Ziyuan Kexue (Jun 2023)

Optimization of pricing system for the inventory of grassland resource assets based on intelligent zoning

  • ZHANG Zheyue, CHEN Yiyun, ZHENG Min, WANG Jiaxue, QIAO Zhanming, ZHANG Shuangyin, XIN Yuchun, ZHAO Xia

DOI
https://doi.org/10.18402/resci.2023.06.02
Journal volume & issue
Vol. 45, no. 6
pp. 1107 – 1122

Abstract

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[Objective] In the context of the inventory of state-owned natural resource assets, we aimed to explore the optimization path of the grassland resource assets inventory pricing system from various aspects, such as the division of homogeneous areas, the indicator system of the inventory price and the price correction system, and finally to construct an optimization framework for the pricing system and verify its scientific value and applicability. [Methods] Indicators such as grassland type, grassland area, hay yield, and grassland grade were selected based on 21 attribute fields of 196892 polygons from the natural grassland resources inventory in Qinghai Province, and the regionalization of provincial grassland homogeneous areas in Qinghai Province were performed based on the regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) method. Using the principle of pricing by grade and by type, grassland grade adjustment coefficients and grassland type-specific prices were introduced to form a set of multi-level and top-down “national homogeneous areas-provincial homogeneous areas-townships” grassland resource assets pricing system. [Results] The four national grassland homogeneous areas in Qinghai Province were refined into 23 provincial grassland homogeneous areas, the number of subareas was reasonable and the characteristics of grassland resources of different subareas were significantly different. The grassland prices at the township scale were between the 30% upper and lower bounds of the grassland prices of the national homogeneous areas. [Conclusion] An optimization framework for the inventory pricing system of grassland resource assets driven by the knowledge of natural resource assets and with an intelligent regionalization algorithm as the core is proposed in this study, which can not only support the construction of the technical system, but also aid the value assessment work for the inventory of natural resource assets.

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