Soil properties and weather conditions are known to affect soil N availability plant uptake; however, studies examining response as affected by sometimes give conflicting results. Meta‐analysis is a statistical method for estimating treatment effects in series of experiments explain the sources heterogeneity. In this study, technique was used examine influence parameters on corn ( Zea mays L.) across 51 involving same rate treatments that were performed diversity North American locations...

Segmentation and classification are two imperative, yet challenging tasks in image analysis for remote-sensing applications. In the former, an is divided into spatially continuous, disjoint, homogeneous regions, called clusters, terms of their various properties: shape, intensity, texture, colour, contrast, etc. Classification, on other hand, applied later process, to recognize or categorize individual objects targets. Each task plays important role refinement enhancement utilizations remote...

It is becoming increasingly accepted that beekeeping declining due to the damaging effect of global changes such as climate and land-use change directly indirectly impact Apis Melliferas. Despite numerous investigations, a comprehensive study incorporates both local knowledge has yet be conducted. For long time, researchers have suggested expert should taken into account when creating decision support tools for managing activities related natural resources, beekeeping. Unlike previous...

Extracting and identifying objects in very high resolution imagery has been a popular research topic remote sensing. Since the beginning of this decade, deep learning techniques have revolutionized computer vision providing significant performance gains compared to traditional "shallow" various challenging problems. The training neural networks usually requires large datasets. advantage using features is exploit already trained Convolutional Neural Networks (CNN) order produce level without...

Satellite observations provide critical data for a myriad of applications, but automated information extraction from such vast datasets remains challenging. While artificial intelligence (AI), particularly deep learning methods, offers promising solutions land cover classification, it often requires massive amounts accurate, error-free annotations. This paper introduces novel approach to generate segmentation task dataset with minimal human intervention, thus significantly reducing...

The Bidirectional Reflectance Distribution Function (BRDF) defines the anisotropy of surface reflectance and plays a fundamental role in many remote sensing applications. This study proposes new machine learning-based model for characterizing BRDF. integrates capability Radiative Transfer Models (RTMs) to generate simulated data with power deep neural networks emulate, learn approximate complex pattern physical RTMs BRDF modeling. To implement this idea, we used one-dimensional convolutional...

Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing methodology extracting buildings from textured meshes, employing PicassoNet-II semantic architecture. Additionally, we integrate Markov field-based contextual analysis post-segmentation assessment cluster algorithms building instantiation. Training model to adapt diverse...

Training a deep learning model requires highly variable data to permit reasonable generalization. If the variability in about be processed is low, interest obtaining this generalization seems limited. Yet, it could prove interesting specialize with respect particular theme. The use of enhanced super-resolution generative adversarial networks (ERSGAN), specific type architecture, allows spatial resolution remote sensing images increased by “hallucinating” non-existent details. In study, we...

Le présent article comporte une analyse critique de l'Atlas Solaire l'Algérie réalisé par Capderou en 1987. L'auteur utilise un modèle l'atmosphère basé fondamentalement sur la connaissance du trouble atmosphérique pour détermination des différentes composantes rayonnement solaire d'un site. Par ciel clair, le donne bonne estimation composante directe mais surestime diffuse. moyen, fonctions distribution permettent générer gisement site connaissant uniquement moyenne mensuelle l'insolation....

This paper presents three applications of SAR interferometry. In the first study, DInSAR technique applied to TerraSAR-X images acquired in Nunavik, northern Canada, showed that surface subsidence observed permafrost thaw period is more important loose soil areas while no movement were detected rock outcrop areas. second one, electricity transmission tower was simulated through controlled vertical displacements corner reflectors. These clearly six interferometric pairs, surrounding stable...

To be able to estimate crop biophysical variables (BoVs) accurately from remote sensing data is key enhance agricultural mapping and monitoring. Ignoring the impact of reflectance anisotropy in vegetation introduces uncertainties, affecting accuracy, particularly for wide-angle sensors like MODIS or Sentinel-3 OLCI. Taking into account Bidirectional Reflectance Function (BRDF), which characterizes anisotropy, can improve BoVs estimation accuracy. This study hence a hybrid framework that...

Information-based crop management, such as variable rate technology, allows for changing rates of fertilization according to local needs. Fertilizer prescription maps can be derived from growth status assessed through proximal canopy sensing technologies. Typically, a vegetation index, the NDVI, is used estimate Nitrogen Sufficiency Index (NSI=NDVI/NDVI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N-rich</sub> ). NSI related N intake in...

Abstract. The last three decades have seen significant mining development in the northern regions of Canada, where freeze and thaw cycle permafrost corresponding surface subsidence heave represent a challenge at all stages, from design infrastructures to monitoring restored areas. Over past ten years, SAR interferometry has been widely used monitor ground deformation. With this technique, changes phase between two acquisitions are detect centimetre millimetre displacements over large area...

Digital twins are gaining in popularity for simulating complex natural and urban environments. In this context, accurate segmentation of objects within 3D environments is crucial importance. The aim project to develop a methodology extracting buildings from textured meshes. To end, PicassoNet-II, semantic architecture employed. also incorporates Markov field-based contextual analysis assess post-segmentation features. addition, building instantiation performed using cluster algorithms....

Airborne LiDAR data allow the precise modeling of topography and are used in multiple contexts. To facilitate further analysis, point cloud classification process allows assignment a class, object or feature, to each point. This research uses ConvPoint, deep learning method, perform airborne at scale, rural urban Specifically, our experiments located near Montreal (QC) Saint-Jean (NB) approach is designed classify five classes; we "Building", "Ground", "Water", "Low Vegetation" "Mid-High...