WANG Xiyi, XU Hailiang, PAN Cunde. Change Features of Cultivated Land Resources and Its Driving Factors in Tarim River Basin[J]. Bulletin of Soiland Water Conservation, 2017, 37(2): 327-332.
DOI:
WANG Xiyi, XU Hailiang, PAN Cunde. Change Features of Cultivated Land Resources and Its Driving Factors in Tarim River Basin[J]. Bulletin of Soiland Water Conservation, 2017, 37(2): 327-332. DOI: 10.13961/j.cnki.stbctb.2017.02.050.
Change Features of Cultivated Land Resources and Its Driving Factors in Tarim River Basin
[Objective] Dynamic change features of agricultural area and the driving factors were elucidate to provide theoretical foundation for the sustainable utilization and protection of cultivated land in Tarim River basin. [Methods] Change characteristics of agricultural area and superficial orthocenter were analyzed according to the statistical data of all regions
including so-called“nine sources and one main stream”. Both PCA and multivariate regression analysis were used to detect the driving factors. [Results] (1) Total cultivated area from 1.01×106 hm2 to 2.05×106 hm2
from 0.131 hm2 to 0.194 hm2 for each person. Orthocenter of the agricultural area moved northeastward with a distance about 61.10 km. (2) Three main factors as socioeconomic development
increase in population and development of agricultural production drove the changes of agricultural area. (3) The established multi-linear regression model (R2=0.960) between agricultural area and driving factors showed that there was no significant difference(p>0.05) between the simulated values and the actual values. [Conclusion] It was always in a dynamically changing status for agricultural area and orthocenter. Human factors were the major influencing cause of the cultivated land.
Thomas W, Karl H E, Niels B S, et al. Linking pattern and process in cultural landscapes:A nempirical study based on spatially explicit indicators[J]. Land Use Policy, 2004,21(3):289-306.
Carreno L, Frank F C, Viglizzo E F. Tradeoffs between economic and ecosystem services in Argentina during 50 years of land-use change[J]. Agriculture, Ecosystems & Environment, 2012,154(5):68-77.
Peng Errui, Wang Sui, Zhang Jiansheng, et al. Quantity and quality analysis of cultivated land in Shilin County[J]. Journal of Yunnan Agricultural University, 2010,25(4):551-555.
Asma T I. Use of MERIS data to detect the impact of flood inundation on land cover changes in the Lake Chad Basin[D]. Hong Kong:Hong Kong Polytechnic University, 2009.
Comber A, See L, Fritz S, et al. Using control data to determine the reliability of volunteered geographic information about land cover[J]. International Journal of Applied Earth Observation & Geoinformation, 2013,23(8):37-48.
Strengers B, Leemans R, Eickhout B, et al. The land-use projections and resulting emissions in the IPCC SRES scenarios scenarios as simulated by the IMAGE2.2 model[J]. Geojournal, 2004,61(4):381-393.
Gijsman A J, Oberson A, Tiessen H, et al. Limited applicability of the CENTURY model to highly weathered tropical soils[J]. Agronomy Journal, 1996,88(6):894-903.
Braud I, Tilmant F, Samie R, et al. Assessment of the SiSPAT SVAT model for irrigation estimation in South-East France[J]. Procedia Environmental Sciences, 2013,19(6):747-756.
Oku E, Aiyelari E O A. Green technology for keeping soil-water-nutrient fluxes on cultivated steep land and climate change mitigation.[J]. Journal of Agriculture & Environment for International Development, 2014,108(1):104-109.
Cao Yinggui, Cheng Ye, Fu Meichen, et al. Analyses on cultivated land population carrying capacity based on weighted Markov chain[J]. Chinese Journal of Soil Science, 2007,37(6):96-104.