NDVI Variation Research Articles

Spatial variation of soil organic carbon in the Qinghai Lake watershed, northeast Qinghai-Tibet Plateau

Soil organic carbon (SOC) on the Qinghai-Tibet plateau is of global significance, due to the high carbon density and potential positive feedbacks to climate warming. Qinghai Lake watershed is an important soil pool in Qinghai-Tibet plateau, but the magnitude and characteristics of SOC stock in the high-altitude basin were not clear. To understand better how much SOC was stored and its spatial patterns in the watershed, this study analyzed the vertical variation of SOC content, quantified its influence by varied environmental factors, and further predict its storage in the entire basin. Results showed that, the SOC content decreased with the increasing depth, and was the highest in the alpine meadow in all depths, following by the alpine steppe and temperate steppe, respectively. It was generally higher in the permafrost region than that in the non-permafrost region at all depths. Soil profile depth, soil water content and NDVI could together explain about 72.6% of total variation in SOC density. The regression-kriging method was the best upscaling approach for the prediction of SOC in the study area. Approximately 317 Tg organic carbon was stored in the entire soil profile of Qinghai Lake watershed, in which 136, 140, and 41 Tg were at 0–30 cm, 30–100 cm, and below 100 cm, respectively. The higher SOC density mainly appeared on the northeast and southern region of Qinghai Lake, while the high-altitude area in the northwest of the watershed had the lower values. Moreover, it increased firstly and then decreased with the increase of altitude, with the maximum values at 3350–3400 m, which was dominated by the elevational variation of soil profile depth and NDVI. Overall, the comprehensive assessment of SOC demonstrated high storage and strong heterogenicity of soil carbon in the Qinghai Lake watershed, and it is critical for the sustainability of regional terrestrial ecosystem with future climate change.

SAMZ-Desert: A Satellite-based agricultural management zoning tool for the desert agriculture region of southern California

• A total of 6852 agricultural fields were studied in southern California. • A GIS/RS-based tool for management zone (MZ) delineation was developed. • Only 25% of strongly clustered fields showed moderately stable static MZs over time. A GIS and remote sensing-based decision support tool called SAMZ-Desert was developed for management zones (MZs) delineation of a total of 6852 fields in the Imperial County region of southern California using Landsat-8 NDVI data acquired on 27/4 2018. In addition, a total number of 11 cloud-free images in 2018–2020 were statistically analyzed to determine the extent of within-field NDVI variability and temporal stability of MZs at the regional level. A majority (approx. 37%) of the fields had four zones as an optimum number of zones in the region, which could explain>85% of the within-field NDVI variance. Around 13% ( n = 873) of the fields in the region were strongly spatially-clustered in at least half the Landsat-8 cloud-free scenes and can benefit from variable rate technologies. Our results suggest that dynamic zoning over time might be necessary for most of these fields. SAMZ-Desert can be accessed from the Haghverdi Water Management Group website: http://www.ucrwater.com/software-and-tools.html .

Random Forest Classification of Land Use, Land-Use Change and Forestry (LULUCF) Using Sentinel-2 Data—A Case Study of Czechia

Land use, land-use change and forestry (LULUCF) is a greenhouse gas inventory sector that evaluates greenhouse gas changes in the atmosphere from land use and land-use change. This study focuses on the development of a Sentinel-2 data classification according to the LULUCF requirements on the cloud-based platform Google Earth Engine (GEE). The methods are tested in selected larger territorial regions (two Czech NUTS 2 units) using data collected in 2018. The Random Forest method was used for classification. In terms of classification accuracy, a combination of these parameters was tested: The Number of Trees (NT), the Variables per Split (VPS) and the Bag Fraction (BF). A total of 450 combinations of different parameters were tested. The highest accuracy classification with an overall accuracy = 89.1% and Cohen’s Kappa = 0.84 had the following combination: NT = 150, VPS = 3 and BF = 0.1. For classification purposes, a mosaic was created using the median method. The resulting mosaic consisted of all Sentinel-2 bands in 10 and 20 m spatial resolution. Altitude values derived from SRTM and NDVI variance values were also included in the classification. These added bands were the most significant in terms of Gini importance.

