Dilated-ResUnet: A novel deep learning architecture for building extraction from medium resolution multi-spectral satellite imagery

M Dixit, K Chaurasia, VK Mishra - Expert Systems with Applications, 2021 - Elsevier
In today's world, satellite images are being utilized for the identification of built-up area,
urban planning, disaster management, insurance & tax assessment in an area, and many …

[HTML][HTML] ReFuse: generating imperviousness maps from multi-spectral sentinel-2 satellite imagery

G Giacco, S Marrone, G Langella, C Sansone - Future Internet, 2022 - mdpi.com
Continual mapping and monitoring of impervious surfaces are crucial activities to support
sustainable urban management strategies and to plan effective actions for environmental …

Review of Various Learning Algorithms Applied to Satellite Image Classification

MV Gupta, RK Dwivedi, A Kumar - 2021 10th International …, 2021 - ieeexplore.ieee.org
Satellite image classification plays a vital role for extracting and analyzing information in
satellite images. It is a process that classify an image according to its characteristics. The …

Monitoring and Analysis of Urban Sprawl Based on Road Network Data and High-Resolution Remote Sensing Imagery: A Case Study of China's Provincial Capitals

L Ding, H Zhang, D Li - Photogrammetric Engineering & …, 2022 - ingentaconnect.com
The primary prerequisite for sustainable urban development is to accurately grasp the
development of the city. The dynamic changes in the urban area can reflect the urban …

Accurate detection of built-up areas from high-resolution remote sensing imagery using a fully convolutional network

Y Tan, S Xiong, Z Li, J Tian, Y Li - … Engineering & Remote …, 2019 - ingentaconnect.com
The analysis of built-up areas has always been a popular research topic for remote sensing
applications. However, automatic extraction of built-up areas from a wide range of regions …

Remote sensing image classification using deep learning

S Gupta, RK Dwivedi, V Kumar, R Jain… - … on System Modeling …, 2021 - ieeexplore.ieee.org
Remote sensing is the technology used for extracting information about the earth surface
with the help of sensors installed on the satellites. The remote sensing technology captures …

Detecting built-up areas in agricultural fields using deep learning on Sentinel-2 Satellite Image Time Series

M Debella-Gilo - Kart og Plan, 2022 - idunn.no
Parts of the limited agricultural land area in Norway are taken up by buildings, roads, and
other permanent changes every year. A method that detects such changes immediately after …

[PDF][PDF] Urban Land Cover Mapping and Change Detection Analysis Using High Resolution Sentinel-2A Data.

S Vigneshwaran, SV Kumar - Environment & Natural …, 2019 - pdfs.semanticscholar.org
Land cover information is essential data required by urban planners and policy makers to
understand existing development and to protect natural resources in a city or town. With the …

Enhancing the Classification of Remote Sensing Data Using Multiband Compact Texture Unit Descriptor and Deep Convolutional Neural Network

K Djerriri, A Sofia, MS Karoui… - IGARSS 2018-2018 IEEE …, 2018 - ieeexplore.ieee.org
This abstract proposes a method to enhance the classification of high spatial remotely
sensed imagery by using Multiband Compact Texture Unit (MBCTU) descriptor and pre …

Convolutional neural network with U-Net architecture to detect buildings in satellite imagery for statistical purposes

M Kharis, S Mariyah - Statistical Journal of the IAOS, 2021 - content.iospress.com
Statistics Indonesia (BPS) carries out a population census every ten years, which provides
data on the number, composition, distribution, and characteristics of the Indonesian …