Abstract: County-cultivated land can be evaluated to rapidly and accurately determine the quality background for the protection zone. In this study, the minimum data set was established to streamline the selection index using principal component analysis (PCA). A land evaluation and site assessment (LESA) system was then constructed to comprehensively evaluate the cultivated land quality. The regional distribution of cultivated land quality was finally obtained to divide the cultivated land protection zone. The results showed that: 1) The minimum data set of the natural quality index was composed of sand, organic matter, total potassium, available phosphorus, pH, soil comprehensive pollution index, topsoil texture, bulk density, and cation exchange capacity. The minimum data set of the site condition index was the drainage conditions, consecutive degree, ecological compatibility, river distance, road network density, irrigation capacity, farmland forest network rate, and cultivated land utilization type. 2) The LESA model was used to calculate the natural quality score of cultivated land and the site environment. The coupled cooperative model was used to determine the LESA system as FLESA=0.5FLE+0.5FSA. The comprehensive evaluation score of the sample point ranged from 51.517 to 81.838. The interpolation error test was carried out to combine each space interpolation. The ordinary Kriging method was also used for the spatial interpolation of cultivated land quality. The comprehensive score of cultivated land quality was 52.148 to 79.624 in the evaluation unit. 3) The overall distribution trend of cultivated land quality was "excellent in the center, but inferior in the east and west". The cultivated land resources in Tieling County were divided into five grades: The cultivated land area of Grade 1 was 22 294.396 hm2 (accounting for 20.52%), indicating the permanent protection area of basic cultivated land. The Grade 2 area was 39 974.407 hm2 (accounting for 36.79%), including the key control area in the natural fertility conditions of cultivated land. The Grade 3 and 4 areas were 25 649.334, and 13 837.926 hm2, respectively. Less diversity was found under the soil and site conditions of cultivated land in Grade 3 and 4 areas. The comprehensive improvement area of cultivated land then accounted for 36.33%. The Grade 5 area was 6 913.914 hm2 (accounting for 6.36%), indicating the ecological and natural conservation area of cultivated land. 4) The minimum data set of the indicator screening filter rate was 50%. The redundancy between the indicators was removed to significantly simplify the indicator for the key characteristics. A comparison was performed on the Nash effective coefficient and relative deviation coefficient. The evaluation value of cultivated land quality using MDS and LESA was closer to the benchmark, indicating a small deviation. The index system was simplified to quantify the synergistic relationship between natural quality and site conditions during quality evaluation. The finding can provide a strong reference to improve the quality, protection, and utilization of the county-cultivated land.