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APPLICATION OF DATA MODELING
In natural resources and forest management
Yujia Zhang and Bruce E. Borders
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INTRODUCTION
A database is a collection of
related data. In forestry, Data
are typically stored in electronic
files with additional information
stored on field tally sheets.
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During data collection, data
formats may be changed, or files
may be revised by users
individually without informing
others, which causes problems in
data storage and analysis.
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The traditional data storage
approach results in redundancy
in data storage. For example,
stand information stored in a
tree level file takes large
storage space and increases
storage cost.
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Relational database management
systems (RDBMS) provide a
powerful tool to store and update
forest data, review relationships
among individual components,
and model forest dynamics.
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Data modeling is a conceptual or
logical design of a database. A data
model is a set of concepts that
refers to types, relations,
constraints, and operations of data.
DATA MODELING
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The basic operations of a data
model include accessing and
updating the database. We use
an entity-relation (ER) data model
for conceptual analysis and
implementation of database.
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The concepts involved in the ER
model are entities, attributes,
and relationships. An entity is
an object, attributes are
descriptions of the properties of
the entity, and relationships are
interactions among entities.
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Data are stored in tables. A row in a
table is called a tuple, a column
header is called an attribute, and a
table is called a relation. The data
illustrated here are from the
Consortium for Accelerated Pine
Plantation Studies (CAPPS).
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The CAPPS plantations were
established in 1987. The applied
silvicultural treatments are
herbicide (H), fertilization (F),
herbicide and fertilization (HF),
and control (C).
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A relation schema R of degree n
can be denoted as:
R (A1, A2, … , An)
where R is the name of the
relation and A1, A2, … , An are
attributes.
RELATION SCHEMA
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The relation schemas in our data model are:
STAND (PlOT_ID, Location, Block, Plot, FirstGrowingSeason,
Treatment);
TREE (ID, PlantationAge, TreeNumber, DBH, Height, CrownHeight, CronartiumQuartileCode, TipMothCode, DamageCode, Plot_ID);
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GROUNDCOVER (ID, SubPlot, PlantationAge,
PercentAndropogon, HeightAndropogon, PercentGrass, HeightGrass, PercentBroadLeaf, HeightBroadLeaf, Plot_ID)
SMALLCOMPETITOR (ID, SubPlot, PlantationAge, Species, TreeHeight, CrownLength, CrownWidth, Plot_ID)
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LARGECOMPETITOR (ID, Subplot, PlantationAge, Species, TreeHeight, DBH, CrownHeight, BaseHeight, Plot_ID));
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A relation is a set of tuples. An attribute with distinct value can be used as a primary key to identify a tuple. The value of the primary key must not be null, which is called the entity integrity constraint.
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A foreign key is needed to maintain the consistency among relations. For example, tree level information and stand level information can be combined together using a foreign key, PLOT_ID.
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The operations for a relational
database include select, project,
and join. The notation for operation
select is:
<selection condition>(<relation name>)
To select trees with DBH larger than
10 cm, we use:
DBH>10(TREE)
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Operation project selects certain
columns from a table:
<attribute list>(<relation name>)
To list tree number, plantation
age, and tree height, we use:
TreeNumber, PlantationAge, Height(TREE)
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Operation join combines two
tuples from two relations
together:
R||<join condition>S
To access all trees from location
Athens, we use:
(TREE)|| LOCATION=ATH (STAND)
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The RDBMS installed on the server is Oracle8 Enterprise. Each user can access the database over a network. Data files used by each user can be stored either in the server or PC, or in other external devices.
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The implementation of a data model includes establishing relations and queries. The following query is used to obtain some stand level information from relations STAND and TREE.
DATA MODEL IMPLEMENTATION
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Assuming a forester wants to
know the number of trees per
plot, average DBH and average
height for each age in stands
located in Athens that have
accepted herbicide and
fertilization, the regarding query
is:
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select s.Location, s.Block, s.Plot, s.FirstGrowingSeason, s.Treatment, t.PlantationAge, count(t.TreeNumber), avg(t.DBH), avg(t.Height) fromSTAND s,TREE twheres.Plot_ID = t.Plot_ID and s.Location = 'ATH'and s.Treatment = 'HF'group by s.Location, s.Block, s.Plot, t.PlantationAge;
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THE OUTPUT PRODUCED IS:==============================================================================
LOC BLK PLT FGS TRT AGE TREE DBH(cm) HT(m)ATH 1 1 89 HF 1 81 0.0 0.7ATH 1 1 89 HF 2 81 0.0 0.2ATH 1 1 89 HF 3 81 5.3 3.9ATH 1 1 89 HF 4 81 8.9 5.2ATH 1 1 89 HF 5 81 10.7 7.0ATH 1 1 89 HF 6 80 13.0 8.3ATH 1 1 89 HF 7 78 14.7 9.8ATH 1 1 89 HF 8 78 15.7 11.5ATH 1 1 89 HF 9 77 17.0 13.0ATH 1 1 89 HF 10 75 18.0 14.3…………………………………………………………………………………………
=============================================================================
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where LOC = Location, BLK = Block, PLT= Plot, FGS = First Growing Season, TRT= Treatment, AGE = Plantation Age,TREE = Tree/plot, DBH = AverageDiameter at Breast Height/plot (cm), andHT = Average Total Tree Height/plot (m).
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Forest data are characterized with large size of records, complicated relationships, and a diversity of data types. The traditional approach is far from satisfactory for data storage and manipulation.
SUMMARY
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In our database, The relations
among data files eliminate
redundancy in data storage. All
files are stored in a server, which
ensures updated data available
for each user.
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For data safety, the redundant hard disks in the server store the mirrored data that can be recovered when the server is down. Also, Oracle8 backup manager can backup the whole database to external storage devices.
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Users can be granted privileges at different levels by the database administrator (DBA) to view, revise, and transfer files. The database is protected from unauthorized access.
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Data modeling helps establish a comprehensive database including tree, soil, hydrology, GIS, and wildlife data, which facilitates natural resources and forest management.