Overview

Dataset statistics

Number of variables11
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory91.1 B

Variable types

Text3
Categorical7
Numeric1

Dataset

Description경상남도 거제시 무인도서현황 관리번호, 도서명, 소재지, 지목, 면적, 관리유형, 소유자 등의 항목을 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079270

Alerts

소재지 has constant value ""Constant
기준일 has constant value ""Constant
면적(㎡) is highly overall correlated with 지목 and 1 other fieldsHigh correlation
면동 is highly overall correlated with 리High correlation
리 is highly overall correlated with 면동High correlation
지목 is highly overall correlated with 면적(㎡) High correlation
소유자 is highly overall correlated with 면적(㎡) High correlation
지목 is highly imbalanced (54.6%)Imbalance
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:12:10.469478
Analysis finished2023-12-10 23:12:11.495581
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T08:12:11.672010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters693
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row경남-거제-12-01
2nd row경남-거제-12-02
3rd row경남-거제-12-03
4th row경남-거제-12-04
5th row경남-거제-12-05
ValueCountFrequency (%)
경남-거제-12-01 1
 
1.6%
경남-거제-12-33 1
 
1.6%
경남-거제-12-35 1
 
1.6%
경남-거제-12-36 1
 
1.6%
경남-거제-12-37 1
 
1.6%
경남-거제-12-38 1
 
1.6%
경남-거제-12-39 1
 
1.6%
경남-거제-12-40 1
 
1.6%
경남-거제-12-41 1
 
1.6%
경남-거제-12-42 1
 
1.6%
Other values (53) 53
84.1%
2023-12-11T08:12:12.030358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 189
27.3%
1 80
11.5%
2 80
11.5%
경 63
 
9.1%
남 63
 
9.1%
거 63
 
9.1%
제 63
 
9.1%
3 17
 
2.5%
4 16
 
2.3%
5 16
 
2.3%
Other values (5) 43
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
36.4%
Other Letter 252
36.4%
Dash Punctuation 189
27.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 80
31.7%
2 80
31.7%
3 17
 
6.7%
4 16
 
6.3%
5 16
 
6.3%
0 15
 
6.0%
6 10
 
4.0%
7 6
 
2.4%
8 6
 
2.4%
9 6
 
2.4%
Other Letter
ValueCountFrequency (%)
경 63
25.0%
남 63
25.0%
거 63
25.0%
제 63
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
63.6%
Hangul 252
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 189
42.9%
1 80
18.1%
2 80
18.1%
3 17
 
3.9%
4 16
 
3.6%
5 16
 
3.6%
0 15
 
3.4%
6 10
 
2.3%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 63
25.0%
남 63
25.0%
거 63
25.0%
제 63
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
63.6%
Hangul 252
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 189
42.9%
1 80
18.1%
2 80
18.1%
3 17
 
3.9%
4 16
 
3.6%
5 16
 
3.6%
0 15
 
3.4%
6 10
 
2.3%
7 6
 
1.4%
8 6
 
1.4%
Hangul
ValueCountFrequency (%)
경 63
25.0%
남 63
25.0%
거 63
25.0%
제 63
25.0%

도서명
Text

Distinct61
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T08:12:12.252591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.1904762
Min length2

Characters and Unicode

Total characters327
Distinct characters79
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)93.7%

Sample

1st row북여도(1)
2nd row북여도(2)
3rd row남여도(1)
4th row남여도(2)
5th row소다포도
ValueCountFrequency (%)
뱀쥐섬 2
 
3.2%
황도 2
 
3.2%
망와도 1
 
1.6%
유대도(3 1
 
1.6%
소범북도 1
 
1.6%
소고개도(동섬 1
 
1.6%
북여도(1 1
 
1.6%
고개등대도 1
 
1.6%
송도 1
 
1.6%
복도 1
 
1.6%
Other values (51) 51
81.0%
2023-12-11T08:12:12.670692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 61
18.7%
( 39
 
11.9%
) 39
 
11.9%
대 19
 
5.8%
섬 11
 
3.4%
소 10
 
3.1%
손 8
 
2.4%
병 8
 
2.4%
2 7
 
2.1%
여 7
 
2.1%
Other values (69) 118
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 230
70.3%
Open Punctuation 39
 
11.9%
Close Punctuation 39
 
11.9%
Decimal Number 19
 
5.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 61
26.5%
대 19
 
8.3%
섬 11
 
4.8%
소 10
 
4.3%
손 8
 
3.5%
병 8
 
3.5%
여 7
 
3.0%
동 6
 
2.6%
북 4
 
1.7%
사 4
 
1.7%
Other values (62) 92
40.0%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 7
36.8%
3 3
15.8%
5 1
 
