Mapping and Monitoring Forest Landscape Restoration using Landsat-8 Images
Keywords:Afforestation, Growth Performance, Survival Percentage, Landsat-8, Vegetation Indices
In the context of the Bonn Challenge, Pakistan has started Forest Landscape Restoration (FLR) in 2014. This study assessed growth performance, survival rate of young plantations and developed linear regression models by using Landsat-8 data. Results showed that fast growing species such as Eucalyptus camaldulensis and Robinia pseudoacacia have shown good growth rate as compared to Pinus roxburghii and Cedrus deodara. Landsat-8 vegetation indices include NDVI, SAVI, MSAVI, DVI and GNDVI were correlated with volume (m3). RVI has the highest correlation with R2 value of 0.88 followed by NDVI, SAVI and GDVI with R2 value of 0.83. Stepwise linear regression (SLR) showed that MASVI and SAVI have strong significant relationship with volume compared to rest of the indices. Simple linear regression model of RVI and volume has lowest RMSE (1.19 m3/ha) and considered best for plantation mapping. Temporal assessment of afforestation (2013-2018) by Landsat-8 images showed that plantation was successful in sampled sites. The RVI differencing and threshold measured area under vegetation was 7309.7 ha in 2013 and was increased to 9224.9 ha in 2018. The study suggested that Landsat-8 data have potential for monitoring FLR activities and can be enhanced further when combined with other datasets.