Climate change and intensified human activity have altered the landscape pattern of nature reserves and are expected to induce persistent changes in habitat quality. Using GIS technology and landscape ecological theories, we quantitatively analyzed landscape fragmentation characteristics and the driving factors for the interior and peripheries of the Qinling–Daba Mountains nature reserves during 2010–2017. Using spatial principal component analysis, landscape pattern indices, and Geodetector, we evaluated the habitat quality status of different nature reserve types in different regions and the impacts of human disturbance on these areas. The results are as follows: (1) Most national nature reserves in the Qinling–Daba Mountains were moderately or highly fragmented during 2010–2017, and the fragmentation degree of a few reserves exhibited a decreasing trend. (2) The fragmentation degree of landscape patches from the core areas to the experimental areas of the inner nature reserves showed a trend of being low in the middle and high in the surrounding area; the level of landscape fragmentation gradually decreased from the edge of 1 km (M-1) to 5 km (M-5). (3) There was spatial differentiation in the intensity of landscape fragmentation among the nature reserves; human activity intensity, land-use degree, elevation, slope gradient, and topographic relief were the factors influencing the spatial differentiation of landscape fragmentation, and the contribution of anthropogenic factors was significantly greater than that of natural factors. Human activities, such as the construction of network infrastructures, irrational partition management, expansion of agricultural and industrial production activities, were the main reasons for the spatial differentiation of landscape fragmentation in the nature reserves. These results can provide significant scientific support for ecological restoration in the nature reserves and contribute to the coordinated development between socio-economic system and ecological environment in the exceedingly impoverished areas.

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The ecological environment is important for the natural disaster prevention of human society. The monitoring of ecological environment quality has far-reaching practical significance for the functional construction of ecosystem services and policy coordination. Based on Landsat 8 operational land image (OLI)/thermal infrared sensor (TIRS) remote sensing image data, this study selected the normalized vegetation (NDVI), tasseled cap transformation humidity (WI), bare soil (SI), construction index (NDSI), and land surface temperature (LST) indexes from the aspects of greenness, humidity, dryness, and heat. Using spatial principal component analysis (SPCA) and the remote sensing ecological index (RSEI) analyzed the spatial differentiation characteristics and influencing factors of the original remote sensing ecological index (RSEI0). The results showed that: (1) the overall RSEI average value of the Qinling-Daba Mountains in 2017 was 0.61, and the ecological environment quality was at a “Good” level. Greenness contributed the most to the comprehensive index of the area, and vegetation distribution had a significant impact on the ecological environment quality of the study area. Heat is a secondary impact, and it has an inhibitory effect on habitat quality; (2) the overall distribution of regional ecological environment quality was quite different, with the ecological environment quality level showing a decreasing trend from low to high altitude; RSEI0 spatial heterogeneity at the optimal scale of 2 km was the largest, and the nugget effect was 88% which indicated a high degree of spatial variability, mainly affected by structural factors; (3) Slope, relief amplitude, elevation, the proportion of high-vegetation area, proportion of construction land area, and average population density significantly impact the spatial differentiation of RSEI0. The explanatory powers of slope and relief amplitude were 56.1% and 65.3%, respectively, which were the main factors affecting the spatial differentiation of the ecological environment quality in high undulation. The results can provide important scientific support for ecological environment construction and ecological restoration in the study area.