Climatic warming affects the crop growth and its related vegetation indices. In order to understand the initial response of normalized difference vegetation index (NDVI), normalized green difference vegetation index (GNDVI) and soil adjusted vegetation index (SAVI) to climatic warming, a field warming experiment using infrared radiator was conducted in a highland barley located at the Dazi county of the Tibet since late May, 2015. There were three warming treatments, i.e., control, low (1000 W) and high (2000W) warming. The NDVI, GNDVI and SAVI were obtained using an agricultural digital camera during the period from June to September in 2015. Meanwhile, the soil temperature and soil moisture at depths of 5 cm and 20 cm were also obtained using HOBO microclimate observing systems. Then this study analyzed the response of NDVI, GNDVI and SAVI to infrared warming and the relationships between the three vegetation indices and soil temperature and moisture. The 1000 W and 2000 W infrared warming increased soil temperature at the depth of 5 cm (t5) by 1.62℃ and 1.77℃, and soil temperature at the depth of 20 cm (t20) by 1.16℃and 1.43℃, but decreased soil moisture at the depth of 5 cm (SM5) by 1.8% and 14.1%, and soil moisture at the depth of 20 cm (SM20) by 21.6% and 14.7%, respectively. The 1000 W infrared warming increased NDVI by 2.4%, GNDVI by 4.3% and SAVI by 0.5%, whereas the 2000 W infrared warming increased NDVI by 5.5%, GNDVI by 5.3% and SAVI by 4.8%, although these changes were non-significant. Simple regression analyses showed that (1) NDVI (r2=0.110,P=0.026) and GNDVI(r2=0.254, P=0.0004)decreased with increasingt5,whereas there was non-significant correlation between SAVI andt5 (r2=0.069,P=0.082); (2) GNDVI decreased with increasingt20, (r2=0.218,P=0.001), whereas there were non-significant relationships between NDVI (r2=0.040,P=0.190), SAVI (r2=0.014,P=0.443) andt20; (3) NDVI (r2=0.277,P=0.0002), GNDVI (r2=0.394,P=0.0000) and SAVI (r2=0.208,P=0.002)increased with increasing SM5; and (4) GNDVI increased with increasing SM20(r2=0.193,P=0.003), whereas there were non-significant correlations between NDVI (r2=0.059,P=0.107), SAVI (r2=0.037,P=0.209) and SM20. Multiple regression analyses indicated that SM5dominated the variations of NDVI, GNDVI and SAVI. Partial correlation analyses demonstrated that (1) the correlation coefficients of NDVI, GNDVI and SAVI with SM5were 0.442 (P=0.003), 0.412 (P=0.007) and 0.404 (P=0.008); (2) with SM20were -0.042 (P=0.792), 0.051 (P=0.749) and -0.033 (P=0.837); (3) witht5were -0.154 (P=0.332), -0.019 (P=0.907) and -0.170 (P=0.282); and (4) witht20 were 0.228 (P=0.147), -0.041 (P=0.795) and 0.268 (P=0.086), respectively. Therefore, the soil drying induced by infrared warming suppressed the growth of highland barley, which in turn affected vegetation indices. That is, the non-significant changes of the three vegetation indices may be due to the infrared warming-induced drying.%气候变暖影响着农作物生长及其植被指数。为了探讨西藏高原青稞（Hordeum vulgare Linn. var. nudum Hook.f.）归一化植被指数（normalized difference vegetation index，NDVI）、归一化绿波段差值植被指数（normalized green difference vegetation index，GNDVI）和土壤调节植被指数（soil adjusted vegetation index，SAVI）对气候变暖的初始响应，2014年5月在西藏达孜县布设了一个红外增温实验（3个水平，即对照，1000和2000 W红外增温）。通过对2014年6─9月利用农业多光谱相机获取的3种植被指数和利用HOBO微气候观测系统获取的两个深度（5和20 cm）的土壤温湿度的统计分析，探讨了西藏高原青稞植被指数对红外增温的响应及其与土壤温湿度的相互关系。结果表明，1000和2000 W的增温使5 cm的土壤温度（t5）分别升高了约1.62和1.77℃，使20 cm的土壤温度（t20）分别升高了约1.16和1.43℃；相反使5 cm的土壤湿度（SM5）分别下降了约1.8%和14.1%，使20 cm的土壤湿度（SM20）分别下降了21.6%和14.7%。1000 W的增温使NDVI、GNDVI和SAVI分别增加了约2.4%、4.3%和0.5%；2000 W的增温则使NDVI、GNDVI和SAVI分别增加了约5.5%、5.3%和4.8%，尽管增加幅度并不显著。单因子回归分析表明，t5与NDVI（r2=0.110，P=0.026）和GNDVI（r2=0.254，P=0.0004）为负相关，而与SAVI无关（r2=0.069，P=0.082）；t20与GNDVI为负相关（r2=0.218，P=0.001），而与NDVI（r2=0.040，P=0.190）和SAVI（r2=0.014，P=0.443）无关；SM5与NDVI（r2=0.277，P=0.0002）、GNDVI（r2=0.394，P=0.0000）和SAVI（r2=0.208， P=0.002）为正相关。SM20与GNDVI为正相关（r2=0.193，P=0.003），而与NDVI（r2=0.059，P=0.107）和SAVI（r2=0.037， P=0.209）无关。多重回归分析表明，SM5主导着NDVI、GNDVI和SAVI的变异。偏相关分析表明，NDVI、GNDVI和SAVI与SM5的相关系数分别为0.442（P=0.003）、0.412（P=0.007）和0.404（P=0.008）；与SM20的相关系数分别为-0.042（P=0.792）、0.051（P=0.749）和-0.033（P=0.837）；与 t5的相关系数分别为-0.154（P=0.332）、-0.019（P=0.907）和-0.170（P=0.282）；与 t20的相关系数分别为0.228（P=0.147）、-0.041（P=0.795）和0.268（P=0.086）。因此，红外增温引起的干旱抑制了青稞的生长，进而影响了植被指数，即植被指数的不显著变化可能与红外增温引起的土壤干旱有关。
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