Normalized Difference Vegetation Index Variables Research Articles

Índices de vegetação para monitoramento do desempenho agronômico da batata sob combinações de adubação mineral e orgânica

ABSTRACT Potatoes are one of the main vegetables consumed worldwide. However, dependence on mineral fertilizers compromises producers’ profitability. New alternatives are required to increase agricultural crop yield while sustaining production. Vegetation indices have improved the agility and benefits of experimental evaluations of vegetables; however, there is a scarcity of information on potatoes. Thus, the present study aimed to assess the effectiveness of different vegetation indices for monitoring the agronomic performance of potato crops fertilized with a combination of mineral fertilizers and organic compost. The study was conducted in the municipality of Perdizes, Minas Gerais, Brazil. A randomized block design was used. Each plot was divided into five subplots that received 25 combinations of mineral and organic fertilizer treatments in four replications. Images were acquired using a remote-piloted aircraft, which generated spectral values of vegetation indices in relation to various combinations of fertilizer doses. Mineral fertilizer doses significantly correlated with the normalized green-red difference index (NGRDI), normalized difference vegetation index (NDVI), and green leaf index (GLI) at r = 0.824, 0.836, and 0.833, respectively. Even in an environment with high variability in plant growth, the NGRDI, NDVI, and GLI were significantly correlated with mineral fertilization. The agronomic performance of potato crops under various fertilizer dosages could be monitored using the obtained vegetation indices.

Environmental characterization and cartographic modeling of wild plant habitats at the northern coastal zone of Egypt

Assessing natural vegetation through conventional methods faces considerable constraints, such as limited geographical scope, reduced precision, a lack of historical data, high expenses and time demands. The study aims to use environmental and spectral data to identify and map natural vegetation and plant species along the Mediterranean coast of Egypt. This involves employing spatial analyses and cartographic modeling techniques, marking an initial effort in this endeavor. To fulfill this aim, a total number of 70 wild plant habitats were surveyed and sampled for further laboratory identification of plant species. Multispectral and thermal bands of Landsat imagery were processed to generate land cover map, as well as calculate Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) to be integrated with the naturally grown plants in a cartographic model to predict the wild plant habitats. Coastal wild plant habitats were sparsely located and associated with a vegetation density ranging from 0.096 to 0.280 with an average of 0.167. Besides, the LST of these habitats fluctuated from 30.559 to 38.652 with an average of 34.361°C. Although the wild plant habitats at the Northern coastal region of Egypt are similar in environmental and climatic conditions, there are variability in NDVI and LST of each single habitat (pure or mixed). On the other hand, the lowest LST were associated with Erodium laciniatum/Rumex pictus and Erodium laciniatum habitats reporting 30.559 and 30.741°C, respectively. However, Lotus halophilus mixed with Ifloga spicata habitats reported the highest LST (38.652°C). The high vegetation density is mainly characterized by low LST which indicates the mixed wild plant habitats. The developed cartographic model showed a narrow strip along the Mediterranean region as highly suitable habitats for wild plant growth. The model can be used to map pure and mixed habitats of various wild plants with an accuracy exceeding 90%. The model was applied for mapping Arthrocnemum macrostachyum showing that the middle coastal region is most suitable for its growth. It’s recommended to integrate remotely sensed data with spatial analyses for the environmental analyses of natural plants. Present findings support researchers and scientists interested in environmental, botanic, and medical studies.

Spatial and temporal variation in normalized difference vegetation index of vegetation in Liaoning Province from the perspective of ecogeographic zoning

