Remote sensing for agricultural applications: A meta-review
Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount
for human livelihood. Today, this role must be satisfied within a context of environmental …
for human livelihood. Today, this role must be satisfied within a context of environmental …
Plant phenoty**: from bean weighing to image analysis
Plant phenoty** refers to a quantitative description of the plant's anatomical,
ontogenetical, physiological and biochemical properties. Today, rapid developments are …
ontogenetical, physiological and biochemical properties. Today, rapid developments are …
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Background Above-ground biomass (AGB) is a basic agronomic parameter for field
investigation and is frequently used to indicate crop growth status, the effects of agricultural …
investigation and is frequently used to indicate crop growth status, the effects of agricultural …
High resolution wheat yield map** using Sentinel-2
ML Hunt, GA Blackburn, L Carrasco… - Remote Sensing of …, 2019 - Elsevier
Accurate crop yield estimates are important for governments, farmers, scientists and
agribusiness. This paper provides a novel demonstration of the use of freely available …
agribusiness. This paper provides a novel demonstration of the use of freely available …
Winter wheat yield prediction at county level and uncertainty analysis in main wheat-producing regions of China with deep learning approaches
Timely and accurate forecasting of crop yields is crucial to food security and sustainable
development in the agricultural sector. However, winter wheat yield estimation and …
development in the agricultural sector. However, winter wheat yield estimation and …
Development of an accurate low cost NDVI imaging system for assessing plant health
Background Spectral imaging is a key method for high throughput phenoty** that can be
related to a large variety of biological parameters. The Normalised Difference Vegetation …
related to a large variety of biological parameters. The Normalised Difference Vegetation …
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 …
Contribution of remote sensing on crop models: a review
Crop growth models simulate the relationship between plants and the environment to predict
the expected yield for applications such as crop management and agronomic decision …
the expected yield for applications such as crop management and agronomic decision …
Remote sensing of ecosystem services: A systematic review
Appropriate integration of remote sensing technologies into ecosystem services concepts
and practices leads to potential practical benefits for the protection of biodiversity and the …
and practices leads to potential practical benefits for the protection of biodiversity and the …
Crop yield forecasting on the Canadian Prairies using MODIS NDVI data
Although Normalised Difference Vegetation Index (NDVI) data derived from the advanced
very high resolution radiometer (AVHRR) sensor have been extensively used to assess crop …
very high resolution radiometer (AVHRR) sensor have been extensively used to assess crop …