Evaluation of Climate Change Impacts on Wetland Vegetation in the Dunhuang Yangguan National Nature Reserve in Northwest China Using Landsat Derived NDVI

Monitoring and evaluation of vegetation restoration in the Ebinur Lake Wetland National Nature Reserve under lockdown protection

For a long time, human activities have been prohibited in ecologically protected areas in the Ebinur Lake Wetland National Nature Reserve (ELWNNR). The implementation of total closure is one of the main methods for ecological protection. For arid zones, there is a lack of in-depth research on whether this measure contributes to ecological restoration in the reserve. The Normalized Difference Vegetation Index (NDVI) is considered to be the best indicator for ecological monitoring and has a key role to play in assessing the ecological impacts of total closure. In this study, we used Sentinel-2, Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data to select optimal data and utilized Sen slope estimation, Mann-Kendall statistical tests, and the geographical detector model to quantitatively analyze the normalized difference vegetation index (NDVI) dynamics and its driving factors. Results were as follows: (1) The vegetation distribution of the Ebinur Lake Wetland National Nature Reserve (ELWNNR) had obvious spatial heterogeneity, showing low distribution in the middle and high distribution in the surroundings. The correlation coefficients of Landsat-8 and MODIS, Sentinel-2 and MODIS, and Sentinel-2 and Landsat-8 were 0.952, 0.842, and 0.861, respectively. The NDVI calculated from MODIS remote sensing data was higher than the value calculated by Landsat-8 and Sentinel-2 remote sensing images, and Landsat-8 remote sensing data were the most suitable data. (2) NDVI indicated more degraded areas on the whole, but the ecological recovery was obvious in the localized areas where anthropogenic closure was implemented. The ecological environment change was the result of the joint action of man and nature. Man-made intervention will change the local ecological environment, but the overall ecological environment change was still dominated by natural environmental factors. (3) Factors affecting the distribution of NDVI in descending order were as follows: precipitation > evapotranspiration > land use type > elevation > vegetation type > soil type > soil erosion > slope > temperature > slope direction. Precipitation was the main driver of vegetation change in ELWNNR. The synergistic effect of the factors showed two-factor enhancement and nonlinear enhancement, and the combined effect of the driving factors would increase the influence on NDVI.

Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

Seasonal Dynamics of Leaf Stoichiometry of Phragmites australis: A Case Study From Yangguan Wetland, Dunhuang, China

Leaf stoichiometry can enhance our understanding of leaf elements' (C, N and P) concentrations and their corresponding ratios in an ecosystem with seasonal environment changes. This study quantified the seasonal dynamics of leaf stoichiometry of P. australis from Yangguan wetland, Dunhuang, China as a case study example. The leaf C concentration (LC) of P. australis changed between seasons and was 392.26 (g×kg-1), 417.35 (g×kg-1) and 392.58 (g×kg-1) in spring, summer and autumn, respectively. Leaf N and P concentrations (LN and LP) were 23.49 (g×kg-1), and 17.54 (g×kg-1) and 5.86 (g×kg-1), and 1.00 (g×kg-1), 0.75 (g×kg-1) and 0.16 (g×kg-1), respectively, in the three seasons. The maximum (77.68) and the minimum values (17.00) of LC:LN were observed in the autumn and spring, respectively. Seasonal variations in LC:LP also showed a similar trend, with the greatest value of 3015.91 in autumn and the lowest value of 429.39 in spring. However, the highest (45.67) and the lowest values (24.18) of LN:LP were observed in autumn and summer, respectively, indicating that the growth of P. australis was mainly affected by P. Based on these results, it can be concluded that P. australis adopted a competition strategy during the early growth stage but took on a defense life strategy at the late growth stage to cope with various environments.

