Mapping tree height in burkina faso parklands with tandem-x
Artikel i vetenskaplig tidskrift, 2021

Mapping of tree height is of great importance for management, planning, and research related to agroforestry parklands in Africa. In this paper, we investigate the potential of spotlight-mode data from the interferometric synthetic aperture radar (InSAR) satellite system TanDEM-X (TDM) for mapping of tree height in Saponé, Burkina Faso, a test site characterised by a low average canopy cover (~15%) and a mean tree height of 9.0 m. Seven TDM acquisitions from January–April 2018 are used jointly to create high-resolution (~3 m) maps of interferometric phase height and mean canopy elevation, the latter derived using a new, model-based processing approach compensating for some effects of the side-looking geometry of SAR. Compared with phase height, mean canopy elevation provides a more accurate representation of tree height variations, a better tree positioning accuracy, and better tree height estimation performance when assessed using 915 trees inventoried in situ and representing 15 different species/genera. We observe and discuss two bias effects, and we use empirical models to compensate for these effects. The best-performing model using only TDM data provides tree height estimates with a standard error (SE) of 2.8 m (31% of the average height) and a correlation coefficient of 75%. The estimation performance is further improved when TDM height data are combined with in situ measurements; this is a promising result in view of future synergies with other remote sensing techniques or ground measurement-supported monitoring of well-known trees.

Two-level model (TLM)

Interferometric synthetic aperture radar (InSAR)

Spotlight data

Vegetation height

Geometric corrections

Författare

Maciej Soja

MJ Soja Consulting

University of Tasmania

Martin Karlson

Linköpings universitet

Jules Bayala

World Agroforestry (ICRAF) West and Central Africa Regional Office Sc/Center for International Forestry Research (CIFOR)

Hugues Roméo Bazié

University Joseph KI-ZERBO

Josias Sanou

Institut de l'Environnement et de Recherches Agricoles (INERA)

Boalidioa Tankoano

University Nazi BONI

Leif Eriksson

Chalmers, Rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys

Heather Reese

Göteborgs universitet

Madelene Ostwald

Chalmers, Göteborgs miljövetenskapliga centrum (GMV)

Chalmers, Rymd-, geo- och miljövetenskap, Fysisk resursteori

Lars Ulander

Chalmers, Rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys, Optisk fjärranalys

Remote Sensing

2072-4292 (ISSN)

Vol. 13 14 2747

Ämneskategorier

Geofysik

Naturgeografi

Sannolikhetsteori och statistik

DOI

10.3390/rs13142747

Mer information

Senast uppdaterat

2021-08-06