Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Krištof Oštir"'
Publikováno v:
Big Earth Data, Vol 8, Iss 1, Pp 82-114 (2024)
ABSTRACTThis paper presents a novel approach for predicting the water quality indicator – Secchi disk depth (ZSD). ZSD indirectly reflects water clarity and serves as a proxy for other quality parameters. This study utilizes Deep Neural Network (DN
Externí odkaz:
https://doaj.org/article/6061434f944a424ea106c3df5c053e46
Autor:
Mateja Jemec Auflič, Krištof Oštir, Tanja Grabrijan, Matjaž Ivačič, Tina Peternel, Ela Šegina
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
To create the landslide activity map, we implemented and tested the procedure to fully utilise the 6-day repeatability of the Sentinel-1 constellation in three pilot areas in Slovenia for the observation period from 2017 to 2021. The interferometric
Externí odkaz:
https://doaj.org/article/f8aafaa6e5c144a5845b359844fc11ca
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 270 (2024)
Crop classification is an important task in remote sensing with many applications, such as estimating yields, detecting crop diseases and pests, and ensuring food security. In this study, we combined knowledge from remote sensing, machine learning, a
Externí odkaz:
https://doaj.org/article/4f7598a1aa704e23b30998039b431564
Publikováno v:
Geodetski Vestnik, Vol 66, Iss 02, Pp 220-257 (2022)
The Sentinel-2 is a high resolution optical satellite mission, developed by the European Space Agency (ESA) for the European Commission. Currently the mission has two satellites in orbit: Sentinel-2A from 23rd June 2015, and Sentinel-2B from 7th Marc
Externí odkaz:
https://doaj.org/article/d3055f48658c4c40a1d16f81742dc1e7
Publikováno v:
Geodetski Vestnik, Vol 65, Iss 04, Pp 559-593 (2021)
Building footprint detection based on orthophotos can be used to update the building cadastre. In recent years deep learning methods using convolutional neural networks have been increasingly used around the world. We present an example of automatic
Externí odkaz:
https://doaj.org/article/94f3717ed9294a6ea9a0ed08a945d73c
Publikováno v:
Remote Sensing, Vol 15, Iss 15, p 3861 (2023)
Studying karst water dynamics is challenging because of the often unknown underground flows. Therefore, studies of visible karst waters receive considerable research emphasis. Researchers are turning to various data sources, including remote sensing
Externí odkaz:
https://doaj.org/article/bf2817ab53074293bff887f08ff6eb24
Publikováno v:
European Journal of Remote Sensing, Vol 54, Iss S1, Pp 31-46 (2021)
The paper presents a method for mapping fluvial gravel bars based on Sentinel-2 and Landsat imagery. The proposed method therefore uses spectral signal mixture analysis (SSMA) because its results allow the development of land cover fraction maps for
Externí odkaz:
https://doaj.org/article/645f31ab296748918a4c11fccc0dc18b
Publikováno v:
Geodetski Vestnik, Vol 63, Iss 03, Pp 344-378 (2019)
Exact data about the location and area of vacant building land have been a major issue in several Slovene municipalities. This article deals with automatic vacant building land delineation. The presented methodology is based on the object-based class
Externí odkaz:
https://doaj.org/article/2bd55cbe84a3481db7c14a463cf37965
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3387 (2022)
Detailed spatial data on grassland use intensity is needed in several European policy areas for various applications, e.g., agricultural management, supporting nature conservation programs, improving biodiversity strategies, etc. Multisensory remote
Externí odkaz:
https://doaj.org/article/1dca7d77501247cab64361662c78b0d7
Autor:
Andrej Novak, Krištof Oštir
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4211 (2021)
Alpine topography is formed by a complex series of geomorphological processes that result in a vast number of different landforms. The youngest and most diverse landforms are various Quaternary sedimentary bodies, each characterised by its unique lan
Externí odkaz:
https://doaj.org/article/eaf703923f224fabae428a2dc6643723