Environmental Change Monitoring - A Case Study in the Region of Yinchuan, Ningxia, China
Cross-sectional analysis:
At a point of time t: Ej = b0 + SbiSi + e0 (3)
where Ej - dependant variable (environmental element j), b0 - a constant or rather an intercept, bi - regression coefficients, Si - interdependent variables (socio-economic indices), e0 - error term.
Panel analysis :
During the time interval Dt: DEj = b0 + SbiDSi + e1 (4)
where DEj - change in environmental element j during the time interval Dt, and DSi - changes in socio-economic indices during the corresponding period and e1 - error term.
These two kinds of analysis both link the environment elements with the human activity by combining the results acquired by remote sensing processing with the meteorological data and socio-economic data - the best presentation way of human activity.
The environmental changes (table 1) and the corresponding changes in socio-economic data and meteorological data from 1988 to 1999 (tables 2 and 3) were incorporated in SYSTAT. The changes in environment are regarded as dependent variables and the development in socio-economy and evolution in climate as independent variables. The modelling was conducted in a stepwise manner within a confidence level of 0.05 and the results are shown in table 4.
Cross-sectional analysis links the classification results of land use pattern from the ETM images dated 1999 with the socio-economic data of 1999, which has been discussed in another paper of the author (Wu et al., 2003). The modelling results are re-presented in table 5.
Table 2: Evolution in socio-economic indices from 1988 to 1999 in the region of Yinchuan
| Counties |
ΔTotal population (1000 people) |
ΔUrban population (1000 people) |
ΔRural population (1000 people) |
ΔRural labour force(1000 people) |
ΔTotal sown area(1000 ha) |
ΔFood crop area(1000 ha) |
ΔFood production(1000 ton) |
| Huinong |
-1.10 |
7.90 |
-9.00 |
10.10 |
8.70 |
7.00 |
43.98 |
| Pingluo |
19.70 |
21.50 |
-1.80 |
31.00 |
15.50 |
15.50 |
139.98 |
| Taole |
9.10 |
2.30 |
6.80 |
2.70 |
5.00 |
3.70 |
17.55 |
| Shizuishan |
59.30 |
68.70 |
-9.40 |
0.90 |
0.10 |
0.10 |
2.31 |
| Helan |
12.60 |
14.50 |
-2.00 |
26.20 |
4.20 |
8.50 |
112.59 |
| Yinchuan |
43.90 |
146.40 |
-2.50 |
10.00 |
2.30 |
0.60 |
34.85 |
| Yongning |
18.00 |
14.50 |
3.50 |
19.40 |
4.90 |
5.30 |
67.71 |
| Total region |
261.50 |
275.80 |
-14.40 |
100.30 |
40.70 |
40.70 |
418.97 |
| County |
ΔVegetable oil product(1000 ton) |
ΔTotal meat product(1000 ton) |
ΔAgric. output(million yuan) |
Annual agric. growth rate (%) |
ΔIndustrial output (million yuan) |
Annual industrial growth rate (%) |
ΔGDP(million yuan) |
ΔGDP per capita(yuan) |
| Huinong |
5.84 |
2.86 |
250.10 |
13.96 |
368.50 |
31.17 |
290.16 |
3895.10 |
| Pingluo |
3.88 |
12.08 |
508.40 |
14.21 |
739. 10 |
15.05 |
738.05 |
2792.10 |
| Taole |
1.04 |
1.14 |
54.30 |
10.73 |
17.90 |
16.93 |
69.06 |
2679.90 |
| Shizuishan |
-0.05 |
0.52 |
26.30 |
11.36 |
3024.20 |
12.89 |
2020.80 |
5870.50 |
| Helan |
-0.86 |
4.35 |
402.30 |
12.70 |
583.80 |
19.01 |
582.67 |
3269.20 |
| Yinchuan |
-0.44 |
5.80 |
446.60 |
14.04 |
4421.60 |
13.20 |
4973.62 |
7918.40 |
| Yongning |
0.20 |
2.83 |
402.00 |
11.89 |
693.4 |
21.73 |
699.10 |
3747.00 |
| Total region |
9.61 |
29.58 |
2090.50 |
13.17 |
9844.10 |
14.95 |
9373.46 |
4310.31 |
Note: Data are from the Statistical Yearbooks of Ningxia, published by China Statistics Press in 1989 and 2000. ?GDP = GDP1999-GDP1991
Table 3: Climate changes in the region of Yinchuan between 1999 and 1988
| Counties |
Huinong |
Pingluo |
Taole |
Shizuishan |
Helan |
Yinchuan |
Yongning |
| Mean Temperature (°C) |
1999 |
10.2 |
10.4 |
10.0 |
11.5 |
10.5 |
10.3 |
10.3 |
|
| 1988 |
9.1 |
8.6 |
8.4 |
9.6 |
8.8 |
8.8 |
|
8.7 |
| ΔT = T1999 - T1988 (°C) |
1.1 |
1.8 |
1.6 |
1.9 |
1.7 |
1.5 |
1.6 |
| Annual Precipitation (mm) |
1999 |
120.0 |
154.9 |
133.3 |
127.0 |
132.3 |
165.1 |
13.4 |
| 219.0 |
1988 |
211.0 |
245.0 |
227.0 |
158.0 |
200.9 |
|
162.4 |
| ΔP = P1999 - P1988 (mm) |
-99 |
-56.1 |
-111.7 |
-100 |
-25.7 |
-35.8 |
-19 |
| Annual Evaporation (mm) |
1999 |
2318.0 |
1897.5 |
1904.1 |
2147.2 |
1814.4 |
1675.7 |
1907.0 |
| 1988 |
1860.3 |
1604.8 |
1645.3 |
2115.8 |
1473.4 |
1491.9 |
1513.2 |
| ΔE = E1999 - E1988(mm) |
457.7 |
292.7 |
258.8 |
31.4 |
341 |
183.8 |
393.8 |
Note: The original data are from Ningxia Statistical Yearbook, 1989 and 2000.
