ICES Journal of Marine Science (2011), 68(4), 773 –780. doi:10.1093/icesjms/fsq163
Aquaculture site selection for Japanese kelp (Laminaria japonica)
in southern Hokkaido, Japan, using satellite remote sensing and
GIS-based models
I Nyoman Radiarta 1,2*, Sei-Ichi Saitoh 1, and Hajime Yasui 3
1
Laboratory of Marine Bioresource and Environment Sensing, Faculty of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho, Hakodate,
Hokkaido 041-8611, Japan
2
Center for Aquaculture Research and Development, Agency for Marine Affair and Fisheries Research and Development, Jl. Ragunan 20, Pasar
Minggu Jakarta Selatan 12540, Indonesia
3
Laboratory of Science and Technology on Fisheries Infrastructure System, Faculty of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho,
Hakodate, Hokkaido 041-8611, Japan
*Corresponding Author: tel: +81 138 40 8843; fax: +81 138 40 8844; e-mail: radiarta@salmon.fish.hokudai.ac.jp; [email protected].
Radiarta, I N., Saitoh, S-I., and Yasui, H. 2011. Aquaculture site selection for Japanese kelp (Laminaria japonica) in southern Hokkaido, Japan,
using satellite remote sensing and GIS-based models. – ICES Journal of Marine Science, 68: 773 – 780.
Received 16 February 2010; accepted 19 July 2010; advance access publication 17 November 2010.
Japanese kelp (Laminaria japonica) is an important species cultured and harvested in Japan. The most suitable areas for hanging
culture in southern Hokkaido were determined using geographic information system (GIS) models and a multicriteria evaluation
approach. Analyses of physical parameters (sea surface temperature and suspended solid from SeaWiFS and MODIS) and available
bathymetric data indicated that some 74% (1139 km2) of the total potential area with bottom depths ,60 m had the two
highest suitability scores. A local sensitivity analysis indicated that suspended solids were more important than temperature in affecting model output. This study demonstrates that GIS databases of different formats and sources can be used effectively to construct
spatial models for kelp aquaculture.
Keywords: aquaculture site selection, GIS, Hokkaido, kelp, Laminaria japonica, remote sensing.
Introduction
More than 50 species of kelp have been reported worldwide, of which
20 are present in the Asia-Pacific region (Scoggan et al., 1989).
Japanese kelp [Laminaria japonica (“Ma-kombu”)] grows in the temperate, cold-water zone and is native to the northwest Pacific coast,
occurring as far south as 368N (Scoggan et al., 1989). Globally, it is
one of the most valuable cultured and harvested seaweed species
(Critchley, 1993). Landings have increased consistently during the
past 17 years, from 2.5 × 106 t in the 1990s to more than 4.5 ×
106 t in 2007 (FAO, 2009). China leads in Japanese kelp production,
followed by Japan and Korea. In Japan, this species is mainly found
along Hokkaido Island and the northeast coast of Honshu.
Traditionally, kelps were harvested from wild stocks, but these are
declining because of overharvesting. Recent advances in marine aquaculture techniques have contributed significantly to kelp production.
Currently, more than 36% of Japanese kelp production in Japan is
from aquaculture (FAO, 2009), mainly in Hokkaido.
The location and amount of aquaculture activity must balance
the needs of conservation and economic return in a sustainable
manner (GESAMP, 2001). Final determination of site suitability
involves careful consideration of social, economic, and environment factors. Environmental suitability forms the basis for planning exercises and management interventions.
With the development of the geographic information system
(GIS) and availability of remote sensing data, it is now possible to
# 2010
select environmentally suitable areas rapidly and systematically.
