Journal of Natural Disaster Science, Volume 25, Number 1, 2003, pp23-36

Effect of Flooding on Megalopolitan Land Prices:
A Case Study of the 2000 Tokai Flood in Japan
Guofang ZHAI, Teruki FUKUZONONational Research Institute for Earth Science and Disaster Prevention (NIED),
Ten-nodai 3-1, Tsukuba, 305-0006, Japan.
Saburo IKEDA
University of Tsukuba, Ten-nodai 1-1, Tsukuba, 305-8573, Japan(Received for 31. Mar., 2002 and in revised form 18 Jul., 2003)

ABSTRACTA framework for analyzing the effect of flooding on land prices is proposed based on a case study of the Tokaiflood in September 2000. The flood effect was examined by cross-sectional and panel analyses, panel data comprising land price and its attributes. Interesting findings were that land prices in flood-prone areas are lower andhave less variance than in other areas. The price of land for commercial use in flood-prone areas is higher thanthat for residential or industrial land, and the amount and ratio of diminution also are larger. Spatially, of thethree areas in the Tokai region studied, land prices in Nishi Ward, Nagoya are the highest, but diminution and thediminution ratio of land prices vary greatly. It is necessary to differentiate flood effects from the location effect onland prices when estimating the scale of the effect of flooding. The Tokai flood effect has a reverse Z-shaped pattern. At onset, the greater the inundation, the greater the decrease rate. In the case of the Tokai flood of 2000, theflood effect appeared in part in 2001 and in entirety in 2002. The mean of the effect in monetary value was-2204.7 yen/m2 in 2001 and -8888.3 yen/m2 in 2002, change in the rates being -1.27% in 2001 and -4.7% in 2002.
The higher the price, the stronger the impact; whereas, the impact on the rate of land-price change was similar
regardless of the price. Even so, it seems that residents prefer cheap land rather than low risk of flooding.

1. INTRODUCTION
Flooding is one of the oldest, most frequent, and severest natural disasters. A study by the Munich Reinsurance Company foundthat among the major natural catastrophes that occurred in 2000,
flooding accounted for 50% of the total economic loss (MunichRe,
2001). The characteristics of floods have altered with urbanizationand industrialization, and have become particularly complex withthe rise of the megalopolis, a densely populated region with avibrant market economy, intensive land use, and rapid transportation. Slowly but surely more and more areas are becoming prime
targets for natural disasters. The megacity, in particular, is a ticking time bomb (MunichRe, 2001).
Researchers have studied the effects of natural disasters onproperty values in the affected areas. Some have focused on earthquakes (Palm, 1982; Scawththorn et al., 1982; Brookshire et al.,
1985; Beron et al., 1997; and Yamaga et al., 2002), others haveconcentrated on flooding and floodplain locations (Babcock and
Mitchell, 1980; Burby and French, 1981; Muckleston et al., 1981;
Sheaffer and Greenberg, 1981; Changnon et al., 1983; MacDonald;
Tamai and Ishihara, 1999; Yabe and Murayama, 2000). All thesestudies attempted to determine the effect of a disastrous event onland prices, but the methods used differ and findings on whether adisastrous event affects land prices are sometimes contradictory.
For example, in the case of flooding, most studies have attempted
to detect a discount for a floodplain location (i.e., the net effect of

all attributes that affect property values), rather than focus primary
flood damage. The data available are insufficient to conclude
whether flood damage resulting from floodplain activities isreflected in the fair market value of floodplain property (Chao etal., 1998). Some researchers (Chao et al., 1998; Ichikawa et al.,2002) tried to detect primary flood damage, but failed, perhaps
because other effects, such as differences in land development history, were not completely excluded. After the Tokai flood of 2000,
civil engineers, disaster scientists, and hydrologists conductedmany surveys and studies in an attempt to clarify the characteristics of the flood and the direct damage done (Katada andKuwasawa, 2001; Yamamoto and Iwaya, 2002; Ushiyama and
Takara, 2002), but no one looked into the indirect damage, such as
the falling off of property values.
In any attempt to ascertain the effect of primary flood damage
on land prices in Japan, Korea, or other Asian countries, an important consideration is that the price of a piece of land greatly
exceeds the value of any buildings on it. Land prices and building
values therefore should be evaluated separately, and property values as the sum of them.
We sought to determine the effect of primary flood damage onland prices, rather than building values; in particular, how a lowprobability flood temporally and spatially affects megalopolitan
land prices. For this purpose, we established an analytical framework and applied it to the Tokai Flood of 2000. After briefly
describing that framework, data sources are introduced. The effect

