GeoJournal 52: 203–212, 2001.© 2001 Kluwer Academic Publishers. Printed in the Netherlands.

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A GIS-based study toward forecast of suburban forest change

Yasuhiro Suzuki1,∗, Keiji Kimura2 and Tatsuto Aoki31Aichi prefectural University, Aichi, Japan; 2Tokyo Metropolitan University, Tokyo, Japan: 3HokkaidoUniversity, Hokkaido, Japan; ∗Author for correspondence (Tel: +81-561-64-1111 (ext. 3302); Fax: +81-561-64-1108;E-mail: y-suzuki@ist.aichi-pu.ac.jp)

Received 31 March 2001; accepted 5 October 2001

Key words: carbon fixation, environmental assessment, forest growth, GIS, global environment, photogrammetry, remotesensing

Abstract

At a time when the concept of ‘human and environmental symbiosis’ has taken on much significance, protection of suburbanforests (i.e. forests adjacent to or near developed areas) is a topic that has drawn much attention. Suburban forests have, sinceancient times, been places where people have gathered firewood and cultured trees. As a result, the vegetation of suburbanforests is only partially natural and continues to change as the forms of human activity in and around them changes. Accurateforecasts of how suburban forests will change are, therefore, an important element in the debate over how to protect them.In this study, a suburban forest was analyzed with laser radar sensing, multi-spectrum scanning, digital photogrammetryanalysis, aerial photograph interpretation, and a field survey. Data gathered using these techniques were compiled on a GISto forecast future changes in the forest. Aerial photographs taken over the past 50 years were analyzed to illuminate changesin the forest over that period. Specifically, comparisons of precise Digital Elevation Models (DEMs) measured by usingdigital photogrammetry workstations made it possible to estimate growth in forest height. The possible future conversion ofsuch results to estimates of amounts of carbon dioxide consolidated by forests should be very significant for discussions ofglobal environmental problems.

Introduction - What is required in an epoch of humanand environmental symbiosis

In recent years, the concept of environmental symbiosis hasgained wider acceptance, and greater attention has been paidto the changes that human activity has brought about in thenatural environment. One result of this increased concernwas the 1997 passage of a new law requiring environmentalimpact studies. This law does much to correct the shortcom-ings of previous laws, and among its highlights are that it(1) leaves no room for exceptions to the requirement that en-vironmental assessments be performed before developmentbegins, (2) requires that assessment results be directly re-flected in decisions regarding the granting of approvals, and(3) provides for more opportunities for citizen involvementin environmental assessments (Harashina, 1998). Neverthe-less, this law has received strong criticism for requiringno more than qualitative studies in most cases. Qualita-tive studies often use the words ‘impact will be minimal.’With only this to go on, however, verifying the proprietyof forecasts is difficult and comparing forecasts with actualfeedback is problematic. The consequence of this is that itis difficult to improve methods of forecasting environmentaleffects as we go into the future (Matsuda, 1998). New envi-ronmental forecasting methods that have clearly understooddegrees of precision (or imprecision) and that use explicitlogic (hypotheses) are needed.

Under the current state of affairs, the role that a GIS(Geographic Information System) can play is enormous.Environmental data that have been organized using a GIS fa-cilitate both public disclosure and common use. It is obviousthat GIS data simplify the work of understanding the currentstatus of the environment, and people in many quarters havepointed this out. However, it should also be possible to usea GIS as the basis for analyzing not only current data butalso historical data to look at how environmental conditionshave changed over time and at differential change due toparticular environmental elements. This in turn would makeit possible to develop forecasts based on explicit forecastmodels. There is also a strong possibility that environmentalassessments based on detailed GIS data could contribute sig-nificantly to efforts to deal with global environmental issues.Though it may be seen that society’s need for such researchhas grown rapidly in recent years, it would be difficult to saythat it is being pursued with sufficient vigor. Though GISgraphics functions have gained strong attention, it seemsto be the case, and regrettably so, that very little attentionhas been paid to the advanced analysis capabilities that GISoffers.

