Changes In Vegetation Cover Research Articles

Urban classification of the built-up and seasonal variations in vegetation: A framework integrating multisource datasets

The growing emphasis on integrating natural elements into urban environments to counteract adverse impacts has increased research into the role of vegetation within cities. Nonetheless, the inclusion of vegetation in urban classifications remains limited due to the associated challenges, such as time and cost constraints related to its measurement. This study introduces a classification framework that integrates spatio-temporal vegetation characteristics and built-up density variables at the neighbourhood scale using open-access datasets and remote sensing for data retrieval. Through a combination of statistical and spatial autocorrelation analyses and the application of two distinct classification methods to the 15 assessed variables, we identified four primary urban clusters. These clusters are further refined considering vegetation categories, which encompass general vegetation cover, vegetation cover levels, and vegetation cover changes tracked across two different seasons, corresponding to winter and summer. This comprehensive classification not only characterizes the built-up elements but also elucidates the distribution of vegetation showing the nuances in vegetation within similar urban clusters. The resulting classifications aim to bridge the existing gap in urban studies by incorporating the spatio-temporal scale and cover changes of vegetation. This framework serves as a precedent for creating context-specific classifications, which can be subsequently used for conducting further assessments on various urban issues. The outcomes of this study offer an overview of a study area, encompassing urban density and seasonal variations in vegetation. This information facilitates the identification of specific areas where additional attention may be warranted, particularly concerning the provision of ecosystem services and the development of strategies to enhance urban microclimates and thermal comfort, among other aspects.

Evaluating the impact of private land conservation with synthetic control design.

Programs to protect biodiversity on private land are increasingly being used worldwide. To understand the efficacy of such programs, it is important to determine their impact: the difference between the program's outcome and what would have happened without the program. Typically, these programs are evaluated by estimating the average program-level impact, which readily allows comparisons between programs or regions, but masks important heterogeneity in impact across the individual conservation interventions. We used synthetic control design, statistical matching, and time-series data to estimate the impact of individual protected areas over time and combined individual-level impacts to estimate program-level impact with a meta-analytic approach. We applied the method to private protected areas governed by conservation covenants (legally binding on-title agreements to protect biodiversity) in the Goldfields region of Victoria, Australia using woody vegetation cover as our outcome variable. We compared our results with traditional approaches to estimating program-level impact based on a subset of covenants that were the same age. Our results showed an overall program-level impact of a 0.3-0.8% increase in woody vegetation cover per year. However, there was significant heterogeneity in the temporal pattern of impact for individual covenants, ranging from -4 to +7% change in woody vegetation cover per year. Results of our approach were consistent with results based on traditional approaches to estimating program-level impact. Our study provides a transparent and robust workflow to estimate individual and program-level impacts of private protected areas.

Effects of Sage-Grouse Habitat Restoration Efforts on Pollination Networks in an Arid Ecosystem

On publicly managed lands of western North America, canopy removal is practiced as a habitat improvement for sage grouse (Centrocercus species), often with the goal of converting dominant vegetation cover from pinyon pine (Pinus edulis) and juniper (Juniperus spp.) to sagebrush (Artemisia spp.). However, it remains unclear whether habitat conversion practices impact other species of conservation concern, especially pollinators, which are sensitive to changes in vegetation cover. Here we test how bee-flower assemblages differ between pinyon-juniper and sagebrush habitats and whether removal of canopy by mastication affects bee-flower networks.Three important findings emerged: 1) linkage density (a measure of diversity) of bee-flower interactions was 33% higher in sagebrush habitats; however, mastication treatments were associated with reduced network specialization and there was evidence of interannual variation in network indices; 2) the most-visited floral taxa in pinyon-juniper sites were woody plants (Amelanchier, Opuntia, Prunus) but, in sagebrush sites forbs (Heterotheca, Eriogonum) were more frequently visited; however, weedy taxa including Cirsium and Melilotus were highly utilized in both habitats; and 3) site physiography affected bee assemblages; incident radiation (heat load index, HLI) had larger effects than relative site position in conservation areas, with higher bee abundance and richness at cool sites with low canopy cover.We conclude that conversion of sites from pinyon-juniper to sagebrush is not likely to negatively impact bee-flower interactions in comparison with nontreated sagebrush habitats. Several native forbs and woody species highly visited by bees can be targeted for site restoration efforts, but eradication of “weedy” taxa (Cirsium and Melilotus) may reduce habitat availability. Managers should also consider site physiography when prioritizing treatment landscapes, with an emphasis on prioritizing conservation in habitats with low HLI.

Impact of Land Use/Cover Changes on Soil Erosion by Wind and Water from 2000 to 2018 in the Qaidam Basin

Assessing the impact of land use and land cover change (LUCC) on soil erosion by wind and water is crucial for improving regional ecosystem services and sustainable development. In this study, the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE) were used to reveal changes in the extent of soil erosion by wind and water in the Qaidam Basin from 2000 to 2018 and the impact of LUCC on them. From 2000 to 2018, with global climate change, the areas and intensities of soil erosion by wind decreased, whereas those of soil erosion by water increased. With increased human activities, approximately 12.96% of the total area underwent conversion of the type of use: the areas of cropland, woodland, grassland, and construction land increased, whereas the areas of shrubbery, desert, and other unused land decreased. Land use/cover changes are positive to the soil erosion of water but negative to the soil erosion of wind. Among them, the changes in vegetation coverage of other unused land and grassland contributed to 83.19% of the total reduction in soil erosion by water. Converting other unused land to grassland reduced the total reductions in soil erosion by wind by 94.69%. These results indicate that the increase in vegetative cover and area of grasslands in the Qaidam Basin had a positive impact on the reduction in soil erosion. It is recommended that the arrangement of grasses, shrubs, and trees be optimized to prevent compound erosion by wind and water for protecting regional ecological environments.

Vegetation Dynamics of Sub-Mediterranean Low-Mountain Landscapes under Climate Change (on the Example of Southeastern Crimea)

In the context of a changing environment, understanding the interaction between vegetation and climate is crucial for assessing, predicting, and adapting to future changes in different vegetation types. Vegetation exhibits high sensitivity to external environmental factors, making this understanding particularly significant. This study utilizes geospatial analysis techniques, such as geographic information systems, to investigate vegetation dynamics based on remote sensing data and climatic variables, including annual air temperature, annual precipitation, and annual solar radiation. The research methodology encompasses data collection, processing, and analysis, incorporating multispectral imagery and multilayered maps of various parameters. The calculation of the normalized difference vegetation index serves to evaluate changes in vegetation cover, identify areas experiencing variations in green biomass, and establish strategies for the future development of different vegetation types. During the period from 2001 to 2022, the average normalized difference vegetation index value in the Southeastern Crimea region amounted to 0.443. The highest average values were recorded in the year 2006, reaching a magnitude of 0.469. Conversely, the lowest values were observed in the years 2001–2002, constituting 0.397. It has been ascertained that an overarching positive trend in the evolution of NDVI values from 2001 to 2022 is apparent, thus implying a notable augmentation in vegetative biomass. However, adversarial trends manifest in discrete locales adjacent to the cities of Sudak and Feodosia, along with the coastal stretches of the Black Sea. Correlation analysis is employed to establish relationships between vegetation changes and climatic indicators. The findings contribute to our understanding of the vulnerability of various vegetation types and ecosystems in the Southeastern Crimea region. The obtained data provide valuable insights for the development of sustainable vegetation resource management strategies and climate change adaptation in the region.

Vegetation cover change and its response to climate extremes in the Yellow River Basin

Extreme climate events have increased in frequency and severity under the background of climate change, with vegetation growth exhibiting a sensitive response to them. By assimilating GIMMS NDVI and MODIS NDVI using the Residual Network, we obtained a long time series and high resolution NDVI dataset of the Yellow River Basin (YRB). The dataset was utilized for examining the spatiotemporal variability of NDVI and analyzing the response of vegetation cover to climate extremes with meteorological data. Our findings reveal the following: (1) A significant rise in NDVI was seen in the YRB, displaying a mean growth rate of 0.019/10a (p < 0.001). However, seasonal differences exist. The mean NDVI of multi-year declines from southeast to northwest, while the overall trend of vegetation cover improves. (2) The NDVI response to extreme temperature exhibits noticeable spatiotemporal differences. Daytime extreme high temperature in the northern YRB is negatively correlated with NDVI, while they are positively correlated in the lower YRB and the southern part of the middle YRB. Nighttime extreme high temperature exhibits a positive correlation with NDVI. Overall, NDVI displays a stronger response to extreme precipitation than to extreme temperature, with a negative correlation with CWD and a positive correlation with PRCPTOT. (3) The NDVI demonstrates a lagged response to climate extremes in the YRB, with a greater lag in response to extreme temperature than extreme precipitation. The research findings can provide scientific support for the future management and planning of vegetation in the YRB, as well as contribute to the promotion of ecological environment regulation and sustainable development.

Determining the response of riparian vegetation and river morphology to drought using Google Earth Engine and machine learning

Riparian vegetation composition and channel morphology are susceptible to long-term alterations caused by external stressors, including climate-change-induced droughts and engineered infrastructures. The objectives of this study were to (1) quantify trends in riparian vegetation and channel/floodplain morphology over large spatial (∼290 km) and temporal scales (∼30 years) and (2) investigate the relationships between hydroclimatic drivers and changes in riparian vegetation and channel morphology. We implemented a random forest classifier via a machine learning technique in Google Earth Engine. The study area was a 290 km reach of the Rio Grande located in New Mexico, USA. We used the combination of remotely sensed data and products (e.g., Landsat imagery, Normalized Difference Vegetation Index (NDVI), and land cover) to characterize vegetation, vegetation cover changes, and river morphology shifts from 1984 to 2020. The trend analysis revealed increased vegetated areas and NDVI (0.0004/yr) during long-term drought. The channel experienced a reduction in width associated with vegetation encroachment and the formation of stable vegetated islands. The streamflow hydrograph characteristics were positively correlated with vegetation cover and channel morphology. Our study contributes novel insights into the long-term riparian ecosystem dynamics under drought stress, informing drought impact mitigation and ecosystem management in arid and semi-arid regions.

Analysis of Spatial-Temporal Changes and Driving Factors of Vegetation Coverage in Jiamusi City

This study of vegetation coverage in Jiamusi City provides theoretical support for local urban development, land use, and ecological environmental protection. Based on the land cover data and Landsat remote sensing image data from 2000 to 2020, the vegetation cover and land use data of Jiamusi City were extracted. The study includes the following aspects: (1) an analysis of the spatio-temporal changes in vegetation coverage; (2) analysis of the land use situation in Jiamusi City; and (3) investigation of the impact of natural and human factors on vegetation coverage in Jiamusi City using the Geodetector model. The results show that (1) over the past 20 years, the vegetation coverage of Jiamusi has shown a decreasing trend, declining from 25.22% in 2000 to 17.13% in 2020, representing a decrease of 32%. In terms of spatial distribution, the areas of Fuyuan City and Tongjiang City have experienced more significant decreases in vegetation coverage, decreasing by 73.6% and 54.0%, respectively. (2) The land use pattern of Jiamusi City has undergone significant changes during the study period; except for paddy fields (PF), unused land (UL), and construction land (CL), the areas of all the land categories have decreased. The ranking of the single land use dynamic degree in terms of magnitude is as follows: PF, UL, CL, dry farmland (DF), vegetation coverage land (VCL), and wetland (WET). (3) The changes in vegetation coverage were influenced by both natural and human activities and, according to the Geodetector results, the main influencing factors were CL and DF. The key findings of this study emphasize the need for comprehensive land use planning and ecological environmental protection that focus on sustainable development and conservation practices, and lay the groundwork for future ecosystem management and urban planning efforts in Jiamusi City.

Vegetation cover dynamics on the northeastern Qinghai-Tibet Plateau since late Marine Isotope Stage 3

Knowledge of long-term changes in vegetation cover is essential for paleoenvironmental reconstruction and Earth system modeling. The vegetation on the northeastern Qinghai-Tibet Plateau (QTP) is highly sensitive to climatic changes, but studies of long-term changes in the vegetation cover of this region are lacking. To better understand the changes in the regional vegetation cover since late Marine Isotope Stage (MIS) 3, we obtained a pollen record from Luanhaizi Lake and used it to quantitatively reconstruct changes in the cover of trees and grasses using the random forest method. The pollen spectra show that the vegetation of the Luanhaizi Lake area was probably alpine tundra from late MIS3 to the Last Glacial Maximum, after which it changed to alpine steppe with alpine shrub and sparse forest at lower elevations during the last deglaciation. Alpine steppe and alpine meadow dominated the vegetation during the Holocene, with sparse forest in the surrounding low-elevation areas. The quantitative vegetation cover reconstruction suggests that the vegetation cover of the Luanhaizi Lake area was low (20–30%) during 47.0–20.0 ka. The tree cover then increased from ∼3% to ∼10%, and the grass cover increased from ∼20% to ∼45% during the last deglaciation (20.0–11.9 ka). The increasing Northern Hemisphere summer insolation caused increases in the regional temperature, meltwater supply, and monsoon precipitation, which promoted the development of steppe vegetation. The continued increases in insolation and monsoonal precipitation during the Holocene further increased the tree cover, which reached a maximum of 17.4% at ∼7.2 ka. Vegetation cover reconstructions from two other sites on the eastern QTP for the last deglaciation indicate contrasting patterns of changes, likely due to contrasts in elevation, climate, and environment.

Possible impacts of vegetation cover increment on the relationship between winter snow cover anomalies over the Third Pole and summer precipitation in East Asia

Snow cover over the Tibetan Plateau (TP)–the Third Pole of the earth has been recognized as a reliable signal of summer floods or droughts in East Asia (EA). The distribution of snow cover can be influenced by vegetation, however, the impacts of changes in cover of non-growing season vegetation–withered grass stem over TP on the climatic effects of snow cover remains poorly understood. Here, we showed that the relationship between TP winter snow cover (TPWSC) and EA summer precipitation (EASP) strengthened starting in the early 1990s but weakened after the early 2000s. The weakening of the TPWSC–EASP relationship was linked to the effects of vegetation cover increment (VCI) on winter and spring snow cover over the TP. A possible mechanism behind this linkage is that VCI leads to a shortened persistence of TPWSC anomalies and weakened surface diabatic heating anomalies in spring. Consequently, the influences of TP thermal forcing on the downstream atmospheric circulation in summer were altered, resulting in a different pattern of EASP anomalies. These findings highlight the importance of snow—vegetation feedback and its potential to alter the effectiveness of snow cover in seasonal climate prediction.

Adaptive High Coherence Temporal Subsets SBAS-InSAR in Tropical Peatlands Degradation Monitoring

Peatlands in Southeast Asia have been undergoing extensive and rapid degradation in recent years. Interferometric Synthetic Aperture Radar (InSAR) technology has shown excellent performance in monitoring surface deformation. However, due to the characteristics of high vegetation cover and large dynamic changes in peatlands, it is difficult for classical InSAR technology to achieve satisfactory results. Therefore, an adaptive high coherence temporal subsets (HCTSs) small baseline subset (SBAS)-InSAR method is proposed in this paper, which captures the high coherence time range of pixels to establish adaptive temporal subsets and calculates the deformation results in corresponding time intervals, combining with the time-weighted strategy. Ninety Sentinel-1 SAR images (2019–2022) in South Sumatra province were processed based on the proposed method. The results showed that the average deformation rate of peatlands ranged from approximately −567 to 347 mm/year and was affected by fires and the changes in land cover. Besides, the dynamic changes of peatlands’ deformation rate a long time after fires were revealed, and the causes of changes were analyzed. Furthermore, the deformation results of the proposed method observed 2 to 127 times as many measurement points as the SBAS-InSAR method. Pearson’s r (ranged from 0.44 to 0.75) and Root Mean Square Error (ranged from 50 to 75 mm/year) were calculated to verify the reliability of the proposed method. Adaptive HCTSs SBAS-InSAR can be considered an efficient method for peatland degradation monitoring, which provides the foundation for investigating the mechanisms of peatland degradation and monitoring it in broader regions.

Enhancing resilience against geological hazards and soil erosion through sustainable vegetation management: A case study in Shaanxi Province

As an important component of terrestrial ecosystems, vegetation performs a necessary function in linking the atmosphere, hydrosphere, biosphere as well as soil sphere. The response of vegetation to its driving factors has been a hot research issue that needs to be further explored. Here, the temporal and spatial changes in vegetation cover in Shaanxi Province from 2000 to 2020 was characterized, and the responses to topographic elements, climate factors, geological hazards, and human activities was addressed. The outcomes proved that the average annual vegetation coverage in Shaanxi Province displayed a slight upward trend with a growing rate of 0.0545/10a. Specifically, enhanced vegetation index (EVI) increased significantly in most parts of the study area, while EVI decreased significantly in the border areas of Xi'an and Xianyang. There are differences in the effects of the driving factors on vegetation change during the study period. According to correlation analysis, vegetation was positively associated with temperature and negatively associated with precipitation. In addition, when the elevation was under 2500 m, EVI increased with elevation, while when the elevation used to be above 2500 m, EVI decreased with elevation. Moreover, geological disasters and soil erosion are the major driving factors in the reduction of vegetation cover. Human activities and national policies are the main driving factors for vegetation recovery in the study area. The results of the study are of great significance for ecosystem monitoring and provide a scientific basis for ecosystem restoration.

