Overview

Dataset statistics

Number of variables10
Number of observations272
Missing cells9
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.9 KiB
Average record size in memory82.5 B

Variable types

Categorical5
Text3
Numeric2

Dataset

Description경상북도 김천시 산사태취약지역 정보입니다.(272개소- 주소, 위도,경도, 소유별, 산사태취약지역 지정사유,데이터기준일)
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15123761/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
소유별 has constant value ""Constant
데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
리 has 9 (3.3%) missing valuesMissing
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:34:16.262560
Analysis finished2023-12-12 05:34:17.592945
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
경상북도
272 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 272
100.0%

Length

2023-12-12T14:34:17.686028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:34:17.828629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 272
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
김천시
272 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김천시 272
100.0%

Length

2023-12-12T14:34:17.967507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:34:18.090771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김천시 272
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
대덕면
31 
조마면
30 
구성면
29 
증산면
29 
대항면
20 
Other values (16)
133 

Length

Max length3
Median length3
Mean length2.9411765
Min length2

Unique

Unique4 ?
Unique (%)1.5%

Sample

1st row감문면
2nd row감문면
3rd row개령면
4th row구성면
5th row대덕면

Common Values

ValueCountFrequency (%)
대덕면 31
11.4%
조마면 30
11.0%
구성면 29
10.7%
증산면 29
10.7%
대항면 20
7.4%
봉산면 20
7.4%
부항면 17
 
6.2%
지례면 16
 
5.9%
어모면 16
 
5.9%
남면 15
 
5.5%
Other values (11) 49
18.0%

Length

2023-12-12T14:34:18.217088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대덕면 31
11.4%
조마면 30
11.0%
구성면 29
10.7%
증산면 29
10.7%
대항면 20
7.4%
봉산면 20
7.4%
부항면 17
 
6.2%
지례면 16
 
5.9%
어모면 16
 
5.9%
감문면 15
 
5.5%
Other values (11) 49
18.0%

리
Text

MISSING 

Distinct97
Distinct (%)36.9%
Missing9
Missing (%)3.3%
Memory size2.3 KiB
2023-12-12T14:34:18.591083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9695817
Min length2

Characters and Unicode

Total characters781
Distinct characters95
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)14.8%

Sample

1st row송북리
2nd row덕남리
3rd row광천리
4th row금평리
5th row조룡리
ValueCountFrequency (%)
운수리 9
 
3.4%
평촌리 8
 
3.0%
대방리 8
 
3.0%
인의리 8
 
3.0%
신평리 6
 
2.3%
대리 6
 
2.3%
신곡리 6
 
2.3%
상금리 6
 
2.3%
마산리 5
 
1.9%
오봉리 5
 
1.9%
Other values (87) 196
74.5%
2023-12-12T14:34:19.101795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 263
33.7%
곡 30
 
3.8%
평 26
 
3.3%
대 23
 
2.9%
신 21
 
2.7%
금 17
 
2.2%
천 17
 
2.2%
산 15
 
1.9%
수 12
 
1.5%
덕 11
 
1.4%
Other values (85) 346
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 263
33.7%
곡 30
 
3.8%
평 26
 
3.3%
대 23
 
2.9%
신 21
 
2.7%
금 17
 
2.2%
천 17
 
2.2%
산 15
 
1.9%
수 12
 
1.5%
덕 11
 
1.4%
Other values (85) 346
44.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 781
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 263
33.7%
곡 30
 
3.8%
평 26
 
3.3%
대 23
 
2.9%
신 21
 
2.7%
금 17
 
2.2%
천 17
 
2.2%
산 15
 
1.9%
수 12
 
1.5%
덕 11
 
1.4%
Other values (85) 346
44.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 263
33.7%
곡 30
 
3.8%
평 26
 
3.3%
대 23
 
2.9%
신 21
 
2.7%
금 17
 
2.2%
천 17
 
2.2%
산 15
 
1.9%
수 12
 
1.5%
덕 11
 
1.4%
Other values (85) 346
44.3%

지번
Text

Distinct241
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T14:34:19.493657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.9558824
Min length2

Characters and Unicode

Total characters1348
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)79.4%

Sample

1st row산241-1
2nd row982구
3rd row1002전
4th row산24-1
5th row산101
ValueCountFrequency (%)
산3임 4
 
1.5%
산57임 3
 
1.1%
산99임 3
 
1.1%
산112임 3
 
1.1%
산30임 3
 
1.1%
산37-1임 2
 
0.7%
산5임 2
 
0.7%
산59 2
 
0.7%
산12-1임 2
 
0.7%
산65임 2
 
0.7%
Other values (231) 246
90.4%
2023-12-12T14:34:20.038435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 229
17.0%
1 196
14.5%
임 147
10.9%
2 90
 
