Abstract

In the long term, a sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual sustained yield of timber, fiber or energy from the forest, will generate the largest sustained mitigation benefit. Therefore, it is very much essential to understand and quantify the terrestrial carbon balance of India and its associated uncertainties. Pilot studies have been done in India to estimate forest /vegetation carbon and these estimates are spread over a decade and are based on different approaches viz: historical records, ecological data and population based forest biomass, scales and classification schemes and objectives. In the 11th Five Year Plan it is planned to provide extra thrust to understanding the terrestrial Carbon Cycle through a “National Carbon Project”. The project has three major components and aims to understand Vegetation Carbon pools, Soil Carbon pools and Soil-Vegetation Carbon fluxes. The major objectives of the Vegetation Carbon Pool assessment project are:

1. Assessment of terrestrial vegetation biomass in the country using ground sampling and satellite remote sensing data, and
2. Generation of geospatial data of the terrestrial phytomass carbon of India along with estimates of uncertainty.

Among these, fulfillment of the first objective in the Northern Kerala region is the major thrust area of the current project.

Under this subproject, determination of soil organic carbon in surface and sub-surface soils of forests of Northern Kerala is covered in the present study. A cluster based sampling using remote sensing data for stratification was suggested at national level by ISRO and the same methodology was adopted in the current work.

Information on trees outside Forests (TOF) was generated in three phases: land use classification and mapping; identification of tree-cover classes; and measurement of tree characteristics. Satellite images and aerial photos were suitable for the first two. High-resolution satellite images are likely to allow the identification of single trees (or crowns) and can be a data source for a large-area TOF inventory.