Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review DOI Creative Commons
Mateo Gašparović, Ivan Pilaš, Dorijan Radočaj

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 12020 - 12020

Published: Dec. 22, 2024

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, forest agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global continuous monitoring vegetation cycles. This review provides brief overview key EO satellite missions, including advanced very-high resolution radiometer (AVHRR), moderate imaging spectroradiometer (MODIS), Landsat program, which an important capturing dynamics at various spatial temporal scales. Recent advancements machine learning techniques further enhanced prediction capabilities, offering promising approaches short-term cropland suitability assessment. Data cubes, organize multidimensional data, provide innovative framework enhancing analyses by integrating diverse data sources simplifying access processing. highlights potential satellite-based monitoring, models, cube infrastructure advancing research insights into current trends, challenges, future directions.

Language: Английский

Quantifying the relative importance of natural and human factors on vegetation dynamics in China’s western frontiers during 2010-2021 DOI
Wenyang Shi, Ping Lü, Haoxuan Yang

et al.

Environmental Research, Journal Year: 2025, Volume and Issue: unknown, P. 121120 - 121120

Published: Feb. 1, 2025

Language: Английский

Citations

0
Quantifying the contributions of climate change and human activities to grassland dynamics in southwest of China using a spatiotemporally varying residual method DOI Creative Commons
Tao Chen, Jia Chen, Xiao Wei

et al.

International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)

Published: April 21, 2025

Language: Английский

Citations

0
Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review DOI Creative Commons
Mateo Gašparović, Ivan Pilaš, Dorijan Radočaj

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 12020 - 12020

Published: Dec. 22, 2024

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, forest agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global continuous monitoring vegetation cycles. This review provides brief overview key EO satellite missions, including advanced very-high resolution radiometer (AVHRR), moderate imaging spectroradiometer (MODIS), Landsat program, which an important capturing dynamics at various spatial temporal scales. Recent advancements machine learning techniques further enhanced prediction capabilities, offering promising approaches short-term cropland suitability assessment. Data cubes, organize multidimensional data, provide innovative framework enhancing analyses by integrating diverse data sources simplifying access processing. highlights potential satellite-based monitoring, models, cube infrastructure advancing research insights into current trends, challenges, future directions.

Language: Английский

Citations

2