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Satellite Imagery

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Advancing food security: Rice yield estimation framework using time-series satellite data & machine learning.

PloS one
Timely and accurately estimating rice yields is crucial for supporting food security management, agricultural policy development, and climate change adaptation in rice-producing countries such as Bangladesh. To address this need, this study introduce...

Application of Machine Learning and Deep Neural Visual Features for Predicting Adult Obesity Prevalence in Missouri.

International journal of environmental research and public health
This research study investigates and predicts the obesity prevalence in Missouri, utilizing deep neural visual features extracted from medium-resolution satellite imagery (Sentinel-2). By applying a deep convolutional neural network (DCNN), the study...

Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data.

Marine pollution bulletin
Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable development goals. The water quality monitoring based on discrete water sample analysis is limited to ...

Downscaling MODIS evapotranspiration into finer resolution using machine learning approach on a small scale, Ribb watershed, Ethiopia.

Environmental monitoring and assessment
By monitoring evapotranspiration (ET), the exchange of water and energy between the soil, plants, and the atmosphere can be controlled. Routine estimations of ET on a daily, monthly, and seasonal basis can give relevant information on small-scale agr...

Particulate matter estimation using satellite datasets: a machine learning approach.

Environmental science and pollution research international
In the present work, it is the first time an interpretable machine learning model has been developed for the estimation of Particulate Matter 10 µm (PM) concentrations over India using Aerosol Optical Depth (AOD) from two different satellites, i.e. I...

Extraction of agricultural plastic greenhouses based on a U-Net convolutional neural network coupled with edge expansion and loss function improvement.

Journal of the Air & Waste Management Association (1995)
Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more ...

Plastic debris detection along coastal waters using Sentinel-2 satellite data and machine learning techniques.

Marine pollution bulletin
Few studies have effectively shown how to use satellites that gather optical data to monitor plastic debris in the marine environment. For the first time, floating macro-plastics distinguishable from seaweed are identified in optical data from the Eu...

Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning.

PloS one
In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector, a correct economic balance of the farm depends on making the right decisions. For this purpose, hav...

Assessing the efficiency of pixel-based and object-based image classification using deep learning in an agricultural Mediterranean plain.

Environmental monitoring and assessment
Recent advancements in satellite technology have greatly expanded data acquisition capabilities, making satellite imagery more accessible. Despite these strides, unlocking the full potential of satellite images necessitates efficient interpretation. ...

Aboveground biomass estimation in a grassland ecosystem using Sentinel-2 satellite imagery and machine learning algorithms.

Environmental monitoring and assessment
The grassland ecosystem forms a critical part of the natural ecosystem, covering up to 15-26% of the Earth's land surface. Grassland significantly impacts the carbon cycle and climate regulation by storing carbon dioxide. The organic matter found in ...