Estimation accuracy of fractional vegetation cover based on normalized difference vegetation index and UAV hyperspectral images
-
摘要: 研究波段参数对NDVI估算植被生物物理参数的影响,对于提高NDVI在植被覆盖变化监测中的应用精度具有重要意义。采用无人机载Resonon Pika XC2高光谱仪获取的人工草地高光谱影像,分析红光和近红外波段位置移动与宽度变化对NDVI的影响,评估NDVI对植被盖度的敏感性和植被盖度估算精度。结果表明: 波段位置固定时红光和近红外波段宽度扩展对NDVI及其敏感性影响不大,窄波段NDVI估算植被盖度的精度优于宽波段。红光和近红外波段位置向长波方向移动时对NDVI及其敏感性有不同程度的影响,随着敏感性增强NDVI抗扰动性降低,估算植被盖度的精度有所下降。窄波段NDVI的灵敏度系数及其与植被盖度线性拟合的R2波动剧烈,植被盖度估算的位置稳定性较差。10 nm NDVI在不同位置处取得了较高的盖度估算精度,R2最大值为0.83。4种主流卫星影像计算的宽波段NDVI对于高植被覆盖区盖度反演具有良好的适用性,但与窄波段10 nm NDVI相比其盖度反演精度仍然有一定程度的衰减。研究结果可为NDVI精确反演植被参数提供科学参考和依据。Abstract: The researches on the effects of band parameters on the biophysical parameters of vegetation estimation using the normalized difference vegetation index (NDVI) have great significance for the improvement in the application accuracy of NDVI in vegetation dynamic monitoring. Based on the hyperspectral images of artificial grassland obtained from a Resonon, Inc. Pika XC2 Hyperspectral Imaging Camera loaded by an unmanned aerial vehicle (UAV), this study analyzes the effects of the positions and width of red and near-infrared bands on NDVI and assesses the sensitivity of NDVI to fractional vegetation cover and the estimation accuracy. The results are as follows. When band positions were fixed, the width expansion of red and near-infrared bands had little effects on NDVI and its sensitivity, and the accuracy of fractional vegetation cover estimated using narrowband NDVI is higher than the accuracy based on broadband NDVI. When the red and near-infrared bands moved towards long waves, the NDVI and its sensitivity were affected to different extents. With an increase in the sensitivity, the anti-disturbance performance of NDVI decreased, and the estimation accuracy of fractional vegetation cover decreased. The sensitivity coefficient of narrowband NDVI and the R2 determined by the linear fitting of the sensitivity coefficient and the fractional vegetation cover greatly fluctuated, and the estimated fractional vegetation cover at various locations was unstable. High estimation accuracy of fractional vegetation was obtained at different locations using the 10 nm NDVI, with the maximum R2 value of 0.83. The broadband NDVI calculated using four popular satellite images can be well applied in the inversion of the fractional vegetation cover in areas with high vegetation cover. However, its inversion accuracy of fractional vegetation cover still suffered some attenuation compared with narrowband NDVI (10 nm). These results will serve as scientific references and bases for accurate inversion of vegetation parameters using NDVI.
-
Key words:
- band position and width /
- NDVI /
- fractional vegetation cover /
- UAV /
- hyperspectral image /
-
-
[1] 田庆久, 闵祥军. 植被指数研究进展[J]. 地球科学进展, 1998, 13(4):327-333.
[2] Tian Q J, Min X J. Advances in study on vegetation indices[J]. Advance in Earth Sciences, 1998, 13(4):327-333.
[3] Rouse J W, Haas R H, Schell J A, et al. Monitoring vegetation systems in the Great Plains with ERTS. Proceedings,3rd Earth Resource Technology Satellite (ERTS) Symposium, 1974(1):48-62.
[4] 李喆, 胡蝶, 赵登忠, 等. 宽波段遥感植被指数研究进展综述[J]. 长江科学院院报, 2015, 32(1):125-130.
[5] Li Z, Hu D, Zhao D Z, et al. Research advance of broadband vegetation index using remotely sensed images[J]. Journal of Yangtze River Scientific Research Institute, 2015, 32(1):125-130.
[6] 王福民, 黄敬峰, 王秀珍, 等. 波段位置和宽度对不同生育期水稻NDVI影响研究[J]. 遥感学报, 2008, 12(4):626-632.
[7] Wang F M, Huang J F, Wang X Z, et al. Effects of band position and bandwidth on NDVI measurements of rice at different growth stages[J]. Journal of Remote Sensing, 2008, 12(4):626-632.
