Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Suzana Dragićević"'
Publikováno v:
Big Earth Data, Pp 1-28 (2024)
Modelling land-use/landcover (LULC) change is vital for addressing global environmental and sustainability issues and evaluating various land system scenarios. However, existing geosimulation methodologies for global LULC change fail to account for s
Externí odkaz:
https://doaj.org/article/d92dd97c0a4e4e48835c89d242cce57d
Publikováno v:
Land, Vol 13, Iss 8, p 1288 (2024)
Geographic Information System-based Multi-Criteria Evaluation (GIS-MCE) methods are designed to assist in various spatial decision-making problems using spatial data. Deriving criteria weights is an important component of GIS-MCE, typically relying o
Externí odkaz:
https://doaj.org/article/7fe26a3e3c3d448ab9eef1027f547791
Publikováno v:
Applied Sciences, Vol 14, Iss 15, p 6530 (2024)
The theoretical paradigm of geographic automata systems (GAS) underpins a wide range of studies to represent dynamic complex geospatial phenomena. Specifically, cellular automata (CA) were used extensively over the past 40 years for geospatial applic
Externí odkaz:
https://doaj.org/article/8266d30b1d424165ade9c81d731ec190
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Unaddressed imbalance of multitemporal land cover (LC) data reduces deep learning (DL) model usefulness to forecast changes. To manage geospatial data imbalance, there is a lack of specialized cost-sensitive learning strategies available. Sample weig
Externí odkaz:
https://doaj.org/article/20392b2f476f4f29855c2422dde3286b
Autor:
Bright Addae, Suzana Dragićević
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 12, Iss 8, p 306 (2023)
Deforestation as a land-cover change process is linked to several environmental problems including desertification, biodiversity loss, and ultimately climate change. Understanding the land-cover change process and its relation to human–environment
Externí odkaz:
https://doaj.org/article/bef6da1a1b674fc08cc4e73dd83323d8
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 11, Iss 12, p 587 (2022)
An open problem impeding the use of deep learning (DL) models for forecasting land cover (LC) changes is their bias toward persistent cells. By providing sample weights for model training, LC changes can be allocated greater influence in adjustments
Externí odkaz:
https://doaj.org/article/42cd308488f94332864ab4a27475e998
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 4957 (2022)
Land cover change (LCC) studies are increasingly using deep learning (DL) modeling techniques. Past studies have leveraged temporal or spatiotemporal sequences of historical LC data to forecast changes with DL models. However, these studies do not ad
Externí odkaz:
https://doaj.org/article/ab93f9917d684f6d91b46eab871dc0d1
Publikováno v:
Land, Vol 11, Iss 3, p 443 (2022)
As many urban areas undergo increasing densification, there is a growing need for methods that can extend spatial analysis and decision-making for three-dimensional (3D) environments. Traditional multicriteria evaluation (MCE) methods implemented wit
Externí odkaz:
https://doaj.org/article/4edfb0204e754d7d9fb5a9ef70c6b77c
Publikováno v:
Land, Vol 10, Iss 3, p 282 (2021)
Recurrent Neural Networks (RNNs), including Long Short-Term Memory (LSTM) architectures, have obtained successful outcomes in timeseries analysis tasks. While RNNs demonstrated favourable performance for Land Cover (LC) change analyses, few studies h
Externí odkaz:
https://doaj.org/article/28fb38e4c88b448297106f20e63367a6
Autor:
Taylor Anderson, Suzana Dragićević
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 9, Iss 4, p 270 (2020)
Many real-world spatial systems can be conceptualized as networks. In these conceptualizations, nodes and links represent system components and their interactions, respectively. Traditional network analysis applies graph theory measures to static net
Externí odkaz:
https://doaj.org/article/771a5d3dd9cb4e7a8513cee17c39a2d6