5.3%
4 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 230
70.3%
Common 97
29.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 61
26.5%
대 19
 
8.3%
섬 11
 
4.8%
소 10
 
4.3%
손 8
 
3.5%
병 8
 
3.5%
여 7
 
3.0%
동 6
 
2.6%
북 4
 
1.7%
사 4
 
1.7%
Other values (62) 92
40.0%
Common
ValueCountFrequency (%)
( 39
40.2%
) 39
40.2%
2 7
 
7.2%
1 7
 
7.2%
3 3
 
3.1%
5 1
 
1.0%
4 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 230
70.3%
ASCII 97
29.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 61
26.5%
대 19
 
8.3%
섬 11
 
4.8%
소 10
 
4.3%
손 8
 
3.5%
병 8
 
3.5%
여 7
 
3.0%
동 6
 
2.6%
북 4
 
1.7%
사 4
 
1.7%
Other values (62) 92
40.0%
ASCII
ValueCountFrequency (%)
( 39
40.2%
) 39
40.2%
2 7
 
7.2%
1 7
 
7.2%
3 3
 
3.1%
5 1
 
1.0%
4 1
 
1.0%

소재지
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
경상남도 거제시
63 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 거제시
2nd row경상남도 거제시
3rd row경상남도 거제시
4th row경상남도 거제시
5th row경상남도 거제시

Common Values

ValueCountFrequency (%)
경상남도 거제시 63
100.0%

Length

2023-12-11T08:12:12.783008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:12.859819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 63
50.0%
거제시 63
50.0%

면동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
남부면
18 
장목면
14 
사등면
9 
둔덕면
6 
하청면
6 
Other values (5)
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row남부면
2nd row남부면
3rd row남부면
4th row남부면
5th row남부면

Common Values

ValueCountFrequency (%)
남부면 18
28.6%
장목면 14
22.2%
사등면 9
14.3%
둔덕면 6
 
9.5%
하청면 6
 
9.5%
거제면 3
 
4.8%
옥포동 2
 
3.2%
일운면 2
 
3.2%
동부면 2
 
3.2%
장평동 1
 
1.6%

Length

2023-12-11T08:12:12.935758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:13.028346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부면 18
28.6%
장목면 14
22.2%
사등면 9
14.3%
둔덕면 6
 
9.5%
하청면 6
 
9.5%
거제면 3
 
4.8%
옥포동 2
 
3.2%
일운면 2
 
3.2%
동부면 2
 
3.2%
장평동 1
 
1.6%

리
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size636.0 B
다포리
10 
창호리
6 
갈곶리
6 
연구리
4 
시방리
4 
Other values (20)
33 

Length

Max length4
Median length3
Mean length3.0634921
Min length3

Unique

Unique11 ?
Unique (%)17.5%

Sample

1st row갈곶리
2nd row갈곶리
3rd row갈곶리
4th row갈곶리
5th row다포리

Common Values

ValueCountFrequency (%)
다포리 10
15.9%
창호리 6
 
9.5%
갈곶리 6
 
9.5%
연구리 4
 
6.3%
시방리 4
 
6.3%
유호리 4
 
6.3%
학산리 3
 
4.8%
<NA> 3
 
4.8%
장목리 2
 
3.2%
탑포리 2
 
3.2%
Other values (15) 19
30.2%

Length

2023-12-11T08:12:13.136097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다포리 10
15.9%
갈곶리 6
 
9.5%
창호리 6
 
9.5%
연구리 4
 
6.3%
시방리 4
 
6.3%
유호리 4
 
6.3%
학산리 3
 
4.8%
na 3
 
4.8%
법동리 2
 
3.2%
오량리 2
 
3.2%
Other values (15) 19
30.2%

지번
Text

Distinct60
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T08:12:13.327987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.8730159
Min length2

Characters and Unicode

Total characters244
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)90.5%

Sample

1st row431
2nd row432
3rd row433
4th row434
5th row산23
ValueCountFrequency (%)
산23 2
 
3.1%
산91 2
 
3.1%
산97 2
 
3.1%
산4 1
 
1.6%
산158 1
 
1.6%
산132 1
 
1.6%
산131 1
 
1.6%
431 1
 
1.6%
산155-1외 1
 
1.6%
산75 1
 
1.6%
Other values (51) 51
79.7%
2023-12-11T08:12:13.636360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 58
23.8%
1 43
17.6%
3 22
 
9.0%
4 21
 
8.6%
2 19
 
7.8%
외 14
 
5.7%
9 12
 
4.9%
5 11
 
4.5%
8 11
 
4.5%
- 11
 
4.5%
Other values (4) 22
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
65.6%
Other Letter 72
29.5%
Dash Punctuation 11
 