El Niño–Southern Oscillation (ENSO)-driven hypersedimentation in the Poechos Reservoir, northern Peru

Abstract. Although extreme El Niño events (EENEs) have always impacted hydrological anomalies and sediment transport in South America, their intensification by global warming and their association with changes in human activities and land cover after humid periods may lead to the acceleration of sediment transfers in river systems and dam reservoirs. This situation may threaten soil and water resources in arid and semiarid regions highly dependent on water originating from large dams. In this study, we investigated the sediment sequence accumulated in the Poechos Reservoir (northern Peru) and provided a retrospective reconstruction of the interactions of El Niño–Southern Oscillation (ENSO), agricultural practices and vegetation cover changes with sediment dynamics (1978–2019). To this end, a sediment core was dated and characterized by physical and chemical analyses (e.g., scanner tomography, X-ray fluorescence, particle size analysis) to estimate the evolution of sedimentation rates and changes in sediment sources during the last 5 decades. Sediment tracing results indicated the occurrence of changes in sediment sources associated with positive and negative phases of the Eastern Pacific index with a greater contribution of the lowland dry-forest area in comparison to that of the Andean area to sediment during the El Niño events (mean contribution of 76 %; up to 90 % during the coastal El Niño events (CENEs) of 2016–2017). This source contribution was mostly controlled by the stationary rainfall occurring during the EENEs in the lowland dry-forest area characterized by a low vegetation cover. Overall, after an extreme phase of ENSO, like after the EENE 1982–1983, the normal discharges and persistent sediment supplies from the middle- and upper-catchment parts led to river aggradation and the storage of substantial amounts of sediment in alluvial plains. In the absence of a significant EENE between 1983 and 1997, the large volume of sediment stored in the alluvial plains was exported by the EENE 1997–1998 resulting in an increase in sedimentation rate of 140 % after 1997 with a significant aggradation of the deltaic zone of the reservoir. In addition to the impact of extreme climate events on sediment dynamics, the development of agriculture along the riverine system after an extreme phase of ENSO increased the availability of sediments in the main channel of the rivers, easily transported by the next EENE. This study suggests that intensification of human activities associated with a higher frequency of extreme rainfall events amplified the quantity of sediment transported by the river system, which will significantly decrease the lifespan of the reservoir, which is essential to meeting the freshwater demands of the farmers and the populations living in this arid and semiarid region.

Heterogeneity Analysis of Spatio-Temporal Distribution of Vegetation Cover in Two-Tider Administrative Regions of China

Vegetation cover is a crucial component of regional ecological environments that plays a vital role in maintaining ecosystem balance. This investigation utilized Google Earth Engine and MODIS NDVI products to examine the spatiotemporal heterogeneity of regional vegetation coverage based on the multi-year average NDVI in China. Using the multi-year average NDVI, multi-year change trend slope, coefficient of variation, and Hurst exponent, the spatial and temporal heterogeneity of provincial and prefectural administrative regions were quantified. The results indicated an upward trend in vegetation coverage from 2000 to 2021 at both provincial and prefectural levels, with growth rates of 0.032/10a and 0.03/10a, respectively. Moreover, the multi-year average NDVI significantly correlated with regional precipitation. Notably, vegetation growth was fastest in the Loess Plateau, while degradation was observed in southern Jiangsu and northern Zhejiang. Additionally, the degree of vegetation cover change in Ningxia and Macau was particularly prominent. These findings support the effectiveness of the Loess Plateau greening project and highlight the potential cost of economic and population growth on the ecosystem in eastern and southeastern coastal areas, where local vegetation degradation occurs. This study can serve as a valuable reference for ecosystem restoration and developmental planning at the administrative regional level, with the goal of enhancing vegetation management and conservation efforts in China.

