Vegetation Cover In Region Research Articles

Detection of spatial and temporal variation characteristics of vegetation cover in the Lower Mekong region and the influencing factors

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

Change in Fractional Vegetation Cover and Its Prediction during the Growing Season Based on Machine Learning in Southwest China

Fractional vegetation cover (FVC) is a crucial indicator for measuring the growth of surface vegetation. The changes and predictions of FVC significantly impact biodiversity conservation, ecosystem health and stability, and climate change response and prediction. Southwest China (SWC) is characterized by complex topography, diverse climate types, and rich vegetation types. This study first analyzed the spatiotemporal variation of FVC at various timescales in SWC from 2000 to 2020 using FVC values derived from pixel dichotomy model. Next, we constructed four machine learning models—light gradient boosting machine (LightGBM), support vector regression (SVR), k-nearest neighbor (KNN), and ridge regression (RR)—along with a weighted average heterogeneous ensemble model (WAHEM) to predict growing-season FVC in SWC from 2000 to 2023. Finally, the performance of the different ML models was comprehensively evaluated using tenfold cross-validation and multiple performance metrics. The results indicated that the overall FVC in SWC predominantly increased from 2000 to 2020. Over the 21 years, the FVC spatial distribution in SWC generally showed a high east and low west pattern, with extremely low FVC in the western plateau of Tibet and higher FVC in parts of eastern Sichuan, Chongqing, Guizhou, and Yunnan. The determination coefficient R2 scores from tenfold cross-validation for the four ML models indicated that LightGBM had the strongest predictive ability whereas RR had the weakest. WAHEM and LightGBM models performed the best overall in the training, validation, and test sets, with RR performing the worst. The predicted spatial change trends were consistent with the MODIS-MOD13A3-FVC and FY3D-MERSI-FVC, although the predicted FVC values were slightly higher but closer to the MODIS-MOD13A3-FVC. The feature importance scores from the LightGBM model indicated that digital elevation model (DEM) had the most significant influence on FVC among the six input features. In contrast, soil surface water retention capacity (SSWRC) was the most influential climate factor. The results of this study provided valuable insights and references for monitoring and predicting the vegetation cover in regions with complex topography, diverse climate types, and rich vegetation. Additionally, they offered guidance for selecting remote sensing products for vegetation cover and optimizing different ML models.

Restoration of vegetation in the Yellow River Basin of Inner Mongolia is limited by geographic factors

Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000–2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

Population regeneration of two Haloxylon species in central Asian deserts as affected by groundwater depth

Haloxylon ammodendron and Haloxylon persicum are the dominant species in the deserts of Central Asia. As groundwater exploration has resulted in a decline in groundwater depth in this region, the impact on the regeneration of these two Haloxylon populations calls for urgent attention. Therefore, we conducted an intensive vegetation survey, including population density, age structure and seed production and seed characteristics, along a groundwater depth gradient in the Gurbantunggut Desert of Central Asia. The result shows that for H. ammodendron, groundwater depth of 15 m is its survival and regeneration limit, beyond which this species cannot grow. However, for H. persicum, this limit does not apply. Instead, declined groundwater depth promotes a reproduction strategy with low seed quantity, high quality, and a high germination rate for H. ammodendron. Ultimately, H. ammodendron exhibits a tighter regeneration trait coordination, with a reasonable age structure being crucial for its population continuation and environmental adaptation. In contrast, H. persicum demonstrates higher resource acquisition and reproductive ability, along with tolerance to groundwater depth decline. In conclusion, if the groundwater depth decline continues, the continuation of H. ammodendron will be seriously threatened but H. persicum will not be. This study is beneficial for evaluating the future trend of vegetation cover in desert region and planning water resources management in Central Asia.

