An overview of global leaf area index (LAI): Methods, products, validation, and applications
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …
feedback of vegetation to the climate system. The advancement of the global Earth …
[HTML][HTML] Earth observation based monitoring of forests in Germany: a review
Forests in Germany cover around 11.4 million hectares and, thus, a share of 32% of
Germany's surface area. Therefore, forests shape the character of the country's cultural …
Germany's surface area. Therefore, forests shape the character of the country's cultural …
[HTML][HTML] Current status of Landsat program, science, and applications
Formal planning and development of what became the first Landsat satellite commenced
over 50 years ago in 1967. Now, having collected earth observation data for well over four …
over 50 years ago in 1967. Now, having collected earth observation data for well over four …
Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians
Abstract Information about forest stand species distribution is essential for biodiversity
modelling, forest disturbances, fire hazard and drought monitoring, biomass and carbon …
modelling, forest disturbances, fire hazard and drought monitoring, biomass and carbon …
Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product
Landsat and Sentinel-2 sensors together provide the most widely accessible medium-to-
high spatial resolution multispectral data for a wide range of applications, such as vegetation …
high spatial resolution multispectral data for a wide range of applications, such as vegetation …
[HTML][HTML] Improvement of the Fmask algorithm for Sentinel-2 images: Separating clouds from bright surfaces based on parallax effects
Reliable identification of clouds is necessary for any type of optical remote sensing image
analysis, especially in operational and fully automatic setups. One of the most elaborated …
analysis, especially in operational and fully automatic setups. One of the most elaborated …
Super-resolution-guided progressive pansharpening based on a deep convolutional neural network
Pansharpening and super-resolution (SR) methods share the same target to improve the
spatial resolution of images. Based on this similarity, we propose and develop a novel …
spatial resolution of images. Based on this similarity, we propose and develop a novel …
[HTML][HTML] Improvement in land cover and crop classification based on temporal features learning from Sentinel-2 data using recurrent-convolutional neural network (R …
Understanding the use of current land cover, along with monitoring change over time, is vital
for agronomists and agricultural agencies responsible for land management. The increasing …
for agronomists and agricultural agencies responsible for land management. The increasing …
[HTML][HTML] Quantifying drought effects in Central European grasslands through regression-based unmixing of intra-annual Sentinel-2 time series
Severe droughts caused unprecedented impacts on grasslands in Central Europe in 2018
and 2019. Yet, spatially varying drought impacts on grasslands remain poorly understood as …
and 2019. Yet, spatially varying drought impacts on grasslands remain poorly understood as …
[HTML][HTML] Characterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series
Vegetation phenology has a great impact on land-atmosphere interactions like carbon
cycling, albedo, and water and energy exchanges. To understand and predict these critical …
cycling, albedo, and water and energy exchanges. To understand and predict these critical …