6.7%
- 81
 
6.0%
3 79
 
5.9%
4 71
 
5.3%
5 66
 
4.9%
6 64
 
4.7%
9 60
 
4.5%
Other values (18) 265
19.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 790
58.6%
Other Letter 460
34.1%
Dash Punctuation 81
 
6.0%
Math Symbol 9
 
0.7%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 229
49.8%
임 147
32.0%
구 36
 
7.8%
외 9
 
2.0%
답 9
 
2.0%
전 7
 
1.5%
대 5
 
1.1%
천 4
 
0.9%
인 4
 
0.9%
근 4
 
0.9%
Other values (4) 6
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 196
24.8%
2 90
11.4%
3 79
10.0%
4 71
 
9.0%
5 66
 
8.4%
6 64
 
8.1%
9 60
 
7.6%
8 58
 
7.3%
0 54
 
6.8%
7 52
 
6.6%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 888
65.9%
Hangul 460
34.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 229
49.8%
임 147
32.0%
구 36
 
7.8%
외 9
 
2.0%
답 9
 
2.0%
전 7
 
1.5%
대 5
 
1.1%
천 4
 
0.9%
인 4
 
0.9%
근 4
 
0.9%
Other values (4) 6
 
1.3%
Common
ValueCountFrequency (%)
1 196
22.1%
2 90
10.1%
- 81
9.1%
3 79
8.9%
4 71
 
8.0%
5 66
 
7.4%
6 64
 
7.2%
9 60
 
6.8%
8 58
 
6.5%
0 54
 
6.1%
Other values (4) 69
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 888
65.9%
Hangul 460
34.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 229
49.8%
임 147
32.0%
구 36
 
7.8%
외 9
 
2.0%
답 9
 
2.0%
전 7
 
1.5%
대 5
 
1.1%
천 4
 
0.9%
인 4
 
0.9%
근 4
 
0.9%
Other values (4) 6
 
1.3%
ASCII
ValueCountFrequency (%)
1 196
22.1%
2 90
10.1%
- 81
9.1%
3 79
8.9%
4 71
 
8.0%
5 66
 
7.4%
6 64
 
7.2%
9 60
 
6.8%
8 58
 
6.5%
0 54
 
6.1%
Other values (4) 69
 
7.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.049812
Minimum35.848444
Maximum36.250722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:34:20.272574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.848444
5-th percentile35.872196
Q135.962598
median36.04793
Q336.129321
95-th percentile36.227593
Maximum36.250722
Range0.40227777
Interquartile range (IQR)0.16672278

Descriptive statistics

Standard deviation0.10811733
Coefficient of variation (CV)0.0029991094
Kurtosis-0.95697653
Mean36.049812
Median Absolute Deviation (MAD)0.084
Skewness0.039019304
Sum9805.5489
Variance0.011689357
MonotonicityNot monotonic
2023-12-12T14:34:20.481630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.24831 1
 
0.4%
36.22355528 1
 
0.4%
36.10944417 1
 
0.4%
36.084705 1
 
0.4%
36.07169361 1
 
0.4%
36.12055528 1
 
0.4%
36.0595275 1
 
0.4%
36.21997194 1
 
0.4%
36.2342775 1
 
0.4%
36.10238889 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
35.84844417 1
0.4%
35.85333306 1
0.4%
35.85371722 1
0.4%
35.85598111 1
0.4%
35.85691639 1
0.4%
35.86019583 1
0.4%
35.86259472 1
0.4%
35.86514194 1
0.4%
35.86688861 1
0.4%
35.86972194 1
0.4%
ValueCountFrequency (%)
36.25072194 1
0.4%
36.24872194 1
0.4%
36.24831 1
0.4%
36.24688861 1
0.4%
36.24649972 1
0.4%
36.24386083 1
0.4%
36.24309194 1
0.4%
36.23494194 1
0.4%
36.23474972 1
0.4%
36.2342775 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.06513
Minimum127.90221
Maximum128.29424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:34:20.716429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.90221
5-th percentile127.93029
Q1127.99843
median128.05658
Q3128.12057
95-th percentile128.23399
Maximum128.29424
Range0.3920272
Interquartile range (IQR)0.12214418

Descriptive statistics

Standard deviation0.092906872
Coefficient of variation (CV)0.00072546579
Kurtosis-0.33260733
Mean128.06513
Median Absolute Deviation (MAD)0.06281835
Skewness0.48940561
Sum34833.716
Variance0.0086316869
MonotonicityNot monotonic
2023-12-12T14:34:20.934543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.1551672 1
 