Normalized difference vegetation index (NDVI) is an important indicator reflecting vegetation cover and growth status. It is of significance for regional ecological conservation and natural resource management to investigate its spatial and temporal variation trends and response to ecological factors. We divided Liaoning Province into three ecological geographical regions, including northwest agro-pastoral zone, central agricultural zone, and eastern agroforestry zone. Based on remote sensing, vegetation, climate, topography and human activities, we used trend analysis and geographic probe model to examine the spatial and temporal trends of NDVI in Liaoning Province, and analyzed the intensity and interaction mechanism of each driver on the spatial distribution pattern of NDVI. The results showed that the annual average NDVI in Liaoning Province from 2001 to 2020 was 0-0.92, showing a distribution pattern of high in the east and low in the west, high in the inland and low in the coastal land. The overall trend of vegetation cover was increasing, and the NDVI increasing areas were mainly concentrated in the northwest agro-pastoral zone and the eastern agroforestry zone, the NDVI reduction areas were mainly concentrated at the border between the central agricultural zone and the eastern agroforestry zone, as well as in the coastal area of the eastern agroforestry zone. The annual average NDVI change varied among the three ecological-geographic zones. The NDVI of the northwest agro-pastoral zone from 2001 to 2020 were generally low, but showed a fluctuating trend of slow increase. The NDVI of the eastern agroforestry zone was high overall, and the interannual variation of NDVI was generally stable. The distribution of high and low NDVI in the central agricultural zone was staggered, and the interannual variation of NDVI showed a decreasing trend. Natural factors were the key drivers of NDVI changes in the three ecogeographic zones, with cumulative temperature and precipitation having the greatest influence. The interactions between the factors were all mutually and nonlinearly enhanced.

Temperate grassland vegetation restoration influenced by grazing exclusion and climate change

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003–0.0319 year−1. The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration.

Spatio-temporal linkage variations between NDVI and tree rings on the leeward side of the northern Patagonian Andes

The Normalized Difference Vegetation Index (NDVI) and tree rings provide different approaches that allow evaluating the productivity of ecosystems. Following this premise, we evaluated the relationship between NDVI and tree-ring widths of Austrocedrus chilensis forests at sectors of the Argentinian northwestern foothills of the Patagonian Andes. To proceed with this study, wood core samples were taken from 153 trees at 6 sites located at different latitudes and along a strong west-east precipitation gradient. The NDVI presented a significant and positive spatial correlation with precipitation, the Standardized Precipitation-Evapotranspiration Index (SPEI-3), soil moisture, and a negative correlation with air temperature at large geographical coverages. Stand location in the latitudinal and meridian coordinates showed a species-specific effect, with greater sensitivity to NDVI in sites located at higher latitudes and under drier conditions. We found stronger associations between stem biomass (tree rings) and canopy biomass (NDVI) in drier sites, assuming a closer link to stressful water conditions. This behavior was accentuated since 1988, which coincides with the increase in air temperature as a result of regional warming processes. These results suggest that site environmental conditions influence how NDVI and ring width are linked, showing the complex dynamics between climate and growth. The results indicate that ring widths of A. chilensis trees have the potential to assess current NDVI variations in the study area, allowing reconstructions of past productivity and potential predictive models of future changes.

Investigating the Relationship between Topographic Factors and Vegetation Spatial Patterns in the Alpine Plateau: A Case Study in the Southwestern Tibetan Plateau

Vegetation on the Southwestern Tibetan Plateau (SWTP) is critical to ensuring ecological security and promoting regional economic and social development. Here, we explored the relationship between topographic factors (elevation, slope, and aspect) and the spatial patterns in the normalized difference vegetation index (NDVI) in the SWTP over the past 20 years. The results found that the NDVI in the SWTP was primarily influenced by elevation and slope. The regions with significant variations in NDVI were concentrated between 4500 m to 5500 m and slopes ranging from 0° to 15°. Although the influence of aspect on NDVI was small, there was a decreasing trend in NDVI on sunny slopes and an increasing trend on shady slopes. Dominant topographic conditions were identified by considering 230 different combinations of elevation, slope, and aspect. The combination of topographic parameters indicated stronger patterns in NDVI variability, notably within sections of 0°–25°slopes and below 5000 m elevation. These findings highlight the relevance of topography, notably slope and aspect, for vegetation in alpine settings. The information gathered from this study about the prevailing topographic distribution and vegetation growth state in the SWTP can help with future ecological restoration and conservation efforts in the Tibetan Plateau and other comparable regions worldwide.

The Impact of Dam Construction on Downstream Vegetation Area in Dry Areas Using Satellite Remote Sensing: A Case Study

The assessment of ecosystem quality and the maintenance of optimal ecosystem function require understanding vegetation area dynamics and their relationship with climate variables. This study aims to detect vegetation area changes downstream of the Hali dam, which was built in 2009, and to understand the influence of the dam as well as climatic variables on the region’s vegetation areas from 2000 to 2020. The case study is located in an arid area with an average rainfall amount from 50 to 100 mm/year. An analysis of seasonal changes in vegetation areas was conducted using the Normalized Difference Vegetation Index (NDVI), and supervised image classification was used to evaluate changes in vegetation areas using Landsat imagery. Pearson correlation and multivariate linear regression were used to assess the response of local vegetation areas to both hydrologic changes due to dam construction and climate variability. The NDVI analysis revealed a considerable vegetation decline after the dam construction in the dry season. This is primarily associated with the impoundment of seasonal water by the dam and the increase in cropland areas due to dam irrigation. A significantly stronger correlation between vegetation changes and precipitation and temperature variations was observed before the dam construction. Furthermore, multivariant linear regression was used to evaluate the variations in equivalent water thickness (EWT), climate data, and NDVI before and after the dam construction. The results suggested that 85 percent of the variability in the mean NDVI was driven by climate variables and EWT before the dam construction. On the other hand, it was found that only 42 percent of the variations in the NDVI were driven by climate variables and EWT from 2010 to 2020 for both dry and wet seasons.

Tracing climatic and human disturbance in diverse vegetation zones in China: Over 20 years of NDVI observations

Over the past two decades (2000–2021), China has experienced a significant increase in vegetation cover. However, the intricate spatial and temporal variations in vegetation cover, arising from the interaction of climate change and human activities, remain enigmatic, particularly across diverse vegetation zones. This research endeavors to unravel the dynamics of vegetation cover using the MOD13A1 Normalized Difference Vegetation Index (NDVI) dataset, delving into China's seven distinct vegetation zones (VZ1-VZ7). This research employs residual analysis, relative analysis, and geo-detector techniques to investigate the drivers of NDVI variation and spatial heterogeneity across China's seven distinct vegetation zones. The findings reveal a compelling upward trajectory in NDVI, predicted NDVI, and residual NDVI across China during the 2000–2021 period. Notably, significant and extremely significant increases are discernible in approximately 53.90%, 50.13%, and 23.29% of China's NDVI, respectively. Among the vegetation zones, VZ3 displays the highest change rates, yet the proportion with a significant increase in VZ1 surpasses other zones. The relative analysis underscores climate change as the predominant catalyst for vegetation enhancement, although an exception is noted in VZ3. Furthermore, the spatial heterogeneity of China's NDVI is primarily influenced by the interactions between land use types and relative humidity, sunshine duration, and precipitation, especially the interaction between relative humidity and land use types. Significant changes in climate can lead to marked alterations in the structure and function of terrestrial ecosystems, while changes in land use patterns at the regional level also alter the type of land cover, which together exert a significant impact on the vegetation NDVI. These results accentuate the importance of formulating tailored ecosystem management strategies tailored to the distinct characteristics of each vegetation zone to ensure the sustainable development of terrestrial ecosystems across China.

Study of Changes in the Ulan Buh Desert under the Dual Impacts of Desert Farmland Development and Climate Change.