KEY WORDS: land price, primary flood effect, location effect, reverse Z-shaped pattern, Tokai flood of 2000

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G. ZHAI, T. FUKUZONO AND S. IKEDA

of flooding on land prices, as indirect damage caused by the Tokaiflood, is discussed based on results for a statistical method andhedonic-approach-based panel analysis. Lastly, we offer concluding remarks, and mention areas of future research.
2.

FRAMEWORK FOR ANALYZING THE EFFECTS
OF FLOODING ON LAND PRICES

2.1

Changes in land prices in floodplains
Land is nothing but a physical object if not being used. Land
price, the product of a market economy is determined by many factors or attributes: the land s physical characteristics and location,social and economic plans for the land, its developmental history,administrative regulations and laws, and the public s perception of
the land.
Urban areas are regional or national centers of political, economic and social activities, therefore, land prices usually are higher than in rural areas. As urbanization spreads, floodplains become
developed and land prices increase. This floodplain change isFig. 1

Evolution of floodplain development

shown in Fig. 1. Historically, a city normally took root near afloodplain, land use spreading outward; typically in concentric circles of the central business district (CBD), industrial districts, residential areas, suburbs, and rural areas . Land prices (rents) gradually decreased with the distance from the CBD. With industrialization, the need for land increased. To meet this need, cheaply valued nearby floodplains were rapidly developed. Rural areas andnatural floodplains disappeared. River embankments were built to
reduce high-probability flooding and to protect residents to someextent. As a result, more and more people moved to urban areas,
more and more floodplains were developed, and land prices
increased. Historically, therefore, land price based on location was
mainly a phenomenon arising from development intensity and notconsidered an effect of flood risk. Actually, some CBDs of cities,
such as Shanghai, China, are located along rivers and are the highest priced land areas. In other words, a flood does not determine
land prices but land-price fluctuation.
2.2

Analysis framework
The literature on the effects of disastrous events on land prices
shows that research methods used to detect the effect of environmental attribute changes on land prices is classifiable basically into
two methods: cross-sectional analysis, which focuses on land pricechange along the time axis at the same point, and hedonicapproach-based panel analysis, which focuses on land price change
at different points at various times. Because both methods provide
only a partial view of the event s effect on land prices, to see thebroad picture, we used both methods.
When evaluating flooding s effect on land prices by means ofcross-sectional or hedonic-approach-based panel analysis, it should
be made clear that the evaluation is based on the hypothesis thatthe land price change trend, excluding the other factors effects islinear, even though the reality of land price change may not be.
Here, the evaluation is implemented by comparison of the trend;
the diminution trend in land prices due to the current recession in
the Japanese economy.
Fig. 2 outlines the framework for analyzing the effects offlooding on land prices. There are five steps:
1. Identify the purposes and scope of the research.
2. Collect panel data: land prices, land attributes (physicalFig. 2

Framework for analyzing the effects of flooding on land prices.