Nature-Based Solutions Benefit the Economic–Ecological Coordination of Pastoral Areas: An Outstanding Herdsman’s Experience in Xilin Gol, China

Grassland has always had a difficult economic–ecological relationship, as coordination between its ecological conservation and the sustainable development of animal husbandry is required. Nature-based Solutions (NbS), who make full use of the natural ecosystem services, have successfully solved some economic–ecological issues, but still have unclear implementation prospects for grassland management. The Xilin Gol grassland is one of the most typical pastoral areas in China; there is a village chief named Bateer, who has already used NbS for grassland management. To confirm whether the solutions employed by Bateer have been effective for both increasing economic profits and protecting grassland ecosystem, we interviewed him, and many other herdsmen, using questionnaires about their livelihood. Based on these questionnaires, we calculated and compared their income–cost ratios. Meanwhile, we analyzed the NDVI variations inside their rangelands through high-resolution remote sensing images. The results showed that the herdsmen in Bateer’s village had a much higher disposable income and income–cost ratio than others, and their rangelands also had a higher value and a more obvious increasing trend of NDVI. Bateer’s success proves that the NbS can also play a positive role in grassland management, which can provide a valuable guidance for economic–ecological coordination in pastoral areas.

Spatial and temporal variation in NDVI and NDWI of the Ukhma River Basin, Central India

The present study is a reasonable step on quantitative approaches of water management and advancement of groundwater potential for watershed development of the Ukhma River Basin with the help of remote sensing and GIS techniques. The Ukhma River is one of the significant NW (north-west) flowing tributaries of the Tons River in Central India occupying a 745 sq km area within the Kaimur and Rewa Group of rocks in the Son valley sector. It originates from Ledari Village and joins the Tons River near Deokhar village, Satna District, Madhya Pradesh, Central India. In the present study variations in NDVI and NDWI of the Ukhma River Basin has been measured significantly from 2006-2019. The NDVI and NDWI provide turbidity estimations of the basin's vegetation cover and water resources. The change in NDVI and NDWI detection from 2006-2019 indicates that the area susceptible to erosivity increases the surface runoff reduces the infiltration rate.

Genetic analysis and marker association of physiological traits under rainfed and heat stress conditions in spring wheat (Triticum aestivum L.)

Identifying gene interactions and markers associated with physiological traits, especially at later stages of grain filling, can help develop effective breeding methodology in wheat crop. Six generations (P1, P2, F1, F2, BC1P1 and BC1P2) of four different spring wheat crosses (drought-responsive x drought susceptible) and F3 generation of a single cross, i.e., MACS6272 x UP2828 were phenotyped and genotyped to decipher gene action and associated markers. Ample variation in canopy temperature depression (CTD - 2.6 - 5.6?C), chlorophyll content by SPAD (39.6 - 51.3), relative water content (RWC - 51.5 - 75.4 %), grain filling period (GFP - 61.1 - 80.1 days), 100 seed weight (3.7 - 5.5 grams), harvest index (HI - 25.8 - 46.2 %), biological yield (BY - 35.5 - 89.8 grams) and grain yield (GY - 13.4 - 36.5 grams) per plant were observed in six generations. GY positively correlated with CTD, SPAD, 100SW, BY and HI (0.08* - 0.85**). BY had the maximum direct (0.82) and indirect effect via other traits on GY. Significant non-additive epistatic interactions (j & l) and duplicate gene action were found for most traits except GFP and 100SW. Seven different SSR markers associated with CTD, SPAD, NDVI, RWC, 100SW, and explained phenotypic variation (PVE) ranging from 10.1% to 18.4%, with marker Xcfd35 explaining highest PVE for RWC. The identified candidate genes (in silico) belonged to transmembrane proteins (Xcfd32, Xcfd50), nucleic acid binding domains (Xbarc124, Xgwm484) and having enzymatic activity (Xcfd35, Xwmc47, Xwmc728) important for abiotic stress tolerance. Complex inheritance deciphered by six generations indicated delaying the selection to later stages of segregation so that useful transgressive segregants can be selected for improving grain yields in wheat.

Multiple Effects of Topographic Factors on Spatio-Temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Qinghai-Tibet Plateau

Topographic factors are critical for influencing vegetation distribution patterns, and studying the interactions between them can enhance our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000–2019), combined with the Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Qinghai-Tibet Plateau (QTP) in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000–2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the entire basin and each sub-basin. During 2000–2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with variations in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with higher NDVI in the southern regions NDVI than those in the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation. Our results confirmed the importance of topographic factors on vegetation growth processes and have implications for understanding the sustainable development of mountain ecosystems.

