TY - JOUR
T1 - Machine learning
T2 - New potential for local and regional deep-seated landslide nowcasting
AU - van Natijne, Adriaan L.
AU - Lindenbergh, Roderik C.
AU - Bogaard, Thom A.
PY - 2020
Y1 - 2020
N2 - Nowcasting and early warning systems for landslide hazards have been implemented mostly at the slope or catchment scale. These systems are often difficult to implement at regional scale or in remote areas. Machine Learning and satellite remote sensing products offer new opportunities for both local and regional monitoring of deep-seated landslide deformation and associated processes. Here, we list the key variables of the landslide process and the associated satellite remote sensing products, as well as the available machine learning algorithms and their current use in the field. Furthermore, we discuss both the challenges for the integration in an early warning system, and the risks and opportunities arising from the limited physical constraints in machine learning. This review shows that data products and algorithms are available, and that the technology is ready to be tested for regional applications.
AB - Nowcasting and early warning systems for landslide hazards have been implemented mostly at the slope or catchment scale. These systems are often difficult to implement at regional scale or in remote areas. Machine Learning and satellite remote sensing products offer new opportunities for both local and regional monitoring of deep-seated landslide deformation and associated processes. Here, we list the key variables of the landslide process and the associated satellite remote sensing products, as well as the available machine learning algorithms and their current use in the field. Furthermore, we discuss both the challenges for the integration in an early warning system, and the risks and opportunities arising from the limited physical constraints in machine learning. This review shows that data products and algorithms are available, and that the technology is ready to be tested for regional applications.
KW - Deep-seated landslide
KW - Early warning systems
KW - Hazard assessment
KW - Machine learning
KW - Remote sensing
UR - http://www.scopus.com/inward/record.url?scp=85081032959&partnerID=8YFLogxK
U2 - 10.3390/s20051425
DO - 10.3390/s20051425
M3 - Article
AN - SCOPUS:85081032959
SN - 1424-8220
VL - 20
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 5
M1 - 1425
ER -