GIS has been widely used in aquaculture development, including
site suitability determination, zoning, environmental impacts, planning, inventory and monitoring of aquaculture and the environment, and competitive exploitation of common areas (Arnold
et al., 2000; Bacher et al., 2003; Pérez et al., 2005; Corner et al.,
2006; Longdill et al., 2008; Radiarta et al., 2008). Many studies
have been done on aquaculture site selection (Arnold et al., 2000;
Pérez et al., 2003; Radiarta et al., 2008), but few have used satellite
ocean-colour data to investigate site suitability for kelp aquaculture.
This paper presents a quantitative evaluation of coastal areas using
GIS-based physical models to identify suitable sites for Japanese
kelp aquaculture development in southern Hokkaido, Japan.
Material and methods
Study area
The study area includes a 368-km coastline from Muroran to
Kikonai, Hokkaido, between 41840′ and 42835′ N and 140815′
and 141815′ E (Figure 1). The oceanography of the region is
affected by the inflow of two water masses: Tsuguru warm water
from autumn to winter, and Oyashio water (a Subarctic oceanic
water mass) from spring to summer (Ohtani, 1971; Ohtani and
Kido, 1980; Takahashi et al., 2004). Sea surface temperatures
(SSTs) range from ,58C in March to .208C in August/
September, and salinity is relatively stable, with values ranging
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774
I N. Radiarta et al.
Figure 1. Location of the study area in southern Hokkaido, Japan, including major depth contours and place names.
Table 1. Parameter requirements for Japanese kelp aquaculture development in the southern part of Hokkaido Island, Japan.
Parameters
Sea surface temperature
Suspended solids
Bathymetry
Slope
Interpretation parameter
Favourable temperature for kelp culture
Indicates level of water clarity (turbidity)
Favourable depth for hanging culture
Favourable slope for hanging culture
from 31 to 34 psu (Shimada et al., 2000). Levels of chlorophyll a
are very high (.3 mg m23) during the spring bloom in March,
but relatively low (,1 mg m23) during summer (Radiarta and
Saitoh, 2008). These unique characteristics provide a favourable
environment, making the region one of the most important cultivation areas in Hokkaido for scallops (Mizuhopecten yessoensis)
and kelp.
Identification of parameters and spatial database
acquisition
The main factors (Table 1) used in this study are described below.
SSTs were derived from the Moderate Resolution Imaging
Spectroradiometer (MODIS) Aqua sensor as level-2 data, with
1-km resolution, from the Distribution Active Archive Centre/
Goddard Space Flight Centre/National Aeronautic and Space
Optimum
9 –128C
,2 g m – 3
10 –30 m
,108
Reference
Scoggan et al. (1989), Fang et al. (1996), Suzuki et al. (2008)
Otero and Siegel (2004), Nezline et al. (2005)
Scoggan et al. (1989), Kawashima (1993), Fang et al. (1996)
Bushing (1995), Bekkby et al. (2009)
Administration (DAAC/GSFC/NASA; Savtchenko et al., 2004).
In all, 287 images with good coverage were collected from June
2002 to August 2004.
Suspended solid (SS) concentrations were determined from
remotely sensed, normalized, water-leaving radiance at 555 nautical mile wavelength, nLw(555). Daily level-2 SeaWiFS data with
1-km resolution (February 1998 to August 2004) were obtained
from DAAC/GSFC/NASA (Acker et al., 2002). The nLw (555)
values were extracted from the daily SeaWiFS data. Monthly
average (g m23) images of nLw (555) were produced following
Ahn’s equation (Ahn et al., 2001): SS ¼ 3.18nLw(555)0.95.
All SST and SS images from all seasons were combined to generate composite maps of average values for each parameter (Pérez
et al., 2003). These images were then reclassified according to suitability scores. A bathymetric map was prepared by combining a
775
Aquaculture site selection using remote sensing and GIS
scanned hydrographic chart (Japan Hydrographic Department
1:150 000) and a digitized map of 500-m gridded bathymetric
points (Japan Oceanographic Data Center, JODC, http://jdoss1
.jodc.go.jp/cgi-bin/1997/depth500_file). A digital terrain model
(DTM) was used (triangulated irregular network; Hutchinson
and Gallant, 2000) to create the final contour map (either as
raster or vector data) for classification according to the suitability
criteria.
