Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Raul Zurita-Milla"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 2842-2852 (2020)
Random forest (RF) is a popular ensemble learning method that is widely used for the analysis of remote sensing images. RF also has connections with the kernel-based method. Its tree-based structure can generate an RF kernel (RFK) that provides an al
Externí odkaz:
https://doaj.org/article/c686732a1b8d4870b09d66ecf802ec83
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 11, Iss 4, p 242 (2022)
Applications of machine-learning-based approaches in the geosciences have witnessed a substantial increase over the past few years. Here we present an approach that accounts for spatial autocorrelation by introducing spatial features to the models. I
Externí odkaz:
https://doaj.org/article/db136f0a8b5e450e936a7417b9048e51
Autor:
Norhakim Yusof, Raul Zurita-Milla
Publikováno v:
International Journal of Digital Earth, Vol 10, Iss 3, Pp 238-256 (2017)
Holistic understanding of wind behaviour over space, time and height is essential for harvesting wind energy application. This study presents a novel approach for mapping frequent wind profile patterns using multi-dimensional sequential pattern minin
Externí odkaz:
https://doaj.org/article/76ecc528868640e7bbee4d6ab8c22885
Publikováno v:
PLoS ONE, Vol 14, Iss 12, p e0216511 (2019)
The socio-economic and demographic changes that occurred over the past 50 years have dramatically expanded urban areas around the globe, thus bringing urban settlers in closer contact with nature. Ticks have trespassed the limits of forests and grass
Externí odkaz:
https://doaj.org/article/4baf859897f84a6d8117fd6642ad5d45
Autor:
Lorena Alves Santos, Karine Ferreira, Michelle Picoli, Gilberto Camara, Raul Zurita-Milla, Ellen-Wien Augustijn
Publikováno v:
Remote Sensing, Vol 13, Iss 5, p 974 (2021)
The use of satellite image time series analysis and machine learning methods brings new opportunities and challenges for land use and cover changes (LUCC) mapping over large areas. One of these challenges is the need for samples that properly represe
Externí odkaz:
https://doaj.org/article/0108cc685d9f41fabd0e6e004c067e65
Publikováno v:
Remote Sensing, Vol 11, Iss 12, p 1489 (2019)
The authors wish to make the following correction to the paper [...]
Externí odkaz:
https://doaj.org/article/303853c8c17e4e85bcebdf4d3547e4fc
Publikováno v:
Remote Sensing, Vol 11, Iss 5, p 575 (2019)
The production of land cover maps through satellite image classification is a frequent task in remote sensing. Random Forest (RF) and Support Vector Machine (SVM) are the two most well-known and recurrently used methods for this task. In this paper,
Externí odkaz:
https://doaj.org/article/e9d4bfa4510445a5b2051ca619b15956
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 8, Iss 2, p 55 (2019)
The Singular Value Decomposition (SVD) is a mathematical procedure with multiple applications in the geosciences. For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-tempora
Externí odkaz:
https://doaj.org/article/3e30e0339c2e4ddb80f10252fb8f1d57
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 7, Iss 12, p 487 (2018)
The increasing availability of volunteered geographic information (VGI) enables novel studies in many scientific domains. However, inconsistent VGI can negatively affect these studies. This paper describes a workflow that checks the consistency of Vo
Externí odkaz:
https://doaj.org/article/67919e5bbdc44430a8b40d5aa3722a84
Publikováno v:
Remote Sensing, Vol 10, Iss 5, p 729 (2018)
Smallholder farmers cultivate more than 80% of the cropland area available in Africa. The intrinsic characteristics of such farms include complex crop-planting patterns, and small fields that are vaguely delineated. These characteristics pose challen
Externí odkaz:
https://doaj.org/article/8038f33d275f41a9924ea07059ca24f7