Satellite- and drone-based remote sensing of crops and soils for smart farming - a review

被引:49
|
作者
Inoue, Yoshio [1 ]
机构
[1] Univ Tokyo, Grad Sch Engn, Tokyo 1138656, Japan
关键词
Diagnosis; geoinformation; plant nutrition; precision farming; soil fertility; spectral image; MOISTURE; AGRICULTURE; BIOMASS;
D O I
10.1080/00380768.2020.1738899
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Present climate and socioeconomic issues would threaten the global food and environmental security. Smart farming (SF) based on advances in sensing, robotic, and information and communication technologies is a promising approach to support the efficient, sustainable, and profitable crop production. This paper discusses the background needs for SF and the role of remote sensing. Recent advances in remote sensing technology (platforms, sensors, algorithms) for diagnostic information of crops and soils are reviewed based on some leading case studies. The operation of a bundle of similar satellites (constellation) allows timely or frequent observations, and their spatial resolution (1 similar to 10 m) is applicable to agricultural regions of relatively small farmlands. The efficient use of high-resolution satellite sensors would strongly support the diagnostics and decision-making in SF on regional scales. Drone-based remote sensing would allow low-cost, high resolution, and flexible observations of crops and soils. Diagnostic information on crop growth, water stress, soil fertility, weed, disease, lodging, and 3D topography can be created from the optical, thermal and/or video images. The linkage between the remote sensing function and drone-based application of seeds, pesticides, fertilizes would greatly enhance the efficiency of labor and material applications and profitability.
引用
收藏
页码:798 / 810
页数:13
相关论文
共 50 条
  • [1] A New Classification Method for Drone-Based Crops in Smart Farming
    Al-Rami, Bandar
    Alheeti, Khattab M. Ali
    Aldosari, Waleed M.
    Alshahrani, Saeed Matar
    Al-Abrez, Shahad Mahdi
    [J]. International Journal of Interactive Mobile Technologies, 2022, 16 (09) : 164 - 174
  • [2] Spectral and 3d measurement by drone-based remote sensing of farmland-geo-lnformation for smart farming
    Inoue, Yoshio
    Yokoyama, Masaki
    [J]. Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2019, 85 (03): : 236 - 242
  • [3] System Architecture for Autonomous Drone-Based Remote Sensing
    Koutsoubelias, Manos
    Grigoropoulos, Nasos
    Polychronis, Giorgos
    Badakis, Giannis
    Lalis, Spyros
    [J]. MOBILE AND UBIQUITOUS SYSTEMS: COMPUTING, NETWORKING AND SERVICES, 2022, 419 : 220 - 242
  • [4] A Review on Drone-Based Data Solutions for Cereal Crops
    Panday, Uma Shankar
    Pratihast, Arun Kumar
    Aryal, Jagannath
    Kayastha, Rijan Bhakta
    [J]. DRONES, 2020, 4 (03) : 1 - 29
  • [5] A drone-based movable smart remote control for household appliances
    Fukushiro, Makoto
    Kitagawa, Yusuke
    Banno, Ryohei
    [J]. IEICE COMMUNICATIONS EXPRESS, 2022, 11 (12): : 778 - 783
  • [6] Drone-Based Multispectral Remote Sensing Inversion for Typical Crop Soil Moisture under Dry Farming Conditions
    Qu, Tengteng
    Li, Yaoyu
    Zhao, Qixin
    Yin, Yunzhen
    Wang, Yuzhi
    Li, Fuzhong
    Zhang, Wuping
    [J]. AGRICULTURE-BASEL, 2024, 14 (03):
  • [7] DRONE-BASED OPTICAL, THERMAL, AND 3D SENSING FOR DIAGNOSTIC INFORMATION IN SMART FARMING - SYSTEMS AND ALGORITHMS
    Inoue, Yoshio
    Yokoyama, Masaki
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 7266 - 7269
  • [8] Comparative assessment of satellite- and drone-based vegetation indices to predict arthropod biomass in shrub-steppes
    Traba, J.
    Gomez-Catasus, J.
    Barrero, A.
    Bustillo-de la Rosa, D.
    Zurdo, J.
    Hervas, I
    Perez-Granados, C.
    Garcia de la Morena, E. L.
    Santamaria, A.
    Reverter, M.
    [J]. ECOLOGICAL APPLICATIONS, 2022, 32 (08)
  • [9] Towards Effective Aerial Drone-based Hyperspectral Remote Sensing of Coral Reefs
    Kok, Jon
    Bainbridge, Scott
    Olsen, Melanie
    Rigby, Paul
    [J]. GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST, 2020,
  • [10] Drone-Based Remote Sensing for Research on Wind Erosion in Drylands: Possible Applications
    Zhang, Junzhe
    Guo, Wei
    Zhou, Bo
    Okin, Gregory S.
    [J]. REMOTE SENSING, 2021, 13 (02) : 1 - 19