0.4%
128.2048333 1
 
0.4%
128.0302778 1
 
0.4%
128.0233397 1
 
0.4%
127.9898178 1
 
0.4%
127.9911111 1
 
0.4%
128.1291944 1
 
0.4%
128.2085833 1
 
0.4%
128.1923611 1
 
0.4%
127.9973861 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
127.9022086 1
0.4%
127.9029722 1
0.4%
127.9036389 1
0.4%
127.9062958 1
0.4%
127.9099997 1
0.4%
127.9109444 1
0.4%
127.9123889 1
0.4%
127.9158333 1
0.4%
127.92175 1
0.4%
127.9228875 1
0.4%
ValueCountFrequency (%)
128.2942358 1
0.4%
128.2916636 1
0.4%
128.2898717 1
0.4%
128.28475 1
0.4%
128.2819444 1
0.4%
128.2767722 1
0.4%
128.2755667 1
0.4%
128.2752222 1
0.4%
128.2736558 1
0.4%
128.2700556 1
0.4%

소유별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
사유림
272 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사유림 272
100.0%

Length

2023-12-12T14:34:21.100060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:34:21.233395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유림 272
100.0%

취약지역지정사유
Text

Distinct246
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T14:34:21.584004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length57.5
Mean length47.106618
Min length3

Characters and Unicode

Total characters12813
Distinct characters337
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)85.7%

Sample

1st row암반풍화도가 높고 침식 및 세굴
2nd row집중 호우 시 침식, 세굴에 의한 퇴적물 발생이 우려
3rd row지속적인 풍화로 인해 계류 황폐화가 유역 전반에 걸쳐 진행된 상태
4th row계류내 침식
5th row낙석피해예상
ValueCountFrequency (%)
계류 104
 
3.3%
및 84
 
2.6%
내 42
 
1.3%
시 37
 
1.2%
계류수가 32
 
1.0%
계류내 30
 
0.9%
전석 29
 
0.9%
있음 29
 
0.9%
퇴적물이 28
 
0.9%
의한 26
 
0.8%
Other values (1000) 2750
86.2%
2023-12-12T14:34:22.202764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2953
 
23.0%
이 356
 
2.8%
류 321
 
2.5%
가 312
 
2.4%
계 280
 
2.2%
적 253
 
2.0%
로 250
 
2.0%
의 214
 
1.7%
지 208
 
1.6%
사 206
 
1.6%
Other values (327) 7460
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9687
75.6%
Space Separator 2953
 
23.0%
Other Punctuation 138
 
1.1%
Decimal Number 22
 
0.2%
Lowercase Letter 4
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 356
 
3.7%
류 321
 
3.3%
가 312
 
3.2%
계 280
 
2.9%
적 253
 
2.6%
로 250
 
2.6%
의 214
 
2.2%
지 208
 
2.1%
사 206
 
2.1%
유 200
 
2.1%
Other values (311) 7087
73.2%
Decimal Number
ValueCountFrequency (%)
1 7
31.8%
0 5
22.7%
2 5
22.7%
3 1
 
4.5%
5 1
 
4.5%
6 1
 
4.5%
9 1
 
4.5%
7 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 120
87.0%
. 18
 
13.0%
Space Separator
ValueCountFrequency (%)
2953
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
V 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9687
75.6%
Common 3120
 
24.4%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 356
 
3.7%
류 321
 
3.3%
가 312
 
3.2%
계 280
 
2.9%
적 253
 
2.6%
로 250
 
2.6%
의 214
 
2.2%
지 208
 
2.1%
사 206
 
2.1%
유 200
 
2.1%
Other values (311) 7087
73.2%
Common
ValueCountFrequency (%)
2953
94.6%
, 120
 
3.8%
. 18
 
0.6%
1 7
 
0.2%
0 5
 
0.2%
2 5
 
0.2%
( 3
 
0.1%
) 3
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
Other values (4) 4
 
0.1%
Latin
ValueCountFrequency (%)
m 4
66.7%
V 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9686
75.6%
ASCII 3126
 
24.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2953
94.5%
, 120
 
3.8%
. 18
 
0.6%
1 7
 
0.2%
0 5
 
0.2%
2 5
 
0.2%
m 4
 
0.1%
( 3
 
0.1%
) 3
 
0.1%
V 2
 
0.1%
Other values (6) 6
 
0.2%
Hangul
ValueCountFrequency (%)
이 356
 
3.7%
류 321
 
3.3%
가 312
 
3.2%
계 280
 
2.9%
적 253
 
2.6%
로 250
 
2.6%
의 214
 
2.2%
지 208
 
2.1%
사 206
 
2.1%
유 200
 
2.1%
Other values (310) 7086
73.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-09-21
272 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-21
2nd row2023-09-21
3rd row2023-09-21
4th row2023-09-21
5th row2023-09-21

