Evaluation of Eco-environmental Sensitivity in Lake Dianchi Basin Based on the Fractal Analysis

Energy Procedia 00 (2011) 000–000 Energy Procedia 13 (2011) 4945 – 4956

Energy

Procedia

www.elsevier.com/locate/procedia

ESEP 2011: 9-10 December 2011, Singapore

Evaluation of Eco-environmental Sensitivity in Lake Dianchi

Basin Based on the Fractal Analysis

Jian Lia,*, Mengchao Guob, Kaishuang Luo c, Lianhong Lv d, Baoli Ane, Zheng

Zhanga,f

a. The Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083,

China,

b.Department of Mechanical Engineering, Academy of The Armored Force Engineering, Beijing 100072,China,

c. Dept. of Mater. Sci. & Eng., Tsinghua Univ., Beijing, China.

d. Department of Environment and Economy; Chinese Research Academy of Environmental Sciences,Beijing 100012,China

e. International Center for Research and Training on Seabuckthorn, Beijing 100038, China

f. College of Environment Science & engineering, Beijing Forestry, University, Beijing 100083, China

Abstract

Sustainable ecological and environmental development is the basis of regional development. The sensitivity classification of the ecological environment is the premise of its spatial distribution for land use planning. In this paper, patch fractal dimension method and weighted sum of multi-factor model were employed to analyze the eco-environmental sensitivity in Lake Dianchi Basin. Two eco-environmental indexes, including soil erosion and land use type were used to classify the eco-environmental sensitivity. The results were categorized into five ranks: insensitive, slightly sensitive, moderately sensitive, highly sensitive and extremely sensitive zones. The spatial distribution map of eco-environmental sensitivity in Lake Dianchi Basin was obtained by using GIS (Geographical Information System) techniques. The results illustrated that the extremely sensitive and highly sensitive areas accounted for 30.32% and 22.51% of the total area, respectively, while the moderately sensitive and slightly sensitive areas are 10.19% and 13.34%, respectively. The results provide the theoretical foundation for determining priority areas of the eco-environmental protection and treatment in Lake Dianchi Basin.

© 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Singapore Institute of © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of ESEP 2011 Electronics

Keywords: Land use types, Soil erosion, Fractal dimension, Eco-environmental sensitivity evaluation, Lake Dianchi Basin

Corresponding author. Tel.: +0086134240360. E-mail address:shary092009@hotmail.com.

*

1876-6102 © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Singapore Institute of Electronicsdoi:10.1016/j.egypro.2011.12.114

4946 Jian Li et al. / Energy Procedia 13 (2011) 4945 – 4956

1. Introduction

The eco-environmental sensitivity evaluation is an effective way which the priority or key areas of the eco-environmental construction and protection can be determined. The sensitivity of ecological environment is the sensitive degree of ecological system reflected all sorts of eco-environmental variation and human activities, which reflect the possibility of resulting in eco-environmental imbalance and eco-environmental issues [1]. Under natural conditions, ecological processes maintain a relatively stable coupled relationship to ensure the relative stability of ecological systems, but if the outside interference exceeds a certain limit, this coupled relationship will be broken and some of the ecological processes will take the opportunity to expansion, which leading to some serious eco-environmental problems [2]. Therefore, the essence of eco-environmental sensitivity evaluation is the possibility of bringing out potentially eco-environmental problems in evaluating the specific ecological processes under natural conditions [2].

At present, ecological sensitivity analysis is a hot study at home and abroad. Many scholars have made some useful exploration in this study area [3-6]. The study focused primarily on studies of large-scale eco-environmental sensitivity, including the continental shelf ecological sensitivity [7], the ecological sensitivity of forest to choosing the cutting [8], the sensitivity of agriculture to climate change [9], the sensitivity of hydrological system to climate change [3], the sensitivity of wetlands and wetland plants to climate change [10], the regional index of ecological sensitivity selected according to the space similarity model [11] ,and so on.

