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Article
V. Gumus ; N. El Moçayd ; M. Seker ; M. Seaid |The present study evaluates the future drought hazard in Morocco using a Multi-Model Ensemble (MME) approach. First, the artificial neural network-based MME is constructed using the General Circulation Models (GCMs) from the Climate Models Inter[...]
Article
L. Shang ; J. Wang ; D. Schäfer ; T. Heckelei ; J. Gall ; F. Appel ; H. Storm |Technological change co-determines agri-environmental performance and farm structural transformation. Meaningful impact assessment of related policies can be derived from farm-level models that are rich in technology details and environmental in[...]
Article
Ecological agriculture (E.A.) protects soil, water, and the climate, ensuring nutritious food. It encourages biodiversity and prohibits chemical inputs or hybrids. Agricultural development strategy should prioritize the development of water, lan[...]
Article
F. Mohammadi Kashka ; Z. Tahmasebi Sarvestani ; H. Pirdashti ; A. Motevali ; M. Nadi ; M. Valipour |The increase in population has increased the need for agricultural and food products, and thus agricultural production should be increased. This goal may cause increases in emissions and environmental impacts by increasing the consumption of agr[...]
Article
D. Paudel ; A. de Wit ; H. Boogaard ; D. Marcos ; S. Osinga ; I.N. Athanasiadis |Machine learning models for crop yield forecasting often rely on expert-designed features or predictors. The effectiveness and interpretability of these handcrafted features depends on the expertise of the people designing them. Neural networks [...]
Article
K. Mainali ; M. Evans ; D. Saavedra ; E. Mills ; B. Madsen ; S. Minnemeyer |Landscape scale wetland conservation requires accurate, up-to-date wetland maps. The most useful approaches to creating such maps are automated, spatially generalizable, temporally repeatable, and can be applied at large spatial scales. However,[...]
Article
Machine learning (ML) and its branch, deep learning (DL), is rapidly evolving and gaining popularity as it outperforms other, more traditional methods in different areas of agriculture. However, ML and DL techniques must be correctly applied to [...]
Article
Machine-learning methodologies are part of the artificial intelligence approaches with several applications in different fields of science and dimensions of human life. These techniques appear in the frameworks of the digital transition, where s[...]
Article
A.M.S. Kheir ; K.A. Ammar ; A. Amer ; M.G.M. Ali ; Z. Ding ; A. Elnashar |Combining machine learning (ML) with dynamic models is recommended by recent research for creating a hybrid approach for robust simulations but has received less attention thus far. Herein, we combined multi- ML algorithms with multi-crop models[...]
Article
G. Cecili ; P. De Fioravante ; L. Congedo ; M. Marchetti ; M. Munafò |In recent years, deep learning (DL) algorithms have been widely integrated for remote sensing image classification, but fewer studies have applied it for land consumption (LC). LC is the main factor in land transformation dynamics and it is the [...]
Article
Parcel-level cropland maps are an essential data source for crop yield estimation, precision agriculture, and many other agronomy applications. Here, we proposed a rice field mapping approach that combines agricultural field boundary extraction [...]
Article
The existing cultivated land in the Mediterranean region faces great pressure from various sources. A suitability evaluation of potential arable land is urgent for helping adaptation measures to mitigate the impacts of climate change and human p[...]
Article
J. Wang ; M. Bretz ; M.A.A. Dewan ; M.A. Delavar |Land-use and land-cover change (LULCC) are of importance in natural resource management, environmental modelling and assessment, and agricultural production management. However, LULCC detection and modelling is a complex, data-driven process in [...]
Article
In the field of agriculture, the water used for irrigation should be given special treatment, as it is responsible for a large proportion of total water consumption. Irrigation scheduling is critical to food production because it guarantees prod[...]
Article
Short-range predictions of crop yield provide valuable insights for agricultural resource management and likely economic impacts associated with low yield. Such predictions are difficult to achieve in regions that lack extensive observational re[...]
Article
A. Sharma ; M. Georgi ; M. Tregubenko ; A. Tselykh ; A. Tselykh |The increasing demand of smart agriculture has led to the significant growth and development in the field of crop estimation and prediction improving its productivity. The analysis of crop age status is very important to prevent the excessive fe[...]
Article
V. Ramachandran ; R. Ramalakshmi ; B.P. Kavin ; I. Hussain ; A.H. Almaliki ; A.A. Almaliki ; A.Y. Elnaggar ; E.E. Hussein |The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less than 75% of fresh water utilization globally. Irrigation, being t[...]
Article
A. Elbeltagi ; A. Nagy ; S. Mohammed ; C.B. Pande ; M. Kumar ; S.A. Bhat ; J. Zsembeli ; L. Huzsvai ; J. Tamás ; E. Kovács ; E. Harsányi ; C. Juhász |Reference crop evapotranspiration (ETo) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was [...]
Article
L. Schmidt ; M. Odening ; J. Schlanstein ; M. Ritter |CONTEXT Weather is a pivotal factor for crop production as it is highly volatile and can hardly be controlled by farm management practices. Since there is a tendency towards increased weather extremes in the future, understanding weather-related[...]
Article
M. Engen ; E. Sando ; B.L. Sjolander ; S. Arenberg ; R. Gupta ; M. Goodwin |Farm-scale crop yield prediction is a natural development of sustainable agriculture, producing a rich amount of food without depleting and polluting environmental resources. Recent studies on crop yield production are limited to regional-scale [...]
Article
Artificial neural networks are one of the most important elements of machine learning and artificial intelligence. They are inspired by the human brain structure and function as if they are based on interconnected nodes in which simple processin[...]
Ouvrage
Agricultural Water Management: Theories and Practices advances the scientific understanding, development and application of agricultural water management through an integrated approach. This book presents a collection of recent developments and [...]
Ouvrage
Ce livre tente de fournir des informations sur la télédétection à partir de divers concepts de base de la télédétection, ainsi que sur des sujets avancés tels que les grandes données, l'intelligence artificielle et les réseaux neuronaux. Le livr[...]
Thèse, Mémoire, Master
Ce travail a pour objectif, la création d’un outil innovant basé sur les technologies de l’information et de la communication (TIC) permettant l’évaluation de la qualité fourragère des prairies permanentes. Cette étude vise à identifier l’intérê[...]