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPANcharacteristics, locational attributes, social and economic landplanning, land development history, administrative or legal regulations, and environmental quality), inundation situation (inundation
depth, duration, and velocity).
3. Statistically analyze the collected data to see whether theland price and its attributes changed and what the relationship is
between them if they did .
4. Estimate the effect of flooding on land prices by hedonicapproach-based panel analysis.
5. Summarize the results of steps 3 and 4 and show the
implications for land use policies. If the results are not satisfactory,
go back to step 1 and re-examine the data and methods until reasonable results are obtained.
In step 4, more attention should be focused on the decrease inland prices than on land price themselves, because the former ismore sensitive to statistical testing. This can tell us whether a flood
has an impact on land prices. The hedonic approach usually is used
to analyze one year s worth of data; but, to obtain the net effect ofeach land attribute, including the flood, an analysis that stretches
over several years is desirable. This is because the net effect of aflood is the effect of primary flood damage on land prices; i.e., atemporal not locational effect on a given location. We developed ahedonic-approach-based panel analysis that considers land-pricechange trends and exclusion of the location effect. In this hedonicapproach-based panel analysis, all cautionary aspects of the hedonic approach, such as its conditions, and model forms, are applicable.
3.

THE 2000 TOKAI FLOOD AND ANALYSIS DATASET

3.1

The Tokai FloodIn September 2000, heavy rainfall (97 mm hourly precipitation, 567mm total precipitation) inundated the city of Nagoya

Fig. 325(population: 2.1 million) in the Tokai area. This has popularly
been called the Tokai Flood Disaster of 2000 (Fig. 3). Such highdaily precipitation is said to occur only once every 200 years(Kawada, 2002). This flood was one of the severest ever experienced in Japan, causing 10 deaths, 20 serious injuries, and a direct
economic loss of 978.3 billion Japanese yen, according to the statistics of the Ministry of Land, Infrastructure and Transport(MLIT). Spatially, Aichi Prefecture accounted for 90% of the total
direct economic loss and 89% of the loss related to general property, a much higher ratio than usual. According to the MLIT s statistical data , the average ratio of general-property to total direct economic loss from flooding was 29.8% from 1964 to 1999. In termsof the general property, enterprise and household loss roughly
accounted for 50%. As to household loss, building and householdarticles accounted for more than 50% (Zhai & Sato, 2002). Here,
we have focused on the most severely flooded area, which includes
Nishi Ward in Nagoya and Shinkawa-cho and Nishibiwajima-cho.
3.2

Data sources
To determine the effects of the Tokai flood on land prices, wecollected panel data representing land prices, environmental attributes that contribute to land prices, and flooding experiences (mainly inundation depth) before and after the flood (Table 1).
In Japan, there are several types of land prices, which depend
on who is doing the appraisal and how the land is used. The koujichika (appraised land value), published annually by the MILT on
April 1, gives the common land accession standards for the nationand its prefectures. The kijun-chika (average residential and commercial land prices), published annually by each prefecture on July
1, provides another set of common land accession standards for thenation and its prefectures. Both the kouji-chika and kijun-chika
focus on urban-planning areas, the latter publication including
forestlands outside those areas. In addition, there are the other val-

Area studied

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G. ZHAI, T. FUKUZONO AND S. IKEDA

ues: the rosenka (prices of land fronting major roads) published by
the National Tax Administration Agency, the assessed value of
fixed assets of land computed by the Home Affairs Ministry every
three years, and the transaction price of real estate. The transaction
prices of real estate would be ideal for our purposes, but the sample number is small and prices before flooding are not known.
Fortunately, these land pricing systems are highly correlated. For
example, kouji-chika is an average value of transaction prices in a
block (Hidano, 1998). The rosenka, gives approximately 80% of
the assessed values of fixed land assets, approximately 70% that ofkouji-chika values (Nikkei Net, 2000). Based on careful examination of the differences between the real and assessed land prices,
either can be used to detect trends in how the Tokai flood affected
land prices.
Environmental attributes include the land s physical characteristics, infrastructure maintenance status, location, and regulations. Flooding experience mainly is represented by inundation
Table 1Panel dataset for the analysis.