Spatial Evapotranspiration Modeling Assisted With Landsat 8 Image Using Sebal And Geographically Weighted Regression Methods In Magelang District

Information about evapotranspiration is very important in relation to vegetation because it can be used for planning both in urban planning and agriculture. Magelang Regency has a lot of vegetated green land, both agricultural and non-agricultural and has no information about evapotranspiration. The calculation of evapotranspiration uses the SEBAL (Surface Energy Balance Algorithm for Land) method and modeling uses the GWR (Geographiccaly Weighted Regression) model. Calculation and modeling assisted by QGIS 2.14, QGIS 3.6, SPSS 20, and GWR 4.09 applications. The results showed that (1) GWR evapotranspiration model with significance (sig.) 5% is divided into 3 sub-district groups according to the significant variables in the sub-district (2) NDVI and Surface Albedo variables have a small effect on a global scale and have a large effect on a local scale.

Phenotyping of productivity and resilience in sweetpotato under water stress through UAV‐based multispectral and thermal imagery in Mozambique

AbstractSweetpotato is a crucial crop to guarantee food security in sub‐Saharan Africa, and drought events are considered one of the most critical factors affecting sweetpotato productivity in this region. In this study, airborne imagery based on reflectance (NDVI, CIred‐edge) and canopy temperature minus air temperature (dT) indices was used to characterize sweetpotato genotypes under drought treatments in Mozambique. Two field experiments established in rainy/hot (Trial A) and dry/cool (Trial B) seasons were assessed. In Trial A, 24 genotypes were subjected to early‐ (ESD), mid‐ (MSD) and late‐season (LSD) drought stress treatments and compared against a control. In Trial B, 120 genotypes were subjected to LSD only. The percentage of reduction in vine weight (PRVW) under drought was related primarily to temporal variation of NDVI and CI, regardless of drought treatment and seasons. dT in relation to control (dTAmp) was associated with PRVW in ESD‐Trial A and LSD‐Trial B, whereas under LSD‐Trial A, dTAmp was related to total fresh storage root weight (TRW). During the rainy/hot season, higher TRW reduction was promoted under ESD; however, under LSD, it was possible to identify productive genotypes able to withstand drought stress, highlighting their relevance for drought‐tolerance selection purposes.

Vegetation dynamics and responses to climate change and anthropogenic activities in the Three-River Headwaters Region, China

The Three-River Headwaters Region (TRHR) is an area of crucial significance for the ecological security of China. Owing to dramatic climate change and human activities driven by a series of ecological restoration projects, the ecological environment and vegetation have changed drastically in recent years. However, our knowledge of the current state and driving force of the change in the entire region is limited. This study mapped the spatiotemporal changes in vegetation coverage and quantitatively identified the contributions of climate change and anthropogenic factors to such variations from 2000 to 2018 using 133 MODIS NDVI images at 250 m resolution. The results show that over the past 19 years, the average NDVI demonstrated a fluctuating but upward trend, with a rate of increase of 0.0013 yr−1. Areas with increased vegetation coverage accounted for 54.93% of the entire area, and among them, 18.52% showed a significant greening trend. Based on the Hurst exponent, areas with sustained increasing trends were primarily concentrated in the northeastern, western, and southwestern parts of the Yellow River region, and the western Yangtze River region. The average contributions of the precipitation, temperature, and sunshine duration to NDVI were 0.069, 0.098, and 0.059%·yr−1, respectively. Sunshine duration had the greatest influence on the inter-annual change of NDVI during the entire study period, while the temperature was the main climatic factor from 2000 to 2010. The average contributions of climate change and anthropogenic factors to inter-annual variations of NDVI were 0.226 and –0.096%·yr−1, respectively. The general climate conditions are beneficial to the vegetation recovery, whereas human activities negatively impact the vegetation growth. However, the ecological afforestation projects positively influenced the east Yellow River, Lancang River, and west Yangtze River regions.

Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data

The study uses 30 years of the third generation of Advanced Very-High-Resolution Radiometer (AVHRR) NDVI3g monthly data from 1982 to 2012 to identify the natural clusters and important driving factors of the upstream watersheds in Taiwan through hierarchical cluster analysis (HCA) and redundancy analysis (RDA), respectively. Subsequently, as a result of HCA, six clusters were identified based on the 30 years of monthly NDVI data, delineating unique NDVI characteristics of the upstream watersheds. Additionally, based on the RDA results, environmental factors, including precipitation, temperature, slope, and aspect, can explain approximately 52% of the NDVI variance over the entire time series. Among environmental factors, nine factors were identified significantly through RDA analysis for explaining NDVI variance: average slope, temperature, flat slope, northeast-facing slope, rainfall, east-facing slope, southeast-facing slope, west-facing slope, and northwest-facing slope, which reflect an intimate connection between climatic and orthographic factors with vegetation. Furthermore, the rainfall and temperature represent different variations in all scenarios and seasons. With consideration of the characteristics of the clusters and significant environmental factors, corresponding climate change adaptation strategies are proposed for each cluster under climate change scenarios. Thus, the results provide insight to assess the natural clustering of the upstream watersheds in Taiwan, benefitting future sustainable watershed management.

NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam

Tea is one of the most significant cash crops and plays an important role in economic development and poverty reduction. On the other hand, tea is an optimal choice in the extreme weather conditions of Tanuyen Laichau, Vietnam. In our study, the NDVI variation of tea in the growing season from 2009 to 2018 was showed by calculating NDVI trend and the Mann-Kendall analysis to assess trends in the time series. Support Vector Machine (SVM) and Random Forest (RF) model were used for predicting tea yield. The NDVI of tea showed an increasing trend with a slope from −0.001–0.001 (88.9% of the total area), a slope from 0.001–0.002 (11.1% of the total area) and a growing rate of 0.00075/year. The response of tea NDVI to almost climatic factor in a one-month time lag is higher than the current month. The tea yield was estimated with higher accuracy in the RF model. Among the input variables, we detected that the role of Tmean and NDVI is stronger than other variables when squared with each of the independent variables into input data.

Differing Fine-Scale Responses of Vegetation and Bare Soil to Moisture Variation in a Pinyon-Juniper Woodland Underlie Landscape-Scale Responses Observed from Remote Sensing

Pinyon juniper woodlands in the American southwest face an uncertain ecological future with regard to climate altered precipitation. Although satellite remote sensing will be relied upon to assess the overall health of these plant communities more fine scaled information is needed to elucidate the mechanisms shaping the broader scaled regional assessments. We conducted a study to assess the NDVI response at the plant canopy level (insitu sensors placed over the canopies) of three tree and one shrub species to changes in precipitation, reference evapotranspiration and soil volumetric water content. Landsat data was used to compare stand integrated and satellite NDVI values. We also provided supplemental water in the amount of 10.85 cm over the study period to additional trees and shrubs which also had insitu NDVI sensors placed over their canopies. NDVI at the canopy level separated statistically by species and when contrasted with bare soil (p<0.001). Spring early summer dry down events were inversely related to increasing ETref-precipitation with a steeper dry down slope in the first year associated with no rainfall occurring in May and June. All three-tree species did not show any significant difference in canopy NDVI based on supplemental water, however the shrub species did reveal a significant response to water (p<0.001). Although all of the three-tree species revealed a one-month period in which they responded to precipitation in July of the first year after 11.2 cm of precipitation, no immediate (day of or next day) response was observed to precipitation or supplemental water events. Snowberry was unique in its NDVI response during the spring green up period in the second year revealing a highly linear shift over a 40-day period with a clear separation between treatments (p<0.001) with those plants receiving supplemental water having a higher more positive slope. Landsat NDVI values revealed an inverse sinusoidal relationship with ETref-precipitation (R2=0.59 p=0.012). Landsat values (0.19+/- 0.01) were found to have no significant difference with bare soil NDVI (0.17+/- 0.01) but were significantly different from all four tree and shrub species. Integrated NDVI based on sensor weighted % cover estimates (0.37+/-0.03) were nearly double Landsat values (0.19+/-0.01). Both NDVI values of pinyon pine and Utah juniper were found to be linear correlated with Landsat NDVI in the second Year (R2>0.75, p<0.001). Multiple regression analysis revealed that 95% of the variation in Landsat NDVI in the second year could be accounted for based on bare soil NDVI and pinyon pine NDVI (p<0.001). et al., NDVI interspace (bare soil) of pinyon juniper woodlands dominated the nature of the Landsat curve. Our results demonstrate the value of ground sensors to help fill the gap between what can be inferred at the forest canopy level and what is occurring at the plant level.