Vegetation and Evapotranspiration Analyses on Climate Maps

This study focuses on the investigation of evapotranspiration (ET) processes under the climatic and geographical characteristics of Turkey. Evapotranspiration refers to the process by which plants transfer water vapour to the atmosphere and is an important part of the water cycle. Vegetation cover, climatic conditions and topographic structures in different regions of Turkey are among the main factors affecting evapotranspiration. In this study, the seasonal and annual variations of evapotranspiration in different regions of Turkey are discussed and the importance of this process in water resources management, agriculture, ecosystems and climate change is emphasised. This research focuses on conducting an evapotranspiration analysis in Turkey by employing imagery data from NASA Global Land Data Assimilation System Version 2 (GLDAS-2), MODIS, TerraClimate, SMAP Level-4, and Penman-Monteith-Leuning Evapotranspiration V2 (PML_V2) sources. Evapotranspiration, a pivotal process in the hydrological cycle, significantly impacts water resource management and ecosystem dynamics. This study aims to provide a comprehensive assessment of evapotranspiration dynamics across diverse regions within Turkey. For Turkey, SSM data between 2016-2022 and LST data between 2000-2022 were obtained from MODIS images. In the study, regression analyses were performed with evapotranspiration values and SSM and LST data. The best result was a medium level relationship (R 0.56) between evapotranspiration generated from SMAP Level-4 data and LST. A high correlation (R 0.87) was observed with SSM. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation data between 1981 and 2023 and Surface pressure (PS) data between 1981 and 2023 were obtained from MERRA image. Regression analyses were performed between evapotranspiration data and PS and Precipitation values. A moderate relationship (R 0.37) was observed between evapotranspiration and PS generated from MOD16A2 V105 data. A moderate relationship (R 0.55) was observed between evapotranspiration and precipitation generated from TerraClimate data. This study aims to contribute to the development of strategies to effectively manage water resources and improve agricultural sustainability by analysing evapotranspiration in various regions of Turkey. Understanding evapotranspiration processes under the climatic diversity and geographical structure of Turkey will be an important step in planning and managing the future use of water resources.

Analysis of Vegetation Environmental Stress and the Lag Effect in Countries along the “Six Economic Corridors”

Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

Changes in Vegetation NDVI and Its Response to Climate Change and Human Activities in the Ferghana Basin from 1982 to 2015

Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.

Declined terrestrial ecosystem resilience

AbstractTerrestrial ecosystem resilience is crucial for maintaining the structural and functional stability of ecosystems following disturbances. However, changes in resilience over the past few decades and the risk of future resilience loss under ongoing climate change are unclear. Here, we identified resilience trends using two remotely sensed vegetation indices, analyzed the relative importance of potential driving factors to resilience changes, and finally assessed the risk of future resilience loss based on the output data of eight models from CMIP6. The results revealed that more than 60% of the ecosystems experienced a conversion from an increased trend to a declined trend in resilience. Attribution analysis showed that the most important driving factors of declined resilience varied regionally. The declined trends in resilience were associated with increased precipitation variability in the tropics, decreased vegetation cover in arid region, increased temperature variability in temperate regions, and increased average temperature in cold regions. CMIP6 reveals that terrestrial ecosystems under SPP585 are expected to experience more intense declines in resilience than those under SSP126 and SSP245, particularly in cold regions. These results highlight the risk of continued degradation of ecosystem resilience in the future and the urgency of climate mitigation actions.

Integrating ecosystem service supply–demand and ecological risk assessment for urban planning: A case study in Beijing, China

The balance between ecosystem service supply–demand and landscape ecological risk are two crucial aspects influencing the sustainable development of regional ecosystems. Current evaluations ignore these aspects and lead to partial landscape planning in urban areas. As a result, a framework was built for regional planning in urban areas based on multidimensional evaluations of ecosystems for high-efficiency land use planning. First, to determine the ecosystem service balance in regional scale, the supply and demand of five ecosystem services were quantified—biodiversity conservation, carbon sequestration, water conservation, food production, and landscape recreation. Second, landscape ecological risks were identified using the “natural–social–landscape” research framework combined with spatial principal component analysis. Third, spatial clustering analysis of ecosystem service supply–demand ratios and landscape ecological risks was then performed through spatial autocorrelation, which aimed to identify areas for protection and restoration priority. Finally, GeoDetector was used to determine the main factors influencing ecosystem service balance and landscape ecological risks and develop targeted planning measures. The results revealed an imbalance in total ecosystem service supply–demand in Beijing's plain area, coupled with a high level of landscape ecological risk. The combined ecosystem service supply–demand ratios exhibited a significant negative correlation and aggregation with landscape ecological risk, and the significant area accounted for approximately 31.9% of the total area. Priority areas for protection and restoration accounted for 10.39% and 19.94%, respectively, of the total regional area. Land use, distance to settlements, and vegetation cover were the primary environmental variables influencing the distributions of the combined ecosystem service supply–demand ratios and landscape ecological risk. So, this study emphasizes the need to strengthen intensive land use and prevent the uncontrolled expansion of urban land and settlements. It is crucial to enhance urban green infrastructure construction, promote the development of biodiversity-friendly agriculture, and implement measures such as afforestation restoration to increase regional vegetation cover. Overall, by integrating a framework of ecosystem services and landscape ecological risk, a comprehensive scientific reference can be provided for the efficient land use and sustainable development planning in urban areas.