4.5%
Space Separator 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43
26.9%
3 22
13.8%
4 21
13.1%
2 19
11.9%
9 12
 
7.5%
5 11
 
6.9%
8 11
 
6.9%
7 10
 
6.2%
6 7
 
4.4%
0 4
 
2.5%
Other Letter
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
70.5%
Hangul 72
29.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 43
25.0%
3 22
12.8%
4 21
12.2%
2 19
11.0%
9 12
 
7.0%
5 11
 
6.4%
8 11
 
6.4%
- 11
 
6.4%
7 10
 
5.8%
6 7
 
4.1%
Other values (2) 5
 
2.9%
Hangul
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
70.5%
Hangul 72
29.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 58
80.6%
외 14
 
19.4%
ASCII
ValueCountFrequency (%)
1 43
25.0%
3 22
12.8%
4 21
12.2%
2 19
11.0%
9 12
 
7.0%
5 11
 
6.4%
8 11
 
6.4%
- 11
 
6.4%
7 10
 
5.8%
6 7
 
4.1%
Other values (2) 5
 
2.9%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
임야
57 
전/임야
6 

Length

Max length4
Median length2
Mean length2.1904762
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임야
2nd row임야
3rd row임야
4th row임야
5th row임야

Common Values

ValueCountFrequency (%)
임야 57
90.5%
전/임야 6
 
9.5%

Length

2023-12-11T08:12:13.752115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:13.834383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임야 57
90.5%
전/임야 6
 
9.5%

면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21655.127
Minimum79
Maximum434181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T08:12:13.919463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79
5-th percentile238.7
Q11770
median6029
Q314454.5
95-th percentile80879.5
Maximum434181
Range434102
Interquartile range (IQR)12684.5

Descriptive statistics

Standard deviation58322.889
Coefficient of variation (CV)2.6932601
Kurtosis41.584211
Mean21655.127
Median Absolute Deviation (MAD)5178
Skewness6.0381316
Sum1364273
Variance3.4015594 × 109
MonotonicityNot monotonic
2023-12-11T08:12:14.021276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8331 2
 
3.2%
723 1
 
1.6%
4264 1
 
1.6%
121488 1
 
1.6%
2083 1
 
1.6%
5256 1
 
1.6%
9818 1
 
1.6%
81090 1
 
1.6%
8232 1
 
1.6%
38416 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
79 1
1.6%
205 1
1.6%
218 1
1.6%
229 1
1.6%
326 1
1.6%
392 1
1.6%
402 1
1.6%
437 1
1.6%
457 1
1.6%
595 1
1.6%
ValueCountFrequency (%)
434181 1
1.6%
121488 1
1.6%
101449 1
1.6%
81090 1
1.6%
78985 1
1.6%
54255 1
1.6%
49099 1
1.6%
47363 1
1.6%
38416 1
1.6%
35802 1
1.6%

관리유형
Categorical

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
이용가능
29 
준보전
14 
개발가능
8 
<NA>
6 
절대보전
5 

Length

Max length4
Median length4
Mean length3.7619048
Min length3

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row이용가능
2nd row이용가능
3rd row이용가능
4th row이용가능
5th row준보전

Common Values

ValueCountFrequency (%)
이용가능 29
46.0%
준보전 14
22.2%
개발가능 8
 
12.7%
<NA> 6
 
9.5%
절대보전 5
 
7.9%
분보전 1
 
1.6%

Length

2023-12-11T08:12:14.135526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:14.230541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용가능 29
46.0%
준보전 14
22.2%
개발가능 8
 
12.7%
na 6
 
9.5%
절대보전 5
 
7.9%
분보전 1
 
1.6%

소유자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size636.0 B
사유지
32 
국(재정경제부)
13 
국(산림청)
10 
국(재무부)
4 
국(국토해양부)
 
2
Other values (2)
 
2

Length

Max length10
Median length3
Mean length5.015873
Min length3

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row국(재정경제부)
2nd row국(재정경제부)
3rd row국(재정경제부)
4th row국(재정경제부)
5th row국(산림청)

Common Values

ValueCountFrequency (%)
사유지 32
50.8%
국(재정경제부) 13
20.6%
국(산림청) 10
 
15.9%
국(재무부) 4
 
6.3%
국(국토해양부) 2
 
3.2%
국(국방부) 1
 
1.6%
국(국방부)경상남도 1
 
1.6%

Length

2023-12-11T08:12:14.335224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:14.439768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유지 32
50.8%
국(재정경제부 13
20.6%
국(산림청 10
 
15.9%
국(재무부 4
 
6.3%
국(국토해양부 2
 
3.2%
국(국방부 1
 
1.6%
국(국방부)경상남도 1
 
1.6%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
2017-11-22
63 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-11-22
2nd row2017-11-22
3rd row2017-11-22
4th row2017-11-22
5th row2017-11-22