The study of ecological sensitivity evaluation for watershed focused on the ecological value of environmental sensitivity area (ESA) and the protection and the application value of sensitive areas [12-14]. The analysis process of watershed ecological sensitivity is an integrated process which includes the principles and methods of geography, ecology, economics and many other subjects. Moreover, the applications of these principles and methods in this study area have been getting matured day by day.

In the field of uncertainty and non-linear analyses, several mathematical methods have emerged and got well developed during recent years such as fractal-geometry methods [15-19].

Fractal geometry provides a mathematical model for many complex objects found in nature [20-22], such as coastlines, mountains, and clouds. These objects are too complex to possess characteristic sizes and to be described by traditional Euclidean geometry. Self- similarity is an essential property of fractal in nature and maybe quantified by a fractal dimension (FD). Several methods exist to determine a fractal dimension, e.g., similarity method, cantor-dust method, balls-covering method, sandbox method, patch method and box-counting method [23].

Among them, the patch fractal dimension reflects the complexity and stability of fractal geometry. Meanwhile, the eco-environmental sensitivity evaluation is one of the main methods to analyze the stability of the regional ecological environment, which the eco-environmental sensitivity evaluation has an important role in the stability analysis of regional (or watershed) ecosystem. In the paper, taking Lake Dianchi Basin as the study unit, on the basis of researches in the regional eco-environmental sensitivity and combining the characteristics of the Lake Dianchi Basin, all kinds of the sensitivity of the ecological problems were analyzed and the evaluation index system of eco-environmental sensitivity in Lake Dianchi Basin were established. The fractal theory (or methodology) and eco-environmental sensitivity evaluation were tried to combine under the circumstances every selected evaluation factors could be analyzed qualitatively and quantitatively by using the patch fractal dimension. ARCGIS what has powerful data processing and spatial analysis capabilities can improve the accuracy and efficiency of the eco-environmental sensitivity evaluation and zoning. Therefore, the eco-environmental sensitivity evaluation and zoning were completed by using ARCGIS technology so as to provide a scientific basis for determining priority areas of eco-environmental protection and treatment in Lake Dianchi Basin.

Jian Li et al. / Energy Procedia 13 (2011) 4945 – 495947

2. Study region, data and methods 2.1 Study region and data

Lake Dianchi Basin (24028＇to 25028＇N, 102030＇to 103000＇E) is located in the middle of Yunnan-Guizhou Plateau in Southwest China. The entire basin has a total area of approximately 2,920 km2, including part of Kunming City (the capital of Yunnan Province) and Songming, Chenggong, Jinning, and Xishan Counties. With a surface area of about 300 km2 and maximum and mean depths of 10 and 4.4 m respectively, Lake Dianchi is the sixth largest fresh water highland lake in China. The geographic location of Lake Dianchi Basin (or the study area) is shown in figure 1.

Fig.1 Geographic location of the study area

In the paper, the study period is only one year (2005). If the data of evaluated index in 2005 is lack, collected data around the 2005 will be used because the eco-environmental change range is not large within a few years [24].

For this study, 1: 100,000-scale vector diagram of land use type in 2005 in Lake Dianchi Basin and a 1: 100,000-scale vector diagram of soil erosion in 2000 in Lake Dianchi Basin which were provided by Institute of Remote Sensing Applications, Chinese Academy of Sciences were used as data source. Then, these vector diagrams (or data) were converted to raster data on the ArcGIS platform. The spatial distribution map of eco-environmental sensitivity in Lake Dianchi Basin was obtained by using spatial analyst module which has the map algebra analysis function to combine the eco-environmental sensitivity distribution maps of every evaluated factor. 2.2 Methods

2.2.1 Patch fractal dimension

Mandelbrot [21](1982) had proposed the relationship formula between surface area S (r) and volume V (r) when he studied the fractal structure of animal brain plait. The formula of patch fractal dimension was determined by Eq. (1):