The 2005 World Exposition is scheduled to take placein Aichi, Japan. The theme of the Exposition is ‘BeyondDevelopments Rediscovering Nature’s Wisdom’. However,symbolizing the depth of the issues at hand, how human

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Figure 1a. A bird’s-eye view of the Kaisho Forest in 1995. Based on a 5 m-mesh DSM (Digital Surface Model), which is a kind of DEM (Digital ElevationModel) reflecting treetop elevations. DSM was created with a digital photogrammetry workstation.

Figure 1b. A bird’s-eye view of the Kaisho Forest in 1949. Based on a 5 m-mesh DSM reflecting treetop elevations. DSM was created with a digitalphotogrammetry workstation.

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Figure 2. Change in forest height between 1949 and 1995, based on the 5 m-mesh DSMs.

activity and nature should coexist has become a problemfor the Exposition itself. This problem is not just one ofprotecting nature – it requires a detailed analysis of the in-teraction of human activity with nature and the developmentof a method for forecasting future changes in a forest.

To respond to this need, the Research Group fora Regional Environmental GIS, an industry-academia-government joint research group headquartered at the De-partment of Information Science and Technology of AichiPrefectural University and organized by the authors in 1998,began to research the suburban forest known as the KaishoForest. This forest is partially overlapped by the plannedExposition site, which is located in Seto City and NagakuteTown, in Aichi Prefecture. One goal of this research is to es-timate the growth of this suburban forest’s biomass, togetherwith the amount of carbon dioxide that could be consolidatedby it. Another is the development of a method for estimatingfuture forest growth. This research has only recently got-ten underway and methodologies are still being worked out,but the authors would like to venture a presentation of theconcepts they are working with and the progress they haveachieved to date. It is their intent that in doing so, they mayalso discuss the effectiveness of, and issues related to the useof, GIS in future research of environmental change forecast.

Conceptual description of suburban forest researchintegrating digital photogrammetry analysis, remotesensing, and a GIS

Suburban forests, which have been significantly affected byhuman activities over the ages, exhibit great complexity interms of the species and ages of trees that comprise them.The application of digital photogrammetry analysis (per-formed with a digital photogrammetry workstation (DPW)),aerial photograph interpretation, multi-spectrum scanning(MSS), laser radar sensing, and other remote sensing tech-niques to a suburban forest; the use of a GIS to manage andintegrate the various types of resulting data; and illuminationof the change experienced by the subject suburban forestmake up the primary elements of this research. In morespecific terms, this research involves the following:

Creation of 5m-mesh DEMs

For subject areas with topographies characterized by a highconcentration of hills and valleys, it is impossible to performprecise topographical and runoff analyses using the tradi-tional 50 m-mesh DEM. These types of analyses require ahigh-resolution 5–10 m-mesh DEM (Oguchi et al., 1999).However, collecting the data necessary for producing DEMsof this resolution requires that the subject land be surveyed.Therefore, except for cases addressing land of very limitedarea, data collection has been practically impossible. An al-ternative approach involves the use of DPWs, developed inrecent years. DPWs use stereo matching to process aerialphotographs and make it possible to automatically survey

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Table 1. The members of the Research Group as of April 1, 2001.

Yasuhiro SUZUKI, Nobuhiko HANDA, Hiroki YOSHIOKA (Aichi prefectural University),

Takashi OGUCHI, Hiroaki SUGIMORI, Yasushi TANAKA, Keiichi KATSUBE,

Shu LIN (University of Tokyo), Keiji KIMURA (Tokyo metropolitan university),

Kazukiyo YAMAMOTO, Chisato TAKENAKA, Sachiko KIYONAGA (Nagoya University),

Yuuichi ONDA, Tsuyoshi WAKATSUKI, Tetsu ITOKAZU (Tsukuba University),

Takashi KUMAMOTO (Okayama University). Daichi NAKAYAMA,

Daisake KAWABATA (Kyoto University), Tatsuto AOKI (Hokkaido University),

Shigeki SANO, Tatsujiro NOZAWA, Naoki KATSUNO, Masayuki YUHARA, Tetsuro NOMURA,

Masahiko HIROSE, Masaru NAKAJIMA (TAMANO Consultants Co.,Ltd.),

Naoaki MURATE, Satoshi MIYASAKA, Kimiaki TOKUMURA, Satoru KATO,

Tomomi TSUBOI (Nakanihon Air Service Co., Ltd),

Nobuyuki TSUTSUI, Yasunari SEKIHARA, Tsuyoshi ITO, Keiji NAGATA, Miha UENO,

Toshiro HASHIMOTO, Hisayuki SUGAUCHI, Yuuichi NOMURA (SOKEN, INC.),

Yuuichi FURUSE, Kiyoshi TAKEJIMA (Falcon Corporation)