Common Values

ValueCountFrequency (%)
2017-11-22 63
100.0%

Length

2023-12-11T08:12:14.569421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:12:14.641948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-11-22 63
100.0%

Interactions

2023-12-11T08:12:10.940659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:12:14.690246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도서명면동리지번지목면적(㎡)관리유형소유자
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
도서명1.0001.0000.9830.9600.9801.0001.0001.0000.987
면동1.0000.9831.0001.0000.9360.4660.0000.6190.721
리1.0000.9601.0001.0000.0000.7500.5240.8490.519
지번1.0000.9800.9360.0001.0001.0001.0000.8070.827
지목1.0001.0000.4660.7501.0001.0000.7540.0000.081
면적(㎡)1.0001.0000.0000.5241.0000.7541.0000.2480.681
관리유형1.0001.0000.6190.8490.8070.0000.2481.0000.504
소유자1.0000.9870.7210.5190.8270.0810.6810.5041.000
2023-12-11T08:12:14.778558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유자지목리면동관리유형
소유자1.0000.0730.1740.4590.344
지목0.0731.0000.4780.3310.000
리0.1740.4781.0000.8320.474
면동0.4590.3310.8321.0000.284
관리유형0.3440.0000.4740.2841.000
2023-12-11T08:12:14.852987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(㎡)면동리지목관리유형소유자
면적(㎡)1.0000.0000.2040.5370.2000.530
면동0.0001.0000.8320.3310.2840.459
리0.2040.8321.0000.4780.4740.174
지목0.5370.3310.4781.0000.0000.073
관리유형0.2000.2840.4740.0001.0000.344
소유자0.5300.4590.1740.0730.3441.000

Missing values

2023-12-11T08:12:11.039194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:12:11.445891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

관리번호도서명소재지면동리지번지목면적(㎡)관리유형소유자기준일
0경남-거제-12-01북여도(1)경상남도 거제시남부면갈곶리431임야723이용가능국(재정경제부)2017-11-22
1경남-거제-12-02북여도(2)경상남도 거제시남부면갈곶리432임야437이용가능국(재정경제부)2017-11-22
2경남-거제-12-03남여도(1)경상남도 거제시남부면갈곶리433임야392이용가능국(재정경제부)2017-11-22
3경남-거제-12-04남여도(2)경상남도 거제시남부면갈곶리434임야326이용가능국(재정경제부)2017-11-22
4경남-거제-12-05소다포도경상남도 거제시남부면다포리산23임야1587준보전국(산림청)2017-11-22
5경남-거제-12-06대손(병)대도(1)경상남도 거제시남부면다포리산42임야54255절대보전국(산림청)2017-11-22
6경남-거제-12-07대손(병)대도(2)경상남도 거제시남부면다포리산43임야49099절대보전국(산림청)2017-11-22
7경남-거제-12-08소손(병)대도(1)경상남도 거제시남부면다포리산44임야2217준보전국(산림청)2017-11-22
8경남-거제-12-09소손(병)대도(2)경상남도 거제시남부면다포리산45임야17233절대보전국(산림청)2017-11-22
9경남-거제-12-10대손(병)대도(4)경상남도 거제시남부면다포리산50임야5475절대보전국(재정경제부)2017-11-22
관리번호도서명소재지면동리지번지목면적(㎡)관리유형소유자기준일
53경남-거제-12-54려봉도(수야봉도)경상남도 거제시하청면대곡리산33-1외전/임야101449이용가능사유지2017-11-22
54경남-거제-12-55동굴도경상남도 거제시하청면연구리산76임야2281이용가능사유지2017-11-22
55경남-거제-12-56씨릉도(섬)경상남도 거제시하청면연구리28-1외전/임야78985개발가능사유지2017-11-22
56경남-거제-12-57소광이도경상남도 거제시하청면연구리산157임야9025이용가능사유지2017-11-22
57경남-거제-12-58대광이도경상남도 거제시하청면연구리산158임야17058이용가능사유지2017-11-22
58경남-거제-12-59광지말도경상남도 거제시장목면구영리산91임야35802이용가능사유지2017-11-22
59경남-거제-12-60망와도경상남도 거제시장목면유호리산4임야15074준보전사유지2017-11-22
60경남-거제-12-61대범북도경상남도 거제시장목면장목리산131임야9521이용가능사유지2017-11-22
61경남-거제-12-62소범북도경상남도 거제시장목면장목리산132임야3868이용가능사유지2017-11-22
62경남-거제-12-63귤도경상남도 거제시장평동<NA>산130임야2975이용가능사유지2017-11-22