The change in snow cover under climate change is poorly understood in Tianshan Mountains. Here, we investigate the spatiotemporal characteristics and trends of snow-covered area (SCA) and snow-covered days (SCD) in the Tianshan Mountains by using the cloud-removed MODIS fractional snow cover datasets from 2001–2015. The possible linkage between the snow cover and temperature and precipitation changes over the Tianshan Mountains is also investigated. The results are as follows: (1) The distribution of snow cover over the Tianshan Mountains exhibits a large spatiotemporal heterogeneity. The areas with SCD greater than 120 days are distributed in the principal mountains with elevations of above 3000 m. (2) In total, 26.39% (5.09% with a significant decline) and 34.26% (2.81% with a significant increase) of the study area show declining and increasing trend in SCD, respectively. The SCD mainly decreases in Central and Eastern Tianshan (decreased by 11.88% and 8.03%, respectively), while it increases in Northern and Western Tianshan (increased by 9.36% and 7.47%). (3) The snow cover variations are linked to the temperature and precipitation changes. Temperature tends to be the major factor effecting the snow cover changes in the Tianshan Mountains during 2001–2015.

The spatial and temporal variations of snowcover distribution, and snowmelt runoff are considered as sensitive indicators for climatic change. The purpose of this paper is to analyze and forecast the responses of snowmelt runoff to climate change in an inland river basin. The upper basin of Heihe River in Northwestern China was chose as the study area, and the observation data from the meteorological and hydrological stations were utilized to analyze the status and regularity of the climatic change over the past 50 years. Snow cover area was obtained by an optimized technology using Moderate Resolution Imaging Spectroradiometer data with Normalized Difference Snow Index adjustment and topographic correction. A concept of potential snowmelt was suggested to illustrate the response of spatial snowmelt to climate change. The results show that the annual SCA proportion and the potential snowmelt keep an increasing trend since 2000. There is a negative relationship between annual air temperature and SCA proportion from 2000 to 2008. Snowmelt Runoff Model was chose to simulate snowmelt runoff and scenario forecast the change trend of snowmelt runoff in this region. The results show that climatic warming was apparent in the upper basin of Heihe River over the past 50 a. Annual average air temperature of three different weather stations located in the basin has increased 2.1 °C, 2.6 °C and 2.9 °C respectively from 1956 to present. The snowmelt runoff has increased obviously from 1970 to present. With different warming climate scenarios, the results by using SRM simulating showed that the first occurred time of snowmelt runoff shift ahead and discharge become larger as responses of snowmelt runoff to air temperature increasing, and the influence of temperature rising on average discharge of the whole snow season is not obvious.

The Normalized Difference Snow Index (NDSI) is an effective index for snow-cover mapping at large scales, but in forested regions the identification accuracy for snow using the NDSI is low because of forest cover effects. In this study, typical evergreen coniferous forest zones on Qilian Mountain in the Upper Heihe River Basin (UHRB) were chosen as example regions. By analyzing the spectral signature of snow-covered and snow-free evergreen coniferous forests with Landsat Operational Land Imager (OLI) data, a novel spectral band ratio using near-infrared (NIR) and shortwave infrared (SWIR) bands, defined as (ρ_nir − ρ_swir)/(ρ_nir + ρ_swir), is proposed. Our research shows that this band ratio, named the normalized difference forest snow index (NDFSI), can be used to effectively distinguish snow-covered evergreen coniferous forests from snow-free evergreen coniferous forests in UHRB.

Seasonal snow cover is a critical component of the energy and water budgets of mountainous watersheds. Capturing the snow cover in complex environments is crucial for monitoring and understanding the temporal and spatial effects of climate change on alpine snow cover. The normalized difference snow index (NDSI) can be used to effectively and accurately estimate snow cover information from satellite images. However, the NDSI has limited utility for estimating the snow cover in heavily forested areas and relating this information to snowmelt-based runoff. In this study, a new algorithm based on a multi-index technique is proposed. The technique combines the NDSI, the normalized difference forest snow index, and the normalized difference vegetation index, and decision rules are established to increase the accuracy of snow mapping in forested areas. The new algorithm based on a multi-index technique is tested in the mountainous forested areas of North Xinjiang, China. In a winter image with full snow and a spring image with patchy snow, most of the forest snow, which is underestimated by the NDSI, is recognized by the multi-index technique. The accuracy of snow detection in forested areas is more than 90%. Additionally, in an experiment using a summer image without snow in forested areas no commission errors were detected. The snow detection algorithm based on a multi-index technique uses a simple set of decision rules for snow and can be run automatically without a priori knowledge of the surface characteristics.

The MODIS land surface temperature (LST) product is one of the most widely used data sources to study the climate and energy-water cycle at a global scale. However, the large number of invalid values caused by cloud cover limits the wide application of the MODIS LST. In this study, a two-step improved similar pixels (TISP) method was proposed for cloudy sky LST reconstruction. The TISP method was validated using a temperature-based method over various land cover types. The ground measurements were collected at fifteen stations from 2013 to 2018 during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) field campaign in China. The estimated theoretical clear-sky temperature indicates that clouds cool the land surface during the daytime and warm it at nighttime. For bare land, the surface temperature shows a clear seasonal trend and very similar across stations, with a cooling amplitude of 4.14 K in the daytime and a warming amplitude of 3.99 K at nighttime, as a yearly average. The validation result showed that the reconstructed LST is highly consistent with in situ measurements and comparable with MODIS LST validation accuracy, with a mean bias of 0.15 K at night (−0.43 K in the day), mean RMSE of 2.91 K at night (4.41 K in the day), and mean R² of 0.93 at night (0.90 in the day). The developed method maximizes the potential of obtaining quality MODIS LST retrievals, ancillary data, and in situ observations, and the results show high accuracy for most land cover types.

The scientific assessment of regional ecosystem service value (ESV) is helpful in developing scientific ecological protection plans and compensation policies. However, an ESV evaluation method that can adapt to the complex and diverse characteristics of the ecological environment has not been established. This study takes Gansu Province in China as an example, fully considering the regional differences in ecosystem service function. Five correction indices for the value equivalent factor per unit area were constructed on a provincial scale, and a regional difference adjustment index for 11 categories of ecosystem services was constructed on a regional scale. In this way, a value evaluation model based on regional differences was established. The results show that in 2015, the total ESV reached 2,239.56 billion yuan in Gansu Province, with ESV gradually increasing from the northeast to the southwest, and the high-value areas of service function being located in Qilian and Longnan Mountains. The forest and grassland ecosystems contributed the most to the ESV. From the perspective of value composition, local climate regulation and biodiversity maintenance functions are the main service functions of Gansu Province. From 2000 to 2015, ESV increased by 3.43 billion yuan in the province. The value of forest and urban ecosystems continued to increase, whereas the value of cultivated land ecosystem continued to decrease. In terms of spatial characteristics of the service value change, the area that experienced value reduction gradually moved from the central part of Gansu Province to the surrounding areas. The evaluation method proposed in this paper provides a relatively comprehensive evaluation scheme for the spatiotemporal dynamic evaluation of ESV in complex ecological environments.