Spatial and Temporal Characteristics and Driving Forces of Vegetation Changes in the Huaihe River Basin from 2003 to 2018

Abstract

In this study, MODIS normalized difference vegetation index (NDVI), TRMM3B43 precipitation, and MOD11A2 land-surface temperature (LST) data were used as data sources in an analysis of temporal and spatial characteristics of vegetation changes and ecological environmental quality in the Huaihe River basin, China, from 2003 to 2018. The Mann–Kendall (MK) non-parametric test and the Theil–Sen slope test were combined for this analysis; then, when combined with the results of the MK mutation test and two introduced indexes, the kurtosis coefficient (KU) and skewness (SK) and correlations between NDVI, precipitation (TRMM), and land-surface temperature (LST) in different time scales were revealed. The results illustrate that the mean NDVI in the Huaihe River basin was 0.54. The annual NDVImax curve fluctuations for different land cover types were almost the same. The main reasons for the decrease in or disappearance of vegetation cover in the Huaihe River basin were the expansion of towns and impact of human activities. Furthermore, vegetation cover around water areas was obviously degraded and wetland protections need to be strengthened urgently. On the same time scale, change trends of NDVI, TRMM, and LST after abrupt changes became consistent within a short time period. Vegetation growth was favored when the KU and SK of TRMM had a close to normal distribution within one year. Monthly TRMM and LST can better reflect NDVI fluctuations compared with seasonal and annual scales. When the precipitation (TRMM) is less than 767 mm, the average annual NDVI of different land cover types is not ideal. Compared with other land cover types, dry land has stronger adaptability to changes in the LST when the LST is between 19 and 22.6 °C. These trends can serve as scientific reference for protecting and managing the ecological environment in the Huaihe River basin.

Quantitative Contributions of Climate Change and Human Activities to Vegetation Changes in the Upper White Nile River

“…This method does not need samples to fit a specific distribution and is not influenced by outliers [43]. This method is currently extensively used for mutation testing with long-term sequence data [44][45][46][47].…”

“…The Theil-Sen median trend analysis method was adopted to analyze the spatial distribution characteristics of vegetation trends, and the statistical significance of the trend analysis results was tested by the MK test [41,45]. The combined use of the two methods can enhance the immunity to noise, and it can be not affected by the sample distribution pattern and the interference of outliers.…”

“…The combined use of the two methods can enhance the immunity to noise, and it can be not affected by the sample distribution pattern and the interference of outliers. The combination improves the accuracy of the test results to a certain extent and is an available method to test the tendency of time series [45,[48][49][50].…”

“…The merits of the MK nonparametric significance test method are that the sample data do not need to fit a certain distribution, and they cannot be disturbed by outliers. Therefore, this method can be adopted to test the significance of vegetation change trends in the time sequence [41,45,48,51,52]. For time series [x i ], i = 1, 2, .…”

Ecological Safety Assessment and Analysis of Regional Spatiotemporal Differences Based on Earth Observation Satellite Data in Support of SDGs: The Case of the Huaihe River Basin

“…The HRB covers a wide area, and considering the difficulty of data acquisition and the suitability of temporal and spatial resolution, the study mainly used MODIS data to calculate indicators. Additionally, MODIS products are widely used in ecological research [62] and they are reliable.…”