉, 张梦琦, 王亚文, 等. 适期追肥对‘江大紫豇1号’豇豆叶片光谱参数及产量的影响[J]. 江汉大学学报(自然科学版), 2022, 50(6): 5-12.

Z H

, Zhang

M Q

, Wang

Y W

, et al. Effect of suitable topdressing on leaves spectral parameters and yield of Cowpea ‘Jiang Da Zi Jiang 1 Hao’[J]. Journal of Jianghan University (Natural Science Edition), 2022, 50(6): 5-12.

[21]

张敏, 郭涛, 刘轲, 等. 基于高光谱植被指数的水稻LAI遥感估算[J]. 西南农业学报, 2022, 35(11): 2651-2658.

Zhang

, Guo

, Liu

, et al. Rice LAI estimation by remotely sensed hyperspectral vegetation index[J]. Southwest China Journal of Agricultural Sciences, 2022, 35(11): 2651-2658.

[22]

王瑾, 陈书涛, 丁司丞, 等. 大豆叶片呼吸与植被指数和叶片性状的关系[J]. 光谱学与光谱分析, 2022, 42(5): 1607-1613.

Wang

, Chen

S T

, Ding

S C

, et al. Relationships between the leaf respiration of soybean and vegetation indexes and leaf characteristics[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1607-1613.

[23]

陆婷婷, 闫文惠, 苏新全, 等. 多年生稻产量品质抗逆响应形成的生理生态机制及其调控途径研究进展[J]. 中国水稻科学, 2025, 39(5): 586-600.

T T

, Yan

W H

, Su

X Q

, et al. Research progress on physiological and ecological mechanisms and regulation pathways of yield, quality and stress resistance response in perennial rice[J]. Chinese Journal of Rice Science, 2025, 39(5): 586-600.

[24]

王小燕, 廖立国, 李金凤, 等. 广西亚热带人工林土壤碳氮含量及其驱动因素研究[J]. 林业科学研究, 2025, 38(5): 185-195.

Wang

X Y

, Liao

L G

, Li

J F

, et al. Soil carbon and nitrogen contents and their driving factors in subtropical plantation forests of Guangxi[J]. Forestry Research, 2025, 38(5): 185-195.

[25]

Zhang

L M

, Zheng

Q F

, Liu

Y L

, et al. Combined effects of temperature and precipitation on soil organic carbon changes in the uplands of eastern China[J]. Geoderma, 2019, 337: 1105-1115.

[26]

Deng

X F

, Ma

W Z

, Ren

Z Q

, et al. Spatial and temporal trends of soil total nitrogen and C/N ratio for croplands of east China[J]. Geoderma, 2020, 361: 114035.

[27]

马爽, 韩阳, 黄梦雪, 等. 基于不同植被指数的植被-土壤混合像元高光谱偏振信息与模型研究[J]. 光谱学与光谱分析, 2017, 37(11): 3549-3556.

, Han

, Huang

M X

, et al. Study on information and model of high polarization hyperspectral about vegetation-soil mixed pixels based on different vegetation indices[J]. Spectroscopy and Spectral Analysis, 2017, 37(11): 3549-3556.

[28]

吴娟娟, 李先信, 苑平, 等. 柑橘紫色酸性磷酸酶PAP基因的低磷胁迫表达特征[J]. 分子植物育种, 2020, 18(21): 6975-6980.

J J

, Li

X X

, Yuan

, et al. Expression characteristic of the PAP gene responses to phosphorus starvation in Citrus[J]. Molecular Plant Breeding, 2020, 18(21): 6975-6980.

[29]

王纪华, 黄文江, 劳彩莲, 等. 运用PLS算法由小麦冠层反射光谱反演氮素垂直分布[J]. 光谱学与光谱分析, 2007, 27(7): 1319-1322.

Wang

J H

, Huang

W J

, Lao

C L

, et al. Inversion of winter wheat foliage vertical distribution based on canopy reflected spectrum by partial least squares regression method[J]. Spectroscopy and Spectral Analysis, 2007, 27(7): 1319-1322.

[30]

Klem

, Rajsnerova

, Novotna

, et al. Changes in vertical distribution of spectral reflectance within spring barley canopy as an indicator of nitrogen nutrition, canopy structure and yield parameters[J]. Agriculture (Polnohospodárstvo), 2014, 60(2): 50-59.

[31]

Curran

P J

. Remote sensing of foliar chemistry[J]. Remote Sensing of Environment, 1989, 30(3): 271-278.

[32]

J S

, Eitel

J U H

, Engels

, et al. Improving unmanned aerial vehicle (UAV) remote sensing of rice plant potassium accumulation by fusing spectral and textural information[J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 104: 102592.

2026年第46卷第10期

PDF下载

引用本文

BibTeX

文章信息

doi: 10.14067/j.cnki.1673-923x.2026.10.004

接收时间：2025-09-23
首发时间：2026-10-30
出版时间：2026-10-25

补充材料

相关文章

文章信息

作者

出版历史

收稿日期：2025-09-23
修回日期：2025-11-13

基金

国家自然科学基金项目(32171783; 32572046)

作者信息

^1.安徽农业大学　林学与园林学院，安徽　合肥　230036

^2.安徽省林木资源培育重点实验室，安徽　合肥　230036

通讯作者:

唐雪海（tangxuehai@ahau.edu.cn），副教授，博士，硕士研究生导师。

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/znlykj/CN/10.14067/j.cnki.1673-923x.2026.10.004

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

关闭全屏

BibTeX
EndNote
RefWorks
TxT