Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

T Kattenborn, J Leitloff, F Schiefer, S Hinz - ISPRS journal of …, 2021 - Elsevier
Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …

Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications

T Hoeser, F Bachofer, C Kuenzer - Remote Sensing, 2020 - mdpi.com
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …

[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

PTT Ngo, M Panahi, K Khosravi, O Ghorbanzadeh… - Geoscience …, 2021 - Elsevier
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …

Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection

O Ghorbanzadeh, T Blaschke, K Gholamnia… - Remote Sensing, 2019 - mdpi.com
There is a growing demand for detailed and accurate landslide maps and inventories
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …

Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks

BG Weinstein, S Marconi, S Bohlman, A Zare, E White - Remote Sensing, 2019 - mdpi.com
Remote sensing can transform the speed, scale, and cost of biodiversity and forestry
surveys. Data acquisition currently outpaces the ability to identify individual organisms in …

Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images

J Zheng, H Fu, W Li, W Wu, L Yu, S Yuan… - ISPRS Journal of …, 2021 - Elsevier
For both the positive economic benefit and the negative ecological impact of the rapid
expansion of oil palm plantations in tropical developing countries, it is significant to achieve …

Surveying coconut trees using high-resolution satellite imagery in remote atolls of the Pacific Ocean

J Zheng, S Yuan, W Wu, W Li, L Yu, H Fu… - Remote Sensing of …, 2023 - Elsevier
Coconut (Cocos nucifera L.) is one of the world's most economically important tree species,
and coconut palm plantations dominate many islands and tropical coastlines. However, the …

Plant image recognition with deep learning: A review

Y Chen, Y Huang, Z Zhang, Z Wang, B Liu, C Liu… - … and Electronics in …, 2023 - Elsevier
Significant advances in the field of digital image processing have been achieved in recent
years using deep learning, which has significantly exceeded previous methods. Deep …

Very high resolution object-based land use–land cover urban classification using extreme gradient boosting

S Georganos, T Grippa, S Vanhuysse… - … and remote sensing …, 2018 - ieeexplore.ieee.org
In this letter, the recently developed extreme gradient boosting (Xgboost) classifier is
implemented in a very high resolution (VHR) object-based urban land use-land cover …

Identification of citrus trees from unmanned aerial vehicle imagery using convolutional neural networks

O Csillik, J Cherbini, R Johnson, A Lyons, M Kelly - Drones, 2018 - mdpi.com
Remote sensing is important to precision agriculture and the spatial resolution provided by
Unmanned Aerial Vehicles (UAVs) is revolutionizing precision agriculture workflows for …