Dynamic monitoring of vegetation coverage in weibei dry plateau based on remote sensing

Taking Fu County, a typical area of Weibei dry plateau, as the research object, the normalized difference vegetation index ( NDVI ) was calculated by using Landsat 8 OLI remote sensing image. On this basis, the vegetation coverage in the study area was estimated and graded according to the binary pixel model, and the dynamic changes of vegetation coverage in the study area from 2013 to 2017 were quantitatively analyzed. Results showed that the overall NDVI value in the study area increased from 2013 to 2017. The vegetation cover in the study area is dominated by extremely high vegetation cover. The coverage area of low, medium and high vegetation cover decreases, and the coverage area of extremely high and extremely low vegetation cover increases. The coverage area of high vegetation and extremely high vegetation cover accounts for more than 75% of the study area. The study area showed a transfer trend of extremely low vegetation→low vegetation→medium vegetation→high vegetation coverage. The vegetation coverage generally developed to a good trend, but there was also a transfer of high vegetation coverage to medium vegetation coverage. The areas with the greatest changes in the study area are mainly concentrated in the northwest and near the southern Damagou, and the high NDVI area of Ziwuling National Nature Reserve has moved eastward and narrowed. Accuracy assessment indicates that the dynamic monitoring using the fused image time series produces results with relatively high accuracy. Bangladesh J. Bot. 52(2): 479-486, 2023 (June) Special

Dynamic monitoring of vegetation coverage in weibei dry plateau based on remote sensing

Taking Fu County, a typical area of Weibei dry plateau, as the research object, the normalized difference vegetation index ( NDVI ) was calculated by using Landsat 8 OLI remote sensing image. On this basis, the vegetation coverage in the study area was estimated and graded according to the binary pixel model, and the dynamic changes of vegetation coverage in the study area from 2013 to 2017 were quantitatively analyzed. Results showed that the overall NDVI value in the study area increased from 2013 to 2017. The vegetation cover in the study area is dominated by extremely high vegetation cover. The coverage area of low, medium and high vegetation cover decreases, and the coverage area of extremely high and extremely low vegetation cover increases. The coverage area of high vegetation and extremely high vegetation cover accounts for more than 75% of the study area. The study area showed a transfer trend of extremely low vegetation→low vegetation→medium vegetation→high vegetation coverage. The vegetation coverage generally developed to a good trend, but there was also a transfer of high vegetation coverage to medium vegetation coverage. The areas with the greatest changes in the study area are mainly concentrated in the northwest and near the southern Damagou, and the high NDVI area of Ziwuling National Nature Reserve has moved eastward and narrowed. Accuracy assessment indicates that the dynamic monitoring using the fused image time series produces results with relatively high accuracy. Bangladesh J. Bot. 52(2): 479-486, 2023 (June) Special

Influence of Cattle Grazing Methods on Changes in Vegetation Cover and Productivity of Pasture Lands in the Semi-Desert Zone of Western Kazakhstan

Influence of Cattle Grazing Methods on Changes in Vegetation Cover and Productivity of Pasture Lands in the Semi-Desert Zone of Western Kazakhstan

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

The Yan River Basin of the Loess Plateau is a key region for ensuring the environmental protection and sustainable development of the Yellow River Basin. Therefore, it is essential to identify how vegetation cover has changed and determine the factors that have driven these changes. In this study, we applied a three-dimensional vegetation cover model to examine the spatiotemporal variation characteristics of vegetation cover at the watershed scale in the Yan River Basin from 2001 to 2020 and forecast future trends. Subsequently, the driving forces of fractional vegetation cover (FVC) change were quantified based on meteorological, surface, and anthropogenic factors to explore the common driving relationships among these factors. (1) The accuracy of 3DFVC is better than that of FVC in the Yanhe River Basin, where the terrain is complex. (2) The temporal change trends indicated that the vegetation cover in the Yan River Basin significantly recovered and the basin FVC increased rapidly from 2001 to 2013 (S = 0.0152/a, p &lt; 0.01) and increased gradually from 2013 to 2020 (S = 0.0015/a). The main reason for the increase in vegetation cover was the enhanced growth of medium FVC. (3) The vegetation spatial distribution showed that the FVC values varied substantially from north to south, indicating spatial heterogeneity, and 83.9% of the area presented a trend of increasing vegetation. Furthermore, vegetation cover was predicted to improve in the future. (4) The spatial heterogeneity of FVC was mainly influenced by relative humidity and rainfall, and the spatial variations in FVC were mainly determined by climate factors. Land use and cover change variations, which are influenced by human activities, represent major factors underlying the observed spatial heterogeneity. Most interactions between driving factors showed two-way enhancement or non-linear enhancement, with relative humidity and land use patterns presenting the strongest explanatory power. This study provides a scientific basis for vegetation conservation in the Yan River Basin and contributes theoretical support for decision-making regarding ecological environmental protection in the Loess Plateau and sustainable development in the Yellow River Basin.

