Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Spatial analysis of vegetation cover response to climate trends in Khakassia(South Siberia)

An analysis of the changes in vegetation cover on the territory of the Republic of Khakassia in 2000–2021 due to climatic trends was carried out based on the MODIS data.The changes in vegetation cover were estimated based on trends in Normalized Difference Vegetation Index(NDVI)and Enhanced Vegetation Index(EVI).In general,in the 21st century,an increase in the biomass of vegetation cover is observed.Positive trends were observed in 16%–22%of the territory,and negative only in 1%–3%.For about 20%of the analyzed territory,a significant influence of climate on the changes in vegetation cover was revealed.The most pronounced negative impact on vegetation cover was caused by summer air and soil temperatures,spring temperature,and summer winds,and the positive impact was caused by summer precipitation and soil moisture.The response of the vegetation cover to climate was non-uniform concerning the topography.Thus,a significant correlation with the amount of precipitation was observed for~20%–35%of vegetation growing below 600 m above sea level and for less than 5%above this elevation.The negative effect of summer temperatures on plants prevailed mainly at an elevation below~1400 m above sea level.Projected climate change is likely to lead to significant degradation of vegetation in the steppe and foreststeppe in Khakassia in the coming decades.

The Influence of Vegetation Cover on Summer Precipitation in China: a Statistical Analysis of NDVI and Climate Data

This study provides new evidence for the feedback effects of vegetation cover on summer precipitation in different regions of China by calculating immediate (same season), and one-and two-season lagged correlations between the normalized difference vegetation index (NDVI) and summer precipitation. The results show that the correlation coefficients between NDVI in spring and the previous winter and precipitation in summer are positive in most regions of China, and they show significant difference between regions. The stronger one-and two-season lagged correlations occur in the eastern arid/semi-arid region, Central China, and Southwest China out of the eight climatic regions of China, and this implies that vegetation cover change has more sensitive feedback effects on summer precipitation in the three regions. The three regions are defined as sensitive regions. Spatial analyses of correlations between spring NDVI averaged over each sensitive region and summer precipitation of 160 stations suggest that the vegetation cover strongly affects summer precipitation not only over the sensitive region itself but also over other regions, especially the downstream region.

Vegetation cover change and the driving factors over northwest China

In this paper the spatio-temporal variation of vegetation cover in northwest China during the period of 1982-2006 and its driving factors were analyzed using GIMMS/NDVI data. The annual average NDVI was increased with a rate of 0.0005/a in northwest China and there was an obvious difference between regions. The trend line slopes of NDVI were higher than 0.0005 in the Tianshan Moutains and Altay Mountains of Xinjiang, the Qilian Mountains of Gansu and the eastern part of Qinghai, which indicated the vegetation cover was significantly increased in these areas. The trend line slopes of NDVI were lower than -0.0005 in the southern region of Qinghai, the border regions of Shaanxi and Ningxia, the parts of Gansu and Tarim Basin, Turpan and Tuoli in Xinjiang, which indicated the vegetation cover was declined in these areas. The NDVI of woodland, grassland and cultivated land had an ascending tendency during the study period. The study shows that the vegetation cover change was caused by both natural factors and human activities in northwest China. The natural vegetation change, such as forests was influenced by climate change, while human activities were the main reason to the change of planting vegetation. The changes of vegetation covers for different elevations, slopes and slope aspects were quite different. When the eleva- tion is exceeded to 4,000 m, the NDVI increasing trend was very low; the NDVI at the slope of less than 25~ was increased by the ecological construction; the variation of NDVI on sunny slope was stronger than that on shady slope. The temperature rose significantly in recent 25 years in northwest China by an average rate of 0.67^-C/10a, and precipitation increased by an average rate of 8.15 mm/10a after 1986. There was positive correlation between vegetation cover and temperature and annual precipitation changes. Rising temperature increased the evaporation and drought of soils, which is not conducive to plant growth, and the irrigation in agricultural areas reduced the correlation between agricultural vegetation NDVI and precipita- tion. The improvement of agricultural production level and the projects of ecological construction are very important causes for the NDVI increase in northwest China, and the ecological effect of large-scale ecological construction projects has appeared.