SUBRECENT POLLEN ASSEMBLAGES IN ALLUVIAL DEPOSITS OF THE DON AND KUBAN RIVERS AND THEIR SIGNIFICANCE FOR PALAEOGEOGRAPHIC RECONSTRUCTIONS

The paper presents the results of studying modern alluvial deposits of the Don and Kuban rivers by the pollen analysis method. The study was carried out to clarify methodological issue, including the movement of pollen and spores by flowing waters. The obtained data show that pollen assemblages of river sediments formed in the process of pollen mixing by water and air characterize the composition of the regional vegetation cover rather than local nearriver plant groups. According to the results for the subrecent sediments of the Don River the transfer of pollen grains and spores by water was insignificant, which can be clearly seen at the border of the forest-steppe and steppe zones. Pollen assemblages of the forest-steppe zone contain 50% of tree species pollen, while in the steppe zone, including its northern part, tree species make up less than 30-35%. Sporadic forest elements such as Picea pollen, Lycopodium species spores and Sphagnum mosses in alluvial deposits of the steppe section of the Don River, as well as in the subrecent sediments of the Sea of Azov, could be neglected in the palaeoreconstructions. The composition of subrecent pollen assemblages of the Kuban River sediments is less variable from the middle course to the mouth with rather stable ratio of components. Pollen of the Caucasian flora elements (Fagus orientalis, Carpinus caucasica) is poorly dispersed by water from high and midmountain landscapes of the upper reaches of the river. The comparison of pollen assemblages from alluvial and marine (the Sea of Azov) sediments have shown that the distortion of fossil assemblages’ composition due to material input by water is minimal

Quantitative Holocene climate reconstruction and anthropogenic impact analysis based on the pollen records in peat sediment in Southern China

The quantitative reconstruction of Holocene paleoclimate is pivotal for unraveling the evolution of East Asian Monsoon (EAM). Some recent studies have highlighted the escalating human activities in the late Holocene, which could potentially pose significant challenges to the precise quantitative reconstruction of paleoclimate. In this study, we undertake a quantitative reconstruction of Holocene climate and human influence index (HII) based on pollen data from the Shiwangutian (SWGT) in Southern China. This is achieved by developing and applying a pollen-based calibration model utilizing Locally Weighted Average-Partial Least Squares Regression (LWWA-PLS) and the Modern Analogue Technique (MAT). Our findings reveal that evergreen forests experienced expansion between 11.6 and 9.0 cal ka BP, coinciding with elevated Mean Annual Precipitation (Map) and Mean Annual Temperature (Mat) levels. These patterns signify a progressively warm and wet climate during this period. Subsequently, evergreen forests achieved their maximum abundance between 9.0 and 4.0 cal ka BP, aligning with a notable increase in vegetation richness, indicating a warmer and wetter climate during the mid-Holocene. Notably, during the interval of 6.0–4.0 cal ka BP, the Map, Mat, and Precipitation of Warmest Month (Mpwa) reached the Holocene optimum, approximately 14% higher than modern. Consequently, we deduce that in the early and middle Holocene, when the monsoon was particularly strong, synchronous changes in precipitation fostered the regional expansion of evergreen broad-leaved forests. Furthermore, the record demonstrates a substantial reduction in forest cover and a noteworthy increase in the HII value since 4.0 cal ka BP, likely attributable to anthropogenic impacts. Our analysis suggests that the influence of anthropogenic activities surpassed that of natural climate factors in shaping regional vegetation cover. These findings offer insights into potential drivers of climate change. As a preliminary conclusion, we propose that the summer insolation, ice sheets, and meltwater fluxes were the primary controlling factors for climate variations during the early to mid-Holocene in Southern China.

Cloud-Based Remote Sensing and Analysis of Vegetation Cover Changes in Key Regions of Oceania

The main objective of this research is to use cloud platforms to conduct a shallow survey of vegetation cover variations in Oceania. It is well-known that compared with the northern hemisphere, Oceania has a more unique ecosystem. The geographic position of Oceania is close to the equator. Therefore, the climate of some regions in Oceania is warm and has full precipitation, which is different from that in the Northern Hemisphere. This considerably influences changes in vegetation cover and makes comprehending vegetation cover tendency important for environmental protection measures. The change in vegetation cover from 2015 to 2022 was analyzed using cloud technology and remote sensing data. My findings mainly include the expansion and reduction of vegetation cover in major regions of Oceania. These results provide valuable insight into the dynamic properties of Oceanian ecosystems. This study contributes to a deeper understanding of the ecological environment in Oceania and highlights the potential of cloud platforms in remote sensing and ecological monitoring. These findings have important implications for environmental policies, biodiversity conservation, and sustainable resource management in the region.