Suitable water depth for Japanese kelp aquaculture depends on
the length of kelp ropes used and the hanging-raft culture methods
employed. In general, the sites should be selected where the
minimum water depth is 15 –25 m. In this analysis, to minimize
operation costs and difficulty in mooring systems, water depths
.60 m were excluded, resulting in a potential area of
1541 km2. The slope of the bottom (degrees) was obtained
from the DTM of the bathymetry image using the ArcGIS 9.2
slope function that calculates the maximum rate change between
each cell and its neighbours.
All spatial data were registered to the study area’s coastline,
obtained from the International Steering Committee for Global
Mapping (http://www.iscgm.org/cgi-bin/fswiki/wiki.cgi). All
data used in the GIS models were built on a WGS 84 UTM
Zone 54 North coordinate system. Data on the above parameters
prepared for input to the GIS database were built based on a
10 m × 10 m pixel size (Pérez et al., 2005; Radiarta et al., 2008).
Analytical framework and model construction
Suitability levels (scores) for each parameter were defined according to requirements for kelp aquaculture using the hanging technique (Table 2). Parameter values were ranked and classified
from 1 (least suitable) to 8 (most suitable) following Radiarta
et al. (2008). Parameter weights were determined by pairwise comparisons according to the Analytical Hierarchy Process of Saaty
(1977) for decision-making. Their relative importance was
obtained through a literature review and experts’ opinions
(Table 3). Relative parameter importance was evaluated on a ninepoint, continuous-rating scale from 1 (least important) to 9 (most
important). The principal eigenvector of the pairwise comparison
matrix was computed to produce the best fit for a total weighting
of 1. In addition, the consistency ratio of the matrix was also calculated. This value indicates the probability that ratings were randomly assigned. A consistency ratio of 0.10 or less was considered
to be acceptable (Saaty, 1977; Banai-Kashani, 1989). Once the
scores and weights of the spatial data had been determined, a multicriteria evaluation procedure (weighted linear combination)
available in the ArcGIS model builder function was applied.
Sensitivity analysis
A sensitivity analysis was done to examine how the weighting of
time-variable parameters could affect the determination of
Table 2. Physical factor requirements and suitability scores for Japanese kelp aquaculture-site selection in southern Hokkaido, Japan.
Suitability rating and score
Parameter
Sea surface
temperature (8C)
Bathymetry (m)
Suspended solids
(g m – 3)
Slope (8)
8
10–11
7
9 –10 or 11– 12
6
8– 9 or 12–13
5
7 –8 or 13– 14
4
6 –7 or 14–15
3
5 –6 or 15 –16
2
4 –5 or 16–17
1
,4 or .17
10–25
,1.6
9 –10 or 25– 30
1.6 –2.0
8– 9 or 30–35
2.0–2.3
7 –8 or 35– 40
2.3 –2.6
6 –7 or 40–45
2.6–2.9
5 –6 or 45 –50
2.9 –3.5
4 –5 or 50–60
3.5–4.0
.60 or ,4
.4.0
,5
5 –10
10–15
15 –18
18–20
20 –23
23– 25
.25
Table 3. Pairwise comparison matrix for assessing the relative importance of parameters for Japanese kelp aquaculture development in the
southern part of Hokkaido Island, Japan (numbers indicate the rating of row relative to column factors).
Parameter
Sea surface temperature
Suspended solids
Bathymetry
Slope
Sea surface temperature
1
1/2
1/3
1/4
Suspended solids
2
1
1/2
1/3
Bathymetry
3
2
1
1/2
Slope
4
3
2
1
Weight
0.46
0.28
0.16
0.10
Consistency ratio (CR) ¼ 0.015, consistency is acceptable.
