Ecological Security Evaluation in Farming-pastoral Ecotone Using TM Data

Haijian MA Xiaoxuan LI* Earth Observation Division

National Earthquake Infrastructure Service

Beijing, 100036, China hjma@neis.gov.cn

De-yong HU College of Resource Environment &

Tourism Capital Normal University

Beijing, 100048, China deyonghu@163.com

Hu Zhao Agriculture Resource Monitoring

Station Chinese Academy of Agriculture

Engineering Beijing, 100125, China

zhaohu@agri.gov.cn

Abstract—Farming-pastoral zone is one of typical ecological transition zone in China. To monitor and evaluate the ecological security in farming-pastoral zone is of great significance for regional environmental protection and rational utilization. This paper chooses Guyuan County as the research area, which is in typical farming-pastoral zone area named Bashang in north China. Then, in the administrative divisions of villages and towns, a comprehensive evaluation index of ecological security at small scale in Guyuan County is set up through the following steps. Firstly, based on the "Pressure - State - Response" (PSR) framework and according to the relationship between each component object, a multi-level evaluation index system is constructed. Then, TM remote sensing images, digital elevation data and statistical data are comprehensive utilized to calculate every evaluation index. Next, index weight is obtained by using the Analytic Hierarchy Process (AHP). Results show that the range of comprehensive evaluation index of ecological security in Guyuan County was 0.28-0.64. At most areas, the ecological security was at the "warning" level. At the minority areas, the ecological security even reaches "dangerous" level, such as Huanggaizhuo and Gaoshanbao. The worst town is Guyuan pasture. This study analyzed the ecological security in the region, provided a decision-making basis for the ecological protection.

Keywords—Ecological security; TM; Farming-pastoral ecotone; Analytic hierarchy process

I. INTRODUCTION The farming-pastoral zone is a typical ecologically fragile

area in China, where grassland desertification, soil erosion and other ecological problems take place frequently because of bad natural conditions and unreasonable human farming [1]. These ecological problems in farming-pastoral zones brings great influence to local production, living and economic development. Farming-pastoral zone is becoming one of the most serious ecological problems in our country. Thus, it has important practical significance to evaluate the ecological security in farming-pastoral zone for reasonably adjusting the regional land use pattern, protecting the regional environment and promoting regional economic and social sustainable development [1].

Ecological security is the overall reflection of ecosystem integrity and health level, is closely related to human survival and sustainable development, and attracts more and more attention gradually [2,3]. Ecological security evaluation is usually based on some concept model, by choosing scientific and reasonable index system and evaluation standard, and by using appropriate methods, to assess the ecological environment factors and the overall situation of ecological security [1]. By now, concept models include "Pressure - State - Response"[4] and “Natural-Economic-Social” [3] framework. Statistical indicators are mainly used in early ecological safety evaluation. However, the development of information technology such as remote sensing and GIS promotes the application of quantitative index of landscape ecology [5, 6]. It makes evaluation index more updating and the results more reliable. Evaluation methods can be divided into four categories [7]; mathematical model method, ecological model, digital terrain model and landscape model. The comprehensive evaluation index method is one of the most widely used mathematical models, which can form the comprehensive evaluation index by integrating distributed information to evaluate regional ecological security [8, 9].

This paper chooses Guyuan County as the research area, which is in typical farming-pastoral zone area named Bashang in north China. Detail information about research area and data will be introduced in Section II. Then, in the administrative divisions of villages and towns, a comprehensive evaluation index of ecological security at small scale in Guyuan County is set up to evaluate the ecological security. Section III will describe how to construct evaluation index system, extract evaluation index and make index weight. Some results and discussion are described in Section IV.

II. RESEARCH AREA AND DATA Guyuan County is selected as the research area, which is in

typical farming-pastoral zone area named Bashang in north China. Guyuan County is located in the southern edge of Inner Mongolia plateau, in the transition zone from Inner Mongolia plateau to the North China Plain. The location of Guyuan shown in Fig.1 is 41 °13 ′N ~40 °57 ′N, 114 °50 ′E ~116 °05

*Corresponding author: xxli@neis.gov.cn

′E. The regional climate is temperate continental steppe climate, with an average elevation of 1536 meters. The total area is about 3654 km2. The county is diverse, with mountains in the south and gradually low in the north.

Fig. 1. Location of Guyuan

TM images, Digital Elevation Model (DEM) and statistical data are used in this paper. TM image shown in Fig.2 was acquired in 2008 September when vegetation is in the growth period. DEM data is shown in Fig.3. Statistical data are from the Guyuan County statistical yearbook, including demographic data, the per capita area of vegetation data, social economic data. The administrative map of towns is also collected.

