ABSTRACT
Understanding the influences of climate change and human activities on vegetation change is the foundation for effective ecosystem management. Based on the 250 m MODIS-NDVI data from 2002 to 2020, we employed Theil-Sen Median trend analysis and the Mann-Kendall test to quantify vegetation change in Hunan Province. By combining with meteorological, nighttime light index, land cover and other data, residual analysis and correlation analysis, we examined the impacts of human activities and climate change on vegetation dynamics at both the pixel level and the county level. The results showed that the normalized difference vegetation index (NDVI) in Hunan Province exhibited a spatial pattern of "overall improvement with localized degradation" during 2002-2020. Approximately 64.9% of the study area experienced significant vegetation improvement, mainly occurring in the western and central-southern parts of Hunan Province. 1.4% of the study area experienced significant vegetation degradation, mostly in the newly developed urban areas and the farmland in the Dongting Lake Plain. Human activities and climate change jointly promoted vegetation improvement in 67.9% of the study area. Human activities and climate contributed to 96% and 4% of the NDVI change, respectively. At the county level, human activities contributed to over 80% of the NDVI change in each district or county. The impacts of human activities on vegetation change exhibited significant spatial heterogeneity. Urban expansion led to vegetation degradation in the newly developed areas, while vegetation growth appeared in the old developed urban areas. The ecological restoration projects promoted vegetation restoration in the western part of Hunan Province. This study could help us better understand the spatiotemporal variations of vegetation and their responses to climate change and human activities, which would offer scientific basis for effective ecological restoration policy.
Subject(s)
Climate Change , Ecosystem , Environmental Monitoring , China , Environmental Monitoring/methods , Conservation of Natural Resources , Satellite Imagery , Human Activities , Plant Development , Trees/growth & developmentABSTRACT
Ecosystem-based cooling helps residents cope with the urban heat-island problem. In order to improve the accuracy of traditional heat-island measurements based on comparisons between urban and rural areas, we use an "on-site" method developed with only urban data. The essence of this method is a regression analysis of the relationships among different types of green space and blue space, elevation, vegetation dynamics, and temperature. We then simulate the temperature pattern in a scenario where there is no built-up area (Scenario A), and then in another scenario where there are no ecological spaces (Scenario B). The gap between the actual temperature pattern and the simulated temperature pattern of Scenario A is considered the heat-island effect. Conversely, the gap between the actual temperature pattern and that of Scenario B is considered as the effect of ecosystem-based urban cooling. This method was tested using data from two megacities in China (each had a population of over 10 million people). For Beijing, the average heat-island effect was 4.87 °C and effect of the ecosystem cooling service was 9.07 °C. For Shenzhen, the respective values were 0.8 °C and 2.71 °C. The "on-site" (local small size sampling), "dynamic coefficient", and "no-positive-coefficient rule" are the three defining characteristics of this method. The application of this method to model ecosystem-based urban cooling can aid urban planning and management in improving the residential thermal environment.