[8] 王正兴, 刘闯, Huete Alfredo. 植被指数研究进展:从AVHRR-NDVI到MODIS-EVI[J]. 生态学报, 2003, 23(5):979-987.
[9] Wang Z X, Liu C, Huete Alfredo. From AVHRR-NDVI to MODIS-EVI:Advances in vegetation index research[J]. Acta Ecologica Sinica, 2003, 23(5):979-987.
[10] Teillet P M, Staenz K, William D J. Effects of spectral,spatial,and radiometric characteristics on remote sensing vegetation indices of forested regions[J]. Remote Sensing of Environment, 1997, 61(1):139-149.
[11] Galvao L S, Vitorello I, Filho R A. Effect of band positioning and bandwidth on NDVI measurements of Tropical Savannas[J]. Remote Sensing of Environment, 1999, 67:181-193.
[12] Galvao L S, Vitorello I, Pizarro M A. An adequate band positioning to enhance NDVI contrasts among green vegetation,senescent biomass,and tropical soils[J]. International Journal of Remote Sensing, 2000, 21(9):1953-1960.
[13] 林贤彪, 何诗, 林啸, 等. 波段位置和宽度对河口湿地4种植被NDVI的影响[J]. 遥感技术与应用, 2013, 28(4):714-720.
[14] Lin X B, He S, Lin X, et al. Effects of band position and bandwidth on NDVI measurements of four kinds of estuary wetland vegetation[J]. Remote Sensing Technology and Application, 2013, 8(4):714-720.
[15] 王福民, 黄敬峰, 唐延林, 等. 采用不同光谱波段宽度的归一化植被指数估算水稻叶面积指数[J]. 应用生态学报, 2007, 18(11):2444-2450.
[16] Wang F M, Huang J F, Tang Y L, et al. Estimation of rice LAI by using NDVI at different spectral bandwidths[J]. Chinese Journal of Applied Ecology, 2007, 18(11):2444-2450.
[17] Du H S, Jiang H L, Zhang L F, et al. Evaluation of spectral scale effects in estimation of vegetation leaf area index using spectral indices methods[J]. Chinese Geographical Science, 2016, 26(6):731-744.
[18] 黄婷, 梁亮, 耿笛, 等. 波段宽度对利用植被指数估算小麦LAI的影响[J]. 农业工程学报, 2020, 36(4):168-177.
[19] Huang T, Liang L, Geng D, et al. Effects of band width on estimation of wheat LAI using vegetation index[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(4):168-177.
[20] 贾坤, 姚云军, 魏香琴, 等. 植被覆盖度遥感估算研究进展[J]. 地球科学进展, 2013, 28(7):774-782.
[21] Jia K, Yao Y J, Wei X Q, et al. 2013. A review on fractional vegetation cover estimation using remote sensing[J]. Advance in Earth Sciences, 2013, 28(7):774-782.
[22] Liu F, Wang X C, Wang C K. Measuring vegetation phenology with near-surface remote sensing in a temperate deciduous forest:Effects of sensor type and deployment remote sensing[J]. Remote Sensing, 2019(11):1063.
[23] 王飞龙, 王福民, 胡景辉, 等. 基于相对光谱变量的无人机遥感水稻估产及产量制图[J]. 遥感技术与应用, 2020, 35(2):458-468.
[24] Wang F L, Wang F M, Hu J H, et al. Estimating and mapping rice yield using UAV-hyperspectral imager based relative spectral variates[J]. Remote Sensing Technology and Application, 2020, 35(2):458-468.
[25] 陶惠林, 冯海宽, 杨贵军, 等. 基于无人机数码影像和高光谱数据的冬小麦产量估算对比[J]. 农业工程学报, 2019, 35(23):111-118.
[26] Tao H L, Feng H K, Yang G J, et al. Comparison of winter wheat yields estimated with UAV digital image and hyperspectral data[J]. Transactions of the Chinese Society of Agricultural Engineering, 2019, 35(23):111-118.
[27] Ji L, Albert J P. Performance evaluation of spectral vegetation indices using a statistical sensitivity function[J]. Remote Sensing of Environment, 2007, 106(1):59-65.
[28] Vincini M, Frazzi E. Comparing narrow and broad-band vegetation indices to estimate leaf chlorophyll content in planophile crop canopies[J]. Precision Agriculture, 2011, 12(3):334-344.
[29] Huemmrich K F, Black T A, Jarvis P G, et al. High temporal resolution NDVI phenology from micrometeorological radiation sensors[J]. Journal of Geophysical Research, 1999, 104(22):27935-27944.
-
计量
- 文章访问数: 1047
- PDF下载数: 221
- 施引文献: 0
下载: