Nature Environment and Pollution Technology ISSN: 0972-6268 Vol. 11 No. 4 pp. 625-630 2012 An International Quarterly Scientific Journal Original Research Paper Effects of Land Use on Ecosystem Service Function of the Songhua River basin in Harbin Region Fengwen Gong, Wenyi Fan* and Li Yuan** College of Hydraulic and Electrical Engineering, Heilongjiang University, Harbin 150086, China *College of Forestry, Northeast Forestry University, Harbin 150040, China **College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China ABSTRACT Nat. Env. & Poll. Tech. Website: www.neptjournal.com Rapid land use pattern change has taken place in Songhua River basin of old industry base in northeast Received: 22-8-2012 region of China over the past decades in Harbin region. In this paper, changes in land use pattern in this Accepted: 22-9-2012 region were analysed by using Landsat TM data in 1989 and 2007, to quantitatively explore the spatio- temporal LUCC (land use and cover change) characteristics, and based on this information, the regional Key Words: ecosystem service value was estimated. Cropland and unused land decreased, while built-up land increased Songhua river basin greatly. The greatest change rate occurred in water bodies but the least occurred in cropland. The ecosystem Urbanization service value increased 4.8496×108 yuan, with increasing range of 8.3285%, cropland turned into forestland Land use pattern change occurred the greatest positive contribution rate, accounted for 18.9437%, while forestland turned into cropland Ecosystem service value occurred the greatest negative contribution rate, accounted for 10.2426%. The increase of built-up land Contribution rate impacted the ecosystem service value and ecological environment negatively, and the increase of forestland and water body and the decrease of unused land improved the ecological environment and its ecosystem service values. Those improving the ecological environment were from other types of land use to forestland and water body, however, those worsening the ecological environment were from forest and grassland to cropland and built-up land. INTRODUCTION et al. 1997). Therefore, the quantitative evaluation of eco- system service value has become the new focus and forward Urbanization process is one of the current new hot researches region of international ecology and ecological economics with the urbanization expansion, because human activities (Costanza et al. 1998, Wang et al. 2006). Moreover, reveal- not only expanded their own survival space and at the same ing the urbanization’s impacts on the mechanism and rule of time significantly changed the land use statues and proper- ecosystem services has become a hot research of international ties, but also disturbed land use pattern components, made scientists (Min et al. 2006, Marina 2010, Grimm et al. 2000, great impacts on regional environment during land use and Pickett et al. 2001). Studying the LUCC associated with re- cover changes (LUCC) process (Yu et al. 2011) and then gional ecosystem service value and its change might pro- initiated many natural phenomenon and changes of ecologi- vide the important significance to study the eco-environment cal process. This process especially resulted in significant change, keep the ecosystem in balance and coordinate the environmental consequences, such as forest degradation, development between regional economics and environment. sedimentation, air, water and noise pollution, increasing in energy consumption, decreased infiltration and an increase The economic reform since 1978 have made China take in surface run-off, destruction of wildlife habitat, and re- part in the increased globalization with the rapid development duction in biodiversity (Ronald & Yuji 2011, Braimoh & of China economy and acceleration of the urbanization. Many Onishi 2007, Fu et al. 1998, Song et al. 1995, Urner et al. of the cities in China are now growing more than million 1995). Eventually, those phenomena not only greatly lashed peoples, where a large intergradation zone is the rural-urban the structure, function and spatial evolution of regional eco- zone (Addo 2010). This has resulted in making land cross- system (Serafy 1998, Wang et al. 2006), but also seriously fusion of urban and rural, accelerating the mutual penetration, affected ecosystem service value ability for human being, and then leading to the obviously contradiction in land use, while the ecosystem service can directly or indirectly offer confusion in spatial layout and fragility in eco-environment. the products in life and service through the structure, proc- It not only hindered urban construction, and at the same time ess and function of ecosystem, meanwhile, these products but affected rural development. Hence, conducting the study and services are necessities of human survival and warrants on the LUCC in large city is helpful to understand spatial of human lives quality (Sutton & Costanza 2002, Costanza change characteristics and temporal evolution process of 626 Fengwen Gong et al. LUCC. Base on this, quantitatively estimating the ecosystem generated and stored in grid form after building spatial to- services values of land use and cover change could make pology, the 6 classes of land use cover were obtained: urbanization spatial pattern control the ecosystem’s dynamics cropland, forestland, grassland, water bodies, built-up land (Liu et al. 2007, Alberti et al. 2007). and unused land. The accuracy assessment was tested by Harbin city, as the important old industrial city and im- monitored samples from GPS survey. portant grain production bases in China (Li et al. 2010), lo- Land use transition in contribution rate: In this paper, cated in middle reach of Songhua river, is the rapid urbani- Markov transition matrix for 18 years of time interval was zation city of northeast region. In this paper, we use the land obtained using land cover database in 1989 and 2007 though use map in 1989 and 2007 extracted from the Landsat TM MARKOV module in IDRISI software, which could quan- images to detect the LUCC changes and analyse the spatio- titatively describe the changes between different two peri- temporal pattern of urban expansion and to quantitatively ods of land use covers (Sang et al. 2011). Then, land use analyse ecosystem value, and then to provide reference on transition contribution rate was generated to reveal mutual maintaining the structure and function of regional ecosys- transition process and law between the different types (Zeng tem and keep ecological city construction and optimize land et al. 2003), and to reflect the important differences in cer- resources allocating. Thus, it will be helpful to control soil tain types transition processes during the whole dynamic and water loss, maintain the ecological security, plan land transition change process in certain extent, which was cal- use and adjust the regional economic structure. culated as follows: MATERIALS AND METHODS Ait - Ajt Tijt = ´100% ...(1) DA Study region: Harbin city, as the important industrial city å ijt with largest area and the second greatest population in prov- Where, i and j represent the land use types in different ince level of China, extend from 44°042 to 46°402 latitude periods, t represents the whole transition time from starting and 125°422 to 130°102 longitude, covering area about 7000 period to monitoring period, km2. The northern, eastern and southern region of this study area is higher, extended to western region as new moon shape. Ait - Ajt The elevation ranges from 84 to 886m. The average tempera- represents the transition area from types to j types, ture is 3.5°C and annual average frost-free period is 135d. i DA Annual precipitation is 545.7mm. Meanwhile, there are many å ijt represents the total transition area during studying pe- riods, and T represents the transition contribution rate. rivers belonging to Songhua river hydrographic net, such as ijt Songhua river, Hulan river and Ashi river etc., obviously, those Ecosystem estimate methods: The value coefficient pro- conditions are very suitable for agricultural development. posed by Costanza has been widely applied to estimate the Image process and interpretation: Before being classified ecosystem service value (Costanza et al. 1998). However, the Landsat TM image, the first processing works included there is a larger deviation in some data during the studying geometric, radiometric correction and image enhancement. process. Its estimation of cropland is too low while of wetland The geometric correction of Landsat TM image in 2007 was is relatively higher. According to the Chinese present situa- carried out in ERDAS IMAGINE 9.2 software by using tion, referring to the Costanza’s research, made the China’s ground controls (GCPs) selected from the topographic map terrestrial ecosystem service value in unit area (Table 1) (Xiao at the scale of 1:50000. The resultant root mean square er- et al. 2003, Xie et al. 2003, Xie et al. 2005). Taking into rors was generally less than 0.5 pixel, and then false colour account the current facts and associating with the ESV for- composites were generated from bands 5, 4 and 3 as red, mula of Costanza, the ecosystem service value was adopted green and blue, respectively, followed by using the corrected to estimate the regional ecosystem services. The formula of image as the geo-referenced image to finish the registration ESV is as follows: of TM image in 1989 through image-to-image. The image ESV = å Ak ´ VC k ...(2) enhancement was performed for better visual of land use fea- ESV = A ´VC ture and texture after masking the images, according to the f å k fk ...(3) land use classification system by National Land Authority Where, the ESV is the ecosystem services value (RMB), and the present situation and distribution characteristics of 2 Ak represents area of the k types of land use (hm ), VCk is the land use types. The images were classified using Maximum 2 value coefficient of ecosystem service (RMB/hm ·a), ESVf Likelihood of supervised classification method in ERDAS is the single ecosystem service value (RMB) and VCfk is its 9.2 (Leica Geosystems 2009).