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| 天山北坡中段山区植被覆盖管理措施因子的时空格局动态变化 |
| Temporal and spatial pattern dynamic variations of vegetation cover and management factors in the middle of the northern slope of Tianshan Mountains |
| 投稿时间：2021-05-17 |
| DOI：10.13254/j.jare.2021.0315 |
| 中文关键词: 植被覆盖管理措施因子，天山北坡，LSMM模型，像元二分模型，ESTARFM模型，时空格局，土地利用类型 |
| 英文关键词: vegetation cover and management factor, the northern slope of Tianshan Mountains, LSMM model, Pixel Binary model, ESTARFM model, temporal and spatial pattern, land use type |
| 基金项目:新疆维吾尔自治区财政专项（213031002） |
| 作者 | 单位 | E-mail | | 常梦迪 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | | | 王新军 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | wxj8112@163.com | | 闫立男 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | | | 马克 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | | | 李永康 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | | | 李菊艳 | 新疆维吾尔自治区水土保持生态环境监测总站, 乌鲁木齐 830011 | | | 贾宏涛 | 新疆农业大学草业与环境科学学院, 乌鲁木齐 830052
新疆土壤与植物生态过程重点实验室, 乌鲁木齐 830052 | |
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| 中文摘要: |
| 植被覆盖管理措施因子（Vegetation cover and management factor，以下简称C因子）是评估植被因素抵抗土壤侵蚀的能力及准确估算土壤侵蚀模数的重要参数，而区域尺度C因子高质量时间序列的准确估算和空间特征对于土壤侵蚀预测、水土保持规划尤为重要。为研究天山北坡中段山区C因子时空动态，采用线性光谱混合模型（Linear Spectral Mixture Model，LSMM）、像元二分模型、增强型自适应反射率时空融合模型（Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model，ESTARFM）等方法计算C因子，定量分析2000—2018年研究区C因子的时空格局特征，并对不同土地利用类型的C因子进行分析。结果表明，时间上，2000—2018年C因子总体呈现先上升后下降的趋势，不同时段C因子值不同，表现为秋季>春季>夏季、旱季>雨季。空间上，南部高山区（海拔>3 000 m）的C因子值较高，北部中低山丘陵区（2 000 m<海拔<3 000 m）的C因子值较低。C因子值的分布与土地利用类型关系密切，表现为裸土地>其他林地>采矿用地>内陆滩涂>其他草地>农村宅基地>灌木林地>旱地>天然牧草地>风景名胜设施用地>水浇地>人工牧草地>乔木林地。本研究探究C因子遥感定量估算方法，分析不同土地利用格局对C因子的影响，为开展大尺度C因子的准确估算及不同土地利用格局水土保持效益的综合评价提供了参考。 |
| 英文摘要: |
| Vegetation cover and management factor(hereinafter referred to as C factor) is an important parameter when evaluating the ability of vegetation factors to resist soil erosion and accurately estimate the modulus of soil erosion. The accurate estimation and spatial characteristics of high-quality time series of C factor at the regional scale are particularly important in predicting soil erosion and planning of soil and water conservation. Taking the middle of the northern slope of Tianshan Mountains as an example, this study used the Linear Spectral Mixture Model(LSMM), Pixel Binary Model, and the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to calculate the C factor, quantitatively analyze the spatial and temporal pattern characteristics of C factor in the study area from 2000 to 2018, and study the C factors of different land use types. The results showed that, from 2000 to 2018, C factor generally showed a trend of first increasing and then decreasing. The value of C factor was different in different periods, showing a trend of autumn> spring>summer, dry season>rainy season. Spatially, the value of the C factor was higher in the southern high mountain area(above sea level > 3 000 m), and lower in the north, middle, and low mountain and hilly area(2 000 m < above sea level < 3 000 m). The distribution of C factor was closely related to land use types, in the order of bare land > other forest land > mining land > inland tidal flat > other grassland > rural homestead > shrub land > dry land > natural pasture land > scenic facilities land > irrigated land > artificial pasture land > arbor forest land. This study explored the quantitative estimation method of C factor by remote sensing and analyzes the influence of different land use patterns on C factor, in order to provide a reference for the further accurate estimation of large-scale C factor and comprehensive evaluation of soil and water conservation benefits of different land use patterns. |
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