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[HTML][HTML] Revolutionizing the circular economy through new technologies: A new era of sustainable progress
Nowadays the pace of production and consumption is reaching environmentally
unsustainable levels. In this regard, the great technological advances developed in recent …
unsustainable levels. In this regard, the great technological advances developed in recent …
[HTML][HTML] A systematic review of trustworthy artificial intelligence applications in natural disasters
Artificial intelligence (AI) holds significant promise for advancing natural disaster
management through the use of predictive models that analyze extensive datasets, identify …
management through the use of predictive models that analyze extensive datasets, identify …
Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives
Extreme events such as heat waves and cold spells, droughts, heavy rain, and storms are
particularly challenging to predict accurately due to their rarity and chaotic nature, and …
particularly challenging to predict accurately due to their rarity and chaotic nature, and …
[HTML][HTML] Monitoring and predicting the influences of land use/land cover change on cropland characteristics and drought severity using remote sensing techniques
Abstract The Federal University of Technology at Akure (FUTA) in Nigeria is experiencing
ongoing development that is leading to the replacement of agricultural and forestry land …
ongoing development that is leading to the replacement of agricultural and forestry land …
Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India
To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in
Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together …
Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together …
Future food production prediction using AROA based hybrid deep learning model in agri-sector
S Baswaraju, VU Maheswari, K Chennam… - Human-Centric …, 2023 - Springer
Policymaking and administration of national tactics of action for food security rely heavily on
advances in models for accurate estimation of food output. In several fields, including food …
advances in models for accurate estimation of food output. In several fields, including food …
Application of machine learning and emerging remote sensing techniques in hydrology: A state-of-the-art review and current research trends
A Saha, SC Pal - Journal of Hydrology, 2024 - Elsevier
Water, one of the most valuable resources on Earth, is the subject of the study of hydrology,
which is of utmost importance. Satellite remote sensing (RS) has emerged as a critical tool …
which is of utmost importance. Satellite remote sensing (RS) has emerged as a critical tool …
Harnessing urban analytics and machine learning for sustainable urban development: A multidimensional framework for modeling environmental impacts of …
Sustainable urban development is crucial for managing natural resources and mitigating
environmental impacts induced by rapid urbanization. This study demonstrates an …
environmental impacts induced by rapid urbanization. This study demonstrates an …
[HTML][HTML] Combing transfer learning with the OPtical TRApezoid Model (OPTRAM) to diagnosis small-scale field soil moisture from hyperspectral data
R Du, Y **ang, F Zhang, J Chen, H Shi, H Liu… - Agricultural Water …, 2024 - Elsevier
Accurate, timely, and continuous soil moisture information is helpful for crop stress diagnosis
and irrigation management decision. OPtical TRApezoid Model (OPTRAM) based on optical …
and irrigation management decision. OPtical TRApezoid Model (OPTRAM) based on optical …
Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm
Droughts pose a severe environmental risk in countries that rely heavily on agriculture,
resulting in heightened levels of concern regarding food security and livelihood …
resulting in heightened levels of concern regarding food security and livelihood …