Study On The Response Of Spatial Pattern For Land Use Change And Soil Salinization In Yinchuan Plain

Soil salinization is a significant inducement of soil resource damage,habitat destruction and agricultural unsustainability in arid and semi-arid regions.Quantitative analysis of the mutual feedback coupling relationship of the temporal and spatial distribution patterns between land use and soil salinization is of great significance for monitoring salinized soil and protecting the ecological security of the land.Based on GIS analytical method,take Yinchuan Plain as the investigated area,this paper used land use data,remote sensing image data,ASD hyperspectral data and soil salinity as well as analysis approaches such as transfer matrix,geo-informatic spectrum,standard deviation ellipse,hotspot analysis and density to obtain the evolution of land use quantity structure and characteristics of spatial pattern change in this area.Salinity inversion models,including RR(Ridge Regression,RR)and PLSR(Partial Least Square Regression,PLSR)are constructed.The measured hyperspectral data that adopted to match the Sentinel-2B image according to the spectral characteristic indices is to optimize the salinity inversion models.Then,soil salinization in Yinchuan Plain,Ningxia,China is quantitatively inverted and analyzed by using the optimal salinity inversion model.Finally,integrate geostatistics of semivariance function and gray correlation method to reveal the spatial correlation between land use and soil salinization,and realize the quantitative analysis of the two in space.The primary findings are as follows:(1)The dominant types of land use during the research period were cultivated land and unused land.The area of construction land and arable land aggrandized tremendously,and the grassland and unused land minished markedly,which were mainly reclaimed for arable land.The construction land was mainly turned into arable land.Forest land and water body were less transformed,but the area reduced overall during the time.As for the spatial differentiation characteristics,the spectrum unit was dominated by the conversion of water body to grasslands and arable land,mainly concentrated in Pingluo County,the foot of the Helan Mountains,and east of the Yellor River.Another great change of spectrum unit was the conversion of arable land to construction land,located mainly in Qingtongxia City and Litong District.The variation of land use types spatially demonstrated a centralized distribution trend from northeast to southwest,and the coverage gradually expands during the period.Cities alone the Yellow River are dominated by cultivated land,residential areas,and construction land.The rapid development of industry and agriculture economy has accelerated the transformation of land types and made them a hot spot and dense area for land use change.Helan Mountain Nature Reserve and Baijitan Nature Reserve,whose primary land use types were forest land and desert grassland,are the main cold spots area of land use in the Yinchuan Plain.(2)Spectral transformation can considerably emhance the sensitivity of soil salinity and spectral reflectivity.The characteristic spectral index can provide a theoretical and practical reference for the spectral matching and combination of remote sensing data at different scales,and contributes to the quantitative monitoring of salinization from the surface point to the spatial surface scale.The optimal hyperspectral transformation is[lg(R)]',and the characteristic bands are ?435,?500,?499,?498,? ?501.The B6,B7,B8 and B8a after 1/R transformation are multi-spectral characteristic bands.And after lg(R)transformation,Salinity index 3(S3),Intensity index 1(Int1),Intensity index 2(Int2)are the multi-spectral characteristic spectral indices,which can can realize the scale transition from measured hyperspectral cell to multispectral image pixel,efficiently improving the accuracy of the salinity inversion model of multispectral image.The PLSR model after spectral matching can perform the best accuracy(R2=0.721,RMSE=4.856g·kg-1)of soil salinity inversion,with a 0.311 increment of R2 and a 1.974 decrement of RMSE compared with the Sentinel-2B image modeling alone.The inverted salinity in the Yinchuan Plain is consistent with that from the field sampling,indicating that the model can be used to predict soil salinity in this area.(3)The spatio-temporal changes of land use in Yinchuan Plain are affected by the radiation driving effect of irrigation canal system,transportation facilities and urban settlement distribution pattern,showing a certain degree of agglomeration.From 1990 to 2019,the spatial distribution range of salinization in Yinchuan Plain was reduced overall,but the degree of local salinization tended to aggravate,and the spatial correlation between soil salinization and land use intensity changes was obvious.The worse the conditions such as irrigation and groundwater,the weaker intensity of land use change and the higher degree of land abandonment,the more serious the degree of soil salinization.Conversely,the more convenient the irrigation,drainage and transportation,the more closer to urban settlements and administrative centers,therefore,the rehabilitation activities become more stronger and the soil salinization changes become more frequent.The overall correlation between land use intensity and salinization intensity in the investigated area is 0.8332,which has a highlg local correlation with non-salinization and salinized soil.Agricultural land and water body are two main factors affecting the growth and changes of salinization in Yinchuan Plain.Non-salinization and light salinization are highly correlated with unused land,urban and village settlement land,while moderately salinized,severely salinized,and salinized soil are highly correlated with agricultural land and water body.