Desert farmland provides food for desert areas, but water is the main limiting factor of this region, thus desert farmland has an extremely fragile ecological environment. This study investigated the temporal and spatial variations of vegetation NDVI (Normalized Difference Vegetation Index) in the Ulan Buh Desert, China, from 1990 to 2022, using long-term Landsat satellite data obtained from the Google Earth Engine platform and local statistical data. The results showed that from 1990 to 2022, the NDVI exhibited relatively small fluctuations and a steady increase. Furthermore, the study analyzed the impact of climate factors, namely precipitation and temperature, on NDVI, and collected the groundwater lever changes under irrigation and farmland development. The results demonstrated a positive correlation between NDVI and both precipitation and temperature from 1990 to 2006. The study area experienced an overall trend of increasing humidity. Specifically, from 1990 to 2006, significant positive correlations with precipitation and temperature were observed in 4.4% and 5.5% of the region, respectively. From 2007 to 2022, significant positive correlations were observed in 5.4% and 72.8% of the region for precipitation and temperature, respectively. These findings suggest that temperature has become increasingly influential on vegetation NDVI, while the impact of precipitation remains relatively stable. Moreover, the study assessed the impact of human activities on vegetation NDVI. The results revealed that from 1990 to 2006, human activities contributed to 43.1% of the promotion of local vegetation NDVI, which increased to 90.9% from 2007 to 2022. This study provides valuable insights into the dynamics of vegetation in the Ulan Buh Desert and its response to climatic changes and human activities. The findings highlight the significance of climate conditions and human interventions in shaping the vegetation dynamics in the region, offering essential information for ecological restoration and conservation efforts.

REMOTE SENSING AND GEOSTATISTICS APPLIED TO NDVI, KC AND PRODUCTIVE PARAMETERS IN IRRIGATED CORN CROP

Remote sensing (SR) has contributed to digital agriculture, associated with the use of geostatistical techniques that allow data acquisition, analysis and decision making. In view of this, the objective of this work was to evaluate the spatial variability of soil physical attributes, NDVI and second crop corn productivity in the territory of Santa Helena de Goiás, and to estimate values of crop coefficient (KC) through the NDVI, and to evaluate the spatiality. Soil samples were collected in a georeferenced way using a regular grid. The images were from the Sentinel 2A satellite. The Normalized Difference Vegetation Index (NDVI) was calculated, the Kc values of the crop were estimated, using two methodologies Toureiro et al., (2017) and Kamble et al. (2013), and later the values were extracted through a regular GRID, with which the geostatistical analyzes and correlations with productivity were submitted. The NDVI showed an increase up to 69 days after planting, in addition to proving the spatial variability and spatial dependence. With the geostatistics it was possible to generate a map of the spatial distribution of productivity. The NDVI allowed to obtain the Kc corresponding to the different phases of cultivation, sensitive to the methodologies used. The Kc obtained presents a high response and potential to the management of irrigated corn..

Assessing the Vegetation Dynamics and Its Influencing Factors in Central Asia from 2001 to 2020

As vegetation plays a critical role in terrestrial ecosystems, understanding its status and variation is vital for preserving the stability of an ecosystem. Central Asia serves as a representative example of an arid and semi-arid region characterized by sparse vegetation and poor soils, making its vegetation particularly fragile and sensitive. To investigate the vegetation condition in the region, this study examined the spatial and temporal characteristics of vegetation variation from 2001 to 2020, utilizing the normalized difference vegetation index (NDVI) as an indicator. Meanwhile, trend analysis, Mann–Kendall abrupt change point test, geodetector, and correlation analysis were used to quantitatively analyze the natural and anthropogenic drivers of these variations over the past two decades. The results suggest that vegetation coverage in Central Asia was relatively low, with an annual average NDVI of 0.16 over the past 20 years. Moreover, the spatial distribution of NDVI in Central Asia exhibited significant spatial heterogeneity, with vegetation coverage declining from north to south and from east to west. Furthermore, the NDVI exhibited a slightly increasing trend during the period of 2001 to 2020 with an increased rate of 0.00025/yr. However, we detected an abrupt change point in vegetation dynamics in Central Asia around 2010, which indicated a significant shift in vegetation variation in the region. Land-use type has a great influence on the spatial heterogeneity of NDVI in Central Asia, which can explain 46% of the vegetation distribution in this region. Moisture factors such as precipitation and soil water content followed with 35% and 32% contributions, respectively. Regarding the temporal variation of NDVI, it is mainly driven by the fluctuation in precipitation, with the degree of influence of precipitation on NDVI varying for different regions in various geographical conditions. This study offers a more comprehensive insight into the spatial and temporal dynamics of NDVI in Central Asia and indicates that precipitation plays a significant role in driving the spatial heterogeneity and temporal variation of NDVI. These findings are essential for predicting vegetation changes in arid regions under future environmental conditions and formulating effective strategies to prevent and alleviate vegetation degradation.

Influence of climatic conditions on Normalized Difference Vegetation Index variability in forest in Poland (2002–2021)

AbstractThe influence of climate change on forest condition is noticeable. Forest ecosystem stress caused by climate change has already been manifested in several parts of Europe, including Poland. Thus, the main objective of this paper is to investigate for the entire area of Poland a long‐term trend and variability of forest greenness expressed as the Normalized Difference Vegetation Index (NDVI), derived from two decades (2002–2021) of remote sensing Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the next step, selected meteorological elements – temperature (T), precipitation (P) and evapotranspiration (ETo), derived from ERA5‐Land reanalysis—were used to determine the influence of climatic conditions on the variability of NDVI in forests. The study documents the general greening of forests in Poland in 2002–2021. The greening is mostly visible in central‐eastern Poland, where the annual mean NDVI increased by 0.030 in 20 years, while it is weaker in the Baltic coast and in the southern edges of Poland (increase by 0.009 in 20 years). Overall, the positive, statistically significant trends in annual NDVI prevail over the negative, statistically significant trends and account for 32.5% of forest area, whereas the negative trends account for 3.9%. The study indicates an overall moderate impact of meteorological elements on variability of NDVI in forests in Poland. The most important factors affecting forest condition are P and ETo. The strongest correlations between NDVI and P and ETo reach 0.55 and are located in central Poland, in the form of a belt from western to eastern borders.

Detection of the nonlinear response of vegetation to terrestrial water storage changes in central Asian endorheic basins

The terrestrial water storage anomaly (TWSA) is an important parameter for assessing the land water budget, and it interacts well with terrestrial ecosystems via complex hydrological processes. Recently, the decline in central Asian terrestrial water storage (TWS) has threatened the health of local ecosystems. Therefore, it is of great significance to adopt an efficient approach to explore and identify the nonlinear relationship between two important indicators, i.e., the TWSA and normalized difference vegetation index (NDVI) in the arid central Asian endorheic basins. In this study, we analysed the long-term trends of the TWSA and NDVI, and identified the lag month (1 month) as the optimal moving window of the nonlinear Granger causality test embedded in random forest to detect the nonlinear NDVI change response of NDVI changes in vegetation to the TWSA from 2003 to 2015. There are decreasing trends in TWSAs over approximately 81.7% of the study area and the NDVI generally decreased resulting in approximately 36% vegetation browning in the study area. The nonlinear Granger unidirectional causes of the TWSA were responsible for 97.9% of the NDVI variation in the study area considering the optimal response time for moving windows. The causes of vegetation browning in the central Asian Aral Sea basin and vegetation greening in the basins of Northwest China could be mostly explained by the changes in TWS. Our findings contribute to understanding the nonlinear causal linkages between vegetation and the TWSA in endorheic basins, and these findings provide insights for obtaining terrestrial water consumption patterns and water resource management under the joint influence of climate change and human activities.

Vegetation responses to ecological water delivery and prolonged droughts in an artificial desert oasis, Northwestern China