Characterization of water status and vegetation cover change in a watershed in Northeastern Brazil

The existing water scarcity in the Brazilian semiarid region, associated with anthropic activities, imply in the degradation of the watersheds present in the Caatinga. Therefore, the objective of this study was to characterize water and vegetation cover changes in the Ipanema River Watershed (IRW). IRW is inserted in municipalities that make up the dairy basins of the states of Alagoas and Pernambuco, one of the main economic activities in the Northeast of Brazil (NEB). Land use and land cover (LULC) maps, Modified Normalized Difference Water Index (MNDWI) and rainfall product via TerraClimate were used in the study. The MNDWI was based on the annual mean between 2010 and 2020 for the dry and rainy periods. For rainfall patterns and variability, pixel values were extracted and submitted to the Inverse Distance Weighted (IDW) interpolation method. We highlight the inverse relationship between the categories Forestry, Agriculture and Cattle Raising, with a decrease in the area of Caatinga due to agriculture and cattle raising. In the dry period via MNDWI there was higher water availability in 2010, 2017, 2018, 2019 and 2020, the exceptions were the years 2013–2016. In the rainy season, clouds interfered in the MNDWI analyses, with lower water availability in 2013, the exceptions were 2017 and 2018. Comparatively, the images from 2010 to 2020 via MNDWI, showed a water reduction in the IRW, mainly in the southern portion. For the dry period, the years 2011, 2012, 2016 and 2019 showed less than 138 mm of rainfall, especially in 2016 (<64 mm). In the rainy season, the years 2012, 2013, 2016, 2018 and 2019 also showed less than 482 mm of rainfall, with 2012 and 2016 standing out (<101 mm), mainly, the months with the highest rainfall record at IRW. The results obtained in this study show that droughts in the NEB continue to the present day, followed by an increase in water deficit. Anthropic action implies environmental degradation in one of the most threatened ecosystems (Caatinga), affecting mainly the water resource, an important factor in the survival of the local population and in the territorial dynamics.

Spatial and Temporal Variation in Vegetation Cover and Its Response to Topography in the Selinco Region of the Qinghai-Tibet Plateau

In recent years, the vegetation cover in the Selinco region of the Qinghai-Tibet Plateau has undergone significant changes due to the influence of global warming and intensified human activity. Consequently, comprehending the distribution and change patterns of vegetation in this area has become a crucial scientific concern. To address this concern, the present study employed MODIS-NDVI and elevation data, integrating methodologies such as trend analysis, Hurst exponent analysis, and sequential cluster analysis to explore vegetation cover changes over the past 21 years and predict future trends, while examining their correlation with topographic factors. The study findings indicate a fluctuating upward trend in vegetation cover, with a notable decrease in 2015. Spatially, the overall fractional vegetation cover (FVC) in the study area showed a basic stability with a percentage of 78%. The analysis of future trends in vegetation cover revealed that the majority of areas (68.26%) exhibited an uncertain trend, followed by stable regions at 15.78%. The proportion of areas showing an increase and decrease in vegetation cover accounted for only 9.63% and 5.61%, respectively. Elevation and slope significantly influence vegetation cover, with a trend of decreasing vegetation cover as elevation increases, followed by an increase, and then another decrease. Likewise, as the slope increases, initially, there is a rise in vegetation cover, followed by a subsequent decline. Notably, significant abrupt changes in vegetation cover are observed within the 4800 m elevation band and the 4° slope band in the Selinco region. Moreover, aspect has no significant effect on vegetation cover. These findings offer comprehensive insights into the spatial and temporal variations of vegetation cover in the Selinco region and their association with topographic factors, thus serving as a crucial reference for future research.