the elevation of points in a mesh of designated spacing. Forthe purpose of discussing tree height, two kinds of DEMs –one reflecting the height of treetops and the other, the groundsurface – were produced. The former is referred to specifi-cally as a Digital Surface Model (DSM), while the latter issimply referred to as a DEM. Figures 1a and 1b show bird’s-eye views of a surveyed area based on DSMs created using aDPW. The DSM for Figure 1a is based on aerial photographstaken in 1995, while the DSM for Figure 1b is based onaerial photographs taken in 1949.

Using DSMs and DEMs to survey forest growth

To examine a progression of changes in the forest, DSMsreflecting treetops and DEMs reflecting the ground surfacewere created for three points in time – 1949, 1977, and 1995.Data for these years is maintained in the form of land surveycoordinates in a GIS, so it is possible to examine marginaldifferences between them (Suzuki et al., 2000). In particular,when comparing DSMs, it is now possible to determine theamount of change in forest height. Figure 2 presents resultsof measurements performed with the method described here.Though aerial photographs have been used to evaluate theheight of trees, they have not previously been applied inevaluating the height of forests extending over several squarekilometers.

Creating a detailed vegetation map

To clarify changes in vegetation, aerial photograph interpre-tation was used to produce detailed vegetation classificationmaps for the years, 1949, 1977, and 1995. This work wasperformed by a forestry researcher with many years of prac-tical experience at District Forest Offices. Because thesemaps were intended for use in discussing forest growthcharted using a 5 m mesh, the vegetation boundaries wereoverlaid on positive film and reprocessed using a photogram-metry system to create a set of GIS data. This work wasreported on in detail by Nomura and Nakajima (2000).

Also being examined are vegetation classifications de-veloped by processing MSS images taken from an aircraft.

Table 2. Simplified description of vegeta-tion and land-use categories. (Revised fromNomura and Nakajima, 2000.)

A Fir and Hemlock forest

B Evergreen Broad Leave forest

C Deciduous Broad Leave forest

D Pine tree forest

E Bamboo tree forest

F Afforested Cedar and Cypress

C Bare Ground

H Residential land and Artificial pond

I Cultivate field and Cleared section

Using a 5 m-mesh DSM to perform detailed geometriccorrections, and taking measurements of the same areaover several time periods, the volume of data for analysiswas increased. Research team members aim to use knowl-edge gained from the vegetation classification results of theaerial photograph interpretation referred to above, to im-prove the effectiveness of image-analysis-based vegetationclassification (Miyasaka and Tokumura, 2000).

Forest measurements at the level of individual trees andassessments of carbon dioxide consolidation

The use of changes in forest height to estimate carbondioxide consolidation requires the construction of a growthmodel that addresses individual trees and, therefore, themeasurement of individual trees. Those working in the fieldof forest mensuration continue to accumulate forest mea-surement data and are striving to develop an examinationmethod that is based on a growth model that applies remotesensing data (Yamamoto, 2000). They are also aiming to de-velop a system in which helicopter-based laser radar sensingwould be used to take measurements with a resolution of50 cm. It is their hope that such measurements could then beused to develop estimates of carbon dioxide consolidationover a wide area (Tsuboi and Murate, 2000).

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Figure 3. A 50 cm-mesh DSM of the ‘Kaisho Forest’ created using a helicopter-mounted laser-radar system. Shown is a north-facing view of a 400 m ×400 m section of the Kaisho Forest, known as the Kaisho District.

Forest growth simulation

The ultimate goal of this research project is the simulationof the future growth of a forest based on analyses of changesit has undergone over time. This would involve the accumu-lation in a GIS of topographical data, such as that indicatingslope direction and incline, together with geologic, soil, andother types of data, all of which would be accumulated basedon a 5 m-mesh DEM. These data would then be compared todata on patterns and speed of vegetation change to build anempirical equation. Because the subject is a suburban forest,many issues, such as the effect of human activity over time,will have to be resolved.