Impact of Soil Temperature and Precipitation on Vegetation Cover Over Selected Stations in Iraq

Records of precipitation and soil temperature, two of the most significant climatic elements impacting vegetation cover, were gathered as annual and monthly data over a period of 20 years from the European Center for Long-term Numerical Weather Forecasts. The goal of this study was to ascertain the impact of plant cover on climatic variations. The study’s final findings revealed that Mosul station had the greatest value of vegetation at 0.24 and Basra station had the lowest value at 0.15. The Mosul station recorded the maximum amount of precipitation, 1400 mm in the northern and central parts during the winter, and the lowest amount, 8 mm, during the fall and summer months in the districts west of the Rutba station. Using the Pearson test, it was discovered that the relationship between vegetation cover and soil temperature is inverse, and this, in turn, plays a significant role in the lack of vegetation cover in the southern regions because of nature. The desert of the region, as well as the lack of precipitation and high temperatures, is responsible for the region’s lack of vegetation. The highest value reached by the soil temperature was in the year 2018 at the Basra station.

Impact of climate variability and environmental policies on vegetation dynamics in the semi-arid Tigray

Anthropogenic and climate-related phenomena are among the main factors responsible for variations in vegetation structure and composition worldwide. However, studies that integrate the effects of human activities and climate variability in fragile tropical ecosystems, including the semi-arid Tigray region, are lacking. The objective of this study was to examine the effects of climate variability and environmental policy changes on the spatial distribution and pattern of vegetation cover in the semi-arid Tigray region of Ethiopia over the past four decades. We used satellite-based vegetation index (normalized difference vegetation index) and monthly rainfall data to analyze the relationship between vegetation cover and climatic variability. Residual analysis was also used to further disentangle the effects of climatic variability and environmental policy on vegetation cover. The regression analysis (r2 = 0.19) showed an insignificant causal relationship between vegetation dynamics and precipitation over the 41-years study period. This study also highlighted negative impact of the global rise in temperature on vegetation cover due to water stress caused by evapotranspiration. On the other hand, the residual analysis results (r = − 0.55, z-stat = − 11.58, p < 0.01) indicated a strong relationship between vegetation change and environmental policies implemented within the specified study period. Overall, the study revealed that environmental policies had a greater impact than climate variables on vegetation. Policymakers should, therefore, prioritize implementing effective environmental policies to restore degraded ecosystems and mitigate the effects of climate change.

Quantitative analysis of fractional vegetation cover in southern Sichuan urban agglomeration using optimal parameter geographic detector model, China

Vegetation is a main part of ecosystems and an essential indicator for monitoring changes in terrestrial ecosystems. It is crucial for us to discover the temporal and spatial features and potential drivers of vegetation change to promote regional ecological environment protection and management. However, it can be difficult to pinpoint the causes of vegetation change when considering both human activity and climate change. We used trend and stability method to study the temporal and spatial patterns of vegetation evolution in the South Sichuan Urban Agglomeration (SSUA) from 2001 to 2021 with the Google Earth Engine (GEE) platform. An optimal parameter-based geographical detector (OPGD) model was applied to optimize the spatial scale and zoning effect of geographic data, effectively solving the problem of spatial data heterogeneity. It compensates for the inadequacies of conventional approaches that neglect the modifiable areal units problem (MAUP), and improving the science and accuracy of quantitative analysis and identification of vegetation drivers. We studied demonstrate that (1) During the last 21 years, Fractional Vegetation Cover (FVC) has generally been in good condition, with a multi-year average FVC greater than 0.4 of 71.74 %, and the vegetation is significantly characterized by a low fluctuation of 78.16 %. However, there is a significant trend of vegetation degradation, accounting for 8.89 %, mainly in the main urban areas of Neijiang and Zizhong County, Lu County of Luzhou City, Gao County of Yibin City, and other areas with rapid urbanization. In general, FVC is low in the built-up areas of towns and along transportation roads, while the mountainous and agricultural areas have a high level of vegetation cover. (2) The OPGD model detection showed the optimal spatial scale of vegetation cover in this study region was 2 km. Optimal discrete parameter combinations for slope, elevation, temperature and GDP are quantile breaks with 9 intervals, which contribute to improved scientific accuracy and precision in studies of vegetation change and its drivers. (3) The explanatory power of urbanization rate, land use type, slope, GDP, population density, and average annual precipitation were all above 20 % and were the main drivers of vegetation change. Moreover, any two factors interacted in a nonlinear enhancement and a bi-variable enhancement, increasing the impact on vegetation spatial variation. When the slope is 26.9°∼87.4°, the elevation is 967 m ∼ 4207 m, the average annual temperature is 0.18 °C ∼ 13.6 °C, the average annual precipitation is 328 mm ∼ 439 mm, the GDP is 4.07 ∼ 5.23 million yuan km−2, the population density is 12.7 ∼ 21.1 people/km2, the urbanization rate is 33.4 %∼37.7 %, and the land-use type is forest land, the FVC value is the highest and suitable for vegetation growth. The study showed that using the OPGD model to detect the zoning effects and spatial scale of the explanatory variables solves for the shortcomings of the previous methods for variable regional units and discrete methods, may more precisely explore the features of temporal and spatial changes in the vegetation and the driving mechanisms, offers scientific references for environmental conservation and long-term economic growth in the region.

