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Land Degradation Detection, Mapping, and monitoring in the Northwestern part of Hebei Province, China, Using RS and GIS Technologies
Change Detection Methodology
Detection by image differencing (Lambin, 1994 and 1997) was adopted to detect the land cover change in our study complemented with visual comparison to distinguish and quantify the county-level change types. The procedures followed in our research are shown as following:
- Image to vector file rectification and image to image registration of the remotely sensed data using forty ground control points (GCP) whose ground coordinates were read from a vector file of the same scale for the same region. Accuracy with a RMS error of < 1 pixel (0.50 pixel) using the first model of polynomial function and Nearest Neighbor re-sampling method in datum WGS84 and projection UTM (50N).
- Tasseled Cap transformation (Crist and Cicone, 1984) on the TM images to convert the land cover information included in seven bands into three indicators: brightness, greenness and wetness, which respectively means the land bareness, vegetation vigor and soil moisture.
- Indicator differencing (e.g., NDVI, Greenness, Brightness, Wetness) between two different dates.
- Thresholding to acquire the changed areas and produce the general change maps which contain three classes: positive change, negative change, and no-change.
- Visual comparison to identify the types of land cover change (e.g., vegetation increase, land degradation) and creates detailed land cover change maps based on the previous general change map.
- Quantification of the land covers changes at county level by GIS technique.
Figure 2 shows the thresholding method to acquire the changed area using RS and GIS technologies for the study area in the Northwestern part of Hebei Province.
Figure 2. Flowchart of the land cover change detection method
Results and Discussion
Greenness Tasseled Cap Indicator
The results of the Greenness Tasseled Cap indicator were presented in table 1 and figures 3, 4. The results showed that highest greenness positive change (vegetation increase) was for Lai Shui County. It was 24.069% for the total area of the county.
The highest greenness negative change (vegetation degradation) value was for Chi Cheng County; it was 19.264% of the total area of the county. The vegetation cover increased by 17.462% of the total area of Lai Shui County in the period from 1987 to 1996; at a change rate 32.917 km 2.yr- 1. The overall greenness positive change (vegetation increase) in the district was 7.431% of the total areas, while it was 6.181% for the greenness negative change (vegetation degradation) over the whole district. The general average in the vegetation increase rate was 28.662 km 2.yr- 1, while was 23.842 km 2.yr- 1 for the vegetation degradation. The lowest percentage of no-change in greenness indicator was 76.171% for the total area of Chi Cheng County. The difference between the percentages for the greenness positive and negative changes was 29.009%, which means there is a vegetation increase in the studied area.
Wetness Tasseled Cap Indicator
The results showed that Chi Cheng County had the highest percentage (6.114%) of wetness positive change, while Wan Quan County had the lowest percentage (0.634%) for the total area of the county. Lai Shui County had the highest percentage of wetness negative change (3.830%) during the period from 1987 to 1996. The overall difference between the wetness positive and negative change was 1.642 % of the total areas of the counties in the region. The overall wetness positive change rate for the entire counties was 6.712 km2.yr-1, while was 3.259 km2.yr-1 for the wetness negative change rate. Table 2 and figures 5, 6 show the results of the wetness tasseled cap indicator.
Table 1. County-level Greenness Tasseled Cap indicator results of the Northwestern part of Hebei Province for the period from 1987 to 1996.
