Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
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 …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Smart farming becomes even smarter with deep learning—a bibliographical analysis
Z Ünal - IEEE access, 2020 - ieeexplore.ieee.org
Smart farming is a new concept that makes agriculture more efficient and effective by using
advanced information technologies. The latest advancements in connectivity, automation …
advanced information technologies. The latest advancements in connectivity, automation …
[HTML][HTML] Delineation of agricultural fields using multi-task BsiNet from high-resolution satellite images
This paper presents a new multi-task neural network, called BsiNet, to delineate agricultural
fields from high-resolution satellite images. BsiNet is modified from a Psi-Net by structuring …
fields from high-resolution satellite images. BsiNet is modified from a Psi-Net by structuring …
U-Net convolutional networks for mining land cover classification based on high-resolution UAV imagery
Mining activities are the leading cause of deforestation, land-use changes, and pollution.
Land use/cover mapping in Vietnam every five years is not useful to monitor land covers in …
Land use/cover mapping in Vietnam every five years is not useful to monitor land covers in …
Coastal wetland classification with deep u-net convolutional networks and sentinel-2 imagery: A case study at the tien yen estuary of vietnam
The natural wetland areas in Vietnam, which are transition areas from inland and ocean,
play a crucial role in minimizing coastal hazards; however, during the last two decades …
play a crucial role in minimizing coastal hazards; however, during the last two decades …
Mapping the complex crop rotation systems in Southern China considering cropping intensity, crop diversity, and their seasonal dynamics
Y Liu, Q Yu, Q Zhou, C Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Crop rotation increases crop yield, improves soil health, and reduces plant disease.
Mapping crop rotation is difficult because crop data from a single time point do not …
Mapping crop rotation is difficult because crop data from a single time point do not …
Agricultural field boundary delineation with satellite image segmentation for high-resolution crop mapping: A case study of rice paddy
Parcel-level cropland maps are an essential data source for crop yield estimation, precision
agriculture, and many other agronomy applications. Here, we proposed a rice field mapping …
agriculture, and many other agronomy applications. Here, we proposed a rice field mapping …
Extraction of cropland field parcels with high resolution remote sensing using multi-task learning
L Xu, P Yang, J Yu, F Peng, J Xu, S Song… - European Journal of …, 2023 - Taylor & Francis
Parcel-level farmland information contains rich spatial distribution and boundary details,
which is crucial for digital agriculture and agricultural resource surveys. However, the spatial …
which is crucial for digital agriculture and agricultural resource surveys. However, the spatial …
Farm parcel delineation using spatio-temporal convolutional networks
Farm parcel delineation (delineation of boundaries of farmland parcels/segmentation of
farmland areas) provides cadastral data that is important in developing and managing …
farmland areas) provides cadastral data that is important in developing and managing …