| Currently, Agricultural Land Evaluation places emphases on assessment of land productivity and land sustainable use, and is on its way to synthesis, multi-analysis, exactness, quantification and information. Cultivated land quality evaluation has become a basic work to insure food security, as Chinese food security draws more and more attention of both domestic and abroad people. Chinese land management is on the era of changing from paying attention to the quantity of land resource to paying equal attention to both of its quantity and its quality. To establish a cyber-means, multi-hierarchy, comparable trans-region, cultivated land grading system is the actual demands for sustainable land use management, such as dynamic equilibrium of gross arable land, prime farmland conservation, calculation of potential grain productivity of cultivated land. Agricultural Land Classification is a methodology, which applies crop potential productivity model, for evaluating land productivity. The model is theoretically based on crop productivity principle, production factor theory and land rent theory, and by attenuating Photo-Thermal or Climatic Productivity Index step by step, it calculates physical quality grade index, use grade Index and economic Grade Index. This paper, assimilating experts' thoughts and production, focusing on poor trans-region comparability of Grading Index as mechanically applying methods of Regulation of Agricultural Land Classification, taking Chongqing as a case, suggests method of module-control and checking method of independent data of crop yield with unified conversion coefficient of standard yield, so as to realize the comparability goal of Grading Index of trans-region & trans-crop-system. Taking Cultivated Land updated to end of 2003 in 39 counties in Chongqing as the evaluated object, using Physical Quality Grade & use Grade Index models, with the help of GIS technology, this paper builds up the cultivated land quality grading system in Chongqing, which includes parameter determination, basic data operation in model and macroscopical & microcosmic checking, as well as grade grain productivity determination. After that, the cultivated land quality spatial distributing orderliness in Chongqing is discovered, by the study of classifying counties and dividing zones on cultivated land, analyzing interrelationship between cultivated land distributing and physical factors distributing, and economic factors distributing. From the angle of relationship between natural resources and economics, this paper tries to introduce method of spatial autocorrelation analysis, combining with the correlation analysis in common use, and discovers quantificationally the spatial coupling relationship between cultivated land and economic factors in Chongqing. Study results as follow: 1 Building up of Cultivated Land Quality Evaluation Model in ChongqingAfter zones divided for Classification, Photo-Thermal & Climatic Productivity Index were calculated and obtained. According to physiognomy, Chongqing was divided into 4 factor index zones. Then based on crop ecological Suitability and regional environmental index, Chongqing was divided into 2 standard farming system zones, designed crops of which were determined as middle rice, winter wheat, maize, sweet potato, rape, benchmark of which was determined as rice. Surveyed planting & harvest time of designed crops under different altitude of 39 counties were referred to office of Agricultural Land Classification of the Ministry of Land and Resources P.R.C to calculate Photo-Thermal & Climatic Productivity Index, which were verified and validated on the spot.Max. Physical Quality Grade Index model Rimax=∑αij,·βj , which was separated from Physical Quality Grade Index model, as a key of module-control, was analyzed theoretically and practically, and was ameliorated in arithmetic.①The arithmetic ofβcoefficient is conditional, i. e. when crops ecologic factors are similar and whole growing stages of 2 crops are basically equal, Photo-Thermal Productivity Index in Chongqing provided by the State have deflection practically, and whole growing stages of 2 crops superpose partly differently between standard farming systems including 2 crops, which cause Max. Physical Quality Grade Index deflection among factor index zones and among paddy field & dry land.②An ameliorated model Rimax=∑αij·βj·γj was suggested. Based upon the essence thatβis of a convertion coefficient of theoretical standard grain yield, the arithmetic ofβwas converted from yield ratio into energy ratio of crops, to take the same energy to standardize crop yield. And based upon the principle that the same climate, the equal sum of Photo-Thermal Productivity Index in the rough, Harmonizing Photo-Thermal Productivity Coefficientγwas introduced. The arithmetic ofγadopted yield potential ratio method and reference frame method, so as to adjust deflection of Photo-Thermal Productivity Index of crops among factor index zones and among standard farming systems in the same climatic region.