Contributions of suburban forest research using GISs toglobal environmental research and geography

The significance of this research, which aims to develop away to forecast suburban forest change by using data fromthe monitoring of the subject suburban forest, is not limitedto the preservation of suburban forests. It has the potentialof making important contributions to the problem of fore-casting global climate change. Because an increase in forestbiomass is intimately related to the amount of carbon diox-ide that is absorbed, there is potential for estimates of forestbiomass to be applied in the assessment of the role of terres-trial life forms in the carbon cycle, of which carbon dioxideresulting from human activities is a part.

There is much debate over how man-made carbon diox-ide, which is said to be 60% responsible for causing thegreenhouse effect, is consolidated in the atmosphere, in theoceans, and in terrestrial plant life. Currently, based on dataprovided by surveys and models, it is estimated that 55%of carbon dioxide is absorbed into the atmosphere and an-other 25–28% is absorbed by the world’s oceans. How muchcarbon dioxide is absorbed by terrestrial plant life, however,remains unclear and is estimated simply by subtracting theabove estimates from the whole. It is for this reason thatdevelopment of a methodology for estimating carbon diox-ide consolidation, one that uses positive measurements offorest growth, is being called for by the IntergovernmentalPanel on Climate Change (IPCC) and other quarters of theinternational community. There is a strong potential for thiskind of study to make a significant contribution to globalenvironmental research (Handa, 2000).

There are multiple and complicated aspects to the terres-trial consolidation of carbon dioxide that make measuringthrough models very difficult. Of interest is the idea of treat-ing ‘forests’ of at least a certain area as a single unit, takingpositive measurements of them, and assembling these mea-surements to develop an overall assessment of the terrestrialconsolidation of carbon dioxide. This would be a clear ap-plication of a concept used in geographic research – one ofidentifying component parts of a whole as units and ana-lyzing these to develop an assessment of the whole. Keyissues to address for a global assessment will include the

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determination of units of forest to measure, as well as waysto achieve high-precision observations, and high efficiencyin wide-area surveys. This is certainly a unique contributionby the field of geography to global environmental research.

In summary, areas that will be the focus of attentionare: (1) precise verification through photographic surveys,(2) modeling of forest growth, (3) determination of mea-surement areas for wide-area assessments, (4) improving theefficiency of forest surveys by laser radar sensing, (5) au-tomation of vegetation classification through the use ofMSS, and (6) the use of IKONOS and other high-resolutionsatellite imagery. Because the topics involved are quitevaried, cooperation among those working in the fields ofgeography, photogrammetry and other types of remote sens-ing, forest mensuration, forest ecology, and other areas willbe essential. And this will require a strengthening of jointresearch cooperation among industry, academia, and gov-ernment (see Table 1 for a list of researchers participating inthe research project described herein).

The authors have only now embarked on a study thatwould lead to this type of simulation, but discuss the resultsof a preliminary study performed by Kimura et al. (2000)and other in the next section.

Results of a preliminary GIS analysis of changes in thevegetation of the Kaisho Forest

As a first step toward creating a forest-growth simulationmethod, the authors clearly describe, in the section that fol-lows, the Kaisho Forest’s representative variation pattern forthe last fifty years. Digital vegetation charts and a digitalelevation model provided the data to begin this analysis.Nomura and Nakajima (2000) classified vegetation and land-use into 16 types shown in the right column of Table 2, asof three points in time – 1949, 1977 and 1995. Starting withthese 16 types of vegetation and land-use, similar species oftrees and types of land-use were grouped together in orderto focus the analysis on variation patterns. This resulted in 9categories, which are shown in the left column of Table 2.

As elevation data, a 1995 5 m-mesh DEM was used, andslope angle and slope distribution were calculated accordingto the method described by Oguchi and Katsube (2000). Inthis area, the slope at first rises in a southeasterly direc-tion about one kilometer horizontally, and then continuesrising about three kilometers horizontally to the east. Fur-thermore, the terrain is characterized by many small ridgesand troughs. These small undulations could not be analyzedwith a 50 m-mesh DEM (Oguchi and Katsube, 1999). Thus,the more detailed DEM of a 5 m-mesh was necessary toprovide data for the analysis.