Spatio-temporal variations of vegetation cover in semi-arid regions and its response to climate change: A case study of Xilin Gol, Inner Mongolia, China

The quantitative analysis of spatio-temporal variations of vegetation cover and its correlation with climate are of great significance for understanding of ecological environment, ecological civilization construction, and sustainable development in semi-arid areas. We investigated the spatio-temporal variations of normalized difference vegetation index (NDVI) and its response to climate change during 2000-2020 in Xilin Gol, Inner Mongolia, by using trend analysis, regression analysis and partial correlation analysis based on the data of MODIS-NDVI, tempe-rature, precipitation, digital elevation model. The results showed that vegetation cover in Xilin Gol had been increased from 2000 to 2020, which generally included three phases, i.e., stable fluctuation, rapid growth, and steady growth. The mean NDVI showed a zonal increasing distribution from southwest to northeast, and had a strong correlation with elevation and population density in Xilin Gol region. The high values of NDVI were mainly in the east, with a significant increasing trend, and the low values were in the southwest, with a local degradation. The sensitivity of vegetation cover to climate change showed spatial and temporal variations. The spatial variation of vegetation was more sensitive to temperature and the interannual variation was sensitive to annual precipitation. In summary, vegetation cover improved overall in Xilin Gol, but there was degradation in some areas. We should formulate differentiated and precise vegetation restoration and ecological environmental protection policies.

Quantifying the relative impacts of climate and human activities on vegetation change in Hunan Province between 2000 and 2015

Since1999, Hunan Province has embarked on a series of ecological projects to return farmland to forests across the province to explore the impacts of anthropogenic policies and actions on changes in vegetation cover between 2000 and 2015.It is important to understand the impacts of anthropogenic and climatic changes on regional vegetation cover change is an important guide for formulating reasonable environmental protection and restoration strategies in the region .this paper analysed the influence of climate and anthropogenic activities on the change of vegetation cover of Hunan Province during 2000-2015, which combined with an improved vegetation-climate residual regression model at the meta-scale. During 2000-2015, the contribution of anthropogenic activities to the increase of vegetation cover was 49%, 53%, 62% and 66% for unconverted forest land, grassland, unused land and water area respectively, while the contribution of climatic factors was 51%, 47%, 38% and 44% respectively. At the same time, all the land use types of contributions to vegetation cover change in Hunan Province is positive, and the land type without forest land change has the largest contribution to vegetation cover change in Hunan Province at 66.28%, while the land type where other land is converted to unused land has a lower contribution to vegetation cover change.

Analysis of Spatial and Temporal Changes in Vegetation Cover and Driving Forces in the Wuding River Basin, Loess Plateau

Vegetation cover in the Loess Plateau region is an important component of ecological protection in the Yellow River Basin, and this study provides a scientific reference for further vegetation restoration. Based on Landsat images and related data, we utilized the dimidiate pixel model and Geodetector method to study the vegetation cover in the Wuding River Basin from 2000 to 2022. The results indicated the spatial and temporal distribution of the vegetation cover and its changes over the study period. Additionally, the driving factors influencing its spatial changes were also uncovered. We also propose a land use shift vegetation cover contribution formula to quantify the effect of land type change on the FVC. The study showed that (1) the overall vegetation cover of the watershed increased significantly, and the FVC showed an increasing trend from 2000 to 2013 and a slow decline from 2013 to 2022, with the gradual transformation of low-graded FVC into a higher graded one. (2) The FVC increased spatially from northwest to southeast, and the trend of future changes is mainly decreasing. (3) The strongest explanatory power for the FVC change is the land use type and its interactive combination with rainfall. (4) The conversion of grassland to cropland contributes the most to the vegetation cover at 1.52%, and the increase in the cropland area is more conducive to the increase in the vegetation cover.

