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20222026
most citedCloud gap-filling with deep learning for improved grassland monitoring

15 citations · 27 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Tree species mapping in Denmark: A comparison of spectral-temporal features with geospatial foundation model embeddings

Alkiviadis Koukos, Spyros Kondylatos, Thomas Nord-Larsen +3

We map tree species across Denmark using National Forest Inventory plots and EO data, while evaluating the potential of foundation models for large-scale forest characterization. W…

cs.CV2026

Space2Ground 2.0: A Multi-Source Dataset and Framework for Agricultural Monitoring through Fusion of Street-Level and Satellite Imagery

Iason Tsardanidis, Alkiviadis Koukos, George Choumos +2

Accurate and scalable parcel-level agricultural monitoring remains challenging because satellite Earth Observation alone provides only an overhead perspective of agricultural parce…

cs.CV2024★ 15 cited

Cloud gap-filling with deep learning for improved grassland monitoring

Iason Tsardanidis, Alkiviadis Koukos, Vasileios Sitokonstantinou +2

Uninterrupted optical image time series are crucial for the timely monitoring of agricultural land changes, particularly in grasslands. However, the continuity of such time series…

cs.CV2022★ 3 cited

Towards Global Crop Maps with Transfer Learning

Hyun-Woo Jo, Alkiviadis Koukos, Vasileios Sitokonstantinou +2

The continuous increase in global population and the impact of climate change on crop production are expected to affect the food sector significantly. In this context, there is nee…

cs.CV2022★ 1 cited

A Data Cube of Big Satellite Image Time-Series for Agriculture Monitoring

Thanassis Drivas, Vasileios Sitokonstantinou, Iason Tsardanidis +3

The modernization of the Common Agricultural Policy (CAP) requires the large scale and frequent monitoring of agricultural land. Towards this direction, the free and open satellite…

cs.CV2022

Towards Space-to-Ground Data Availability for Agriculture Monitoring

George Choumos, Alkiviadis Koukos, Vasileios Sitokonstantinou +1

The recent advances in machine learning and the availability of free and open big Earth data (e.g., Sentinel missions), which cover large areas with high spatial and temporal resol…