(1) S(r)1/D～V(r)1/3

4948 Jian Li et al. / Energy Procedia 13 (2011) 4945 – 4956

Dong Lianke[25] (1991) has derived the formula of fractal dimension by using the physical dimension analysis method in the land use planning. The fractal dimension formula what the areas and perimeters of fractal geometry of land use type should meet is defined as Eq. (2):

P(r) 1/D = k * r (1-D)/D * A(r) 1/2 (2) Where, the D is the value of patch fractal dimension, the r is the measurement scale, the A (r) is the area of fractal geometry taken the r as measurement scale, the P (r) is the perimeter of fractal geometry taken the r as measurement scale, and the k is a constant. Eq. (2) can be transformed into the following formula by taking the natural logarithm:

lnP(r) = (D/2) lnA(r) + C (3) Here, Eq.(3) is the final fractal dimension formula. Thus, lnP (r) and lnA (r) are a kind of linear relationship, and the value of fractal dimension (D) is two times of linear slope value.

The theory value range of D located between 0 and 2 which reflects the stability and complexity of fractal geometry. The greater the D is, the more complex spatial mosaic structure of the fractal geometry is. Or the smaller the D is, the more simple spatial mosaic structure of the fractal geometry is. When D equals to 0, it means that the shape of fractal geometry is definitely to a point. When D equals to 1, it means that the shape of fractal geometry is a square. When D equals to 1.5, it indicates that the space distribution of fractal geometry is in a similar to the random motion state of Brownian motion, which the spatial structure of the fractal geometry is the most unstable. When D equals to 2, it indicates that the space distribution of the fractal geometry is even [26].

The stability index (S) of the fractal geometry is defined as Eq. (4). That is, the closer to 1.5 the value of D is, the smaller the value of S is, and the more stable the spatial structure is:

S = 1.5 – D (4) The value of S is closely related to the stability of spatial structure. When S> 0, it means that the stability of the fractal geometry is in the simple state. That is, the larger the value of S is, the more stable the fractal geometry is. On the contrary, when S <0, it means that the stability of the fractal geometry is in the complex state. That is, the smaller the value of S is, the more stable fractal geometry is [26].

2.2.2 Mathematical model of the eco-environmental sensitivity evaluation

2.2.2.1 The determining of weighing values

At present, there are many methods of the weight value determined, but more commonly used method is Delphi method and AHP [27]. The right method should be chosen to determine the weight value depending on the special circumstances so that the determined weight is more scientific. The influencing factors of the eco-environmental sensitivity include natural factors and human factors [28]. The ecosystem itself is a huge complex dynamic system. Sometimes, it is difficult to distinguish between the natural factors (such as floods, droughts and fire disasters) and human disturbance (pollutant emissions, the development and utilization of resources, etc.) in the eco-environmental sensitivity evaluation. Meanwhile, the eco-environmental sensitivity evaluation is not a simple task when the ecological process was gradually familiar with human being, which indicates the selection and assortment of evaluated index have a strong human subjectivity.

In summary, natural factors that influence eco-environmental sensitivity were defined as natural indexes and human factors that influence eco-environmental sensitivity are defined as human indexes (or vulnerability indexes). Meanwhile, the sort of selected natural factors and human factors is taken into consideration, and selected natural factors and human factors can be calculated by the patch fractal dimension method. Therefore, land use type is set for natural factors of the eco-environmental sensitivity evaluation in Lake Dianchi Basin, and soil erosion is set for human factors of the eco-environmental sensitivity evaluation in Lake Dianchi Basin. Then, the weights of human factors and natural factors are assigned 0.5, respectively.

Jian Li et al. / Energy Procedia 13 (2011) 4945 – 495949

2.2.2.2 Weighted sum of multi-factor model

The eco-environmental sensitivity evaluation of Lake Dianchi Basin based on weighted sum of multi-factor model can be expressed as Eq. (5):

(5)

Where, S is the grade of the eco-environmental sensitivity, ωi is the weight of the evaluated factors, pi is the quantitative value of descriptive grade of the ith evaluated factor, and n is the number of the evaluated factor.

i=1

S=∑ωipi

n

3 Results and discussion

3.1 Discussion on the fractal characteristic of land use type

Land use type of the study area is divided into five types which include cultivated land, forest land, grass land, water area, urban, rural and resident land based on 1: 100,000-scale vector diagram of land use type for Lake Dianchi Basin in 2005. Figure 2 shows the classification map of land use type in Lake Dianchi Basin.

