GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography

W Li, CY Hsu - ISPRS International Journal of Geo-Information, 2022 - mdpi.com
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …

[HTML][HTML] From parcel to continental scale–A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations

R d'Andrimont, A Verhegghen, G Lemoine… - Remote sensing of …, 2021 - Elsevier
Detailed parcel-level crop type mapping for the whole European Union (EU) is necessary for
the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in …

[HTML][HTML] Agricultural policy in the era of digitalisation

MH Ehlers, R Huber, R Finger - Food policy, 2021 - Elsevier
Digitalisation in the agricultural sector continues to expand. At the same time demands for
an agricultural policy offering better support for sustainability become increasingly fervent …

The first wetland inventory map of newfoundland at a spatial resolution of 10 m using sentinel-1 and sentinel-2 data on the google earth engine cloud computing …

M Mahdianpari, B Salehi, F Mohammadimanesh… - Remote Sensing, 2018 - mdpi.com
Wetlands are one of the most important ecosystems that provide a desirable habitat for a
great variety of flora and fauna. Wetland mapping and modeling using Earth Observation …

Positioning methods and the use of location and activity data in forests

RF Keefe, AM Wempe, RM Becker, EG Zimbelman… - Forests, 2019 - mdpi.com
In this paper, we provide an overview of positioning systems for moving resources in forest
and fire management and review the related literature. Emphasis is placed on the accuracy …

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 …

[HTML][HTML] Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and-2 time series

R d'Andrimont, M Taymans, G Lemoine… - Remote sensing of …, 2020 - Elsevier
A novel methodology is proposed to robustly map oil seed rape (OSR) flowering phenology
from time series generated from the Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) …

Performance and the optimal integration of Sentinel-1/2 time-series features for crop classification in Northern Mongolia

B Tuvdendorj, H Zeng, B Wu, A Elnashar, M Zhang… - Remote Sensing, 2022 - mdpi.com
Accurate and early crop-type maps are essential for agricultural policy development and
food production assessment at regional and national levels. This study aims to produce a …

National scale land cover classification for ecosystem services mapping and assessment, using multitemporal copernicus EO data and google earth engine

N Verde, IP Kokkoris, C Georgiadis, D Kaimaris… - Remote Sensing, 2020 - mdpi.com
Land-Use/Land-Cover (LULC) products are a common source of information and a key input
for spatially explicit models of ecosystem service (ES) supply and demand. Global …

[HTML][HTML] Monitoring crop phenology with street-level imagery using computer vision

R d'Andrimont, M Yordanov… - … and Electronics in …, 2022 - Elsevier
Street-level imagery holds a significant potential to scale-up in-situ data collection. This is
enabled by combining the use of cheap high-quality cameras with recent advances in deep …