③By the ameliorated model,βandγof five designed crops in Chongqing were determined,βof rice, winter wheat, maize, sweet potato, rape are respectively 1.00,0.99, 1.04,0.23,1.66, andγof them are respectively 1.00,1.11,0.90,0.86,1.05. Secondly, as a compare system, by the method of regulations of Farmland classification,βCoefficients of five designed crops of 4 factor index zones were determined respectively. Thirdly, calculated in both methods were mean sums of Photo-Thermal Productivity Index of paddy field & dry land and sums of Climatic Productivity Index of dry land of 4 factor index zones. Results show that, the ameliorated arithmetic is superior to that of regulation, succeeds in making comparable Max. Physical Quality Grade Index of paddy field & dry land of 4 factor index zones in Chongqing, and organically integrates the contribution of each Photo-Thermal Productivity to Farmland quality in different regions, which validated the ameliorated model.While evaluated units of cultivated land were plotted, physical attribute data of which were drawn and Parameters of Physical Quality Cent, of Use Coefficient were determined, Physical Quality Grade Index Model and Use Model were built up.①Evaluated units which are minimal evaluated plots of cultivated land, were plotted by way of superposing scale of 1:50,000-1:100,000 present land use map and map of slope of county under MapGIS circumstance. Citywide evaluated units are 142319 and total acreage of cultivated land was 2347627.48 hm2. Of physical attribute data of evaluated units, physiognomy factors were drawn from scale of 1:50,000-1:100,000 Digital Elevation Model and map of slope, soil factors were drawn from data of the second soil general survey and of supplementary survey.②Based on sample survey of farming systems and crop yield in five trial counties, eight participant evaluating factors of physiognomy & soil of four factor index zones were determined, which were graded in 3-6 levels respectively, evaluated in 0-100-cent close interzone respectively, and given different weights respectively. Then by all-around harmony, united and determined was citywide factor-grading-value table, reserved were difference of weights of factors among four factor index zones, so improved were comparability of Physical Quality Cent among factor index zones.③Based on survey data of samples of each administrative village, the appointed crop of highest yield in every factor index zones were determined, and calculated were Use Coefficient of each administrative village. Physical Quality Grade Index Model was built up through attenuating Max Physical Quality Grade Index by Physical Quality Cent, and Use Grade Index Model was built up through attenuating Physical Quality Grade Index by Use Coefficient. Both Physical Quality Grade Index and Use Grade Index were partitioned into 12 grades by 100-cent equidistant method. While evaluation production maps of county were processed by synthetical Cartography, Evaluation production maps of scale of 1:500,000 of Chongqing andcorresponding spatial connection of unit data between different scales were built up. 2 Macro-check of Cultivated Land Quality Evaluation Production in ChongqingPreliminary analyses of Evaluation Results show that to grade area distributing of both Physical Quality Grade and Use Grade citywide, most area proportion is grade 7, and it is degressive by and large from grade 7 to grade 12 or to grade 1 in turn. The most area proportion warp of the same grade of both type grades is 2.16 cent percent (grade 12). From Physical Quality Grade to Use Grade, area proportion of Grade 5-8 increases, that of Grade 1-4 decreases a little and that of Grade 9-12 decreases a little more. Both type grades citywide show itself in normal distribution, total warp of which is on the small side. Analysis of check models between grain yield per unit of sown area of counties of 2004-2005 and mean grades of counties shows:①Linear correlative coefficients of Physical Quality Grade and Use Grade are -0.83 and -0.87 respectively, which show remarkable high correlative levels. (2) Because rationality of Use Grade of 25 counties is more than that of their Physical Quality Grade, rationality of Physical Quality Grade of 14 counties are more than that of their Use Grade, Prior Selected Grade of counties were determined (25 counties of Use Grade, 14 counties of Physical Quality Grade), Linear correlative coefficient of grain yield per unit with Prior Selected Grade of counties is -0.92. (3) It is suggested to introduce amendatory coefficient to amend Use Grade Index of units of 14 counties, whose Prior Selected Grade is Physical Quality Grade. The study indicates: from the view of Macro-check of county, both Physical Quality Grade and Use Grade have been provided with rationality and comparability trans-region, rationality of Use Grade is more than that of Physical Quality Grade, and rationality of