Tropical forest heterogeneity from TanDEM-X InSAR and lidar observations in Indonesia

Elsa Carla De Grandi; Edward Mitchard

doi:10.1117/12.2241796

18 October 2016 Tropical forest heterogeneity from TanDEM-X InSAR and lidar observations in Indonesia

Elsa Carla De Grandi, Edward Mitchard

Proceedings Volume 10003, SAR Image Analysis, Modeling, and Techniques XVI; 1000305 (2016) https://doi.org/10.1117/12.2241796
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom

Abstract

Fires exacerbated during El Niño Southern Oscillation are a serious threat in Indonesia leading to the destruction and degradation of tropical forests and emissions of CO2 in the atmosphere. Forest structural changes which occurred due to the 1997-1998 El Niño Southern Oscillation in the Sungai Wain Protection Forest (East Kalimantan, Indonesia), a previously intact forest reserve have led to the development of a range of landcover from secondary forest to areas dominated by grassland. These structural differences can be appreciated over large areas by remote sensing instruments such as TanDEM-X and LiDAR that provide information that are sensitive to vegetation vertical and horizontal structure. One-point statistics of TanDEM-X coherence (mean and CV) and LiDAR CHM (mean, CV) and derived metrics such as vegetation volume and canopy cover were tested for the discrimination between 4 landcover classes. Jeffries-Matusita (JM) separability was high between forest classes (primary or secondary forest) and non-forest (grassland) while, primary and secondary forest were not separable. The study tests the potential and the importance of potential of TanDEM-X coherence and LiDAR observations to characterize structural heterogeneity based on one-point statistics in tropical forest but requires improved characterization using two-point statistical measures.

Citation Download Citation

Elsa Carla De Grandi and Edward Mitchard "Tropical forest heterogeneity from TanDEM-X InSAR and lidar observations in Indonesia", Proc. SPIE 10003, SAR Image Analysis, Modeling, and Techniques XVI, 1000305 (18 October 2016); https://doi.org/10.1117/12.2241796

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available