Fig.2 The classification map of land use type in Lake Dianchi Basin

The perimeter and area of every patch were extracted by using the ArcGIS software [29]. The value of fractal dimension (D) were obtained by using the Eq.(3). Table 1 showed the fractal dimension (D) for all land use types of Lake Dianchi basin in 2005. Figure 3 showed the straight line of lnP (r) ～lnA (r) for every patch of land use type by using the SPSS statistical analysis software.

Tab. 1 The fractal dimension (D) for all land use types of Lake Dianchi Basin in 2005

The number of patch(N) 526

The value of fractal dimension (D)

1.23

The index

of stability(S

)

Serial number a

The names of land use type Cultivated land

R20.9

Area(km2)perimeter (km) Area percentage (%)

26.37

0.28 762.14377.14

4950 Jian Li et al. / Energy Procedia 13 (2011) 4945 – 4956

2 3 b c d e

Forest land Grass land Water area urban, rural and resident land

447 277 358

0.95 0.96 0.94 0.91

986.4

1.09 0.41

5 568.5

1.13 0.37

5 340.8

1.26 0.24

2 231.8

1.35 0.15

8

4184.81 34.14 2777.36 19.67 446.35 11.80 1531.36 8.02

a Cultivated land b Forest land

c Grass land d Water area

e Urban, rural and resident land f Total scatter plot chart

Fig.3 The straight line of lnP(r)～lnA (r) for each patch of land use type

(1) Cultivated land

The fractal dimension of cultivated land is 1.23 (Tab.1) and the number of patch of cultivated land is up to 526 in the first place (Tab.1). Natural and geographical conditions of basin are the main factors of affecting land use type [30]. Lake Dianchi is a plateau lake, cultivated land mainly concentrated in areas rounding the lake, cultivated areas of hills and mountains present scattered distribution. So, the cultivated land has less stable. (2) Forest land

Jian Li et al. / Energy Procedia 13 (2011) 4945 – 495951

The fractal dimension of forest land is 1.09 (Tab.1). The value of fractal dimension is close to the minimum threshold of it (Tab.1), which indicates the stability of forest land is the highest and the complexity of it is the lowest. The area of forest land which mainly distribute in the mountainous region accounts for 34.14% of the total basin area (Tab.1) where the development degree of forest land is smaller, the level of its keep resources is better, and the patch broken degree of it is lower, which are consistent with the actual situation of the study area. (3) Grass land

The fractal dimension of the grass land is 1.13 and the value of R2 is 0.96 (Tab.1) which means the degree of fitting a straight line is the highest. The value of fractal dimension is less than the cultivated land and bigger than forest land. Overall, the stability of grass land is higher and the complexity of it is lower because the value of it is far from the minimum threshold of fractal dimension. Grass land mainly distribute in the south east bank of the Lake Dianchi and present semi-circular distribution shape around Lake Dianchi (Fig.2). The area of grass land is smaller due to excessive grazing in Lake Dianchi Basin. (4) Water area

The value of fractal dimension is 1.26(Tab.1). The fractal dimension of the water area can not be a good indication of the complexity and the stability to the study area because water area of the study area includes Lake Dianchi and the rivers flowing into it. The form of lake and river has a greater difference, but lake and river are as a whole when the fractal dimension of water area was calculated [31]. (5) Urban, rural and resident land

The value of fractal dimension is 1.35(Tab.1). The value of fractal dimension is close to the maximum threshold of it (Tab.1), which indicates the stability of patches is lowest and the patch broken degree of these is the highest. The number of patches which scatter throughout the study area is more (Fig.2). The soil erosion of these areas is serious due to vegetation and soil with different damage degree. So, the fractal structure of urban, rural and resident land presents the instability.