5. DISCUSSION
A discussion has been already held on the farmland extension, urban and village development and water-body mobility in the region (Wu et al., 2002a). An insight is particularly given to the change concerning the Yellow River.
The river, with a current surface of 81.3km2 (1.0 % of the total territory), has narrowed by 83.8km2 at a rate of -7.0km2/a or -6.1 %. The river surfaces shown in the TM and ETM images are an overall expression of the instant hydrological conditions, rainfall and human activity around the dates when images were acquired. This surface reduction is thus related to several natural and anthropogenic factors. An analysis is hereby focused on the changes in rainfall in the upper reach basin, taking Xining and Yinchuan for example.
Usually, river surface is to some extent associated with the two or three months of rainfall previous to the image acquisition date. Figure 4 shows the monthly rainfall in Xining and Yinchuan from June to Sept. of 1987 and 1999, concerned with the acquisition periods of Landsat images.
Table 4: Relationships between environmental changes and human activity
| Dependent |
Final entered independent |
Const. |
Parameter estimate |
Std error |
Std coef. |
Df |
F |
Pr>F |
R2 |
| ∆Farmland |
∆Agricultural output |
- 0.3627 |
0.0240 |
0.0060 |
0.855 |
1 |
13.61 |
0.0140 |
0.731 |
| ∆Artificial grassland |
∆Meat product |
- 3.3314 |
3.9910 |
0.5570 |
0.955 |
1 |
51.36 |
0.0010 |
0.911 |
| Land degradation |
∆Industry output |
5.0306 |
0.0020 |
0.0010 |
0.841 |
1 |
12.11 |
0.0180 |
0.708 |
| ∆Rural built-up increase |
∆Rural labour force
|
- 1.0098 |
-1.0305 |
0.2105 |
-1.594 |
1 |
23.96 |
0.0160 |
0.996 |
| ∆Food product |
0.2885 |
0.0417 |
1.949 |
1 |
47.86 |
0.0060 |
| ∆Agricultural output |
0.0281 |
0.0032 |
0.721 |
1 |
76.02 |
0.0030 |
| ∆Urban |
∆Urban population |
- 0.1519 |
0.1340 |
0.0100 |
0.986 |
1 |
170.07 |
0.0002 |
0.971 |
| Water to land |
∆Sown area |
-2.0059 |
1.6716 |
0.3620 |
0.932 |
1 |
22.25 |
0.0050 |
0.867 |
| Land to water |
∆Agriculture output |
0.3965 |
0.0448 |
0.0120 |
0.862 |
1 |
14.46 |
0.0130 |
0.743 |
Table 5: Spatial determinant(s) of the environmental components
|
Dependent |
Final entered independent |
Constan |
t Parameter estimate |
Std error |
Std coeff. |
Df |
F |
Pr>F |
R2 |
|
Farmland |
Rural population |
1.472 |
3.9016 |
0.373 |
0.9779 |
1 |
109.42 |
0.0001 |
0.956 |
|
Urban |
Total industrial output |
2.233 |
0.0101 |
0.001 |
0.9815 |
1 |
131.57 |
< 0.0001 |
0.963 |
|
Village |
Rural population |
3.361 |
0.2160 |
0.060 |
0.8480 |
1 |
12.788 |
0.0160 |
0.719 |
|
Forest |
Total agricultural output |
-17.366 |
0.2000 |
0.072 |
0.7800 |
1 |
7.743 |
0.039 |
0.608 |
|
Saline-land |
Chemical fertiliserUsed |
3.779 |
4.015 |
1.224 |
0.825 |
1 |
10.69 |
0.022 |
0.681 |
|
Lake & pond |
Total sown area |
2.318 |
2.1590 |
0.582 |
0.856
1
13.744 |
0.014 |
0.733 |
|
Marsh |
Total sown area |
5.492 |
0.8840 |
0.274 |
0.8220 |
1 |
10.442 |
0.023 |
0.676 |
|
Fallow-land |
Total sown area |
-3.995 |
2.234 |
0.613 |
4.399 |
1 |
13.302 |
0.022 |
0.894 |
|
Food crop area |
|
-2.035 |
0.677 |
-3.623 |
1 |
9.026 |
0.040 |