×

You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Title
Technical Commission VII










/, 2012
14(10):
oth
) Tree
Caartinen
tion from
10):
and
e
ication.
ng.
T and
r a boreal
, lidar and
'orest
ar
ing of


International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
FUSION OF OPTICAL DATA AND SAR DATA FOR THE ESTIMATION OF NITROGEN
CONCENTRATION IN PEARL RIVER ESTUARY HONG KONG SEAS, CHINA
Xiangnan Liu*, Meiling Liu, Ling Wu
School of Information Engineering, China University of Geosciences, 100083 Beijing, China liuxn@cugb.edu.cn,
liumeiling427@126.com, wl_19830807@sohu.com
KEY WORDS: Total inorganic nitrogen, RADARSAT-2, HJ-1 CCD image, backscattering coefficient, optical parameters,
polarization parameters
ABSTRACT:
The knowledge of nitrogen concentration in the ocean is fundamental for the study of oceanic biogeochemical processes. The
objective of this research is to estimate total inorganic nitrogen (TIN) by integrating optical parameters from HJ-1 CCD image and
polarization parameters from RADARSAT-2 quad-polarization image. The situ data and HJ-1 CCD, RADARSAT-2 image were
acquired from Pearl River Estuary Hong Kong Seas, China in August, 2010. The four sensitive parameters, reflectance of Band 4,
NDSI (Normalized Difference Spectral Index), the backscattering coefficient of HV and VH were derived as input variables to assess
the TIN. A multiple regression model was established between four input variables and TIN. The result showed that the fusion of
optical data and SAR data was proved to be successful in estimating TIN in sea surface, with the correlation coefficient (R?) between
measured TIN and predicated TIN of 0.774, and the root mean square error (RMSE) of 0.063. The optical data in combination with
SAR data is promising for detecting biochemical component in sea surface.
1. INTRODUCTION
The knowledge of temporal and spatial variations of nitrate
concentrations at global or regional scales in the ocean is
needed to quantify the role of nitrates in oceanic
biogeochemical processes, and in particular those linked to new
primary production (Kamykowski et al., 2003, 2005). Many
attempts have been made to estimate nitrate concentrations
using satellite data. Some researchers applied satellite data to
estimate nitrate concentrations in sea according to
temperature—nitrate relationships based on matching vertical
profiles of sea surface temperatures (SST) and nitrate
concentrations (Traganza et al., 1983; Dugdale et al., 1989). In
order to increase the accuracy of estimation nitrate
concentrations, other researchers derived inverse relationships
between nitrate concentrations and chlorophyll-a concentration,
SST by introducing chlorophyll-a concentration as an additional
input to empirical algorithms (Goes et al.,1999,2000;
Silio-Calzada et al., 2008). However, the empirical algorithms
derived from the chlorophyll-a, SST were limited to restricted
periods and areas, due to varying hydrodynamics and
biogeochemical characteristics condition.
In this paper, we proposed a new approach for the estimation of
nitrate concentrations in sea surface, by deriving the sensitive
remotely sensed parameters from optical image and SAR image.
2. STUDY AREA AND MATERIAL
2.1 Study Area
The study area (22?18'08"N, 114?03'30"E) is located in the east
of the Pearl River Estuary (PRE), China, which is
well-developed economical district and has many industrial

* Corresponding author: e-mail: liuxn@cugb.edu.cn

operations, which polluted the coastal areas. The site has a
warm and humid subtropical climate, the Pearl River flows
through large catchment areas into the PRE and finally reaches
the South China Sea, which is the largest marginal sea on the
western boundary of the Pacific Ocean.
2.2 Image data
A scene of HJ-1 CCD image was acquired on 4 August 2010
(Figurel(a))HJ-1 satellite equipped with a CCD camera and
hyperspectral imager (HSI) or infrared camera (IRS), which was
successfully launched on at 11:25 on September 6, 2008,China
to monitor environment and disaster. The HJ-1 CCD image has
a four spectral band (Bandl: 0.43-0.52um, Band2:0.52-0.60um,
Band3:0.63-0.69um, Band4: 0.76-0.90um) with a 30mx30m
spatial resolution. The two identical CCD cameras in the
HJ-1-A satellite and HJ-1-B satellite can image the ground
swath width of 700 km. Revisit cycle is two days. The
preprocessing of HJ-1CCD imagery includes atmospheric
correction and geometric correction.
In this study, a scene of fine quad-polarization RADARSAT-2
image covering the study area was acquired over the study area
on 22:28, 1 August 2010 from China Remote Sensing Satellite
Ground Station (Figurel (b). Band beam is Q19, spatial
resolution is 12mx8 m, incidence angle is about 22° .The image
has been preprocessed to product level of SGX and output to
GeoTIFF data format. The Next European Space Agency (ESA)
SAR Toolbox (NEST) was used for further data processing,
including radiance calibration, geocorrection, coregistration,
multlooking and speckle reduction. For speckle reduction, the
multitemporal speckle filter was adopted, and the filter window
size was set 3 x 3.Overview of RADARSAT-2 image and HJ-1
CCD image are displayed in Tablel.