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Latest Analysis View

Segmentation Analysis

Object-based segmentation results

Segmentation

Resolution: 50 [shape=0.1] Objects: 5,247

Classification Results

Supervised classification output

Classification

Accuracy: 96% Classes: 4

Landslide Susceptibility

Risk assessment mapping

Landslide Susceptibility Index

High Risk: 23% Medium Risk: 45%

Classification Parameters

Region Uttarakhand
Algorithms Supervised random forest
Training Area 65 Sq km
Model Accuracy 75%
Approved By Jarbits

OBIA Parameters

Algorithms Segmentation + Classification
Model Accuracy 85%
5000
Object Count
1498
LS Object
3502
Non LS Object

LS Index Legends

0.8 - 1.0 (Very High Risk)
0.6 - 0.8 (High Risk)
0.5 - 0.6 (Medium Risk)
0.3 - 0.5 (Low Risk)
0.0 - 0.3 (Stable)

Active Monitoring Projects

Project Name Monitoring Frequency Datasets Data Sources AOI Size Training Dataset Count Accuracy Associated Models Actions
OBIA LS Assessment 4 Days Optical, Image, SAR, Geological Sentinel 2, Cartosets UAV, GSI 60 sq km 3 78% LS prediction
OBIA LS Assessment 4 Days Optical, Image SAR, Geological Sentinel 2, Cartosets UAV, GSI 60 sq km 3 78% LS prediction
OBIA LS Assessment 4 Days Optical, Image, SAR, Geological Sentinel 2, Cartosets UAV, GSI 60 sq km 3 78% LS prediction
OBIA LS Assessment 4 Days Optical, Image, SAR, Geological Sentinel 2, Cartosets UAV, GSI 60 sq km 3 78% LS prediction