On the basis of the stability analysis and the fractal characteristics analysis of land use type in Lake Dianchi Basin, combining with the meaning of the eco-environmental sensitivity, progressive increase of the stability and progressive decrease of the eco-environmental sensitivity are defined as the proportional relationship. That is, the higher the stability of land use type is, the lower the sensitivity degree of the regional eco-environment is. Figure 4 shows the stability index and the value of fractal dimension for the different types of landscape. The stability index1.61.41.210.80.60.40.20Cultivated landForest landGrass landWater areaUrban, rural andresident landThe value of fractal dimension

Fig.4 Stability indexes and fractal value of different landscape types

The stability index of different land use types decrease accordingly with the increase of fractal dimension (Fig.4). The landscape type is more stability, which indicates the eco-environmental sensitivity of the landscape type is poor and the area of landscape type belong to insensitive or slightly sensitive

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zones.

3.2 Discussion on the fractal characteristic of soil erosion

Soil erosion of the study area is divided into three types which include micro-degree soil erosion, mild soil erosion and moderate soil erosion based on 1: 100,000-scale vector diagram of soil erosion for Lake Dianchi Basin in 2000. Figure 5 shows the classification map of soil erosion grade in Lake Dianchi Basin.

Fig.5 The classification map of soil erosion grade in Lake Dianchi Basin

The perimeter and area of each soil erosion patch were extracted by using the ArcGIS software [29]. The value of fractal dimension (D) were obtained by using the Eq.(3). Table 2 showed the fractal dimension (D) for soil erosion of Lake Dianchi Basin in 2000. Figure 6 showed the straight line of lnP (r) ～lnA (r) for each patch of soil erosion by using the SPSS statistical analysis software.

Tab. 2 The fractal dimension (D) for soil erosion of Lake Dianchi Basin in 2000 Serial number

The number of patch(N) 278 250 173

The value of fractal dimension (D)

The index

of stability(S)

Area percentage (%)

soil erosion intensity micro-degree soil erosion mild soil erosion moderate soil erosion R 0.95 0.95 0.95 2

Area (km2) perimeter (km)

a b c

1944.81.18 0.32

4 1.28 1.22

0.22 721.590.28 223.41

5086.98 67.30 4076.59 24.97 1798.30 7.73

Jian Li et al. / Energy Procedia 13 (2011) 4945 – 495953

a Micro-degree soil erosion b Mild soil erosion

c Moderate soil erosion d Total scatter plot chart

Fig.6 The straight line of lnP(r)～lnA(r) for each patch of soil erosion

The fractal dimension of different soil erosion intensity in Dianchi Lake Basin can be expressed as follows. The fractal value of mild soil erosion is higher, the fractal value of micro-degree soil erosion is smaller, and the fractal value of moderate soil erosion is placed in the middle of the fractal value of mild soil erosion and the fractal value of micro-degree soil erosion (Fig.5, Fig.6 and Tab.3). The complexity of spatial pattern distribution with different soil erosion intensity in Lake Dianchi Basin can be expressed as follows. The spatial pattern distribution of mild soil erosion is more complex, the spatial pattern distribution of micro-degree soil erosion is simpler, and the spatial pattern distribution of moderate soil erosion is placed in the middle of them (Fig.5, Fig.6 and Tab.3). The distribution of soil erosion within the basin affects the eco-environmental stability of the basin. The type of soil erosion is mainly micro-degree soil erosion whose area accounts for 67.30% of the total basin area, which indicates the regional stability of micro-degree soil erosion is poor. Conversely, still.