Spatial and temporal variations of vegetation cover and the relationships with climate factors in Inner Mongolia based on GIMMS NDVI3g data

Variation in vegetation cover in Inner Mongolia has been previously studied by the remote sensing data spanning only one decade. However, spatial and temporal variations in vegetation cover based on the newly released GIMMS NDVI3g data spanning nearly thirty years have yet to be analyzed. In this study, we applied the methods of the maximum value composite （MVC） and Pearson＇s correlation coefficient to analyze the variations of vegetation cover in Inner Mongolia based on GIMMS NDVI3g data spanning from 1982 to 2013. Our results indicate that the normalized difference vegetation index （NDVI） increased at a rate of 0.0003/a during the growing seasons despite of the drier and hotter climate in Inner Mongolia during the past three decades. We also found that vegetation cover in the southern agro-pastoral zone significantly increased, while it significantly decreased in the central Alxa. The variations in vegetation cover were not significant in the eastern and central regions. NDVI is positively correlated with precipitation （r=0.617, P=0.000） and also with air temperature （r=0.425, P=0.015）, but the precipitation had a greater effect than the air temperature on the vegetation variations in Inner Mongolia.

Responses of vegetation cover to the Grain for Green Program and their driving forces in the He-Long region of the middle reaches of the Yellow River

The implementation of the Grain for Green Program is a great breakthrough in the history of China＇s ecological environment construction,which can control soil erosion effectively,increase land productivity and improve the ecological environment.To investigate the eco-environmental benefits brought by the Grain for Green Program,the spatiotemporal variations of vegetation cover in the growing season from 2000 to 2010 across the Hekou-Longmen （He-Long） region were analyzed by using remote sensing information,meteorological data and land use data.Moreover,the impacts of climate and human activities on vegetation change were evaluated objectively.Annual vegetation cover in the growing season increased very significantly.Increased vegetation cover occurred in 98.7％ of the region,of which the area for vegetation cover improved slightly constituted 79.8％ of the whole area.Vegetation moderately improved was mainly distributed in the south of the He-Long region,covering 9.6％ of the area,and the area for vegetation basically unchanged concentrated in the middle and upper reaches of the Wuding River.Precipitation was found to be an important natural factor influencing vegetation cover change.The area of vegetation cover showing a significantly positive correlation with precipitation occupied 22.14％ of the region.As driven by policies from the Grain for Green Program,forestland increased significantly and land use structure became more intensive.Human activities played a positive and effective role in the protection,restoration and improvement of vegetation in the places where vegetation cover was basically unchanged,even though precipitation declined greatly,and vegetation improved moderately with massive increases of forestland and grassland.

Seasonal variations in the influence of vegetation cover on soil water on the loess hillslope

Soil water is the key factor that restricts the restoration of the local ecological systems in the Loess Plateau of China.Studying the effects of vegetation types on soil water and its seasonal variation helps to understand hydrological characteristics and provides insights into the sustainable restoration of vegetation.Therefore,the Caijiachuan watershed was chosen as the research object to investigate the water status of a 0-10 m soil layer under different vegetation types including Pinus tabulaeformis,Robinia pseudoacacia,Platycladus orientalis,apple orchard,natural forestland,farmland and grassland.By comparing the difference between soil water of different land use types and that of grassland during the same period,the seasonal changes of soil water status of different types were judged.The results show that(1)in the 0-10 m soil layer,the largest value of soil water content was in the0.3-0.4 m layer,and the lowest was in the 5.6-5.8 m layer.The depths at which the vegetation cover influenced the soil water were up to 10 m;(2)among summer,fall and spring,the soil water storage wasthe highest in the fall.In addition,the lowest value of relative accumulation was in the fall,which was the period in which the soil water recovered;(3)the soil water in the 0-10 m layer was in a relatively deficient state in the artificial forestlands,apple orchards and native forestlands,while the relative accumulation was in the farmland.In addition,the relative deep soil layers(8-10 m)had more serious deficits in the areas in which P.tabulaeformis,R.pseudoacacia and the apple orchard grew;(4)during the study period,the farmland in the summer had the largest relative accumulation(182.71 mm),and the land under R.pseudoacacia in the fall had the lowest relative deficit(512.20 mm).In the Loess Plateau,vegetation cover will affect the change of deep soil moisture and artificial forest will cause soil water loss in different degrees.

