Recent applications of Landsat 8/OLI and Sentinel-2/MSI for land use and land cover map**: A systematic review
Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2
MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land …
MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land …
[HTML][HTML] Map** crop phenology in near real-time using satellite remote sensing: Challenges and opportunities
Crop phenology is critical for agricultural management, crop yield estimation, and
agroecosystem assessment. Traditionally, crop growth stages are observed from the ground …
agroecosystem assessment. Traditionally, crop growth stages are observed from the ground …
Bibliometric analysis of global NDVI research trends from 1985 to 2021
Y Xu, Y Yang, X Chen, Y Liu - Remote Sensing, 2022 - mdpi.com
As one of the earliest remote sensing indices, the Normalized Difference Vegetation Index
(NDVI) has been employed extensively for vegetation research. However, despite an …
(NDVI) has been employed extensively for vegetation research. However, despite an …
[HTML][HTML] Cotton yield estimation model based on machine learning using time series UAV remote sensing data
Crop yield prediction is of great practical significance for farmers to make reasonable
decisions, such as decisions on crop insurance, storage demand, cash flow budget …
decisions, such as decisions on crop insurance, storage demand, cash flow budget …
[HTML][HTML] SITS-Former: A pre-trained spatio-spectral-temporal representation model for Sentinel-2 time series classification
Sentinel-2 images provide a rich source of information for a variety of land cover, vegetation,
and environmental monitoring applications due to their high spectral, spatial, and temporal …
and environmental monitoring applications due to their high spectral, spatial, and temporal …
[HTML][HTML] Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data
J Estévez, M Salinero-Delgado, K Berger… - Remote sensing of …, 2022 - Elsevier
The unprecedented availability of optical satellite data in cloud-based computing platforms,
such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval …
such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval …
Recurrent-based regression of Sentinel time series for continuous vegetation monitoring
Dense time series of optical satellite imagery describing vegetation activity provide essential
information for the efficient and regular monitoring of vegetation. Nevertheless, the temporal …
information for the efficient and regular monitoring of vegetation. Nevertheless, the temporal …
[HTML][HTML] Exploring the potential of Chinese GF-6 images for crop map** in regions with complex agricultural landscapes
T ** is crucial for environment assessment, food security and
agricultural production. However, for the areas with high landscape heterogeneity and …
agricultural production. However, for the areas with high landscape heterogeneity and …
[HTML][HTML] Monitoring cropland phenology on Google Earth Engine using gaussian process regression
Monitoring cropland phenology from optical satellite data remains a challenging task due to
the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to …
the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to …
Monitoring rice crop and yield estimation with Sentinel-2 data
The future success of rice farming will lie in develo** productive, sustainable, and resilient
farming systems in relation to coexistent ecosystems. Thus, accurate information on …
farming systems in relation to coexistent ecosystems. Thus, accurate information on …