Common Values

ValueCountFrequency (%)
2023-09-21 272
100.0%

Length

2023-12-12T14:34:22.366021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:34:22.472100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-21 272
100.0%

Interactions

2023-12-12T14:34:16.962468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:16.718126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:17.147242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:16.825884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:34:22.556361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동리위도경도
읍면동1.0000.9980.9090.883
리0.9981.0000.9880.983
위도0.9090.9881.0000.620
경도0.8830.9830.6201.000
2023-12-12T14:34:22.684661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도읍면동
위도1.0000.5020.627
경도0.5021.0000.569
읍면동0.6270.5691.000

Missing values

2023-12-12T14:34:17.325216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:34:17.518876image/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

시도시군구읍면동리지번위도경도소유별취약지역지정사유데이터기준일
0경상북도김천시감문면송북리산241-136.24831128.155167사유림암반풍화도가 높고 침식 및 세굴2023-09-21
1경상북도김천시감문면덕남리982구36.217611128.228917사유림집중 호우 시 침식, 세굴에 의한 퇴적물 발생이 우려2023-09-21
2경상북도김천시개령면광천리1002전36.189361128.208194사유림지속적인 풍화로 인해 계류 황폐화가 유역 전반에 걸쳐 진행된 상태2023-09-21
3경상북도김천시구성면금평리산24-136.025779128.067316사유림계류내 침식2023-09-21
4경상북도김천시대덕면조룡리산10135.951375127.950742사유림낙석피해예상2023-09-21
5경상북도김천시대항면운수리산84-23임36.12448127.9889사유림계류 내 계안침식 및 표층유실, 퇴적물 유동흔적 등 위험요소가 관측되고 집중호우 시 하부 운수암에 피해가 우려2023-09-21
6경상북도김천시대항면주례리999전36.086722127.984889사유림유출구에는 하부 인가가 다수 분포하고 있어 강우 시 위험사면등에서 산사태발생 및 퇴적물과 붕괴 유실물이 발생 가능성2023-09-21
7경상북도김천시봉산면인의리산133구36.169083128.06475사유림계류내 유수로 인한 지속적인 침식 및 붕괴가 반복적으로 이루어 질 것으로 예상2023-09-21
8경상북도김천시봉산면인의리16답36.165694128.073389사유림계류 주변에 위치한 사면에서 지속적으로 토사가 유출되고 있는 상태2023-09-21
9경상북도김천시봉산면태화리산100임36.145222128.023278사유림집중호우로 인하여 현재 계류 곳곳에 퇴적물의 이동흔적 및 월류흔적2023-09-21
시도시군구읍면동리지번위도경도소유별취약지역지정사유데이터기준일
262경상북도김천시남면오봉리산179-19임36.095361128.275567사유림계류 양안으로 암반노출 계류로 퇴적물 분포비율이 높으며, 유동흔적이 관찰2023-09-21
263경상북도김천시농소면봉곡리산81외36.052313128.175782사유림토사유실이 진행있음2023-09-21
264경상북도김천시농소면노곡리산75-136.059847128.206581사유림계류 상부 임도 성토사면부터 하부에 위치한 인가까지 토석류가 발생함2023-09-21
265경상북도김천시신음동<NA>산143-1임36.133889128.106944사유림표층유실, 수목전도, 뿌리노출과 같은 위험요소가 다수 관찰되고 있어 토석류에 취약할 것으로 판단2023-09-21
266경상북도김천시아포읍대성리산159임36.116505128.273656사유림계류 내 심한풍화로 지반이 취약하고 세굴 및 침식 그리고 여러 구역에서 붕괴지를 형성2023-09-21
267경상북도김천시어모면옥율리산8636.180109128.094992사유림계류부수량이 많고 퇴적물분포비율 높음2023-09-21
268경상북도김천시어모면옥율리산228구36.172416128.088417사유림다수의 지류가 합류되어 유량이 클 것ㅇ드로 예상되는 지역으로 전체적으로 사면이 불안정하며 붕괴 및 퇴적물들의 유입이 지속적2023-09-21
269경상북도김천시어모면구례리산104임36.225139128.107083사유림주원인으로 붕괴지가 존재하고 있어 위험하고 부원인으로 전석비율이 높고 토심이 깊고 위험사면의 경사가 급함2023-09-21
270경상북도김천시조마면대방리2121-135천35.983194128.124817사유림유역면적이 큰 유역으로 계류 폭이 넓고 전석 및 자갈분포비율이 높음2023-09-21
271경상북도김천시지례면신평리산25임35.969889128.070778사유림계류수가 항시 존재하며 계류수에 의한 측방 및 하안침식으로 소규모의 붕괴지가 존재2023-09-21