depth: 0 for non-inundation; 1 for 0 to 50 cm inundation; 2 for 50
to 100 cm inundation; 3 for 100 to 150 cm inundation; 4 for 150 to
200 cm inundation; and 5 for more than 200 cm inundation. The
inundation depth can be regarded as an approximate reflection of
the elevation at the point where land is appraised. The relationshipbetween land price and inundation depth therefore partly represents the primary flood damage effect on land price.
Land prices and environmental attributes were obtained fromthe kouji-chika published by the MLIT in 2002. Inundation depth
was estimated by interpolation from the inundation record compiled by the Shinkawa River Administration Association (2001).
We obtained 62 samples for each year in the four-year period
1999 to 2002.
Environmental attributes changed little from 1999 to 2002,
except for the flood of 2000. There is good balance in the sample
numbers for each inundation depth from no inundation to morethan 200 cm. For some land-use types, such as industrial, there is adegree lack diversity in distribution. If industrial land is integrated
with quasi-industrial land as a single type, then the land pricechange for each land use can be determined (Figs. 4 and 5).
4. EFFECTS OF THE 2000 TOKAI FLOOD ON
LAND PRICES
4.1 Cross-sectional analysis of the flood s effect on land prices
4.1.1 General relation between land price and inundation depth
Fig. 6 gives the relationship between land price and inundation depth. There is a similar trend for each year; land pricedecreased with the increase in inundation depth both before andafter the flood. Because historically the lower the elevation of anarea the later land development was in this region, by implication aflood-prone area has low land prices, which can be regarded as lagdifferences in the intensity of development. Fig. 7 indicates thatthe greater the inundation depth, the smaller the variance in land
prices. This is regarded as due to the socio-economic differentiation and agglomeration that follows urban development. Figs. 8
and 9 present the diminutions and their variances in land prices.
The greater the inundation, the less the diminution in land prices,
except for 2001 immediately after the Tokai flood when the situation was the opposite. People may prefer cheap land over land witha relatively low flood risk during the present economic recession.
Figs. 10 and 11 give the attrition rates in land prices and their variances. The years 2000 and 2002 have similar patterns, whereas

Fig. 4

Spatial characteristics of inundation depth.

Fig. 5Inundation depth for various land-use types.

Fig. 6

Land price vs. inundation depth.

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPANFig. 8Fig. 7

Land price variance vs. inundation depth.

Fig. 9Diminution of land price vs. inundation depth.

Variance of diminution in land price vs. inundation depth.

27

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G. ZHAI, T. FUKUZONO AND S. IKEDA

Table 2

Fig. 10

Fig. 11

Attrition rate vs. inundation depth rank.

Attrition rate variance vs. inundation depth rank.

Multiple comparisons with the one-way layout model.

2001 clearly has a decreasing pattern; in 2001, the greater the inundation, the higher the attrition rate. This means that 2001 can be
regarded as the transition period from the pre - to post-flood phase.
A comparison with the average change rates in total land prices in
the Nagoya urban area shows that, in 2000, the rate for the areastudied (-2.9%) is nearly equal to that for the Nagoya urban area(-3.0%), whereas in 2002, the decrease rate (-6.6%) in the areastudied is greater than in Nagoya (-5.3%). The ratio of these areas
decrease rates changed from 0.966 (-2.9%/-3.0%) in 2000 to 1.245(-6.6%/-5.3%) in 2002. This suggests that the Tokai flood 2000
aggravated the drop in land prices in the area studied. The similar
patterns for 2000 and 2002 suggest that the effect of the flood onland prices had diffused from the inundated to non-inundated
areas.
Multiple comparison tests done with a one-way layout model
showed that the diminution and the attrition rate for land prices differed significantly from 2000 to 2002 (Table 2). The significanceprobabilities of diminution in land price were 0.239 for the mean
comparison of 2000 vs. 2001, 0.008 for that of 2001 vs. 2002, and
0.000 for that of 2000 vs. 2002, and those of the attrition rates
were 0.002 for the mean comparison of 2000 vs. 2001, 0.000 for
those of 2001 vs. 2002 and 2000 vs. 2002; indicative that the Tokaiflood of 2000 did aggravate the land price decrease, in terms of theattrition rate and the diminution scale. This was particularly truefor 2002.
In summary, the flood effect on land price based on the inundation depth in the Tokai flood of 2000 has a reverse Z-shaped pattern (Figs. 8 and 10). In other words, the attrition rate and diminution scale had approximately parallel patterns before and after theflood, but there was a transition period in which their relationships
to inundation depth are correlated negatively.
4.1.2 Variability of land use types
The flood did not change the fundamental pattern of land use.
That pattern shows the differences between land-use types, which
decrease with increasing inundation, and the rank orders of themean land prices (Fig. 12).
The annual diminutions in land prices after the flood were-6166 yen/m2, -8947 yen/m2, and -7927 yen/m2 in 2001, and -9100
yen/m2, -17263 yen/m2, and -9000 yen/m2 in 2002 in the order ofresidential, commercial, and industrial land use, the values ofwhich generally are more than those in 2000 (-3400 yen/m 2,-10368 yen/m2, and -3000 yen/m2) (Fig. 13). With respect to inundation depth, all three land-use types show a similar trend.
Diminution in land prices decreased approximately equivalently
before the flood (Fig. 13-a), but immediately following it, thedecrease become linear (Fig. 13-b), after which there was a linear