Spatiotemporal Variations of NDVI in Xinjiang Tianchi Bogda Peak natural reserve from 1990 to 2015

The spatial characteristics of NDVI of Xinjiang Tianchi Bogda Peak natural reserve are analyzed by using the AVHRR and MODIS NDVI date from 1990 to 2015. The temporal change of NDVI of this natural reserve is analyzed by using one variable linear regression and the correlation analysis. The results indicate that, the NDVI values are higher in north than those in south in 2015. As the altitude increases, the NDVI first increases, and then decreases. According to the grading results, the proportion of the moderate vegetation grade is larger than others. From 1990 to 2015, the change rate of NDVI is 0.0171/5a (p > 0.05). The NDVI of this natural reserve shows an increasing tendency, except for 2005-2010. The results of this study provide a theoretical basis for the management department to fully understand the vegetation status in the natural reserve, and to make policies and measures accordingly.

Vegetation responses to climatic and geologic controls on water availability in southeastern Arizona

Vegetation distribution, composition and health in arid regions are largely dependent on water availability controlled by climate, local topography and geology. Despite a general understanding of climatic and geologic drivers in plant communities, trends in plant responses to water distribution and storage across areas under different local controls are poorly understood. Here we investigate the multi-decadal interactions between spatial heterogeneity of geologic controls and temporal variation of climate, and their impacts on water availability to vegetation and plant responses (via normalized difference vegetation index, NDVI) in a monsoon-driven arid region of southeastern Arizona. We find that grasslands display low NDVI and respond directly to monsoonal rainfall. In the uplands, vegetation on west-facing slopes and in canyons share similar NDVI averages and variability, suggesting that they both use water from surface-groundwater flow paths through fractured rocks. Along the San Pedro River, streamflow, groundwater, and NDVI in deciduous riparian woodlands are strongly responsive to monsoonal rainfall, but water availability stratifies between wet (perennial), intermediate, and dry reaches, underlain by different local geologic controls that affect water table elevation. These controls interact with the driving climate to affect water availability in the shallow alluvial aquifer of the riparian zone, a primary water source to the gallery phreatophytes. A recent shift toward a strengthened monsoon in the region has led to an increase in water availability for grasslands and for dry reaches of the San Pedro, while the benefit is more muted along wetter reaches, where the riparian forest shows signs of having reached its maturity, with diminished trends in NDVI. These results have implications for the future vulnerability of dryland vegetation to climate change, which may be either dampened or intensified by local controls such as geology.

Effects of Intermittent Water Allocation on Vegetation Dynamics in Lake Baiyangdian, North China

The ecological effects of intermittent water supplement in Lake Baiyangdian were analyzed with an NDVI time series based on the data from 1 April 1998 to 31 July 2008. Four NDVI categories were extracted, and twelve stages were grouped based on the specific replenishment time of water allocation. STR (a seasonal-trend decomposition procedure based on regression) and its corresponding linear regression and abrupt change detection were used to highlight the temporal variations in vegetation under the effects of water allocation. ANOVA was used to identify the response quality of the vegetation in each stage. The results showed that the significant increasing trend of each NDVI category was detected by linear regression (p < 0.001). The 95% abrupt change intervals showed uncertainty and complexity in the immediate vegetation response to water division times. The most abrupt changes were detected in the growing seasons. The extremely significant differences in NDVI variation before and after water allocations were detected by ANOVA (p < 0.001, t-test). The longer the duration of water allocation was maintained, the higher the detection of vegetation coverage was relatively. The increased vegetation coverage benefited from the constant water supply. Our results provide evidence of vegetation responses to intermittent water divisions. The positive effects of water allocation on regional ecological restoration were confirmed. This study strengthened the water division effects of regional vegetation restoration and provided a practical strategy for an effective implementation of water allocation.

