Systematic analysis of quantitative relationship between leaf nitrogen concentration and vegetation indices
Student name: Ms Vijay Laxmi
Guide: Dr Vinay Shankar Prasad Sinha
Year of completion: 2018
Host Organisation: Jawaharlal Nehru University, New Delhi
Supervisor (Host Organisation): Prof P K Joshi
Abstract: Forests assume tremendous importance in natural ecosystems. They not only provide
livelihood for humans and habitats for animals, but play a humongous role in
preventing soil erosion, protecting watersheds and mitigating climate change through
carbon sequestration. Within this, nitrogen (N) regulates several key processes, such
as plant productivity (Asner and Martin, 2008), rates of litter decomposition, and
dynamics of the terrestrial carbon cycle (Clevers and Gitelson , 2013). Any change in
leaf nitrogen concentration adversely affects the functioning, structure, and overall
condition of an ecosystem. Remote sensing techniques are an excellent alternative to
traditional approaches for mapping the spatial distribution of N concentration over
large areas. The primary aim of this study is to assess the relation of leaf nitrogen with
vegetation indices computed using remote sensing data. The initial segments of the
study deal with forest canopy density mapping. This is followed by forest
characterization using two classification approaches- SVM and RF. The final segment
discusses the quantitative relationship of leaf nitrogen with hyperspectral (hyperion)
and multispectral (sentinel) vegetation indices. SVM classifier using hyperion data
turned out to be a more suitable approach for species mapping. NDVI and RVI turned
out to be best indictors of leaf nitrogen using both hyperion and sentinel bands.
