1） 对绿光 （0.55     ）有一小的反射峰值，反射率大致为20%，这是绿色植物呈现绿色的原因。注意这里也正是太阳光的光能峰值。

2） 在红光处（0.68     ）有一吸收谷，这是光合作用吸收谷。注意此处太阳光能仍很大，若吸收谷减小，则植被发黄、红。

           3） 在 0.7~1.4      与 1.5 ~ 1.9      有很高红外反射峰，反射率可高达70%以上，这两峰与前边红光波谷是植被光谱的特征。这第一峰波长段还处在太阳光能波谱中主要能量分布区（0.2~1.4    ）占有全部太阳光能量90.8%，这是遥感识别植被并判断植被状态的主要依据。          

        4） 在 1.45 至 1.95       有两处吸收谷，表明植被中水分含量。  

        5） 不同种类植物反射光谱曲线的变化趋势相同，而植物与其它地物的反射光谱曲线显著不同，这是遥感可以估测生物量的基础。

        6） 植物叶片重叠时，反射光能量在可见光部分几乎不变，而在红外却可增加20~40%。这是因为红外光可透过叶片，又经下层叶片重复反射。叶片重叠反映作物长势旺盛，生物量高。

     7) 植物叶片可见光区反射率有显著的方向性，这是因为植物叶片反射（散射）不是纯粹的朗伯散射，还有方向性。而在红外区方向性就不显著，这是因为红外光透射性好，透射后重复反射打扰了方向性。

When solar radiation hits a target surface, it may be transmitted, absorbed or reflected. Different materials reflect and absorb differently at different wavelengths. The reflectance spectrum of a material is a plot of the fraction of radiation reflected as a function of the incident wavelength and serves as a unique signature for the material. In principle, a material can be identified from its spectral reflectance signature if the sensing system has sufficient spectral resolution to distinguish its spectrum from those of other materials. This premise provides the basis for multispectral remote sensing.

The following graph shows the typical reflectance spectra of five materials: clear water, turbid water, bare soil and two types of vegetation.

The reflectance of clear water is generally low. However, the reflectance is maximum at the blue end of the spectrum and decreases as wavelength increases. Hence, clear water appears dark-bluish. Turbid water has some sediment suspension which increases the reflectance in the red end of the spectrum, accounting for its brownish appearance. The reflectance of bare soil generally depends on its composition. In the example shown, the reflectance increases monotonically with increasing wavelength. Hence, it should appear yellowish-red to the eye.

Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. The reflectance is low in both the blue and red regions of the spectrum, due to absorption by chlorophyll for photosynthesis. It has a peak at the green region which gives rise to the green colour of vegetation. In the near infrared (NIR) region, the reflectance is much higher than that in the visible band due to the cellular structure in the leaves. Hence, vegetation can be identified by the high NIR but generally low visible reflectances. This property has been used in early reconnaisance missions during war times for "camouflage detection".

The shape of the reflectance spectrum can be used for identification of vegetation type. For example, the reflectance spectra of vegetation 1 and 2 in the above figures can be distinguished although they exhibit the generally characteristics of high NIR but low visible reflectances. Vegetation 1 has higher reflectance in the visible region but lower reflectance in the NIR region. For the same vegetation type, the reflectance spectrum also depends on other factors such as the leaf moisture content and health of the plants.

The reflectance of vegetation in the SWIR region (e.g. band 5 of Landsat TM and band 4 of SPOT 4 sensors) is more varied, depending on the types of plants and the plant's water content. Water has strong absorption bands around 1.45, 1.95 and 2.50 µm. Outside these absorption bands in the SWIR region, reflectance of leaves generally increases when leaf liquid water content decreases. This property can be used for identifying tree types and plant conditions from remote sensing images. The SWIR band can be used in detecting plant drought stress and delineating burnt areas and fire-affected vegetation. The SWIR band is also sensitive to the thermal radiation emitted by intense fires, and hence can be used to detect active fires, especially during night-time when the background interference from SWIR in reflected sunlight is absent.