Irrational water usage in the middle reaches of inland rivers is detrimental to downstream oases, and the Qingtu Oasis is a typical downstream oasis that is degraded by water resource scarcity. The Qingtu Lake ecological water diversion project (EWDP) has restored the oasis, but the response pattern of different vegetation communities to environmental water and the dominant drivers of vegetation dynamics are not clear. Here, based on ground and satellite observations, this study investigated the spatial and temporal patterns of vegetation distribution and growth in the Qingtu Oasis from 2010 to 2022, and the reasons for the interannual variability in vegetation growth were also explained. The results showed that temporal variations in the distribution area of Phragmites australis (PA) followed a logistic curve after the EWDP, which increased rapidly from 2010 to 2019 and stabilized afterward. Meanwhile, the distribution area of Nitraria tangutorum (NT) presented a linear increase during the study period, with a 121.2% increase. Due to water inundation, the central region was occupied by PA communities, while NT communities moved to the edge. The spatial connectivity of PA patches increased significantly in contrast to the overall fragmentation tendency of NT patches in 2010–2022. The oasis tended to be homogenized and aggregated according to the morphological spatial pattern analysis, along with the landscape diversity and contagion indices. Enhanced vegetation growth, as indicated by the normalized difference vegetation index (NDVI), was observed in 76.1% of the vegetated lands, and the NDVI increasing rate was high near the canal. Using the random forest model, this study found that changes in groundwater depth were the most important driver of NDVI variability. The following influencing factors were atmospheric CO2 concentration, water inundation area and water delivery amount. In the absence of large increases in water delivery amount, oasis vegetation growth was susceptible to prolonged droughts. This study uncovers a nonlinear response of different vegetation communities to climate change and the EWDP in the downstream region of arid endorheic basins and identifies meteorological droughts as a key factor that should be fully considered in water delivery strategies. These findings lay a solid foundation for managing oasis restoration and water resource allocation in arid inland river basins.

Historical variation in the normalized difference vegetation index compared with soil moisture in a taiga forest ecosystem in northeastern Siberia

Abstract. The taiga ecosystem in northeastern Siberia, a nitrogen-limited ecosystem on permafrost with a dry climate, changed during the extreme wet event in 2007. We investigated the normalized difference vegetation index (NDVI) as a satellite-derived proxy for needle production and compared it with ecosystem parameters such as soil moisture water equivalent (SWE), larch foliar C/N ratio, δ13C and δ15N, and ring width index (RWI) at the Spasskaya Pad Experimental Forest Station in Russia for the period from 1999 to 2019. Historical variations in NDVI showed a large difference between typical larch forest (unaffected) and the sites affected by the extreme wet event in 2007 because of high tree mortality at affected sites under extremely high SWE and waterlogging, resulting in a decrease in NDVI, although there was no difference in the NDVI between typical larch forest and affected sites before the wet event. Before 2007, the NDVI in a typical larch forest showed a positive correlation with SWE and a negative correlation with foliar C/N. These results indicate that not only the water availability (high SWE) in the previous summer and current June but also the soil N availability likely increased needle production. NDVI was also positively correlated with RWI, resulting from similar factors controlling them. However, after the wet event, NDVI was negatively correlated with SWE, while NDVI showed a negative correlation with foliar C/N. These results indicate that after the wet event, high soil moisture availability decreased needle production, which may have resulted from lower N availability. Foliar δ15N was positively correlated with NDVI before 2007, but foliar δ15N decreased after the wet event. This result suggests damage to roots and/or changes in soil N dynamics due to extremely high soil moisture. As a dry forest ecosystem, taiga in northeastern Siberia is affected not only by temperature-induced drought but also by high soil moisture (led by extreme wet events) and nitrogen dynamics.

Spatial and temporal variation of NDVI and its driving factors based on geographical detector: A case study of Guanzhong plain urban agglomeration

Vegetation is an important component of the ecosystem cycle, which is influenced by a combination of natural and human factors, making it challenging to identify the extent of the contribution of its drivers. As one of the nine largest urban agglomerations in China, the Guanzhong Plain urban agglomeration (GPUA) has a fragile ecosystem and severe human disturbance. We concentrated on GPUA as the research object, which used a Geographical Detector to quantify the degree influence of natural and anthropogenic factors on Normalized Difference Vegetation Index (NDVI). The results are as follow, The NDVI showed an increasing trend with an annual growth rate of 0.0088/year. The variation of NDVI showed an obvious spatial pattern. The area of NDVI increased significantly in the southern region, while the significant degradation area was distributed in the northern and central parts. Natural factors contribute more to NDVI change than anthropogenic factors, with precipitation (19.5%), soil type (17.2%) and landform type (16.1%) making the greatest contributions. It was found that the effect of the two-two factor interaction on NDVI was higher than the single factor effect. The research results can effectively identify the variation characteristics of NDVI in ecologically fragile areas under the complex driving mechanism.

