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

Y Inoue - Soil Science and Plant Nutrition, 2020 - Taylor & Francis
Present climate and socioeconomic issues would threaten the global food and
environmental security. Smart farming (SF) based on advances in sensing, robotic, and …

Remote sensing-based crop lodging assessment: Current status and perspectives

S Chauhan, R Darvishzadeh, M Boschetti… - ISPRS journal of …, 2019 - Elsevier
Rapid and quantitative assessment of crop lodging is important for understanding the
causes of the phenomena, improving crop management, making better production and …

Transfer-learning-based approach for leaf chlorophyll content estimation of winter wheat from hyperspectral data

Y Zhang, J Hui, Q Qin, Y Sun, T Zhang, H Sun… - Remote Sensing of …, 2021 - Elsevier
Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the
photosynthetic productivity estimation and crop growth monitoring in agricultural …

Exploiting the centimeter resolution of UAV multispectral imagery to improve remote-sensing estimates of canopy structure and biochemistry in sugar beet crops

S Jay, F Baret, D Dutartre, G Malatesta, S Héno… - Remote Sensing of …, 2019 - Elsevier
The recent emergence of unmanned aerial vehicles (UAV) has opened a new horizon in
vegetation remote sensing, especially for agricultural applications. However, the benefits of …

Improved estimation of leaf chlorophyll content of row crops from canopy reflectance spectra through minimizing canopy structural effects and optimizing off-noon …

D Li, JM Chen, X Zhang, Y Yan, J Zhu, H Zheng… - Remote Sensing of …, 2020 - Elsevier
Leaf chlorophyll content (LCC), as an important indicator of photosynthetic capacity and
nitrogen status, has been non-destructively estimated from canopy reflectance spectra in …

Data products, quality and validation of the DLR earth sensing imaging spectrometer (DESIS)

K Alonso, M Bachmann, K Burch, E Carmona, D Cerra… - Sensors, 2019 - mdpi.com
Imaging spectrometry from aerial or spaceborne platforms, also known as hyperspectral
remote sensing, provides dense sampled and fine structured spectral information for each …

Dynamic monitoring of biomass of rice under different nitrogen treatments using a lightweight UAV with dual image-frame snapshot cameras

H Cen, L Wan, J Zhu, Y Li, X Li, Y Zhu, H Weng, W Wu… - Plant Methods, 2019 - Springer
Background Unmanned aerial vehicle (UAV)-based remote sensing provides a flexible, low-
cost, and efficient approach to monitor crop growth status at fine spatial and temporal …

Feasibility of combining deep learning and RGB images obtained by unmanned aerial vehicle for leaf area index estimation in rice

T Yamaguchi, Y Tanaka, Y Imachi, M Yamashita… - Remote Sensing, 2020 - mdpi.com
Leaf area index (LAI) is a vital parameter for predicting rice yield. Unmanned aerial vehicle
(UAV) surveillance with an RGB camera has been shown to have potential as a low-cost …

[HTML][HTML] Effects of prediction accuracy of the proportion of vegetation cover on land surface emissivity and temperature using the NDVI threshold method

E Neinavaz, AK Skidmore, R Darvishzadeh - International Journal of …, 2020 - Elsevier
Predicting land surface energy budgets requires precise information of land surface
emissivity (LSE) and land surface temperature (LST). LST is one of the essential climate …

Early detection of plant physiological responses to different levels of water stress using reflectance spectroscopy

M Maimaitiyiming, A Ghulam, A Bozzolo, JL Wilkins… - Remote Sensing, 2017 - mdpi.com
Early detection of water stress is critical for precision farming for improving crop productivity
and fruit quality. To investigate varying rootstock and irrigation interactions in an open …