Ionospheric compensation in L-band InSAR time-series: Performance evaluation for slow deformation contexts in equatorial regions

Multi-temporal Synthetic Aperture Radar Interferometry (MT-InSAR) is the only geodetic technique allowing to measure ground deformation down to mm/yr over continuous areas. Vegetation cover in equatorial regions favors the use of L-band SAR data to improve interferometric coherence. However, the electron content of ionosphere, affecting the propagation of the SAR signal, shows particularly strong spatio-temporal variations near the equator, while the dispersive nature of the ionosphere makes its effect stronger on low-frequencies, such as L-band signals. To tackle this problem, range split-spectrum method can be implemented to compensate the ionospheric phase contribution. Here, we apply this technique for time-series of ALOS-PALSAR data, and propose optimizations for low-coherence areas. To evaluate the efficiency of this method to retrieve subtle deformation rates in equatorial regions, we compute time-series using four ALOS-PALSAR datasets in contexts of low to medium coherence, showing slow deformation rates (mm/yr to cm/yr). The processed tracks are located in Ecuador, Trinidad and Sumatra, and feature 15 to 19 acquisitions including very high, dominating ionospheric noise, corresponding to equivalent displacements of up to 2 m. The correction method performs well and allows to reduce drastically the noise level due to ionosphere, with significant improvement compared with a simple plane fitting method. This is due to frequent highly non-linear patterns of perturbation, characterizing equatorial TEC distribution. We use semivariograms to quantify the uncertainty of the corrected time-series, highlighting its dependence on spatial distance. Thus, using ALOS-PALSAR-like archive, one can expect a detection threshold on the Line-of-Sight velocity ranging between 3 and 6 mm/yr, depending on the spatial wavelength of the signal to be observed. These values are consistent with the accuracy derived from the comparison of velocities between two tracks in their overlapping area. In the case studies that we processed, the time-series corrected from ionosphere allows to retrieve accurately fault creep and volcanic signal but it is still too noisy for retrieving tiny long-wavelength signals such as slow (mm/yr) interseismic strain accumulation.

Восстановление пастбищ, обедненных растительным покровом, засушливых регионов Нижнего Поволжья

Purpose. To study the methods of restoration (reclamation) of disturbed pasture lands based on the comparative aspect of the yield of perennial fodder grasses when creating pastures in the arid regions of the Lower Volga region. Materials and Methods. In the course of the experiment, a comparative study of the ecological and biological properties of perennial fodder grasses was carried out (Colognes rush, Desert wheatgrass, Sandy spare, Couch grass elongated. The experiment was carried out on a prepared field (plowing, harrowing), divided into experimental plots of 50 m2 in size. It was carried out at the end of autumn (November) to a depth of 20-30 mm with a row spacing of 0.45 m. The repetition of reseeding in the experiment was two times. Results. Variation in the yield of dry eaten mass between the control variant of natural pastures and the experimental plots of the tested grasses has been experimentally proven. Among the tested herbs, the highest yield was shown by sandy sirloin (III experimental plot), which amounted to 2.43 t/ha of dry mass eaten. The excess of this indicator relative to experimental plot II (desert wheatgrass) was 7.05%, experimental plot I (rush hair) – 18.54%, experimental plot IV (elongated wheatgrass) – 28.57%, and relative to the control plot (natural forms) the increase in yield was 3.4-4.3 times, depending on the type of herbs tested. Conclusion. Pasture grasses occupy a key place in the development of productive pastures in the arid zone of the Lower Volga region. They have high water and energy efficiency regardless of low humidity conditions, providing stable grass production to support livestock. The bearing capacity of rangelands can be improved with available technologies if they are applied and adapted on a long-term basis. Low-productive rangelands that lead to imbalances in forage production must be restored through low-cost methods such as reseeding to provide more and higher quality forage for livestock and soil protection. Reseeding can provide high plant density at low cost and is a cheap means of providing adequate feed for livestock and increasing income from grazing. An increase in yield by 3.4-4.3 times relative to the control plot (natural forms) is achieved by reseeding natural pastures with the appropriate types of grasses suitable for macroclimatic subregions.