Change detection from very-high-spatial-resolution optical remote sensing images: Methods, applications, and future directions

D Wen, X Huang, F Bovolo, J Li, X Ke… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
Change detection is a vibrant area of research in remote sensing. Thanks to increases in the
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …

[HTML][HTML] Remote sensing object detection in the deep learning era—a review

S Gui, S Song, R Qin, Y Tang - Remote Sensing, 2024 - mdpi.com
Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …

A first Chinese building height estimate at 10 m resolution (CNBH-10 m) using multi-source earth observations and machine learning

WB Wu, J Ma, E Banzhaf, ME Meadows, ZW Yu… - Remote Sensing of …, 2023 - Elsevier
Building height is a crucial variable in the study of urban environments, regional climates,
and human-environment interactions. However, high-resolution data on building height …

[PDF][PDF] Urban landscape fragmentation as an indicator of urban expansion using sentinel-2 imageries

N Kadhim, NT Ismael, NM Kadhim - Civil Engineering Journal, 2022 - core.ac.uk
Rapid urbanization in some cities has led to the emergence of numerous subsidiary
settlements around their primary cities. Due to this rapid urbanization and growth, there is a …

Automated LoD-2 model reconstruction from very-high-resolution satellite-derived digital surface model and orthophoto

S Gui, R Qin - ISPRS Journal of Photogrammetry and Remote …, 2021 - Elsevier
Digital surface models (DSM) generated from multi-stereo satellite images are getting higher
in quality owing to the improved data resolution and photogrammetric reconstruction …

Subsidence monitoring and influencing factor analysis of mountain excavation and valley infilling on the Chinese Loess Plateau: A case study of Yan'an New District

H Zhang, R Zeng, Y Zhang, S Zhao, X Meng, Y Li… - Engineering …, 2022 - Elsevier
With the significant expansion of the urban population on the Chinese Loess Plateau, large-
scale land infilling and excavation projects have been implemented to alleviate the shortage …

Building height calculation for an urban area based on street view images and deep learning

Z Xu, F Zhang, Y Wu, Y Yang… - Computer‐Aided Civil and …, 2023 - Wiley Online Library
The building heights of an urban area are useful for space analysis, urban planning, and city
management. To this end, a novel method for building height calculation for an urban area is …

[HTML][HTML] The use of deep learning methods for object height estimation in high resolution satellite images

S Glinka, J Bajer, D Wierzbicki, K Karwowska… - Sensors, 2023 - mdpi.com
Processing single high-resolution satellite images may provide a lot of important information
about the urban landscape or other applications related to the inventory of high-altitude …

A generalization of Otsu's method and minimum error thresholding

JT Barron - Computer Vision–ECCV 2020: 16th European …, 2020 - Springer
Abstract We present Generalized Histogram Thresholding (GHT), a simple, fast, and
effective technique for histogram-based image thresholding. GHT works by performing …

Does Deep Learning Enhance the Estimation for Spatially Explicit Built Environment Stocks through Nighttime Light Data Set? Evidence from Japanese Metropolitans

Z Liu, R Saito, J Guo, C Hirai, C Haga… - Environmental …, 2023 - ACS Publications
Built environment stocks have attracted much attention in recent decades because of their
role in material and energy flows and environmental impacts. Spatially refined estimation of …