A combined convolutional neural network for urban land-use classification with GIS data
The classification of urban land-use information has become the underlying database for a
variety of applications including urban planning and administration. The lack of datasets and …
variety of applications including urban planning and administration. The lack of datasets and …
Integrating aerial and street view images for urban land use classification
Urban land use is key to rational urban planning and management. Traditional land use
classification methods rely heavily on domain experts, which is both expensive and …
classification methods rely heavily on domain experts, which is both expensive and …
An object-based convolutional neural network (OCNN) for urban land use classification
Urban land use information is essential for a variety of urban-related applications such as
urban planning and regional administration. The extraction of urban land use from very fine …
urban planning and regional administration. The extraction of urban land use from very fine …
Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery
Urban land-use mapping is a significant yet challenging task in the field of remote sensing.
Although numerous classification methods have been developed for obtaining land-use …
Although numerous classification methods have been developed for obtaining land-use …
MAAFEU-NET: a novel land use classification model based on mixed attention module and adjustable feature enhancement layer in remote sensing images
Y Zhang, H Zhao, G Ma, D Xie, S Geng, H Lu… - … International Journal of …, 2023 - mdpi.com
The classification of land use information is important for land resource management. With
the purpose of extracting precise spatial information, we present a novel land use …
the purpose of extracting precise spatial information, we present a novel land use …
Comparison of machine-learning methods for urban land-use mapping in Hangzhou city, China
W Mao, D Lu, L Hou, X Liu, W Yue - Remote Sensing, 2020 - mdpi.com
Urban land-use information is important for urban land-resource planning and management.
However, current methods using traditional surveys cannot meet the demand for the rapid …
However, current methods using traditional surveys cannot meet the demand for the rapid …
Multi-structure joint decision-making approach for land use classification of high-resolution remote sensing images based on CNNs
Land use classification of high-resolution remote sensing (HRRS) images is a challenging
and prominent problem in which pretrained convolutional neural networks (CNNs) have …
and prominent problem in which pretrained convolutional neural networks (CNNs) have …
A framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method
Land-use classification plays an important role in urban planning and resource allocation
and had contributed to a wide range of urban studies and investigations. With the …
and had contributed to a wide range of urban studies and investigations. With the …
Further exploring convolutional neural networks' potential for land-use scene classification
Recently, with the success of deep convolutional neural networks (CNNs), many end-to-end
learning algorithms have yielded excellent results. However, in the field of land use and land …
learning algorithms have yielded excellent results. However, in the field of land use and land …
Urban land use and land cover classification using novel deep learning models based on high spatial resolution satellite imagery
Urban land cover and land use mapping plays an important role in urban planning and
management. In this paper, novel multi-scale deep learning models, namely ASPP-Unet and …
management. In this paper, novel multi-scale deep learning models, namely ASPP-Unet and …