Normalized Difference Vegetation Index Continuity of the Landsat 4-5 MSS and TM: Investigations Based on Simulation

Landsat 4-5, built at the same time and with the same design, carrying the Multispectral Scanner System (MSS) and the Thematic Mapper (TM) simultaneously, jointly provided observation service for about 30 years (1982–2013). Considering the importance of data continuity for time series analyses, investigations on the continuity of the Landsat 4-5 MSS and TM are required. In this paper, characterization differences between the Landsat 4-5 MSS and TM were initially discussed using the synthesized reflectance records generated from a collection of Hyperion hyperspectral profiles which were well calibrated and widely distributed. The difference in near-infrared region mostly contributed to the difference in normalized difference vegetation index (NDVI) between MSS and TM, while the between-sensor difference in red spectrum was relatively minor. Models for transforming MSS NDVI to TM NDVI were proposed, and validated subsequently through cross-validation tests. Furthermore, effectiveness of the transformation models was investigated using eight synchronous observation pairs of the Landsat 5 MSS and TM. On average, the univariate models through ordinary least squares regression (OLS) regression resulted in a decrease about 10% of the median relative difference (MdRD). Meanwhile, the bivariate models improved the NDVI comparability in most cases, especially when the transformation models through ridge regression were implemented. The univariate model through OLS regression could be the only solution for cases when problems of data quality are encountered (e.g., problem in the MSS near-infrared channel (800–1000 nm)). In conclusion, the findings on NDVI transformation models from MSS to TM are valuable for reference, because of the collection of diverse Hyperion hyperspectral profiles used.

Spatiotemporal Characteristic of Land Use/Land Cover Changes in the Middle and Lower Reaches of Shule River Basin Based on an Intensity Analysis

The vegetation response to climatic factors is a hot topic in global change research. With the Support of ArcGIS and ENVI software, six sets of Landsat remote sensing images of the middle and lower reaches of the Shule River Basin were interpreted. Eight types of land use and land covers were obtained and the spatiotemporal characteristics of the land use/land cover changes (LUCCs) were analyzed using an intensity analysis to provide a basis for decision-making on the sustainable development of the basin. In the past 29 years, the area of cropland, construction land and shrubland had a net increase, while high-coverage grassland (HCG), medium-coverage grassland (MCG), low-coverage grassland (LCG), wetland and non-vegetation land all presented a net decrease. The area of artificial vegetation (cropland) presented an expanding trend and increased by 1105.56 km2 in total, while the natural vegetation (grassland, shrubland, wetland) showed a shrinking tendency and decreased by 917.69 km2. The intensity analysis revealed that the rate of LUCC in the period of 2000~2006 and 2006~2010 was relatively higher, although the rate of LUCC in other periods was much lower. The change intensities of MCG and HCG were greatest, followed by LCG, shrubland and wetland. Construction land and cropland were in third place, while non-vegetation land was in last place. The pattern of regional LUCC was generally stable except for cropland loss and the gain/loss change of other land-use/land-cover types was always in an active state. For spatial distribution, few changes were observed in the old irrigated area within the oasis. The LUCC was mainly concentrated in the oasis fringe area, natural vegetation cover area and emigrant arrangement regions.

A Model for Estimating the Vegetation Cover in the High-Altitude Wetlands of the Andes (HAWA)

The natural salt meadows of Tilopozo in the hyperarid, Atacama Desert of northern Chile, which are located at approximately 2800 m above sea level, are under pressure from industrial activity, and cultivation and grazing by local communities. In this research, the land surface covered by salt meadow vegetation was estimated from normalized difference vegetation indices (NDVI) derived from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) and Operational Land Imager (OLI) data from 1985 to 2016. The vegetated area of the Tilopozo salt meadows decreased by 34 ha over the 32-year period studied. Multiple regression models of the area covered by vegetation and climate data and groundwater depths were derived on an annual basis, as well as for both the dry and wet seasons and had R2 values of 83.0%, 72.8% and 92.4% respectively between the vegetated areas modeled and those estimated from remotely sensed data. These models are potentially useful tools for studies into the conservation of the Tilopozo salt meadows, as they provide relevant information on the state of vegetation and enable changes in vegetation in response to fluctuations in climate parameters and groundwater depths to be predicted.