Fig. 2. TM image

Fig. 3. DEM

III. RESEARCH ROADMAP The basic flow is shown in Fig. 4. Evaluation indexes are

selected based on PSR framework, Then, TM remote sensing images, digital elevation data and statistical data are comprehensive utilized to calculate every evaluation index. Next, index weight is obtained by using AHP. At last, a comprehensive evaluation index of ecological security is calculated.

1.Population density2.The per capita area of vegetation3.Annual average income of residents

Slope factor1.Land degradation degree2.The landscape diversity index3.The number of patches4.Vegetation coverage5.Vegetation types AHP

comprehensive evaluation index of ecological security

The normalization factor value

Index weight

DEMTM imagesStatistical data

Evaluation index

PSR framework

Fig. 4. Flow chart

A. Evaluation index The world organization for economic cooperation and

development put forward the PSR model [4]. PSR model emphasizes the influence of human social economic development on the environment, has been widely used in the evaluation of ecological security. In this model, Pressure reflects human activity load, is used to indicate the causes of ecological environment; Status refers to the environment current situation or trend, is mainly used to measure the status change of natural environment which caused by human behavior; Response measures human characterization when facing the environmental problems [4].

Based on the PSR framework, in order to fully consider various factors affecting the farming-pastoral zone, a multi-level evaluation index system is constructed. The evaluation index system is divided into three levels. The final target is comprehensive security index which represents the ecological security situation. The criteria level is the main factors restricting ecological security in farming-pastoral zones. These factors include nature and human pressure factors, vegetation factors and response factors of human society. The index level is formed by direct measurement index and is basic level of the ecological index system.

For Guyuan County, indexes which can be extracted from remote sensing data are given more consideration in the measurement index system. As shown in TABLE I, land degradation, population density and slope are chosen as the ecological pressure index of nature and human; landscape diversity, number of plaques, vegetation coverage and

vegetation type are chosen as vegetation status indexes. The per capita area of vegetation and the annual average income are chosen as the response factors of human society.

TABLE I. INDEXES FOR ECOLOGICAL SECURITY EVALUATION

Target Criteria Index Source

Comprehensive index of ecological security

nature and human pressure

land degradation TM images

population density statistical data

slope DEM vegetation status

landscape diversity TM images number of plaques TM images Fractional Vegetation Cover

TM images

vegetation type TM images

response factors of human society

per capita area of vegetation

statistical data

annual average income

statistical data

B. Information extraction of every evaluation index Values of every factor are extracted or calculated from TM

image, DEM and statistical data. Remote sensing images play a more and more important role in ecological security assessment. Except the terrain slope, population density and annual average income, the other five indexes are all extracted from remote sensing images.

1) Extract index from TM images TM images are preprocessed and classified by supervised

method. The classification results are used as basic information in the following extraction.

Landscape diversity reflects the landscape richness and complexity [10]. Based on landscape classification results, landscape indices are calculated by Fragstats software. Landscape diversity index is calculated as follows:

1ln

m

i ii

H P P=

= −∑ (1)

In the formula, H is diversity index, iP is area ratio of ith landscape type, and m is the number of landscape types.

Vegetation conditions is an important ecological security evaluation input parameters. Fractional Vegetation Cover refers to vegetation in the percentage of the total floor area of the vertical projection area, is a commonly used indicator of vegetation condition. FVC can be approximate estimated by the vegetation index NDVI. The formula is as follow.

( ) ( )min max minIFVC NDVI NDV NDVI NDVI= − − (2)

In the formula, NDVImin is the value at the pixel with bare soil or without vegetation, while NDVImax represents the value at the pixel completely covered with vegetation. The result is shown in Fig.5.

Land degradation is an important factor to measure the overall production capacity change of land environment caused by natural or man-made factors causing. Modified Soil

Adjusted Vegetation Index (MSAVI) is selected for auxiliary calculating land degradation, because it can better eliminate the effects of different soil backgrounds, more suitable to reflect vegetation on the complex underlying surface. The result is shown in Fig.6.

Vegetation types and the number of plaques are obtained from the landscape classification results.

2) Statistics factors The evaluation factors based on statistical data were

collated from statistical yearbook, including population density, per capita area of vegetation and annual average income. A spatial property was created to connect every administrative town in the research area.

3) Terrain factor Terrain factor is obtained from DEM data. A spatial

resolution of 90m acquired by SRTM is used. Slope is calculated by using ArcGIS spatial analysis module.