Assessment of changes in the normalized difference vegetation index (NDVI) of farmlands of Stavropol Territory, Russia, during the period of active vegetation in 2020 based on medium spatial resolution images

Aim. Assess changes in the NDVI of agricultural land in Stavropol Territory under the influence of weather and climate conditions.Methods. Based on earth remote sensing data, the spectral/vegetation index NDVI was calculated. We used data from the Meteor‐M satellite with a spatial resolution of 60 m for the active vegetation period of 2020 (May to September), which made it possible to calculate the NDVI value at different times of the active vegetation period of the main types of agricultural land in the Stavropol Territory. To explain the spatial and temporal variability of NDVI, an analysis of the conditions of heat and moisture supply was carried out using Walter's climatograms at weather stations located in the steppe and semi‐desert landscapes of Stavropol Territory.Results. In 2020, the period of active vegetation in the steppe and semidesert landscapes of Stavropol Territory began in the first ten days of April, when the air temperature rose above +10°С, and ended in mid‐October. In accordance with the change in heat and moisture supply, the NDVI value changed: in general, maximum values were observed in spring and early summer and, as aridity increased, the areas corresponding to low NDVI values increased everywhere. In the steppe zone, where the main crops of winter wheat are located, the NDVI value decreased from 0.45–0.3 at the beginning of the active vegetation period to 0.15 at the end. NDVI values of 0.15–0.30, corresponding to different types of herbaceous vegetation, prevailed at the end of the active vegetation period.Conclusion. The spatial and temporal distribution of the NDVI value over the territory of the Stavropol Territory reflects, first of all, changes in the conditions of heat and moisture supply. The timing of the course of the phenological phases of natural and cultivated vegetation depends on the latter. 2020 was characterized by sufficient moisture at the beginning of active vegetation, as reflected in the high density of seedlings, and, accordingly, a large area of NDVI, corresponding not only to herbaceous, but also to shrubby vegetation within the steppe landscapes. The increase in moisture deficit and harvesting in the second half and end of summer leveled the differences between the steppe and semi‐desert landscapes, since the maximum areas were occupied by territories with NDVI values of 0.15–0.3.

Analysis of Growing Season Normalized Difference Vegetation Index Variation and Its Influencing Factors on the Mongolian Plateau Based on Google Earth Engine.

Frequent dust storms on the Mongolian Plateau have adversely affected the ecological environmental quality of East Asia. Studying the dynamic changes in vegetation coverage is one of the important means of evaluating ecological environmental quality in the region. In this study, we used Landsat remote sensing images from 2000 to 2019 on the Mongolian Plateau to extract yearly Normalized Difference Vegetation Index (NDVI) data during the growing season. We used partial correlation analysis and the Hurst index to analyze the spatiotemporal characteristics of the NDVI before and after the establishment of nature reserves and their influencing factors on the GEE cloud platform. The results showed that (1) the proportion of the region with an upwards trend of NDVI increased from 52.21% during 2000-2009 to 67.93% during 2010-2019, indicating a clear improvement in vegetation due to increased precipitation; (2) the increase in precipitation and positive human activities drove the increase in the NDVI in the study region from 2000 to 2019; and (3) the overall trend of the NDVI in the future is expected to be stable with a slight decrease, and restoration potential is greater for water bodies and grasslands. Therefore, it is imperative to strengthen positive human activities to safeguard vegetation. These findings furnish scientific evidence for environmental management and the development of ecological engineering initiatives on the Mongolian Plateau.

