Using Remote Sensing Observations and Empirical-Statistical Methods to Understand the Present State and Predictable Future Changes in the State of Permafrost Distribution in North-Western Himalayas
Abstract
The impacts of climate change on extent of permafrost degradation in the Himalayas and its effect upon the carbon cycle and ecosystem changes are not well understood due to lack of historical ground-based observations. We have used high resolution optical and satellite radar observations and applied empirical-statistical methods for the estimation of spatial and altitudinal limits of permafrost distribution in North-Western Himalayas. Visual interpretations of morphological characteristics using high resolution optical images have been used for mapping, identification and classification of distinctive geomorphological landforms. Subsequently, we have created a detail inventory of different types of rock glaciers and studied the contribution of topo climatic factors in their occurrence and distribution through Logistic Regression modelling. This model establishes the relationship between presence of permafrost and topo-climatic factors like Mean Annual Air Temperature (MAAT), Potential Incoming Solar Radiation (PISR), altitude, aspect and slope. This relationship has been used to estimate the distributed probability of permafrost occurrence, within a GIS environment. The ability of the model to predict permafrost occurrence has been tested using locations of mapped rock glaciers and the area under the Receiver Operating Characteristic (ROC) curve. Additionally, interferometric properties of Sentinel and ALOS PALSAR datasets are used for the identification and assessment of rock glacier activity in the region.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.C24A..02B
- Keywords:
-
- 0702 Permafrost;
- CRYOSPHERE;
- 0758 Remote sensing;
- CRYOSPHERE