CFNet: A cross fusion network for joint land cover classification using optical and SAR images

W Kang, Y ** using multispectral sentinel-2 and hyperspectral PRISMA …
ST Seydi, M Hasanlou, J Chanussot - Remote Sensing, 2021 - mdpi.com
Wildfires are one of the most destructive natural disasters that can affect our environment,
with significant effects also on wildlife. Recently, climate change and human activities have …

Monthly burned-area map** using multi-sensor integration of Sentinel-1 and Sentinel-2 and machine learning: Case study of 2019's fire events in South Sumatra …

S Arjasakusuma, SS Kusuma, Y Vetrita… - Remote Sensing …, 2022 - Elsevier
Indonesia has experienced massive historical land and forest fire events, creating
transnational environmental and socioeconomic issues. The extent of burned areas (BAs) is …

[HTML][HTML] A hybrid convolutional neural network and random forest for burned area identification with optical and synthetic aperture radar (SAR) data

D Sudiana, AI Lestari, I Riyanto, M Rizkinia, R Arief… - Remote Sensing, 2023 - mdpi.com
Forest and land fires are disasters that greatly impact various sectors. Burned area
identification is needed to control forest and land fires. Remote sensing is used as common …

[HTML][HTML] Image texture analysis enhances classification of fire extent and severity using Sentinel 1 and 2 satellite imagery

RK Gibson, A Mitchell, HC Chang - remote sensing, 2023 - mdpi.com
Accurate and reliable map** of fire extent and severity is critical for assessing the impact
of fire on vegetation and informing post-fire recovery trajectories. Classification approaches …

A novel deep Siamese framework for burned area map** Leveraging mixture of experts

ST Seydi, M Hasanlou, J Chanussot - Engineering Applications of Artificial …, 2024 - Elsevier
Due to the complexity of the areas and the diversity of the objects, traditional Burned Area
Map** (BAM) methods cannot provide promising results. Moreover, these methods focus …

Integrated approach for the assessment of forest fire risk and burn severity map** using GIS, AHP method, and Google Earth Engine in Western Algeria

Y Fekir, MA Hamadouche, D Anteur - Euro-Mediterranean Journal for …, 2022 - Springer
In Algeria, more than 29% of the forest heritage is located in the western part where forest
fires remain the most devastating factor. The assessment of the Forest Fire Risk (FFR) and …

[PDF][PDF] Detection of forest fire damage from Sentinel-1 SAR data through the synergistic use of principal component analysis and K-means clustering

J Lee, W Kim, J Im, C Kwon, S Kim - Korean Journal of Remote …, 2021 - koreascience.kr
Forest fire poses a significant threat to the environment and society, affecting carbon cycle
and surface energy balance, and resulting in socioeconomic losses. Widely used multi …

[HTML][HTML] Forest/Nonforest Segmentation Using Sentinel-1 and-2 Data Fusion in the Bajo Cauca Subregion in Colombia

A Guisao-Betancur, L Gómez Déniz… - Remote Sensing, 2023 - mdpi.com
Remote sensing technologies have been successfully used for deforestation monitoring,
and with the wide availability of satellite products from different platforms, forest monitoring …

Burned area detection using convolutional neural network based on spatial information of synthetic aperture radar data in Indonesia

AI Lestari, D Kushardono, AA Bayanuddin - GEOGRAPHY …, 2024 - ges.rgo.ru
Forest and land fires are disasters that often occur in Indonesia which affects neighbouring
countries. The burned area can be observed using remote sensing. Synthetic aperture radar …