Characteristics of NDVI Temporal and Spatial Variation in the Source Area of the Yangtze River and Its Response to Hydrothermal Conditions

vegetation cover change monitoring is the basis of regional resources and environmental carrying capacity research. Based on the data set MODIS-NDVI 2001∼2018, this paper analyzes the spatial and temporal characteristics of annual NDVI in the Yangtze River source area by using maximum synthesis method and various statistical methods. The effects of surface hydrothermal conditions on space and time were discussed. The results show that:1) the NDVI of the source area of the Yangtze River shows a significant increase trend, and only some areas of Dongyuan NDVI show a downward trend. In spatial distribution, the vegetation coverage in the source area of the Yangtze River is mainly low and medium vegetation coverage, the vegetation coverage increases gradually from northwest to southeast, and the vegetation coverage of Yushu Tibetan Autonomous region is generally higher than that of Hercynian Mongolian Tibetan Autonomous region. At above 4000 m, the vegetation coverage increases more obviously with the increase of altitude. 2) precipitation in the source area of the Yangtze River decreases gradually from southeast to northwest, the low value area is located in the north of the source area of the Yangtze River, and the high value area is located in the eastern part of the Yushu Tibetan Autonomous region. However, the spatial trend of annual mean temperature and precipitation in the source area of the Yangtze River is opposite. The precipitation tendency rate in the source area of the Yangtze River shows obvious spatial difference, the precipitation in the south source generally shows a decreasing trend, and the precipitation in the north source generally shows an increasing trend. The southwest source and east source NDVI of 3) Yangtze River source area are negatively correlated with precipitation, while NDVI and temperature are positively correlated in most areas of the Yangtze River source area, and the effect of temperature on interannual variation is stronger than that of temperature. With the increase of temperature and precipitation, the NDVI also shows an increasing trend in spatial distribution, but precipitation has a stronger effect on the spatial heterogeneity of NDVI. From this we can see that the influence of hydrothermal conditions on the interannual variation of NDVI depends on the temperature, while the effect on spatial distribution mainly depends on the precipitation.

Spatial-temporal variation of NDVI and its responses to precipitation in the upper of Heihe from 2000 to 2019

As the direct result of climate change, Spatio-temporal variation of vegetation cover is an important index in regional ecological change. Based on Google Earth Engine, MODIS-NDVI and precipitation of TRMM from 2000 to 2019 were extracted. Trend analysis method and PCCs were applied to explore the different scales temporal and spatial change of NDVI and the relationship between NDVI and precipitation in the upper of Heihe River Basin. It was found that the annual change of vegetation increased slowly in the study area, and correlation of vegetation NDVI with precipitation are insignificant. On month scale, the vegetation change was cyclical, there was a noticeable increase from June to September, but from November to next February, the vegetation coverage was the lowest, the change of precipitation had the similar variation pattern, and there was a strong positive correlation between precipitation and NDVI. In terms of spatial change, the NDVI rose generally from northwest to southeast, vegetation coverage in northwest was improved.

Effect of fertilizer application on winter wheat productivity under precision agriculture in Kazakhstan

Abstract. Baimuratov, A, Bastaubayeva S, Arslan M, Yeraliyeva Z. 2021. Effect of fertilizer application on winter wheat productivity under precision agriculture in Kazakhstan. Biodiversitas 22: 1558-1563. The effect of mineral fertilization of light chestnut soils of Almalybak, Kazakhstan on the three winter wheat varieties grain yields and NDVI was carried out in 2017/18, 2018/2019 as well as 2019/2020 growing seasons using precision agriculture technologies. The experiments were set up in an incomplete factorial design with rates of NPK N90P60K45, N120P90K60, and N150P120K90. Agrochemical cartograms were ordered for the substance of effectively hydrolyzable nitrogen, extractable phosphorus, and exchangeable potassium. The total variation of NDVI was from 0.62 in the minimum (Bezostaya 100 variety, 2017/18) to 0.88 in the maximum (Aliya variety, 2019/20) in the flowering phase of wheat plants. The highest index of NDVI was observed in the N150P120K90 in the three winter wheat varieties for the three seasons. Studies directed in multivariate analyses built up the connection between fertilizer application, soil fruitfulness, and grain yield. As per the genuine heterogeneity of the fields, standards were determined and differential use of the fundamental phosphorus fertilizer was completed. The yield for the winter wheat varieties varied between 5.6-5.9 t/ha for Aliya variety, 6.5-7.0 t/ha for Grom, and 6.2- 6.7 t/ha for Bezostaya 100, which presents that P120 doses were more suitable in experimental plots for winter wheat varieties. The grain yield on mineral fertilization of NPK for the studied varieties varied from 4.2 to 7.6 t/ha for Aliya variety, from 4.0 to 6.8 t/ha for the Bezostaya 100, and from 4.5 to 7.9 t/ha for Grom. The highest grain yield was observed in the N150P120K90 for three winter wheat varieties in all three seasons.

Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.