Zobrazeno 1 - 10
of 946
pro vyhledávání: '"GEOBIA"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 6721-6738 (2024)
Segmentation is crucial in geographic object-based image analysis for accurate land use and land cover mapping. However, obtaining outstanding segmentation results in all scenarios proves challenging with a single algorithm. This study investigates s
Externí odkaz:
https://doaj.org/article/23e651abb8854903abce357bd487c2a9
Autor:
Marco Aurelio Arizapana-Almonacid, Victor Henry Pariona-Antonio, Italo Castañeda-Tinco, Julio Cesar Ascención Mendoza, Edgar Gutiérrez Gómez, Paolo Ramoni-Perazzi
Publikováno v:
Annals of GIS, Vol 30, Iss 1, Pp 105-120 (2024)
ABSTRACTThe Andes region has a rich history of environmental and human interactions that has shaped the landscape for millennia. Our study quantified the land cover changes in the districts of Huanta and Luricocha after the human population abandoned
Externí odkaz:
https://doaj.org/article/22ebf490833c444ab7ce8c8037dd863c
Autor:
Tiago Monteiro Condé, Niro Higuchi, Adriano José Nogueira Lima, Moacir Alberto Assis Campos, Jackelin Dias Condé, André Camargo de Oliveira, Dirceu Lucio Carneiro de Miranda
Publikováno v:
Ecologies, Vol 4, Iss 4, Pp 686-703 (2023)
Forest phytophysiognomies have specific spatial patterns that can be mapped or translated into spectral patterns of vegetation. Regions of spectral similarity can be classified by reference to color, tonality or intensity of brightness, reflectance,
Externí odkaz:
https://doaj.org/article/037192b321714eaa8aa164e399b70766
Autor:
José Manuel Fernández-Guisuraga, Leonor Calvo, Luis Alfonso Pérez-Rodríguez, Susana Suárez-Seoane
Publikováno v:
Fire, Vol 7, Iss 9, p 304 (2024)
We propose a novel mono-temporal framework with a physical basis and ecological consistency to retrieve fire severity at very high spatial resolution. First, we sampled the Composite Burn Index (CBI) in 108 field plots that were subsequently surveyed
Externí odkaz:
https://doaj.org/article/fdde5440fa5b46b3bbf23feeeeb60354
Autor:
Mukti Ram Subedi, Carlos Portillo-Quintero, Nancy E. McIntyre, Samantha S. Kahl, Robert D. Cox, Gad Perry, Xiaopeng Song
Publikováno v:
Remote Sensing, Vol 16, Iss 15, p 2778 (2024)
In the United States, several land use and land cover (LULC) data sets are available based on satellite data, but these data sets often fail to accurately represent features on the ground. Alternatively, detailed mapping of heterogeneous landscapes f
Externí odkaz:
https://doaj.org/article/cd87cf64fb76439887c46835a411e91c
Autor:
Elie Morin, Ny Tolotra Razafimbelo, Jean-Louis Yengué, Yvonnick Guinard, Frédéric Grandjean, Nicolas Bech
Publikováno v:
Data in Brief, Vol 52, Iss , Pp 109829- (2024)
The land cover data presented here is a reconstruction of the past landscape (1993) at Very High Resolution (VHR) for the city of Poitiers, France. This reconstruction is based on multiple sources of images and data. We combined the strengths of both
Externí odkaz:
https://doaj.org/article/c2e33e155da842529adb580fd53c53af
Autor:
Débora Cristina de Lima Miranda, Marlon Carlos França, Luke Ortiz-Whittingham, Laurent Polidori
Publikováno v:
Quaternary Science Advances, Vol 13, Iss , Pp 100149- (2024)
Mangroves are ecosystems present in a large part of the Brazilian coastal zone that are home to a wide diversity of organisms, providing direct and indirect resources, as well as nursery and foraging habitats. Using images in 5-year intervals (2010,
Externí odkaz:
https://doaj.org/article/5d5b1b634374403e8647885509af141c
Publikováno v:
Anais da Academia Brasileira de Ciências, Vol 95, Iss suppl 2 (2023)
Abstract Mangroves occur in the tropics and subtropics. This region is constantly covered by clouds and therefore highly challenging to map and monitor. Technological advances in remote sensing have increased the flexibility of performing such analys
Externí odkaz:
https://doaj.org/article/702a33322f1047d8b8480ab21d447298
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Modern earth observation sensors have revolutionized the remote sensing community by improving remote sensing image quality. However, Pixel-based image analysis methods have challenges in handling very high-resolution (VHR) imagery. Geographic Based
Externí odkaz:
https://doaj.org/article/bc07a390f8f14e8393abe2895167b174
Autor:
Mohammad D. Hossain, Dongmei Chen
Publikováno v:
Remote Sensing, Vol 16, Iss 5, p 878 (2024)
Identifying urban buildings in high-resolution RGB images presents challenges, mainly due to the absence of near-infrared bands in UAVs and Google Earth imagery and the diversity in building attributes. Deep learning (DL) methods, especially Convolut
Externí odkaz:
https://doaj.org/article/baec1d8fbc55460089b2eea24d721e5b