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPANFig. 1329

Differences in diminution of land prices of land-use types.

increase (Fig. 13-c).
The annual attrition rates of land prices after the flood were
-4.3%, -5.6%, and -4.3% in 2001 and -5.8% -7.5%, and -6.2% in2002 in the order of residential, commercial, and industrial landuse, which again generally are higher than in 2000 (-2.1%, -4.7%,
and -2.1%) (Fig. 14). With respect to inundation depth, the attrition
rates show the same trends as diminution.

Fig. 12Differences in land prices of land use types.

4.1.3 Spatial variability
Land prices differ between areas (Fig. 15). Prices in Nagoya s
Nishi Ward were higher than in the other two areas; in particular,
at slight inundation. The diminution patterns for Shinkawa-cho and30

G. ZHAI, T. FUKUZONO AND S. IKEDA

Fig. 15

Spatial differences in land prices.

analysis-based panel analysis described below allows evaluation ofthat effect.
4.2.1 Hedonic-analysis-based panel analysis
The hedonic approach developed by Rosen (1974) is describedin his classic paper. Provided that the land price depends on theattributes of the land, mathematically this relationship is written
p=f (a 1 , a 1,.....a n )Fig. 14

Difference of attrition rate in land price between land-use types.

Nishi Ward with inundation changed from an increasing trend in2000 to a decreasing one in 2001, then again an increasing one in
2002, whereas Nishibiwajima-cho had a decreasing trend in all
three years (Fig. 16). Although the patterns of the attrition rates in2000 and 2002 were complex, in 2001, except for Shinkawa-cho,they clearly decreased with inundation (Fig. 17).
4.2

Determining the effect of flooding on land prices by hedonic-analysis-based panel analysis
As shown, land prices were affected immediately after theflood, but the effect difference for inundation disappeared in thesecond year. This can be regarded as due to the diffusion effect of
the flood. Temporally, the effect of flooding on land prices was
obtained qualitatively by cross-sectional analysis. The hedonic-(1)

where P is the land price, f (.) an arbitrary function, and ai represents the attributes of the land. Attributes include the physicalaspects and location attributes. The hedonic approach measures thecontribution of each attribute to the land price. Mathematically, thehedonic price is the partial derivative with respect to the attributesuch that(2)
The practical way to empirically calculate a hedonic price isto use a multivariate regression model: a linear or semi-log modelor other forms.
When applying the hedonic approach, it is essential to differentiate the primary effect of flooding from the location effect.
This is difficult because they are interrelated. In a sense, inundation depth reflects both flood severity and the ground elevation of abuilding. Cross-sectional analysis of land prices with inundation
depth for a given year therefore does not provide sufficient infor-

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPANFig. 16

Spatial differences in land price decreases.

