[目的] 分析不同土地利用方式黄土高原植被的覆盖状况，为监测该区植被特别是非绿色植被盖度的变化提供数据支持，为遥感估算植被覆盖度(FVC)在土壤侵蚀预测中的应用提供可靠依据。[方法] 选择黄土高原不同土地利用类型的7块植被样地，采用样带法进行逐半月的分层植被盖度调查，分析了绿色植被盖度(fPV)和非绿色植被盖度(fNPV)在不同类型以及不同层次结构下的年内变化，为侵蚀过程模型中植被因素的获取提供参数。[结果] ①沙地、草地、人工柠条林地、人工油松林地、黄陵和秦岭的天然林地等6个样地中，植被的年内投影总盖度变化不大。投影fPV和其所占投影总盖度的比例年内均随时间先逐渐增加，7—9月达到最大值，其后迅速减小。而投影fNPV随时间的变化趋势与fPV相反。受耕作制度影响，耕地投影fPV和fNPV年内变化剧烈。②7—9月，在黄陵和秦岭的天然林样地，投影fPV比例可达100%，其他4种样地分别可达60.6%，70.5%，58.8%和84.9%，意味着仅考虑投影fPV，将忽略占总盖度39.4%，29.5%，41.2%和15.1%的fNPV的生态效益。③人工柠条、人工油松林地，黄陵、秦岭的天然林地等4种具有明显植被垂直结构的样地中，乔木层、灌木层和地表层的fPV与fNPV的年内变化与投影fPV与fNPV的变化趋势基本一致；4种样地植被的投影总盖度与地表层总盖度呈线性关系，其相关性可达0.85(R2)。[结论] 黄土高原不同土地利用方式耕地投影fPV和fNPV年内变化剧烈，其他样地年内投影fPV先增加后减小，投影fNPV与其相反。占总投影盖度的15.1%～41.2%的投影fNPV，在该区是不可忽略的地被组成。不同层次的fPV和fNPV年内变化趋势与投影fPV和fNPV一致，地表层总盖度与投影总盖度也存在显著的线性相关性。在区域监测时应重点关注耕地植被盖度的提取季节与地表总盖度。
[Objective] The vegetation cover of the Loess Plateau under different land uses was analyzed in order to provide data support for monitoring the changes of vegetation cover in the region, especially non-photosynthetic (fNPV) vegetation cover, and provide a reliable basis for the application of remote sensing estimation of vegetation cover in soil erosion prediction. [Methods] Seven vegetation sample plots under different land use types on the Loess Plateau were selected. A stratified vegetation cover survey was carried out at half-month intervals by the sample band method. Then the intra-annual changes of fPV (photosynthetic vegetation) and fNPV for different vegetation types and layers were analyzed, thereby providing data support for acquiring vegetation factors for an erosion process model. [Results] ① The total projected cover of the six communities (i.e., sand land, grassland, artificial Caragana korshinskii forest, artificial Pinus tabuliformis. forest, and two natural forests at Huangling and Qinling area) did not vary significantly during the year. Both the projected fPV and its proportion to total projected cover increased gradually over time and reached maximum values in July to September, and then decreased rapidly after September. However, the projected fNPV showed the opposite change over time than observed for projected fPV. The projected fPV and fNPV of agricultural land varied dramatically within a year because of the influence of tillage factors. ② During July to September, the proportion of projected fPV was up to 100% in Huangling and Qinling natural forests, and 60.6%, 70.5%, 58.8%, and 84.9% in the other four species, respectively. This means that only considering the projected fPV would ignore the ecological benefits of the fNPV that account for 39.4%, 29.5%, 41.2%, and 15.1% of the total cover. ③ In the vegetation types with obvious vertical structure, such as artificial C. korshinskii forest, P. tabuliformis forest, and the two natural forests in Huangling and Qinling area, the intra-annual changes of fPV and fNPV in the tree layer, bush layer, and surface layer were generally consistent with the trend of the projected fPV and fNPV, respectively. The projected total cover of the four plots was positively related to the total cover of the surface layer (R2 values up to 0.85). [Conclusion] The projection fPV and fNPV of agricultural land with different land use in Loess Plateau varied dramatically within the year, while the projection fPV increased and then decreased in other sample sites within the year, and the projection fNPV was the opposite of them. The projected fNPV, which accounted for 15.1% to 41.2% of the projected total cover, was a non-negligible ground cover component in the area. The intra-annual trends of fPV and fNPV at different layer were consistent with the projected fPV and fNPV, and there was also a significant linear correlation between the total surface cover and the projected total cover. The extraction season of FVC of agricultural land and total surface cover should be focused on during regional monitoring.