Results 11 to 20 of about 231,492 (82)

Application of PCA with georeferenced data in the tourism industry: A case study in the province of Córdoba, Argentina

Tourism Economics, 2021
The spatial analysis of tourism industries provides information about their structure, which is necessary for decision-making. In this work, tourism industries in the departments of Córdoba province, Argentina, for the 2001–2014 period were mapped ...
Laura I Luna
core   +2 more sources

Subfield management class delineation using cluster analysis from spatial principal components of soil variables [PDF]

, 2013
Understanding spatial variation within a field is essential for site-specific crop management, which requires the delineation of management areas. Several soil and terrain variables are used to classify the field points into classes.
Balzarini, Monica Graciela, Bruno, Cecilia Ines, Costa, Jose Luis, Córdoba, Mariano   +3 more
core   +2 more sources

Enhancing edaphoclimatic zoning by adding multivariate spatial statistics to regional data [PDF]

, 2018
Joint spatial variability of soil and climate variables offers the opportunity to delimit contiguous edaphoclimatic zones. These zones can be useful to improve natural resource management.
Balzarini, Monica Graciela, Córdoba, Mariano, Giannini Kurina, Franca, Hang, Susana, Negro, Gustavo José   +4 more
core   +2 more sources

Large trends in French topsoil characteristics are revealed by spatially constrained multivariate analysis

, 2011
Spatially constrained multivariate analysis methods (MULTISPATI-PCA) and classical principal component analysis are applied for the entire country of France to study the main soil characteristics of topsoil and to assess if their multivariate spatial ...
Arrouays, D., Boulonne, L., Jolivet, C., Ratié, C., Saby, N.P.A., Thioulouse, Jean   +5 more
core   +3 more sources

Multivariate spatial analyses of the distribution and origin of trace and major elements in soils surrounding a secondary lead smelter

Environmental science and pollution research international, 2016
International audienceMajor and trace elements in soils originate from natural processes and different anthropogenic activities which are difficult to discriminate. On a 17-ha impacted site in northern France, two industrial sources of soil contamination
A Facchinelli, A Franco-Uria, A Lu, AR Schneider, Arnaud R. Schneider, B Gonzalez-Corrochano, B Minasny, Benjamin Cancès, BJ Alloway, BY Cheng, Béatrice Marin, C Carlon, C Fritsch, C Reimann, C Sun, CE Imrie, D Arrouays, D Arrouays, D Baize, D Chessel, D Cicchella, D Meza-Figueroa, D Romic, D Sollitto, E Remon, E Schreck, EJ Pebesma, F Akbar Jan, F Douay, F Yuan, G Liu, G Uzu, G Woodside, GEM Hall, GL Yuan, H Bourennane, H Chen, H Yongming, J Lv, J Lv, J Tadmor, J Thioulouse, JL Fernandez-Turiel, JW Einax, K Baceva, L Cai, M Anju, M Cecchi, M Dayani, M Wang, Marie Ponthieu, Maxime Gommeaux, MJ Salazar, MJ Salazar, N Cressie, N Nanos, Nicolas P. A. Saby, NPA Saby, NPA Saby, NPA Saby, P Caritat De, P Goovaerts, P Goovaerts, P Thavamani, PA Dowd, PJ Ribeiro, Q Wu, R Chester, R Schulin, R Siddique, R Webster, RA Sutherland, RM Lark, S Dray, S Kartal, S Nickel, S Sobanska, T Nedwed, T Stafilov, T Sterckeman, X Chen, X Li, X Li, X Lu, X Lu, X Morvan, Xavier Morvan, Y Xie, YG Gu, Z Karim   +89 more
core   +3 more sources

Delineation of management zones dealing with low sampling and outliers

Precision Agriculture
Purpose: Management zones (MZs) are the subdivision of a field into a few contiguous homogeneous zones to guide variable-rate application. Delineating MZs can be based on geostatistical or clustering approaches, however, the joint use of these approaches
Grego, Celia Regina, Manzione, Rodrigo Lilla [UNESP], Oliveira, Stanley Robson de Medeiros, Rodrigues, Cristina Aparecida Gonçalves, Rodrigues, Gustavo Costa, Silva, Cesar de Oliveira Ferreira   +5 more
core   +2 more sources

Detection of Tomato Leaf Diseases for Agro-Based Industries Using Novel PCA DeepNet

IEEE Access, 2023
The advancement of Deep Learning and Computer Vision in the field of agriculture has been found to be an effective tool in detecting harmful plant diseases.
Kyamelia Roy, S. S. Chaudhuri, Jaroslav Frnda, Srijita Bandopadhyay, Ishan Jyoti Ray, Soumen Banerjee, J. Nedoma   +6 more
semanticscholar   +1 more source

Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated

Scientific Reports, 2022
Principal Component Analysis (PCA) is a multivariate analysis that reduces the complexity of datasets while preserving data covariance. The outcome can be visualized on colorful scatterplots, ideally with only a minimal loss of information.
E. Elhaik
semanticscholar   +1 more source

Tutorial on PCA and approximate PCA and approximate kernel PCA

Artificial Intelligence Review, 2022
Principal Component Analysis (PCA) is one of the most widely used data analysis methods in machine learning and AI. This manuscript focuses on the mathematical foundation of classical PCA and its application to a small-sample-size scenario and a large ...
S. Marukatat
semanticscholar   +1 more source

DWT-PCA based Video Watermarking

Journal of Electronics,Computer Networking and Applied Mathematics, 2022
Progressed watermarking video may be a methodology for embedding additional data another to video salute. Embedded data is utilized for proprietor copyright or recognizable affirmation. It added up to approach for watermarking is shown in this System, by
Swapnil Takale, Dr. Altaaf Mulani
semanticscholar   +1 more source