Dynamic change of net primary productivity and fractional vegetation cover in the Yellow River Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.

Vegetation cover density and disturbance affected arbuscular mycorrhiza fungi spore density and root colonization in a dry Afromontane forest, northern Ethiopia

Arbuscular mycorrhiza fungi(AMF) are vital in the regeneration of vegetation in disturbed ecosystems due to their numerous ecological advantages and therefore are good indicators of soil and ecosystem health at large. This study was aimed at determining how the seasonal, vegetation cover density, edaphic and anthropogenic factors affect AMF root colonization(RC) and spore density(SD)in Desa’a dry Afromontane forest. AMF RC and SD in the rhizosphere of five dominant woody species, Juniperus procera, Olea europaea, Maytenus arbutifolia, Carissa spinarum and Dodonaea angustifolia growing in Desa’a forest were studied during the rainy and the dry seasons in three permanent study vegetation cover density plots(dense, medium, and poor). Each plot(160 x40 m2) has two management practices(fenced and unfenced plots) of area. A 100 g sample of rhizosphere soil from moisturefree composite soil was used to determine spore density.Spore density ranged from 50 to 4467 spores/100 g soil,and all species were colonized by AMF within a range of 4–95%. Glomus was the dominant genus in the rhizosphere of all species. Vegetation cover density strongly affected SD and RC. The SD was significantly higher(p < 0.05) in the poor vegetation cover density than in the other two and lowest in the dense cover; root colonization showed the reverse trend. Management practices significantly(p <0.05) influenced AMF SD and RC, with the fenced plots being more favoured. Seasons significantly(p < 0.05) affected RC and SD. More RC and SD were observed in the wet period than the dry period. Correlating AMF SD and RC with soil physical and chemical properties showed no significant difference(p> 0.05) except for total nitrogen. Disturbance, vegetation cover density, season and total nitrogen are significant factors that control the dynamics and management interventions to maintain the forest health of dry Afromontane forests.

Spatial and temporal variability in vegetation cover of Mongolia and its implications

In this paper, we attempted to determine the most stable or unstable regions of vegetation cover in Mongolia and their spatio-temporal dynamics using Terra/MODIS Normalized Difference Vegetation Index （NDVI） dataset, which had a 250-m spatial resolution and comprised 6 periods of 16-day composited temporal resolution data （from 10 June to 13 September） for summer seasons from 2000 to 2012. We also used precipitation data as well as biomass data from 12 meteorological stations located in 4 largest natural zones of Mongolia. Our study showed that taiga and forest steppe zones had relatively stable vegetation cover because of forest characteristics and relatively high precipitation. The highest coefficient of variation （CV） of vegetation cover occurred frequently in the steppe and desert steppe zones, mainly depending on variation of precipitation. Our results showed that spatial and temporal variability in vegetation cover （NDVI or plant biomass） of Mongolia was highly dependent on the amount, distribution and CV of precipitation. This suggests that the lowest inter-annual CV of NDVI can occur dur- ing wet periods of growing season or in high precipitation regions, while the highest inter-annual CV of NDVI can occur during dry periods and in low precipitation regions. Although the desert zone received less precipitation than other natural zones of the country, it had relatively low variation compared to the steppe and desert steppe, which could be attributed to the very sparse vegetation in the desert.

