[HTML][HTML] Fifty years of Landsat science and impacts
Since 1972, the Landsat program has been continually monitoring the Earth, to now provide
50 years of digital, multispectral, medium spatial resolution observations. Over this time …
50 years of digital, multispectral, medium spatial resolution observations. Over this time …
A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses
The global population is expected to reach 9.8 billion by 2050. There is an exponential
growth of food production to meet the needs of the growing population. However, the limited …
growth of food production to meet the needs of the growing population. However, the limited …
Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
Crop monitoring information is essential for food security and to improve our understanding
of the role of agriculture on climate change, among others. Remotely sensing optical and …
of the role of agriculture on climate change, among others. Remotely sensing optical 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] Landsat-8: Science and product vision for terrestrial global change research
Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution
measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short …
measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short …
What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?
ER Hunt Jr, CST Daughtry - International journal of remote sensing, 2018 - Taylor & Francis
Remote sensing from unmanned aircraft systems (UAS) was expected to be an important
new technology to assist farmers with precision agriculture, especially crop nutrient …
new technology to assist farmers with precision agriculture, especially crop nutrient …
Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning
V Sagan, M Maimaitijiang, S Bhadra… - ISPRS journal of …, 2021 - Elsevier
Agricultural management at field-scale is critical for improving yield to address global food
security, as providing enough food for the world's growing population has become a wicked …
security, as providing enough food for the world's growing population has become a wicked …
[HTML][HTML] Use time series NDVI and EVI to develop dynamic crop growth metrics for yield modeling
The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)
derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery are …
derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery are …
Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics
We used data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) in
association with county-level data from the United States Department of Agriculture (USDA) …
association with county-level data from the United States Department of Agriculture (USDA) …
A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variables
J Wang, P Wang, H Tian, K Tansey, J Liu… - … and Electronics in …, 2023 - Elsevier
Accurate and timely crop yield estimation is crucial for crop market planning and food
security. Combining remotely sensed big data with deep learning for yield estimation has …
security. Combining remotely sensed big data with deep learning for yield estimation has …