The first step of the analysis was to convert the poly-gon data for vegetation and land-use into point data fittedto a 5 m-mesh DEM. This made it possible to then assignelevation, slope angle, and slope direction data, as well asvegetation data for 1949, 1977 and 1995, to all 244,514points in the study area.

Next, variation patterns for vegetation and land-use werequantitatively analyzed and the primary variation patterns

Figure 4. Vegetation and land-use category maps of the Kaisho Forest in1949, 1975 and 1995. (Revised from Nomura and Nakajima, 2000).

identified. After that, relationships among the primary vari-ation patterns and topographical elements were considered.

In this analysis, the vegetation and land-use categoriesidentified for 1949 were treated as the original conditionof the study area. Based on the 9 vegetation and land-usecategories and the 3 different years for which data are beinganalyzed (Figure 4), it is theoretically possible that one couldobserve up to 729 (or 93) patterns of variation for the studyarea. The authors, however, noted only 323. To more clearlycharacterize the change that has occurred in the study area,principal patterns of variation were selected according to the

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Figure 5. Major patterns of vegetation change. B to I indicate the cate-gorized vegetation shown in Table 2. The sizes of the ovals represent therelative area of each category. Numbers indicate the percentage of the areain 949 associated with each pattern of change. Note that not all patternsare shown, so for any particular category, figures do not sum to 100. Linethicknesses are proportional to percentage figures.

Figure 6. Relationship between tree height (Th) and the volume of bio-mass (Vt), for cedar and cypress. (Based on data from the Aichi PrefecturalGovernment, 1999.)

following criteria: (1) over the three temporal observationpoints, patterns that reflect a greater-than-10% change inpoints assigned to vegetation and land-use categories sincethe base year of 1949 (paths are shown in Figure 5 and cate-gories with extremely small numbers of points in 1949 wereexcluded) and (2) patterns with measured change exceeding100 aggregate points over the three time periods.

Based on these criteria, 13 principal patterns of varia-tion were identified. One additional pattern, the category H(residential areas and ponds) was added, to bring the totalto 14. These 14 patterns covered 116,157 points. In otherwords, they can explain variation for 47.5% of the studyarea. Figure 4 presents models of the principal variation pat-terns. What is shown here indicates that almost all of thepoints not affected by man-made changes had returned tocategory C (deciduous forest) by 1995. Otherwise, Figure 4also shows that old residential areas and areas of culturedforest saw almost no change in terms of land-use.

In regard to the patterns of vegetation variation in thesuburban forest, these 3 trends were identified:

Figure 7. Relationship between tree heights (Th) and numbers of trees (Nt)per unit area in the northern part of Aichi Prefecture and southern partof Gifu Prefecture. (Based on data from the Forestry Agency’s NAGOYARegional Forest Office, 1959, 1960.)

The change from category F (afforested trees) to category C(deciduous forest)

Since before 1949 and until 1977, cedar and cypress werecultured in parts of the study area. After 1977, however,some of these places reverted to deciduous forest. Of thoseparts of the study area classified as category F in 1949, 25%either continued as category F or shifted to category C by1977. By 1995, all of these places had shifted to categoryC. This change was seen to have some relationship to ele-vation. Most of the points in the study area that remainedin category F through all periods were distributed aroundelevations of 200–220 m and 260–340 m. Points that shiftedfrom category F in 1977 to category C by 1995 were distrib-uted around elevations of 220–260 m and 340–360 m. Andpoints that had shifted to category C by 1977 and remainedin category C as of 1995 were distributed around the lowerelevation of 140–200 m.

The change from category B (climax evergreen forest)

The climax forest for the study area is thought to be ever-green – category B for purposes of this study. Most of thepoints classified as category B in 1949 had changed to cate-gory C (deciduous forest) by either 1977 or 1995. However,other points that had been in category B in 1949 shifted tocategories other than C by 1995. An examination of slopedirection for both patterns of variation shows that the formertended to occur in locations with a west-facing slope ex-tending from northwest to southwest, while the latter tendedto occur in places with an east-facing slope extending fromnortheast to south.

