Simulation of Reflectance and Vegetation Indices for Unmanned Aerial Vehicle (UAV) Monitoring of Paddy Fields

被引:43
|
作者
Hashimoto, Naoyuki [1 ]
Saito, Yuki [1 ]
Maki, Masayasu [2 ]
Homma, Koki [1 ]
机构
[1] Tohoku Univ, Grad Sch Agr Sci, Sendai, Miyagi 9808572, Japan
[2] Fukushima Univ, Fac Food & Agr Sci, Fukushima 9601296, Japan
关键词
leaf area index; paddy field; radiative transfer model; unmanned aerial vehicle; vegetation index; LEAF-AREA INDEX; WHEAT; RICE; YIELD; MODEL; ASSIMILATION; RADIATION; FRACTION;
D O I
10.3390/rs11182119
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Reflectance and vegetation indices obtained from aerial images are often used for monitoring crop fields. In recent years, unmanned aerial vehicles (UAVs) have become popular and aerial images have been collected under various solar radiation conditions. The value of observed reflectance and vegetation indices are considered to be affected by solar radiation conditions, which may lead to inaccurate estimations of crop growth. In this study, in order to evaluate the effect of solar radiation conditions on aerial images, canopy reflectance in paddy fields was simulated by a radiative transfer model, FLiES (Forest Light Environmental Simulator), for various solar radiation conditions and canopy structures. Several parameters including solar zenith angle, proportion of diffuse light for incident sunlight, plant height, coordinates of plants and leaf area density, were tested in FLiES. The simulation results showed that the solar zenith angle did not vary the canopy reflectance under the conditions of the proportion of diffuse light at 1.0, but the variation was greater at lower proportions of diffuse light. The difference in reflectance caused by solar radiation was 0.01 and 0.1 at the maximum for red and near-infrared bands, respectively. The simulation results also showed that the differences in reflectance affect vegetation indices (Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index 2 (EVI2)). The variation caused by solar radiation conditions was the least for NDVI and the greatest for SR. However, NDVI was saturated at the least leaf area index (LAI), whereas SR was only slightly saturated. EVI2 was intermediate between SR and NDVI, both in terms of variation and saturation. The simulated reflectance and vegetation indices were similar to those obtained from the aerial images collected in the farmers' paddy fields. These results suggest that a large proportion of diffuse light (close to 1.0) or a middle range of solar zenith angle (45 to 65 degrees) may be desirable for UAV monitoring. However, to maintain flexibility of time and occasion for UAV monitoring, EVI2 should be used to evaluate crop growth, although calibration based on solar radiation conditions is recommended.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] A vehicle routing problem arising in unmanned aerial monitoring
    Zhen, Lu
    Li, Miao
    Laporte, Gilbert
    Wang, Wencheng
    COMPUTERS & OPERATIONS RESEARCH, 2019, 105 : 1 - 11
  • [42] The use of unmanned aerial vehicle imagery in intertidal monitoring
    Konar, Brenda
    Iken, Katrin
    DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2018, 147 : 79 - 86
  • [43] A Nonlinear Filter for Efficient Attitude Estimation of Unmanned Aerial Vehicle (UAV)
    Jarosław Gośliński
    Wojciech Giernacki
    Andrzej Królikowski
    Journal of Intelligent & Robotic Systems, 2019, 95 : 1079 - 1095
  • [44] Design and Control of an Unmanned Aerial Vehicle (UAV) Based on the Coanda Effect
    Jeon, Jaehyeok
    Lee, Hyoju
    Han, Seonhye
    Lee, Hyunyong
    Lee, Choonghan
    Kim, Yong Bum
    Choi, Hyouk Ryeol
    2013 10TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2013, : 129 - 129
  • [45] A Nonlinear Filter for Efficient Attitude Estimation of Unmanned Aerial Vehicle (UAV)
    Goslinski, Jaroslaw
    Giernacki, Wojciech
    Krolikowski, Andrzej
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2019, 95 (3-4) : 1079 - 1095
  • [46] ESTIMATION OF THE VEGETATION COVERAGE FRACTION IN CORN (Zea mays) THROUGH DIGITAL IMAGES TAKEN BY AN UNMANNED AERIAL VEHICLE (UAV)
    Garcia-Martinez, Hector
    Flores-Magdaleno, Hector
    Khalil-Gardezi, Abdul
    Ascencio-Hernandez, Roberto
    Tijerina-Chavez, Leonardo
    Vazquez-Pena, Mario A.
    Mancilla-Villa, Oscar R.
    REVISTA FITOTECNIA MEXICANA, 2020, 43 (04) : 399 - 409
  • [47] Measurement of Greenhouse Gases in UAE by Using Unmanned Aerial Vehicle (UAV)
    Abou-Elnour, Ali
    Odeh, Mohamed
    Abdelrhman, Mohammed
    Balkis, Ahmed
    Amira, Abdelraouf
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2017, 2017, 10168
  • [48] VEGETATION INDEX BASED IN UNMANNED AERIAL VEHICLE (UAV) TO IMPROVE THE MANAGEMENT OF INVASIVE PLANTS IN PROTECTED AREAS, SOUTHERN BRAZIL
    Mallmann, C. L.
    Zaninni, A. F.
    Pereira Filho, W.
    2020 IEEE LATIN AMERICAN GRSS & ISPRS REMOTE SENSING CONFERENCE (LAGIRS), 2020, : 66 - 69
  • [49] Suburban Runoff Modeling for Seasonal Water Management in Rice Paddy Fields: An Elaborated Application of Unmanned Aerial Vehicle Photogrammetry
    Park, Kyu-hyun
    Furumai, Hiroaki
    Kumar, Manish
    ACS ES&T WATER, 2024, 4 (10): : 4323 - 4332
  • [50] Taxi Model of Unmanned Aerial Vehicle: Formulation and Simulation
    Wasim, Maryam
    Ullah, Mukhtar
    Iqbal, Jamshed
    2018 1ST IEEE INTERNATIONAL CONFERENCE ON POWER, ENERGY AND SMART GRID (ICPESG), 2018,