Prior Selected Grade is more than that of Use Grade.3 Determination of grain productivity of cultivated land grade in ChongqingCompare analyses of evaluation results in representative counties show: Under softer hypsography area in Chongqing, Dazu and Liangping take middle & classy grades as the dominant factors; Pengshui which is under lowest sunshine and steeper hypsography area in Chongqing, is short of grade 1, and takes grade 8 as the dominant factor; Wuxi which is under highest sunshine and steepest hypsography area in Chongqing, owns whole 12 grades, and takes grade 11-12 of Physical Quality Grade and grade 9 of Use Grade as the dominant factors. There are different grade characteristics at different position of physiognomy which developed different types of soil under counties.Results of sample surveyed of representative counties show:①Crop yield of 836 units were surveyed and obtained, which distributed in different cultivated land types and diverse cultivated land quality grades, typically and precisely.②Of grain yield all-year of paddy field, of grade 1, is 11625 kg/hm2 around, and of the lowest grade, which is grade 8, is 6750 kg/hm2 around.③Of grain yield all-year of dry land, of the highest grade, which is grade 3 in Dazu & Liangping, is 10275 kg/hm2 around, which is grade 2 in Wuxi or grade 4 in Pengshui, is higher or lower than that of Dazu & Liangping, and of the lowest grade, which is grade 12, is 3825 kg/hm2 around.Analyses of relation models between all-year grain yield & Use Grade Index Model show:①there are much remarkable Linear correlation between grain yield and Use Grade Index in Chongqing, and the differences of grain productivity of the same grade among 4 representative counties and whole city, among paddy field and dry land, are lower than the differences of grain productivity between two grades border upon, which meant high grade comparability. So from the view of Micro-check of units, evaluation results are of reliability and comparability trans-region & trans-farming-system.②Parameters of grade grain productivity in Chongqing were determined as follow: Grain productivity of grade 1 is 11699kg/hm2, that of grade 12 is 4006kg/hm2, average differences of grain productivity between two grades border upon is 699kg/hm2, most convertion coefficient is 2.92, grain productivity coefficient of grade 12 is 0.34, and average differences of grain productivity coefficient between two grades border upon is 0.06. Mean grain productivity coefficient citywide is 0.682, and mean grain productivity per unit is 7974 kg/hm2.4 Classifying counties and partitioning zones on cultivated land qualityBased on Physical Quality Grade, Use Grade and Prior Selected Grade of counties respectively, 39 counties in Chongqing were classified into three clusters through clustering analysis. Take Prior Selected Grade as a case, there are 11 Counties of No.1 cluster of higher cultivated land quality, area of grades 1-6 of which account for biggish proportion; There are 16 Counties of No.2 cluster of middle cultivated land quality, area of grades 2-9 of which account for biggish proportion; There are 12 Counties of No.3 cluster of lower cultivated land quality, area of grades 6-11 of which account for biggish proportion.Based on Prior Selected Grade of counties, spatial autocorrelation analysis shows: There are remarkable positive spatial autocorrelation among cultivated land quality of counties, that is to say, there is a characteristic that counties of similar cultivated land quality centralize in space notablely. Counties of positive local spatial autocorrelation account for 87% out of 39 counties. There are 21 counties of strong HH type, 13 counties of weak LL type, 5 counties of transitional HL type or LH type. There is a biggish corresponding nexus between counties of HH, HL & LH types and Counties of No.1 & No.2 clusters.Based on Priority Grade, five cultivated land quality zones were partitioned in Chongqing, which are west higher quality cultivated land zone, urban moderate & higher quality cultivated land zone, middle-south moderate quality cultivated land zone, south-east lower quality cultivated land zone and north-east lower quality cultivated land zone. The spatial pattern of cultivated land quality in Chongqing presents the characteristics that cultivated land quality decreases from west to east, then to south-east & to north-east, and counties of similar cultivated land quality centralize in spatial.5 Relationship analyses of cultivated land quality distributing and physical factors in ChongqingEffect analyses of climate, physiognomy and soil on cultivated land quality distributing adopted superposition analyses of Photo-Thermal & maps of physical factors, with Climatic Productivity Index distributing, maps of cultivated land quality distributing in Chongqing, Classifying counties and partitioning zones on cultivated land quality in Chongqing. Effect analyses of landscape factors on cultivated land quality distributing adopted correlative analysis.Effect analyses of climate on cultivated land quality distributing indicate:①there is under highest sunshine on north-east area in Chongqing, where is also with highest Photo-Thermal & Climatic Productivity Index, and there is under lowest sunshine on south-east area in Chongqing, where is with lowest Photo-Thermal & Climatic Productivity Index, which means sunshine effects on Photo-Thermal & Climatic Productivity Index evidently.