The change from category D (pine trees)

The authors observed that many points in category D asof 1949 gradually shifted to category C (deciduous forest).Points that remained in category D through all 3 observationperiods were distributed around the elevation of 150–200 m,while the points that shifted from category D in 1949 to cat-egory C in 1977 or 1995 were distributed around the lowerelevation of 100–150 m.

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Figure 8. Histogram of the carbon fixation in each point in a 5 m-mesh in the artificial cedar-cypress forest.

A preliminary attempt to estimate carbon fixation in aforest

As mentioned above, two kinds of digital models are usedin this research. One, a digital surface model, referred to asa DSM, is used to show elevation at the level of treetops.The other, a DEM, is used to show elevation at the groundsurface. The difference between DSM and DEM data in thesame year can be treated as tree height. Similarly, the differ-ence between DSMs in two different years can be considereda measure of growth in tree height (Suzuki et al., 2000).Moreover, comparisons of detailed vegetation charts yieldedlongitudinal vegetation changes (Kimura et al., 2000). Af-ter integrating these data on a GIS, the growth in height ofvegetation in the study area, over particular periods, can beestimated. After that, the relationships between tree heightand the volume of biomass, which is known in bio-ecologicand forestry terms, make it possible to calculate changes inthe amount of forest biomass as of particular points in time.

Using a DEM and DSM prepared using aerial pho-tographs from 1949 and 1995, together with vegetationmaps, the authors estimated the variation in the amount offorest biomass and carbon fixation within the artificial forest(cedar and cypress forest), about which much forestry datahas been accumulated. The data used for this analysis wasDSM, DEM, and vegetation data for the center point of eachsection in a 5 m mesh. As a result, each point represented25 m2 of area. The portion of the study area that was artifi-cial forest (cedar and cypress forest designated as categoryF in the previous paragraph) in both 1949 and 1995 covered8,494 points, or 21.2 ha.

The relationship of the biomass of each tree (Bt) withthe amount of carbon fixation (Ct) is shown in equation (1)(FFPRI, 2001).

Ct = 0.5 Bt (1)

Furthermore, Bt, as the dried weight of a tree, is estimatedby using equation (2),

Bt = Dt × (Vt + Vr) (2)

where Dt represents wood density; Vt, trunk volume; andVr, root volume. It has been shown that Dt equals 0.45(National Astronomical Observatory, 2000) and that Vr =Vt/3.3 (Karizumi, 1949). With the number of trees per unitarea represented by Nt, total carbon fixation per unit area(TC) and total biomass (TB) are calculated as shown inequations (3) and (4).

TB = Bt × Nt (3)

TC = Ct × Nt (4)

The equations above show that two variables, Vt and Nt, areneeded to calculate TB and TC. Using forestry data (NagoyaForest Management Office 1959, 1960; Aichi PrefecturalGovernment, 1999) on an area near the study area, the au-thors sought to determine a relational expression linking Vt,Nt, and tree height (Th) (Figures 6 and 7). Their results in-cluded the following equations for Vt and Nt, which showthat both may be expressed as functions of Th only, and withhigh correlations with Th.

Vt = 2.812 × 10−5Th3.186 (R2 = 0.7555) (5)

Nt = 90.242 Th−1.296 (R2 = 0.944) (6)

The authors confirmed all the above variables were shown asTh in the previous equations.

The authors then followed this up by calculating theamount of biomass and carbon fixation (Table 3). They didthis by using tree heights, for the cedar and cypress forest,

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Table 3. Estimated amount of biomass and carbon fixation.

Biomass Carbon

Total (kg) (kg/m2) (t/ha) Total (kg) (kg/m2) (t/ha)

1949 174606.24 0.82 8.22 87303.12 0.41 4.11

1995 449432.38 2.12 21.16 224716.19 1.06 10.58

that were calculated based on DSMs and DEMs for both1949 and 1995. The average speed of carbon fixation perpoint was calculated as 38.5 mg C/m2 day, as shown inFigure 8.

