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] Assimilation of remote sensing into crop growth models: Current status and perspectives
Timely monitoring of crop lands is important in order to make agricultural activities more
sustainable, as well as ensuring food security. The use of Earth Observation (EO) data …
sustainable, as well as ensuring food security. The use of Earth Observation (EO) data …
A review of data assimilation of remote sensing and crop models
Timely and accurate estimation of crop yield before harvest to allow crop yields
management decision-making at a regional scale is crucial for national food policy and …
management decision-making at a regional scale is crucial for national food policy and …
Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods
Closing the yield gap between actual and potential wheat yields in Australia is important to
meet the growing global demand for food. The identification of hotspots of the yield gap …
meet the growing global demand for food. The identification of hotspots of the yield gap …
[HTML][HTML] Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops
A Kross, H McNairn, D Lapen, M Sunohara… - International Journal of …, 2015 - Elsevier
Leaf area index (LAI) and biomass are important indicators of crop development and the
availability of this information during the growing season can support farmer decision …
availability of this information during the growing season can support farmer decision …
Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS)
Several global gross primary production (GPP) and evapotranspiration (ET) remote sensing
products exist, mainly provided by machine-learning (eg MPI-BGC) and semi-empirical (eg …
products exist, mainly provided by machine-learning (eg MPI-BGC) and semi-empirical (eg …
A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level
Understanding large‐scale crop growth and its responses to climate change are critical for
yield estimation and prediction, especially under the increased frequency of extreme climate …
yield estimation and prediction, especially under the increased frequency of extreme climate …
Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model
To predict regional-scale winter wheat yield, we developed a crop model and data
assimilation framework that assimilated leaf area index (LAI) derived from Landsat TM and …
assimilation framework that assimilated leaf area index (LAI) derived from Landsat TM and …
[HTML][HTML] Challenges and opportunities in mapping land use intensity globally
Highlights•Global patterns of land use intensity are poorly understood, particularly in the
developing world.•The multidimensionality of land use intensity should be considered by …
developing world.•The multidimensionality of land use intensity should be considered by …
A million kernels of truth: Insights into scalable satellite maize yield mapping and yield gap analysis from an extensive ground dataset in the US Corn Belt
Crop yield maps estimated from satellite data increasingly are used to understand drivers of
yield trends and variability, yet satellite-derived regional maps are rarely compared with …
yield trends and variability, yet satellite-derived regional maps are rarely compared with …