②Year-mean air temperature of county weather station effects little on distribution of Photo-Thermal & Climatic Productivity Index.③Precipitation makes impact on Climatic Productivity Index by effecting on water-affected function. there is lowest precipitation in western of west area in Chongqing, where is with lowest water-affected functions; there is secondly lower Precipitation in part of north-east area in Chongqing, where is with lower water-affected functions; and there is highest Precipitation in southern of south-east area in Chongqing, where is with highest water-affected functions. However, regional difference of water-affected function is on the small side.Effect analyses of physiognomy and soil on cultivated land quality distributing indicate: In the region of Yangtze valley east to Wanzhou, along with its north area about, hypsography and slope are soft, soil takes purple soil & paddy soil as the dominant factors, high quality cultivated land of grades 1-4 presents itself under higher frequency, and No.1& No.2 clusters counties and HH, HL & LH counties centralize spatially. South or east of that line, hypsography and slope get steep, soil takes calcareous soil, yellow soil & yellow brown soil as the dominant factors, high quality cultivated land of grades 1-4 presents itself under much lower frequency, and No.3 cluster counties and LL counties centralize spatially. There is a spatial coupling relationship between physiognomy and soil in Chongqing, which causes decisive effect on cultivated land quality distributing.Effect analyses of cultivated land quality distributing with cultivated land quantity & structure distributing indicate: There is a positive logarithmic correlativity between cultivated land quality and cultivated land proportion of total area of counties, with R2 = 0.6252, there is a positive linear correlation between cultivated land quality and paddy field proportion of cultivated land of counties, with R2 = 0.7431, and there is a negative linear correlation between cultivated land quality and dry land proportion of cultivated land of counties, with R2 = 0.8463, which means there are notable or very notable coupling relationships between distributing of cultivated land quality and cultivated land quantity & structure. 6 Coupling relationship analyses of cultivated land quality and economics in ChongqingPrior Selected Grade and four economic indexes were selected to analyze the Coupling relationship. Economic indexes include grain yield per unit of sown area, farming production value per unit of cultivated land, net income per capita of country inhabitants, GDP per capita of 2004-2005 Stat. data of 39 counties.Using Moran's I index, spatial autocorrelation analysis shows: There are clear globe positive spatial autocorrelations of cultivated land quality and economy, that is to say, counties of similar characteristics centralize in space notablely. There are a world of consistency between local spatial autocorrelations of cultivated land quality and that of economy. Because More than 90% out of HH type counties of four economic indexes distribute into 21 HH type counties of cultivated land quality, and in all LL type counties of cultivated land quality which are 13, there are 13 LL type counties of three economic index, 12 LL type counties of one economic index. That means there are marked spatial coupling relationships between cultivated land quality and economy. Divisional correlative analysis between cultivated land quality and economic index shows: There are notable positive correlations between distributing of cultivated land quality and economy of counties in non-urban region, and there are lower positive correlations in urban region than that of non-urban region. Correlative coefficients of four indexes of whole city and non-urban region, three index of urban region, are more than min. correlative coefficients, except for net income per capita of country inhabitants of urban region. From non-urban region, to whole city, to urban region, correlativity is from big to small in turn. In non-urban region and whole city, correlativity are from big to small in turn, from grain yield per unit of sown area, to net income per capita of country inhabitants, to GDP per capita, to farming production value per unit of cultivated land. That means there are marked spatial coupling relationships between cultivated land quality and economy in Chongqing city, especially in non-urban region.
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