Remote sensing in agriculture—accomplishments, limitations, and opportunities

S Khanal, K Kc, JP Fulton, S Shearer, E Ozkan - Remote sensing, 2020 - mdpi.com
Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early
warning system, allowing the agricultural community to intervene early on to counter …

Short-term traffic flow prediction for urban road sections based on time series analysis and LSTM_BILSTM method

C Ma, G Dai, J Zhou - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
The real-time performance and accuracy of traffic flow prediction directly affect the efficiency
of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of …

Road network traffic flow prediction: A personalized federated learning method based on client reputation

G Dai, J Tang, J Zeng, C Hu, C Zhao - Computers and Electrical …, 2024 - Elsevier
Accurate traffic flow prediction can provide effective decision-making support for traffic
management, alleviate traffic congestion, and improve road traffic efficiency. Traffic flow data …

[HTML][HTML] Evaluation of food security based on remote sensing data—Taking Egypt as an example

S Shi, Y Ye, R **ao - Remote Sensing, 2022 - mdpi.com
Egypt, a country with a harsh natural environment and rapid population growth, is facing
difficulty in ensuring its national food security. A novel model developed for assessing food …

Machine learning-based crop recognition from aerial remote sensing imagery

Y Tian, C Yang, W Huang, J Tang, X Li… - Frontiers of Earth Science, 2021 - Springer
Timely and accurate acquisition of crop distribution and planting area information is
important for making agricultural planning and management decisions. This study employed …

[PDF][PDF] A Review on Classification of Land Use/Land Cover change assessment based on the Normalized Difference Vegetation Index

A Somayajula, VA Kiranmai, D Ghai… - ournal of Critical …, 2020 - researchgate.net
Land cover is more effected spatially and temporarily based on land use changes.
Depending on increasing demands of population growth, changes in Land Use/Land Cover …

Investigation on the use of ensemble learning and big data in crop identification

S Ahmed, AS Mahmoud, E Farg, AM Mohamed… - Heliyon, 2023 - cell.com
The agriculture sector in Egypt faces several problems, such as climate change, water
storage, and yield variability. The comprehensive capabilities of Big Data (BD) can help in …

Fuzzy machine learning model for class-based flood damage assessment from planetscope temporal data

AP Sarathamani, A Kumar - Journal of Applied Remote …, 2024 - spiedigitallibrary.org
Natural disasters are calamitous events with causes and effects that need to be examined.
Among them, floods are one of the most devastating natural disasters that demand constant …

[HTML][HTML] Characterising the land surface phenology of middle eastern countries using moderate resolution landsat data

SH Qader, R Priyatikanto, NR Khwarahm, AJ Tatem… - Remote Sensing, 2022 - mdpi.com
Global change impacts including climate change, increased CO2 and nitrogen deposition
can be determined through a more precise characterisation of Land Surface Phenology …

Pattern‐based calibration of cellular automata by genetic algorithm and Shannon relative entropy

E Momeni, A Antipova - Transactions in GIS, 2020 - Wiley Online Library
While cellular automata (CA) are considered an effective algorithm to model urban growth,
their precise calibration can be challenging. The Shannon relative index (SRI) is an indicator …