Hierarchical Approach for Developing Baseline Soil Organic Carbon Database and Its Distribution in India

Abstract

This study involves generation and logical integration of non-spatial and spatial data in a geographical information system framework to address the gap in national level soil organic carbon estimates. Remote sensing derived inputs and other spatial layers are corrected and integrated using same geographical standards. A relational data base of soil organic carbon density of Indian forest was prepared with attribute information. Hierarchical approach was followed to stratify and verify each sample from the data base using the corrected input layers in GIS and the resulting spatially distributed data is called Indian forest soil organic carbon database. The estimated mean soil organic carbon density for Indian forest is 70 t ha−1 and varied from 35.4 t ha−1 in Tropical thorn forest to 104.2 t ha−1 in Himalayan moist temperate forest in the upper 30 cm of soil depth. Due to large variations in the surface layers the estimated standard error ranged from ±1.5 to 15 % for the upper 30 cm layer which is generally higher than the bottom soil layers. The level of detail in the data base helps to establish base line information for global, national and regional level studies.