[HTML][HTML] Unsupervised machine learning in urban studies: A systematic review of applications

J Wang, F Biljecki - Cities, 2022 - Elsevier
Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

Land use/land cover and change detection mapping in Rahuri watershed area (MS), India using the google earth engine and machine learning approach

CB Pande - Geocarto International, 2022 - Taylor & Francis
The change detection and land use and land cover (LULC) maps are more important
powerful forces behind numerous ecological systems and fallow land. The current research …

Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India

D Abijith, S Saravanan - Environmental Science and Pollution Research, 2022 - Springer
The study on land use and land cover (LULC) changes assists in analyzing the change and
regulates environment sustainability. Hence, this research analyzes the Northern TN coast …

Multispectral semantic segmentation for land cover classification: An overview

L Ramos, AD Sappa - IEEE Journal of Selected Topics in …, 2024 - ieeexplore.ieee.org
Land cover classification (LCC) is a process used to categorize the earth's surface into
distinct land types. This classification is vital for environmental conservation, urban planning …

Assessing the impact of land use and land cover on river water quality using water quality index and remote sensing techniques

MA Gani, AM Sajib, MA Siddik… - Environmental Monitoring …, 2023 - Springer
The impact of land use on water quality is becoming a global concern due to the increasing
demand for freshwater. This study aimed to assess the effects of land use and land cover …

Spatial-explicit carbon emission-sequestration balance estimation and evaluation of emission susceptible zones in an Eastern Himalayan city using Pressure …

S Ghosh, S Dinda, ND Chatterjee, S Dutta… - Journal of Cleaner …, 2022 - Elsevier
Urbanization and associated land-use change is one of the major sources of cumulative
greenhouse gas emissions and has become a serious concern for climate change and …

[HTML][HTML] Attention-guided siamese networks for change detection in high resolution remote sensing images

H Yin, L Weng, Y Li, M Xia, K Hu, H Lin… - International Journal of …, 2023 - Elsevier
Understanding surface changes requires the ability to identify changes in high resolution
remote sensing images. Because current deep learning-based change detection algorithms …

Time series analysis for global land cover change monitoring: A comparison across sensors

L Xu, M Herold, NE Tsendbazar, D Masiliūnas… - Remote Sensing of …, 2022 - Elsevier
Comparing the performance of different satellite sensors in global land cover change (LCC)
monitoring is necessary to assess their potential and limitations for more accurate and …

Learning multiscale temporal–spatial–spectral features via a multipath convolutional LSTM neural network for change detection with hyperspectral images

C Shi, Z Zhang, W Zhang, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Change detection (CD) with hyperspectral images (HSIs) can be effectively performed using
deep learning networks (DLNs) by taking advantage of HSIs for their abundant spectral and …

Exploring the relationship between land use land cover and land surface temperature: A case study in Bangladesh and the policy implications for the global South

A Tabassum, R Basak, W Shao, MM Haque… - … of Geovisualization and …, 2023 - Springer
Abstract Changes in land use and land cover (LULC) have a considerable impact on land
surface temperature (LST) and they are a major driver of climate change. Comprehending …