Table 4. Area (km2) and percentage of total area (%) with different suitability scores for Japanese kelp aquaculture development in the
southern part of Hokkaido Island, Japan, with depths ,60 m.
Suitability score
1
Physical model of site
selection
Sea surface temperature
Suspended solids
Bathymetry
Slope
Overall model
km2
0.0
25.0
45.0
0.0
0.0
2
%
0.0
2.0
3.0
0.0
0.0
km2
0.0
29.0
391.0
0.0
0.0
3
%
0.0
2.0
25.0
0.0
0.0
km2
3.0
56.0
182.0
0.0
1.0
4
%
0.2
4.0
12.0
0.0
0.1
km2
16.0
43.0
170.0
0.0
14.0
5
%
1.0
3.0
11.0
0.0
0.9
km2
278.0
46.0
145.0
0.0
64.0
6
%
18.0
3.0
10.0
0.0
4.0
km2
98.0
79.0
134.0
0.2
323.0
7
%
6.5
5.0
9.0
0.1
21.0
km2
402.0
223.0
129.0
10.5
847.0
8
%
26.0
14.0
8.0
0.9
55.0
km2
744.0
1 040.0
345.0
1 530.0
292.0
%
43.8
67.0
22.0
99.0
19.0
776
preferred areas. Bathymetry and slope were assumed to be temporally constant and excluded.
Many methods for sensitivity analysis have been used for
model evaluations (Hamby, 1994; Delgado and Sendra, 2004).
This study used a local sensitivity analysis, because it provides
the most information about parameters influencing the
I N. Radiarta et al.
variability of the suitability model output. The analysis was conducted by varying each parameter by +5, +10, and +20% of
the reference values, but leaving all others constant. Suitability
maps for every interval value were generated and the change
in area for each suitability score and every weighting scheme
determined.
Figure 2. Suitability maps for environmental criteria used in physical modelling, masked to exclude depths .60 m, for Japanese kelp
aquaculture: (a) SST, (b) SSs, (c) bathymetry, and (d) slope.
777
Aquaculture site selection using remote sensing and GIS
Figure 3. Overall site selection map for combined environmental criteria, depths ,60 m, for Japanese kelp aquaculture development in
southern Hokkaido, Japan.
Results
Spatial distribution of suitability
The classifications of surface areas for each parameter are summarized in Table 4, and the corresponding spatial distributions of suitability sites are illustrated in Figures 2 and 3.
Based on SST, 43.8% of the potential area scored 8 (Table 4).
These areas were mostly located in the west (Figure 2a). Regarding
SS, 67 and 14% of the area had scores of 8 and 7, respectively.
Only 8% of the area had low scores (sum of scores 1, 2, and
3). These areas were mostly located along the coastline near the
Yuurap River in the Yakumo region (Figure 2b). Based on water
depth, some 22% of the potential area scored 8 (Table 4 and
Figure 2c). For slope characteristics, most of the potential area
had high suitability scores of 8 (99%) and 7 (0.9%; Figure 2d).
For all parameters combined, the model predicted that 19%
(292 km2) of the potential area had a score of 8 (Table 4).
Figure 3 clearly highlights the suitability of the western and
southern part of the study area, because of the high quality of
water properties, appropriate water depths, and slope
Table 5. Results of local sensitivity analysis, illustrating the change
in suitability areas (km2) as SSTs and SSs are varied by +5, +10,
and +20% from the baseline model.
Parameter
1
Baseline model
0
Sea surface temperature
+20
0
+10
0
+5
0
25
0
210
0
220
0
Suspended solids
+20
0
+10
0
+5
0
25
0
210
0
220
0
2
0
3
1
4
14
5
64
6
323
7
847
8
292
0
0
0
0
0
0
1
1
1
1
1
1
11
11
11
13
15
26
50
60
56
65
68
70
369
363
323
323
285
470
779
797
822
918
880
774
331
309
328
221
292
200
0
0
0
0
0
0
1
1
1
1
1
1
32
16
13
11
11
9
73
79
74
114
99
140
269
292
318
495
502
518
894
861
843
681
689
570
272
292
292
239
239
303
778
I N. Radiarta et al.
