Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis

B Neupane, T Horanont, J Aryal - Remote Sensing, 2021 - mdpi.com
Availability of very high-resolution remote sensing images and advancement of deep
learning methods have shifted the paradigm of image classification from pixel-based and …

Mapping urban tree cover changes using object-based convolution neural network (OB-CNN)

S Timilsina, J Aryal, JB Kirkpatrick - Remote Sensing, 2020 - mdpi.com
Urban trees provide social, economic, environmental and ecosystem services benefits that
improve the liveability of cities and contribute to individual and community wellbeing. There …

GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing

P Zhao, F Zhang, H Lin, S Xu - Remote Sensing, 2021 - mdpi.com
Fire risk prediction is significant for fire prevention and fire resource allocation. Fire risk
maps are effective methods for quantifying regional fire risk. Laoshan National Forest Park …

Identification of the disturbance and trajectory types in mining areas using multitemporal remote sensing images

Z Yang, J Li, CE Zipper, Y Shen, H Miao… - Science of the total …, 2018 - Elsevier
Surface coal mining disturbances affect the local ecology, human populations and
environmental quality. Thus, much public attention has been focused on mining issues and …

Comparing the long‐term effects of artificial and natural vegetation restoration strategies: A case‐study of Wuqi and its adjacent counties in northern China

X Xu, D Zhang - Land Degradation & Development, 2021 - Wiley Online Library
The significant increase in vegetation coverage in northern China over the past two decades
has attracted worldwide attention. Revegetation has been completed via artificial and …

Using an attention-based LSTM encoder–decoder network for near real-time disturbance detection

Y Yuan, L Lin, LZ Huo, YL Kong… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Accurate prediction of future observations based on past data is the key to near real-time
disturbance detection using satellite image time series (SITS). To overcome the limitations of …

Natural forest mapping in the Andes (Peru): A comparison of the performance of machine-learning algorithms

LA Vega Isuhuaylas, Y Hirata, LC Ventura Santos… - Remote Sensing, 2018 - mdpi.com
The Andes mountain forests are sparse relict populations of tree species that grow in
association with local native shrubland species. The identification of forest conditions for …

[HTML][HTML] Adaptive modeling of satellite-derived nighttime lights time-series for tracking urban change processes using machine learning

S Chakraborty, EC Stokes - Remote Sensing of Environment, 2023 - Elsevier
Remotely sensed nighttime lights (NTL) uniquely capture urban change processes that are
important to human and ecological well-being, such as urbanization, socio-political conflicts …

Change detection in SAR images using multiobjective optimization and ensemble strategy

R Liu, R Wang, J Huang, J Li… - IEEE Geoscience and …, 2020 - ieeexplore.ieee.org
This letter puts forward a new algorithm, ensemble strategy multiobjective fuzzy clustering
method (ESMOFCM). To fully combine the gray information and spatial information of …

An assessment of forest cover change and its driving forces in the syrian coastal region during a period of conflict, 2010 to 2020

MA Mohamed - Land, 2021 - mdpi.com
In Syria, 76% of the forests are located in the Syrian coast region. This region is witnessing a
rapid depletion of forest cover during the conflict that broke out in mid-2011. To date, there …