A review of remote sensing for water quality retrieval: progress and challenges

H Yang, J Kong, H Hu, Y Du, M Gao, F Chen - Remote Sensing, 2022 - mdpi.com
Water pollution has become one of the most serious issues threatening water environments,
water as a resource and human health. The most urgent and effective measures rely on …

Challenges in modeling and predicting floods and droughts: A review

MI Brunner, L Slater, LM Tallaksen… - Wiley Interdisciplinary …, 2021 - Wiley Online Library
Predictions of floods, droughts, and fast drought‐flood transitions are required at different
time scales to develop management strategies targeted at minimizing negative societal and …

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

H Chu, X Luo, Z Ouyang, WS Chan, S Dengel… - Agricultural and Forest …, 2021 - Elsevier
Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with
the eddy-covariance technique (eg, FLUXNET2015, AmeriFlux BASE) are widely used to …

Unmanned aerial vehicles in hydrology and water management: Applications, challenges, and perspectives

BS Acharya, M Bhandari, F Bandini… - Water Resources …, 2021 - Wiley Online Library
The hydrologic sciences and water resources management have long depended on a
combination of in situ measurements and remotely sensed data for research and regulatory …

Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning

M Cheng, X Jiao, Y Liu, M Shao, X Yu, Y Bai… - Agricultural Water …, 2022 - Elsevier
An accurate in-field estimate of soil moisture content (SMC) is critical for precision irrigation
management. Current ground methods to measure SMC were limited by the disadvantages …

High-resolution crop yield and water productivity dataset generated using random forest and remote sensing

M Cheng, X Jiao, L Shi, J Penuelas, L Kumar, C Nie… - Scientific data, 2022 - nature.com
Accurate and high-resolution crop yield and crop water productivity (CWP) datasets are
required to understand and predict spatiotemporal variation in agricultural production …

[HTML][HTML] Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

S Wang, K Guan, Z Wang, EA Ainsworth… - International Journal of …, 2021 - Elsevier
Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and
biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can …

Uncrewed aerial systems in water resource management and monitoring: a review of sensors, applications, software, and issues

V Mishra, R Avtar, AP Prathiba… - Advances in Civil …, 2023 - Wiley Online Library
Uncrewed aerial systems (UASs) are becoming very popular in the domain of water
resource map** and management (WRMM). Being a cheaper and quicker option capable …

Towards smart irrigation: A literature review on the use of geospatial technologies and machine learning in the management of water resources in arboriculture

Y Ahansal, M Bouziani, R Yaagoubi, I Sebari, K Sebari… - Agronomy, 2022 - mdpi.com
Agriculture consumes an important ratio of the water reserve in irrigated areas. The
improvement of irrigation is becoming essential to reduce this high water consumption by …

Radiance-based NIRv as a proxy for GPP of corn and soybean

G Wu, K Guan, C Jiang, B Peng, H Kimm… - Environmental …, 2020 - iopscience.iop.org
Substantial uncertainty exists in daily and sub-daily gross primary production (GPP)
estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that …