mation about the effect of flooding on land prices. We establisheda model by which to detect the primary flood effect by applying
the hedonic approach.
When using land prices as panel data, it is important to keep
in mind that the prices vary due to changes in the economic environment, even though there may be no change in the local environment, e.g. in the infrastructure and regulations. This means that itis necessary to take into consideration the land-price trend whenpanel data are used. Therefore, in addition to the local environmental factors that determine land prices (including inundation depth),
the flood situation and trend in appraisals must be integrated into

Fig. 1731

Spatial difference in the attrition rate of land prices.

the dataset as variables such thatLand price =f (local environment attributes of land price,
trend, flood situation)(3)
Mathematically, the relationship is represented in linear andsemi-log forms;
(4)
(5)

32

G. ZHAI, T. FUKUZONO AND S. IKEDA

Fig. 18

Relationships between land prices and the determining factors.

where xi : represents the characteristics of the local environment, including inundation depth; T is the period of the land-pricechange trend; F a dummy variable for the flood effect; P the land
price; and a, b, c,α,β,γ are parameters.
When applying the hedonic approach, care must be taken
because of the strict limitations of its theoretical and statisticalconditions (Kanemoto et al., 1989). The former conditions consistof regional openness for free migration, consumer homogeneity, asmall project or a small area affected by a project, or no substitutability between production and consumption. This study funda-

mentally meets these requirements. The latter conditions concern
the selection of variables, multi-linearity, choice of functional
form, etc.
4.2.2 Relation between land price and its determining factors
Before using hedonic-analysis-based panel analysis to estimate the flood effect on land price, it is necessary to discuss therelationship between land price and its determining factors to findwhat kind of model should be used. The relationships between land
price, its logarithm, and factors other than inundation depth are

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPANFig. 19

33

Relationships between ln (land price) and the determining factors.

plotted in Figs. 18 and 19.
Both land price and its logarithm are closely related to infrastructure development, road width, distance from the nearest subway station, and the building-area and floor-area ratios. That is,land price increases with increases in infrastructure development
intensity, road width, and the building - and floor-area ratios, anddecreases with increasing distance from a subway station. Thereseems to be no apparent relationship between land price and thesize of the plot of land. This indicates that it is reasonable to use
the linear and semi-log forms of the hedonic approach to determine

the flood effect on land prices.
4.2.3 Evaluating the flood effect on land price
The proposed models were used to evaluate the flood effect.
The coefficients of the flood effect, however, have positive signs,
which contradicts common knowledge that a flood may have anegative effect on land prices. To solve the problem of detecting
the flood effects and of evaluating them, as an alternative to the
proposed model, we used dummy time variables instead of landprice-change trend variables in equations 4 and 5 to run the mod-34

G. ZHAI, T. FUKUZONO AND S. IKEDA

Table 3

Panel analysis results for the linear model.

Table 4

Panel analysis results for the semi-log model.

ratios as well as inundation depth significantly determine bothmodels, whereas land area does not at the significance probability
level of 0.05 (5%).
Much more attention must be paid to the dummy variable,
time. Because it is hypothesized that the change trend in land
prices in a given period basically is constant, it may be possible todetermine the flood effect by evaluating the dummy year variablewhich consists of the change trend and flood effect. In both the linear and semi-log models, the significance probabilities of thedummy variables for time decrease from 1999 to 2002, and fall
into two groups; the 1999-2001 and 2002 groups at the significance level of 5%. This means that the Tokai flood of 2000 significantly affected land prices, which is in accord with the cross-sectional analysis findings in 4.1.
Because the flood effect is defined as how much the price ofland before the flood differed from that after it, excluding the landprice change trend, if the change trend is set as the difference inland prices between 1999 and 2000, the flood effect amounts to-2204.7 yen/m2 in 2001 and -8888.3 yen/m2 in 2002, whereas in thechange rates were -1.27% in 2001 and -4.7% in 2002.
5. CONCLUDING REMARKS