Figure 4. Results of sensitivity analysis illustrating differences in area (km2) between each sensitivity factor and the baseline model for each of
the suitability scores.
characteristics. Approximately 55% of the potential area scored 7,
26% scored mid-scale (4– 6), and ,1% scored 3. No area scored
either 1 or 2 in suitability.
Sensitivity analysis
Changes from the baseline model for each of the variables in
square kilometres for each suitability score are given in Table 5
and Figure 4. SS affected the overall model more strongly than
SST. The model was more sensitive to lower than higher values
of SS and SST.
Discussion
Development of kelp aquaculture is affected by many aspects,
including environmental (physical, biological, and chemical), as
well as socio-economic factors (Scoggan et al., 1989; Largo and
Ohno, 1993; Kingzet et al., 2002). The site-selection model used
in this study only focused on the important physical parameters
of SST, SS, bathymetry, and slope. Combining these parameters
through GIS provides a more relevant analysis for decision-makers
than the one based on individual parameters alone. Not surprisingly, areas with the greatest potential for kelp culture are those
where favourable parameter scores coincide.
The results of the GIS model could be only partly verified using
kelp landing production (Hokkaido Central Fisheries Experiment
Station, 2009). Figures 3 and 5 demonstrate that scores tend to
reflect kelp production. For example, the highest production was
in the high-scoring Minamikayabe area, whereas the least productive Kikonai area had low scores. However, this relationship
is complex, because kelp production inside Funka Bay is generally
smaller because of the prevalence of scallop aquaculture there,
rather than lack of suitable kelp areas (Miyazono, 2006).
Weighting is one of the primary challenges in site-selection
analyses using multicriteria evaluation procedures. To the extent
possible, weightings should be consistent with decision-maker
preferences (Butler et al., 1997). Once weights have been assigned,
a sensitivity analysis should be conducted to determine their influence on the overall results. In this study, significant changes in
Figure 5. Kelp landings for southern Hokkaido, Japan, 1991– 2006.
suitable areas were found when parameter weights were varied.
The model was particularly sensitive to SS, but also to SST.
Remote-sensing data have been used in aquaculture site selection for more than 20 years (Kapetsky et al., 1987; Kapetsky and
Anguilar-Manjarrez, 2007). Their analysis with modern GIS techniques could result in an efficient and cost-effective management
tool. There is great potential for remotely sensed, ocean-colour
data in marine aquaculture development (Grant et al., 2009);
however, there are also limitations and potential inaccuracies.
For example, the algorithm for SS in the current model was developed for Korean waters (Ahn et al., 2001). An algorithm based on
local Hokkaido water characteristics could provide more accurate
model output and it should be developed for future assessments.
Environmental characteristics in the study region vary temporally,
as well as spatially. Because temporal variability could influence
kelp growth (Radiarta et al., 2008), the model could be improved
further by including monthly (Eastwood et al., 2001) or seasonal
(Vincenzi et al., 2006) variability of parameters. Further progress
in GIS and remote-sensing technology should contribute to the
Aquaculture site selection using remote sensing and GIS
development of a generic evaluation framework for coastal planners and policy-makers interested in sustainable aquaculture.
Acknowledgements
We thank the Distribution Active Archive Center at the NASA
Goddard Space Flight Center for the production and distribution
of the SeaWiFS and MODIS data. The study was supported by the
2010 Hakodate Marine Bio Industrial Cluster Project of the
Regional Innovation Cluster Program (formerly the Knowledge
Cluster Program), Grants-in-Aid of University and Society
Collaboration, Ministry of Education, Culture, Sports, Science
and Technology (MEXT), Japan. Comments by two anonymous
reviewers contributed greatly to improving the manuscript.
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