Declining trees growth and vegetation productivity resulting from decreasing soil water contents induced by tunnels excavation in karst mountain areas

Tunnel construction in karst areas greatly impacts the local hydrological conditions. The drawdown of groundwater levels and the loss of soil water storage due to tunneling limit the available water resources on the karst land surface, and this may affect the function of plants. Here, we evaluated the responses of the radial growth rates of two major tree species (Masson pine and Camphor laurel) to a tunneling induced water stress event in a typical karst trough valley. Meanwhile, to discuss the overall influence of tunnel excavation on plant growth in all vegetation cover types, the dynamics of vegetation productivity around the tunnel were evaluated using remote sensing indices, the Normalized Difference Vegetation Index (NDVI), and Net Primary Productivity (NPP). Furthermore, we estimated the spatial–temporal variations of NDVI and NPP in other tunneling regions of Southwest China. The results showed that the soil moisture contents (SMC) around the Zhongliang Mountain Railway Line 6 (ZMRL6) tunnel had dramatically declined −5.06%∼−10.53% within the areas < 1500 m. After the excavation of ZMRL6 tunnel, the basal area increment (BAI) for the tree-ring widths of Masson pine and Camphor laurel within 1500 m of the tunnel central reduced by 94.8%∼135.8% and 116.6%∼139.9%, respectively, while the trees beyond this distance range were less influenced. Meanwhile, the remote sensing indices showed that tunnel excavation can reduce 3.3%∼7.6% of the NDVI and 15.7%∼17.4% of the NPP within 1500 m of the ZMRL6 tunnel. A similar distance range of such declines in NDVI and NPP was also found in other tunneling regions throughout the karst mountain areas of Southwest China. The findings in this study suggest that tunnel excavation may cause severe ecosystem degradation within 1500 m of the tunnel center, which should be considered in ecosystem management and conservation strategies in karst mountain areas.

Assessing the interrelation between NDVI and climate dependent variables by using granger causality test and vector auto-regressive neural network model

Changes in ecosystem structure and function can be revealed by examining the prevailing patterns in vegetation growth and the forces that shape those patterns. The mechanism of ecosystem behaviour may be better understood if the trend of vegetation change and its sensitivity to climatic variation are well understood. The interaction of vegetation and climatic factors (it's driving variables) is non-linear in behaviour and affected by time lag and time accumulation. Jharkhand has a typical plateau in eastern India, having a mixed climate (arid and semi-arid), taken as the study area, and the spatiotemporal distributions of the normalized difference vegetation index (NDVI) were explored with interaction driving factors. This study investigated the time-lag and time-accumulation effects of the NDVI response to climate factors Evapotranspiration (ET), Land Surface Temperature (LST), Potential Evapotranspiration (PET), Precipitation (PREC), and Soil Moisture (SM) and identified the primary controlling factors that affect the vegetation dynamics. The observations indicate that the correlation between NDVI and summer LST (- 0.838) was discovered to be greater than the correlation of NDVI with SM (r = 0.90) and PREC (r = 0.751), showing NDVI as more sensitive to LST when comparing to SM, and PREC, while PET exhibits the significant positive correlation (r = −0.751) with the NDVI in autumn during the studied duration. Higher NDVI values were seen during the monsoon (0.54 ± 0.12), which is correlated with a decrease in the monsoon LST (25.8 ± 0.20), followed by the winter (0.47 ± 0.13), summer (0.33 ± 0.18), and fall (0.37 ± 0.04). Vegetation growth is influenced by both the time-lag and time-accumulation effects of temperature and the time-accumulation impact of precipitation. Regarding the climate-vegetation response mechanism, the application of the Granger Causality (GC) Test and GC-based Vector Auto-Regressive Neural Network (VARNN) Model test reveals that the 0–2 month optimum time lag effect is prevalent in the study area. In addition, the LST and SM have a more prominent stimulating influence on plant growth in the study region than precipitation. The above findings highlight the need to effectively monitor vegetation dynamics under environmental changes by considering the temporal impacts of vegetation response to climate when the current climate models research vegetation-climate interactions.