| County Name |
County
area |
GN_P |
GN_N |
No-change |
(GN_P)-
(GN_N)
|
GN P rate |
GN N rate |
| (km2) |
(km2) |
(%) |
(km2) |
(%) |
(km2) |
(%) |
(%) |
(km2 .yr-1) |
| Chi Cheng (1/2) |
2,647.565 |
120.856 |
4.565 |
510.034 |
19.264 |
2,016.675 |
76.171 |
-14.699 |
13.428 |
56.670 |
| Wan Quan |
1,158.246 |
99.502 |
8.591 |
11.021 |
0.952 |
1,047.723 |
90.458 |
7.639 |
11.056 |
1.225 |
| Zhang Jia Kou |
405.414 |
46.040 |
11.356 |
4.538 |
1.119 |
354.836 |
87.524 |
10.237 |
5.116 |
0.504 |
| Cong Li (2/3) |
1,555.442 |
37.168 |
2.390 |
227.259 |
14.611 |
1,291.015 |
83.000 |
-12.221 |
4.130 |
25.251 |
| Huai An |
1,692.094 |
83.782 |
4.951 |
26.388 |
1.560 |
1,581.924 |
93.489 |
3.392 |
9.309 |
2.932 |
| Xuan Hua |
2,474.029 |
141.923 |
5.737 |
50.193 |
2.029 |
2,281.913 |
92.235 |
3.708 |
15.769 |
5.577 |
| Huai Lai |
1,855.068 |
129.132 |
6.961 |
83.283 |
4.489 |
1,642.653 |
88.549 |
2.472 |
14.348 |
9.254 |
| Yang Yuan |
1,838.358 |
50.386 |
2.741 |
12.199 |
0.664 |
1,775.773 |
96.596 |
2.077 |
5.598 |
1.355 |
| Wei Xian |
3,182.889 |
235.979 |
7.414 |
138.719 |
4.358 |
2,808.191 |
88.228 |
3.056 |
26.220 |
15.413 |
| Zhu Lu |
2,788.724 |
306.705 |
10.998 |
142.507 |
5.110 |
2,339.512 |
83.892 |
5.888 |
34.078 |
15.834 |
| Lai Shui (3/4) |
1,230.852 |
296.252 |
24.069 |
81.325 |
6.607 |
853.275 |
69.324 |
17.462 |
32.917 |
9.036 |
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| Sum |
20,828.681 |
1,547.724 |
7.431 |
1,287.467 |
6.181 |
17,993.490 |
86.388 |
1.250 |
171.969 |
143.052 |
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Average |
15.634 |
13.005 |
Table 2. County-level Wetness Tasseled Cap indicator results of the Northwestern part of Hebei Province for the period from 1987 to 1996.
| County Name |
County
area |
WT_P |
WT_N |
No-change |
(WT_P)-
(GN_N)
|
WT P rate |
WT N rate |
| (km2) |
(km2) |
(%) |
(km2) |
(%) |
(km2) |
(%) |
(%) |
(km2 .yr-1) |
| Chi Cheng (1/2) |
2,647.565 |
161.862 |
6.114 |
31.998 |
1.209 |
2,453.705 |
92.678 |
4.905 |
17.985 |
3.555 |
| Wan Quan |
1,158.246 |
7.345 |
0.634 |
7.043 |
0.608 |
1,143.858 |
98.758 |
0.026 |
0.816 |
0.783 |
| Zhang Jia Kou |
405.414 |
11.507 |
2.838 |
5.837 |
1.440 |
388.069 |
95.722 |
1.399 |
1.279 |
0.649 |
| Cong Li (2/3) |
1,555.442 |
52.031 |
3.345 |
7.174 |
0.461 |
1,496.237 |
96.194 |
2.884 |
5.781 |
0.797 |
| Huai An |
1,692.094 |
16.766 |
0.991 |
14.819 |
0.876 |
1,660.509 |
98.133 |
0.115 |
1.863 |
1.647 |
| Xuan Hua |
2,474.029 |
39.950 |
1.615 |
21.313 |
0.861 |
2,412.766 |
97.524 |
0.753 |
4.439 |
2.368 |
| Huai Lai |
1,855.068 |
73.252 |
3.949 |
33.840 |
1.824 |
1,747.977 |
94.227 |
2.125 |
8.139 |
3.760 |
| Yang Yuan |
1,838.358 |
17.817 |
0.969 |
35.727 |
1.943 |
1,784.814 |
97.087 |
-0.974 |
1.980 |
3.970 |
| Wei Xian |
3,182.889 |
95.089 |
2.988 |
88.340 |
2.775 |
2,999.460 |
94.237 |
0.212 |
10.565 |
9.816 |
| Zhu Lu |
2,788.724 |
159.514 |
5.720 |
29.421 |
1.055 |
2,599.789 |
93.225 |
4.665 |
17.724 |
3.269 |
| Lai Shui (3/4) |
1,230.852 |
29.421 |
2.390 |
47.140 |
3.830 |
1,154.291 |
93.780 |
-1.440 |
3.269 |
5.238 |
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| Sum |
20,828.681 |
664.555 |
3.191 |
322.651 |
1.549 |
19,841.475 |
95.260 |
1.642 |
73.839 |
35.850 |
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Average |
6.713 |
3.259 |
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