## 1 Introduction  
In 1984, hemorrhagic fever with renal syndrome (HFRS) broke out in Shaanxi Province, marked by rapidly progressive glomerulephritis symptoms and a high likelihood of mortality caused by the Hantaan virus (HTNV, family Bunyaviridae, genus Hantaavirus): a total of 1439 cases and an incidence of 0.3% occurred in Hu County (Shanxi Province) [1; 2]. Although a significant decrease in the number of HFRS cases has been observed over the long-term, the 493 cases reported between 2010 and 2011 reawakened concern about the possible risk of disease.  
Hantaviruses are primarily associated with the rodent family, Muridae [3]. Hantaaviruses and rodent reservoir species are tightly linked, so that each viral species is primarily associated with a single rodent species, although spillover infections have been reported in other mammals [4; 5]. As HFRS is transmitted by contact with rodent urine, feces or saliva [6; 7], usually considered as a direct, density-dependent transmission [8; 9], the ecology of rodent abundance can largely determine the possibility and magnitude of HFRS [10]. On the Weihe plain, located in central Shaanxi Province, striped field mice (_Apodemus agarius_) are the main rodent host of HTNV [11]. Therefore, understanding the factors that lead to changes in _A. agarius_ abundance is important for better predicting HFRS outbreaks.  
In 2002, a trophic cascade hypothesis was proposed by [PERSON] et al. to explain how environmental variation affects the probability of epidemic outbreaks [12]. Trophic cascades are indirect interactions within a food web that can affect the entire ecosystem. Favorable environmental conditions can bring an increase in primary and secondary productivities, which results in a higher rodent population density and thereby an increased risk of hantaviruses transmission to humans [13; 14]. At present, remote sensing (RS) has been recognized as an important information source for studying hantaviruses ecology, and it is often used in the study of the relationship between environmental variables and hantavirus transmission. [PERSON] et al. [15; 16; 17] and [PERSON] et al. [18; 19] used remote sensing images to identify environments associated with a risk of hantaviral disease in humans caused by Sin Nombre virus. [PERSON] et al. [20] combined ecologic niche modeling with remote sensing techniques to identify the risk factors for hantavirus infections in rodent hosts. [PERSON] et al. [10] and [PERSON] et al. [21] examined the relationship between natural infection rates for hantavirus in rodents and land cover classes. [PERSON] et al. [22] used Landsat TM satellite data to explore the temporal relationship between the number of HFRS cases and a time series of the normalized difference vegetation index (NDVI). These studies highlight the usefulness of RS in anticipating HFRS risk.  
Here we carried out a survey of rodent population dynamics, covering the period from 2005 to 2012 on the Weihe Plain, and used HFRS incidence data, together with satellite data, to test the hypothesis that the population dynamics of the animal reservoir of HTNV is led by trophic cascades (measured via remote sensing indicators), and in turn these can serve as possible predictors of HFRS outbreaks. Our analyses will improve the understanding of the risk of HTNV transmission to humans.