Agricultural and Environmental Modelling
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Related Articles from SNS
Modeling life beneath our feet: A step towards realistic soil ecology at the landscape scale
Modeling life beneath our feet: A step towards realistic soil ecology at the landscape scale Sadie Harley Scientific Editor Andrew Zinin Lead Editor As soil health becomes a defining goal of the EU Soil Strategy for 2030, researchers at Aarhus University are rethinking how we model what lives beneath our feet. Their new spatially explicit population model for the soil invertebrate Folsomia candida (springtails) marks a significant step beyond standard laboratory testing. For more than 60...
Modelling habitat suitability for multiple priority weed species to predict invasion hotspots for strategic management in complex landscapes
Established invasive alien plant species require ongoing, costly management to reduce harm to agricultural and environmental values. Heterogeneous landscapes are often under threat from multiple long-established invasive plants, whose simultaneous management presents strategic and tactical challenges. Systematic monitoring of weed populations enables more strategic management by providing more detailed insights into invasion threats than the more readily available presence-only data.
Diffusion Models for Hyperspectral Image Analysis: A Comprehensive Review
Announce Type: replace-cross Abstract: Hyperspectral image (HSI) analysis plays a critical role in remote sensing, agriculture, and environmental monitoring. However, traditional methods often struggle to handle the high dimensionality, spectral redundancy, and noise inherent in HSI data, limiting their accuracy and scalability. Recently, diffusion models including denoising diffusion probabilistic models and other generative frameworks based on stochastic differential equations have shown...
Sweet basil carbon dots show potential for sustainable agriculture
June 6, 2026 dialog Sweet basil carbon dots show potential for sustainable agriculture Sadie Harley Scientific Editor Robert Egan Associate Editor What if a common herb found in the kitchen could help farmers grow healthier crops? As the global population grows and agriculture faces increasing environmental challenges, scientists are searching for innovative ways to improve crop productivity while reducing reliance on chemical inputs. Nanotechnology has emerged as a potential solution.
Learning Parametric Nitrogen Fertilizer Response Curves Using Neuro Symbolic Regression
arXiv:2605.31276v1 Announce Type: new Abstract: Accurately modeling crop response to Nitrogen (N) fertilization is a fundamental challenge in precision agriculture, as it impacts both economic returns and environmental sustainability. Existing approaches either rely on predefined parametric forms or opaque machine learning models, limiting their ability to interpret or discover site-specific functional relationships from data. In this work, we propose a neuro symbolic regression (SR)...
Q&A: How better climate data supports smarter environmental decisions
Q&A: How better climate data supports smarter environmental decisions Gaby Clark Scientific Editor Andrew Zinin Lead Editor Accurate measurements are the foundation of effective environmental management and decision-making. Through advanced monitoring networks and computer models, Ken Davis, professor of meteorology and atmospheric science in Penn State's College of Earth and Mineral Sciences, and his research group are helping scientists, communities, and policymakers better understand...
UP’s green renaissance: A future where growth & nature will thrive
Today, the world is facing the unprecedented challenge of climate change. Rising global temperatures, erratic monsoons, drying rivers, declining groundwater resources, air pollution, and the loss of biodiversity have emerged as serious threats to human life, economic prosperity, and social stability. Floods, droughts, heatwaves, and other extreme weather events are becoming increasingly frequent across different parts of the world.
A Predictive Control Strategy to Offset-Point Tracking for Agricultural Mobile Robots
arXiv:2603.28439v2 Announce Type: replace Abstract: Robots are increasingly being deployed in agriculture to support sustainable practices and improve productivity. They offer strong potential to enable precise, efficient, and environmentally friendly operations. However, most existing path-following controllers focus solely on the robot's center of motion and neglect the spatial footprint and dynamics of attached implements.
Building user-driven climate adaptation products
Abstract Climate adaptation products have traditionally been developed using a supply-driven model reliant on available climate information, leading to usability gaps1,2,3,4. To better meet user needs, the climate services field has recognized a need to shift towards a demand-driven model emphasizing co-production, that is, user-driven, scientifically informed products created through shared knowledge practices1,2,3,4,5. However, co-production can be challenging, especially for researchers...
Tessera AI model offers accessible way to view Earth
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