Fig. 5. Fractional vegetation cover map

Fig. 6. Land degradation map

C. Make index weight The Analytic Hierarchy Process method [11] was selected

to determine the weight of each index. AHP is a usual method to decide the weight of different factors. Every two factors are compared, and the comparison result decides which factor is given more weight.

Three experts mark weight for every evaluation index in the above system by AHP respectively. The average of three index weight is used as the final weight. The result of index weight is shown in TABLE II.

TABLE II. WEIGHING EVERY INDEX

Name Expert 1 Expert 2 Expert 3 Average

land degradation 0.1418 0.0733 0.1164 0.11

population density 0.1016 0.1094 0.0683 0.09

slope 0.0728 0.0598 0.1336 0.09

landscape diversity 0.0944 0.077 0.0896 0.09

number of plaques 0.0944 0.1335 0.0942 0.11

Fractional Vegetation Cover 0.1556 0.1404 0.1716 0.16

vegetation type 0.1274 0.1208 0.1209 0.12

per capita area of vegetation 0.0851 0.0851 0.0866 0.0856

annual average income 0.1269 0.1269 0.1927 0.15

D. Calculate the ecological security index The weight of every ecological security factor was

calculated by AHP. At last, the ecological security index S is calculated through following formula [12].

1

m

i ii

S w f=

= ∑ (3)

In the formula, if and iw are value and weight of the thi factor.

IV. RESULTS AND DISCUSSION

A. Grading standards of ecological security degree Ecological security refers to the degree of qualitative

ecological security in the region, can be classified according to the comprehensive index, the grading standards as shown in the TABLE III [13].

B. Results The map of comprehensive index of ecological security in

Guyuan County is shown in Fig.7. According to TABLE III, the map of ecological security degree is given in Fig.8. The range of the ecological security index is 0.28~0.64. According to the grade standard of ecological security, the ecological security of most towns in Guyuan County is at the level of

"Warning", and some towns’ ecological security is down to "dangerous" level. Some towns such as Lianhuatan, Fengyuandian and Daerhao are in good ecological regions. However, Huanggaizhuo and Gaoshanbao are with poor ecological condition. Guyuan Ranch has the worst situation.

TABLE III. ECOLOGICAL SECURITY DEGREE [14]

Grades Comprehensive index

Ecological security degree

Description

Ⅰ 0~0.20 Serious danger

Ecological system is destroyed seriously. Service function is almost collapsed. Ecological disasters occurs frequently. Restoration is very difficult.

Ⅱ 0.21~0.40 Danger

Ecological system is destroyed. Service function is degradated. Ecological disasters occurs usually. Restoration is difficult.

Ⅲ 0.41~0.60 Warning Ecological disasters occurs occasionally. Restoration is difficult.

Ⅳ 0.61~0.80 Weak security

Service function is perfect. Ecological problem are not significant.

Ⅴ 0.81~1.00 Safety

Strong ability of regeneration,. Complete ecological system. Ecological problems are not obvious.

Fig. 7. The map of comprehensive index of ecological security

C. Discussion Special climatic conditions and geographic location

resulted in a fragile ecological environment in northern Guyuan County. Dry and windy in the spring and evaporation is great

in the summer. Because northern Guyuan is close to the Inner Mongolia Plateau, sand erosion is more serious. Natural disasters such as drought and dust exacerbate soil erosion and vegetation degradation.

Huanggaizhuo and Gaoshanbao are with poor ecological condition. One reason is that the population density is high and the per capita area of vegetation is low in Huanggaizhuo and Gaoshanbao. Another reason is that underdeveloped economy limit the improvement of ecological environment. This two reasons lead to the predatory exploitation and unreasonable use of ecological resources.

Guyuan Ranch has the worst ecological situation. There is seriously grassland degradation. Single vegetation type in pasture and unreasonable human activities are two main reasons. Overuse and lack of conservation accelerate grassland degradation.

Fig. 8. Ecological security degree map of Guyuan

D. Conclusion The ecological security of Guyuan County as the typical

farming-pastoral zone area in north China is evaluated in this paper. PSR and AHP are used to select index and determine index weight. TM remote sensing images, digital elevation data and statistical data are comprehensive utilized to calculate every evaluation index. The result showed that the situation of ecological security of Guyuan is not optimistic. There are three towns in “dangerous” level completely. This indicates that the ecosystem is destroyed seriously and the ecological restoration is needed.

For the promotion of regional development of farming-pastoral zone in north China, it has very important

significance to built a ecological security evaluation index system and establish an evaluation methods especially quantitative analysis tool. Remote sensing as an important data source supply many quantitative and qualitative basis for ecological evaluation. This will promote the development of quantitatively monitoring and evaluating methods.

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