els, then computed how much land prices before the flood differedfrom those after it, which value was the flood effect.
In the alternative models, besides time, regional land use wasset as a dummy variable. Infrastructure development was set as arank variable because development usually proceeds from piping
for tap water, to that for gas, then to a sewage system.
Both the linear and semi-log models well explain the variable
dependence of land prices (Tables 3 and 4). The respective adjusted square correlation coefficients are 0.738 and 0.777 for the linear
and semi-log models. Concerning land price under current socioeconomic conditions, area, infrastructure development, road width,
and the building-area and floor-area ratios make a positive contribution (plus sign) to land prices, whereas distance from a subway
station and inundation depth (elevation) make a negative one(minus sign). Different surroundings have different effects on land
prices. In the current economic recession, land located in areas ofcommercial and industrial use has decreased much more in pricethan land for residential land use.
The significance of each variable in the models, however, differs greatly. Infrastructure development, road width, distance fromthe nearest subway station, and the building-area and floor-area

We first reviewed previous studies of the flood effect on land
prices and introduced a framework for analyzing that effect. Its
effect on land prices was examined by cross-sectional and panel
analyses, the panel data comprising land price and its attributes.
The main findings were:1) Land prices in flood-prone areas are lower and have asmaller variance than in other areas. This is called the location
effect which mainly is due to the lag in the intensity of development.
2) The price of land for commercial use is higher than thatfor residential and industrial use, and the amount and ratio of
diminution also are higher.
3) Spatially, land prices in Nishi Ward of Nagoya City arehigher than in the other two areas examined, but diminution andthe diminution ratio changed markedly.
4) It is very important to differentiate between the effects offlooding and location on land prices when estimating the scale ofthe flood effect. Many previous studies focused on the location
effect; i.e., whether the area of concern was in the floodplain, or on
differences in the floodplain.
5) The determined flood effect had a reverse Z-shaped pattern for the Tokai flood of 2000. It appeared partly in 2001 andcompletely in 2002. This phenomenon may be termed diffusion of
the flood effect from inundated to un-inundated areas. At theadvent of the flood effect, the greater the inundation, the greater
the decrease rate. When the land-price-change trend is set as thedifference in land price between 1999 and 2000, the mean flood
effects amount to -2204.7 yen/m2 in 2001 and -8888.3 yen/m2 in
2002, and the change rates to -1.27% in 2001 and -4.7% in 2002.
6) Residents prefer cheap land to land with a low flood risk.
Unresolved issues requiring future research remain because of
insufficient data, in particular, after a flood. First, it is important tovalidate the diffusion effect of a flood on land prices over a large
area. This should be done by means of a GIS quantitative analysis
model. Second, although the effect of the Tokai flood of 2000

EFFECT OF FLOODING ON MEGALOPOLITAN LAND PRICES: A CASE STUDY OF THE 2000 TOKAI FLOOD IN JAPAN

could be determined, the relationship between flood scale (e.g., a
100-year flood) and the flood effect is still not clear. Third,
although the utility of our model for determining the flood effecthas been proved, we could not use it fully because of the shortageof data. When it becomes possible to obtain more time-series data,
it will be necessary to re-compute the flood effect to clarify theevolution process. Fourth, the effect of flooding on land prices has
been proved, but how long that effect lasts has not been determined due to the shortness of the period after the Tokai flood. That
necessarily must be followed in real time. Finally, the models usedhere are linear and semi-log ones but the actual practical model
may be nonlinear, more complex. Just as with the behavior of landprice-change trend, developing a new type of model to determine
the flood effect on land prices may be urgent.
ACKNOWLEDGMENTS
This research is a part of the Social Systems Resilient toNatural Disasters project implemented by the NIED, Japan. We
thank the sub-editor and the anonymous referees for their valuablecomments and suggestions. The views expressed in this paper are
those of the authors and do not necessarily reflect the views orpolicies of the NIED or the project team. Any errors are the sole
responsibility of the authors.
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