@InProceedings{SantosNeDuArGaEl:2004:TrFoBi,
author = "Santos, Jo{\~a}o Roberto dos and Neeff, T. and Dutra, Luciano
Vieira and Araujo, L. S. and Gama, Fabio Furlan and Elmiro, M. A.
T.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and University
of Freiburg, Tennenbacher Strabe 4, 79085 Freiburg Brsg. and
Germany and UFMG-Federal University of Minas Gerais, Av.
Ant{\^o}nio Carlos, 6627, B.Horizonte",
title = "Tropical Forest Biomass Mapping from Dual Frequency Sar
Interferometry (X And P- Bands)",
year = "2004",
organization = "ISPRS - International Society for Photogrammetry and Remote
Sensing - Technical Commission 7.",
publisher = "M. Orhan Altan",
keywords = "Interferometer, SAR, Forestry, Land cover, Inventory, Mapping,
Modelling.",
abstract = "Radar sensors operating with different wavelengths and
polarizations have been widely used for large-scale forest mapping
and monitoring. The interferometric phase obtained by microwave
sensors contains additional information on the three-dimensional
structure of the scattering targets in the image. An experiment
was performed in the Brazilian Amazon (Tapaj{\'o}s National
Forest and surroundings) to provide airborne SAR data at X- and P-
bands over tropical rain forest. In a first step of the presented
research the regular radar backscatter results are joined with an
interferometric height model to establish a statistical
relationship to forest biomass (primary and secondary vegetation).
Subsequently, that model is applied for generation of a thematic
land cover map. Backscattering of P-band waves mainly occurs on
the ground surface, and can be used for interferometric generation
of a Digital Elevation Model. The X-band is reflected by dossel,
and thus relates to the forest canopy in a Digital Surface Model.
The difference between both models has been shown to represent
height of vegetation. Care was taken in establishing statistical
models that relate dendrometric parameters from forest types to
both P-band backscatter and interferometric height. A best biomass
model [biomass = 44.965 + 13.887 × h int + 10.556 × s°HH ] was
established after comprehensive testing of a range of specific
allometric equations to achieve statistically high precision in
biomass prediction. A segmentation algorithm (hierarchical region
growth) was applied to the remote sensing dataset to provide means
for application of the biomass model to homogeneous landscape
units with similar biophysical characteristics and site histories.
A final mapping result displays forest biomass, and accounts for
different successional stages and primary forest in intervals.",
conference-location = "Istanbul, Turkey",
conference-year = "12-23 July",
copyholder = "SID/SCD",
isbn/issn = "1682-1777",
language = "en",
targetfile = "tropical forest biomass.pdf",
volume = "35 part. b",
urlaccessdate = "04 maio 2024"
}