To summarize this section, using DSMs and DEMs cre-ated based on aerial photogrammetry, and using only treeheight as a variable, historical amounts of biomass and car-bon fixation in a forest can be estimated. Furthermore, thismeans that future amounts of biomass and carbon fixationcan be estimated if future tree height can be estimated. Infuture studies, the authors will use measurements of thepresent forest to calibrate forest measurements. They willalso work to minimize DSM and DEM measurement errors,and improve estimation accuracy through the use of a laserradar system to measure Nt.

Effectiveness of, and future issues for, the use of a GIS inforecasting environmental change

The example of suburban forest research discussed here be-gins with the gathering of data on kinds of trees (speciesand ages), their locations (expressed in coordinates in a5 m mesh), and how much these trees have grown overthe past 50 years (in terms of height). The research groupthen intends to use environmental factors such as topogra-phy, geologic characteristics, and soil conditions; humanfactors (history of human manipulation of the forest); anddevelopment models based on forest ecology to developexplanations of changes that have occurred The pursuit ofthis research requires that models of the relationships ofthe various factors, each with its own position coordinates,be developed. Clearly, the analysis involved would be verydifficult without a GIS.

If it is possible to develop models that explain how theforest reached its current state, it should also be possible tosimulate how the forest will develop in the future. Also, be-cause it is possible to set various simulation conditions, suchas those for tree harvesting, tree planting, and topographi-cal modifications, it should be possible to simulate changesbrought about by development. This type of forecast is basedon the geographic logic of focusing on the time and spacedistribution of a phenomenon and extracting a law or lawsthat define the phenomenon observed. It is one accepted wayto develop forecasts. The logic is clear to understand andas forecasts developed on a GIS, and therefore with a highdegree of transparency (the degree of precision can be seen),they should also prove useful for society. Furthermore, asobservations are made in the future, the models and their

precision can be tested, and improvements may also be madethrough a GIS.

As mentioned earlier, this type of research can be real-ized through the interdisciplinary cooperation of researchersin science, agriculture, and engineering, as well as special-ists in fields such as remote sensing, environmental studies,and photogrammetry. Joint industry-academia-governmentresearch incorporating technologies from a wide array offields is critical for success. The utility of a GIS in assem-bling diverse types of knowledge and technology cannot beunderestimated.

The work of preserving suburban forests bears the oblig-ation of providing objective data for the social debate sur-rounding how man should coexist with nature. For thispurpose, the operation of a GIS system that is accessible overthe Internet is indispensable.

GISs are expected to make enormous contributions inenvironmental research and in environmental forecasting re-search. Nevertheless, as alluded to at the beginning of thispaper, results have, as of yet, failed to match expectations.One explanation for this is thought to be a data precisionproblem as described below.

Environmental data are often provided in the form ofmap information and, in many cases, no explanations areprovided regarding data precision and/or the meaning ofboundaries. As a result, if work ranging from data ac-quisition to data analysis is not performed under a jointresearch organization, researchers may very well arrive atmistaken conclusions. There is a strong possibility for thisissue to be a significant stumbling block for GIS-basedenvironmental forecasting research. It will not always bepossible to organize joint research projects, so creating andmaintaining a robust environmental database that includesdetailed information on data precision is an issue that mustbe addressed.

Similar considerations were a key concern in the prepa-ration of GIS data on active faults, which generate earth-quakes. This information is fundamental to disaster fore-casting and its assembly is being pursued as a matter of thehighest priority (Kumamoto et al., 2000). For interdiscipli-nary cooperation, a key concept for 21st century science,such detailed preparation and distribution of data is crucial.And GIS preparation will likely play an essential role in thatwork.

Acknowledgements

The authors would like to express special thanks to Pro-fessor Dr Nobuhiko Hand at the department of information

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science and technology, Aichi prefectural university for hisorientation of the whole study from the view point of globalenvironmental researches at the beginning. They should alsothank to all the members of the Research Group for Re-gional Environmental GIS for intensive cooperative workswith the authors and to Mr Lee Katsuji Taniguchi for his sug-gestions to improve our manuscript. This study have beensupported by a scientific research grant of Ministry of Ed-ucation, Culture, Sports, Science and Technology of Japansince 1999 and by a grant to promote telecommunication andinformation industries of Aichi Prefecture since 1998.

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