On the basis of the stability analysis and the fractal characteristics analysis of soil erosion in Lake Dianchi Basin, combining with the meaning of the eco-environmental sensitivity, progressive increase of the stability and progressive decrease of the eco-environmental sensitivity are defined as the proportional relationship. That is, the higher the stability of soil erosion is, the lower the sensitivity degree of the regional eco-environment is. Figure 7 shows the stability index and the value of fractal dimension for the different soil erosion intensity. The stability index1.41.210.80.60.40.20micro-degree soil erosionmild soil erosionmoderate soil erosionThe value of fractal dimension

Fig. 7 Stability indexes and fractal value of different soil erosion types

49 Jian Li et al. / Energy Procedia 13 (2011) 4945 – 4956

The stability index of different soil erosion types decrease accordingly with the increase of fractal dimension (Fig.7). The soil erosion type is more stability, which indicates the eco-environmental sensitivity of the soil erosion type is poor and the area of the soil erosion type belongs to insensitive or slightly sensitive zones.

3.3 Discussion on the eco-environmental sensitivity evaluation

On the basis of the fractal characteristic analysis of land use type and soil erosion and the given weights of them, and the reference to \"Interim Regulations of Ecological Function Zoning Technology \"(2000), the results of the eco-environmental sensitivity evaluation in Lake Dianchi Basin are shown in Figure 8 and Table 3.

Fig.8 The spatial distribution map of eco-environmental sensitivity in Lake Dianchi Basin Tab. 3 The results of eco-environmental sensitivity evaluation in Lake Dianchi Basin

Type of sensitivity Insensitivity Slight sensitivity Moderate sensitivity High sensitivity Extreme sensitivity

Sensitivity index

1 3 5 7 9

Area(km2)683.20 385.52 294.49 650. 876.25

Proportion (%)

23. 13.34 10.19 22.51 30.32

Feasible land type Feasible zones Feasible zones Feasible zones Protected zones Protected zones

The results were categorized into five ranks: insensitive, slightly sensitive, moderately sensitive,

Jian Li et al. / Energy Procedia 13 (2011) 4945 – 495955

highly sensitive and extremely sensitive zones (Fig.8). The extremely sensitive area was 876.25 km2 and accounted for 30.32% of the total area and the highly sensitive area was 650. km2, accounted for 22.51% of the total in Lake Dianchi Basin. These two kinds of sensitive zones are mainly distributed in (or around) the mining areas and reservoirs where some ecological protection measures of preventing water pollution should be taken in order to prevent the major eco-environmental damage in these areas. The moderately sensitive area was 294.49 km2 and accounted for 10.19%, which mainly distribute around the highly sensitive area and play the buffer role to the highly sensitive area. The slightly sensitive area was 385.52 km2, it accounted for 13.34% and located in outlying areas of the mining area and Lake Dianchi. The insensitive area is far from Lake Dianchi and is more concentrated distribution. The moderately sensitive area, the highly sensitive area and the insensitive area have higher regional stability, which indicate external development and construction activities have little effect to the regional stability. Therefore, some reasonable guide measures should be taken to these areas. 4 Conclusions

In the paper, patch fractal dimension method and weighted sum of multi-factor model were employed to analyze the eco-environmental sensitivity in Lake Dianchi Basin. The results proved that the fractal theory (methodology) combined with eco-environmental sensitivity evaluation is feasible, which provide a new idea to the eco-environmental sensitivity evaluation.

The fractal space characteristic of land use type and soil erosion for a specific point in time were analyzed by using the patch fractal dimension method, but the fractal space characteristic of them for different points in time would not be analyzed. However, the fractal space characteristic of evaluated factors should be analyzed for different points in time in order to reveal roundly and systematically the eco- environmental status change of basin.

In the selection process of evaluated indexes, only one evaluated index were respectively selected from the natural indexes and human indexes. But there are a lot of evaluated indexes which reflect the eco-environmental sensitivity of basin and it is difficult to use one or two indexes to describe the eco-environmental status. Therefore, other influencing factors of the eco-environmental sensitivity such as acid rain, biodiversity and landslide collapse should be considered in the follow-up research work in order to reflect roundly and systematically the eco- environmental status change of basin. At the same time, human factors such as GDP per unit area and population density which reflect the eco-environmental sensitivity of the study area should be considered. References

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