Landslide map** with remote sensing: challenges and opportunities

C Zhong, Y Liu, P Gao, W Chen, H Li… - … Journal of Remote …, 2020 - Taylor & Francis
Landslide map** is the primary step for landslide investigation and prevention. At present,
both the accuracy and the degree of automation of landslide map** with remote sensing …

[HTML][HTML] Remote sensing for landslide investigations: An overview of recent achievements and perspectives

M Scaioni, L Longoni, V Melillo, M Papini - Remote Sensing, 2014 - mdpi.com
Landslides represent major natural hazards, which cause every year significant loss of lives
and damages to buildings, properties and lifelines. In the last decades, a significant increase …

[HTML][HTML] Deep into the mud: ecological and socio-economic impacts of the dam breach in Mariana, Brazil

GW Fernandes, FF Goulart, BD Ranieri… - Natureza & …, 2016 - Elsevier
We review the ecological and socio-economic impacts of the catastrophic dam failure in
Mariana, Brazil. Tailing management practices by Samarco mining company ultimately …

[HTML][HTML] Landslide map** from multi-sensor data through improved change detection-based Markov random field

P Lu, Y Qin, Z Li, AC Mondini, N Casagli - Remote Sensing of Environment, 2019 - Elsevier
Accurate landslide inventory map** is essential for quantitative hazard and risk
assessment. Although multi-temporal change detection techniques have contributed greatly …

A new deep-learning-based approach for earthquake-triggered landslide detection from single-temporal RapidEye satellite imagery

Y Yi, W Zhang - IEEE Journal of Selected Topics in Applied …, 2020 - ieeexplore.ieee.org
Accurate landslide detection and map** are essential for land use planning,
management/assessment, and geo-disaster risk mitigation as well as post-disaster …

Remote sensing for assessing landslides and associated hazards

C Lissak, A Bartsch, M De Michele, C Gomez… - Surveys in …, 2020 - Springer
Multi-platform remote sensing using space-, airborne and ground-based sensors has
become essential tools for landslide assessment and disaster-risk prevention. Over the last …

[HTML][HTML] Landslide map** and monitoring by using radar and optical remote sensing: Examples from the EC-FP7 project SAFER

N Casagli, F Cigna, S Bianchini, D Hölbling… - … applications: society and …, 2016 - Elsevier
This paper focuses on the Landslide Thematic services of the EU-funded FP7-SPACE
project SAFER (Services and Applications For Emergency Response) for inventory …

[HTML][HTML] Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis

L Hao, A Rajaneesh, C Van Westen… - … system science data, 2020 - essd.copernicus.org
Event-based landslide inventories are important for analyzing the relationship between the
intensity of the trigger (eg, rainfall, earthquake) and the density of the landslides in a …

Identification of forested landslides using LiDar data, object-based image analysis, and machine learning algorithms

X Li, X Cheng, W Chen, G Chen, S Liu - Remote sensing, 2015 - mdpi.com
For identification of forested landslides, most studies focus on knowledge-based and pixel-
based analysis (PBA) of LiDar data, while few studies have examined (semi-) automated …

Correlation of satellite image time-series for the detection and monitoring of slow-moving landslides

A Stumpf, JP Malet, C Delacourt - Remote sensing of environment, 2017 - Elsevier
Slow-moving landslides are widespread in many landscapes with significant impacts on the
topographic relief, sediment transfer and human settlements. Their area-wide map** and …