PDF
Full
Outline
Land resource type is the basis for evaluating land suitability and development potential. The geomorphic pattern of "three mountains sandwiching two basins" and the significant landscape distribution characteristics of "mountain−oasis−desert" pose great challenges to the classification and utilization of land resources in Xinjiang. The paper aims to propose a grid−based fuzzy self−organizing feature maps (GF−SOFM) coupling classification method through the following steps: 1) A four−tier classification system was established based on dominant factors (climate+topography), stable factors (soil), relatively stable factors (vegetation), and dynamic factors (land use), comprising five factors with multiple indicators. 2) The study area was partitioned into 1 km×1 km grid units, where all indicators were spatially quantified. After fuzzy processing, the indicator data were input into SOFM model with dominant factors as control boundaries, enabling automated land resource type identification. 3) Area consistency test was conducted to compare the classification results of GF−SOFM method with those of the traditional thematic overlay method. The results indicate that Xinjiang was classified into 133 dominant factor types, 1906 stable factor types, 6054 relatively stable factor types, and 38493 dynamic factor types, achieving an average overall accuracy of 86%. The classification results of GF−SOFM method exhibited high spatial consistency with those of the traditional hierarchical overlay method, with 128 dominant factor types showing area consistency exceeding 92.35%. By refining topography classification and land use status, the GF−SOFM method effectively enables fine−scale land resource classification, accurately capturing the spatial patterns of climate−landform−soil−vegetation−land use. This approach serves as an ideal integrative classification method for physical geography, effectively indicating regional differentiation in ecological and geographical studies across varying climatic and landform regions. This research can provide a scientific basis for rational land development and utilization.
PDF
441
207
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
