High temperature targets (temperature above 500 K), are the special on the surface of the earth such as forest fire, prairie fire, oil well torches, heap coking, volcanic eruptions, significantly different from those of normal surfaces at lower temperatures. Identification of high-temperature targets plays an important role in environmental monitoring, disaster warning, and resource investigation. In remote sensing data, high-temperature target pixels and bands are studied. And they are deemed samples and variables, respectively, in multivariate analysis. And classification of samples for identification of high-temperature targets is necessary. To classify samples, feature analysis of spectrum needs to be done first. In feature analysis of spectrum, feature bands that can be used to distinguish samples need to be selected. Correspondence analysis is the method that can project samples and variables into the same factor space in the meantime. It can realize the classification of samples and variables synchronously, and the results can be interpreted by each other. First, the correspondence analysis is conducted on Landsat8/OLI remote sensing imagery to build the relationship between samples and variables. After that the correspondence relationship between identification results of high-temperature targets and feature bands can be built in the physical theory of remote sensing and factors which have indicative significance on fire are confirmed. Finally, the single band threshold method is adopted to realize high temperature target recognition by using factor scores. In the field confirmation, results suggest that the precision of identification of high-temperature targets reaches 92%. And we also get a consistent result with SWIR temperature inversion.

Reduced vegetation cover caused by grassland degradation results in the interception of solar illuminance significantly decreasing, then leading to an increase in ground temperature, which has a significant impact on biological growth and regional climate. Based on the field experiment, we explore the interception of solar illuminance by grasslands with three degrees of degradation and its effect on the soil temperature. Solar illuminance at various heights and times was measured to obtain the interception by vegetation, which included reduction by physical shielding and consumption by the plants’ life activities. Solar illuminance in the subareas sprayed with herbicide was merely reduced by physical shielding, and the difference in solar illuminance interception between normally growing grasslands and fatal grasslands was used for the plants’ life activities. This method described above was almost the first to be used for the exploration of the functional allocation of solar illuminance interception. The percentage of solar illuminance interception was largest in the non-degraded grassland (80–95% at different times), including a 50–60% reduction on account of physical shielding and a 20–45% consumption by the grass’s life activities. Light interception by grassland vegetation directly reduced the grassland temperature. The increment of ground temperature reaches 4–13 °C when a non-degraded grassland turns into a severely degraded grassland.