Estimating wheat fractional vegetation cover using a density peak k-means algorithm based on hyperspectral image data

Fractional vegetation cover(FVC)is an important parameter to measure crop growth.In studies of crop growth monitoring,it is very important to extract FVC quickly and accurately.As the most widely used FVC extraction method,the photographic method has the advantages of simple operation and high extraction accuracy.However,when soil moisture and acquisition times vary,the extraction results are less accurate.To accommodate various conditions of FVC extraction,this study proposes a new FVC extraction method that extracts FVC from a normalized difference vegetation index(NDVI)greyscale image of wheat by using a density peak k-means(DPK-means)algorithm.In this study,Yangfumai 4(YF4)planted in pots and Yangmai 16(Y16)planted in the field were used as the research materials.With a hyperspectral imaging camera mounted on a tripod,ground hyperspectral images of winter wheat under different soil conditions(dry and wet)were collected at 1 m above the potted wheat canopy.Unmanned aerial vehicle(UAV)hyperspectral images of winter wheat at various stages were collected at 50 m above the field wheat canopy by a UAV equipped with a hyperspectral camera.The pixel dichotomy method and DPK-means algorithm were used to classify vegetation pixels and non-vegetation pixels in NDVI greyscale images of wheat,and the extraction effects of the two methods were compared and analysed.The results showed that extraction by pixel dichotomy was influenced by the acquisition conditions and its error distribution was relatively scattered,while the extraction effect of the DPK-means algorithm was less affected by the acquisition conditions and its error distribution was concentrated.The absolute values of error were 0.042 and 0.044,the root mean square errors(RMSE)were 0.028 and 0.030,and the fitting accuracy R2 of the FVC was 0.87 and 0.93,under dry and wet soil conditions and under various time conditions,respectively.This study found that the DPK-means algorithm was capable of achieving more accurate results than the pixel dichotomy method in various soil and time conditions and was an accurate and robust method for FVC extraction.

The application of very high resolution satellite image in urban vegetation cover investigation:a case study of Xiamen City

With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification, information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

Spatio-temporal variation of ecosystem service values adjusted by vegetation cover:a case study of Wuyishan National Park Pilot,China

Ecosystem service values(ESV)are strongly influenced by the vegetation cover,which is heterogeneous across different vegetation types.We develop a dynamic evaluation model of ESV for Wuyishan National Park Pilot adjusted by the rate of inflation and the fractional vegetation cover,which is calculated by an enhanced vegetation index from 2000 to 2018.The spatio-temporal variation of vegetation was also examined.The results demonstrated that:(1)the unit area of ecosystem service values adjusted by vegetation cover(ESVVC)shows a gradient of forest>tea plantation>grassland>cropland,and the major ecosystem services provided by forests include soil formation and conservation,climate regulation,and biodiversity maintenance;(2)the ESV_(VC) increased to 2.1 billion yuan(The reference rate announced by the People’s Bank of China is the US dollar to 6.42 Yuan per dollar.)from 2000 to 2018.Higher and lower ESV_(VC) are predominant in the northwest and southeast region,respectively.In addition,changes of ecological protection structures and human disturbances negatively affected vegetation cover,leading to a decreased ESVVC from 2000 to 2005 in the Jiuqu Stream Ecological Protection Area and the Wuyishan National Scenic Spot.The implementation of ecological protection policies from 2010 to 2018 enhanced the ESV_(VC) in the study area;and,(3)the ESVVC is highest in the southeast and 25°–35°area with altitudes of 800–1000 m.Our model can provide timely and helpful information of changes in ESV for use in ecological corridor design and ecological security monitoring.

Retrieving Multi-Scale Climatic Variations from High Dimensional Time-Series MODIS Green Vegetation Cover in a Tropical/Subtropical Mountainous Island

There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region.Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis(PCA) on 11 years(2001~2011) of highdimensional monthly photosynthetically active vegetation cover(PV) derived from the Moderate Resolution Imaging Spectroradiometer(MODIS) and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climaterelated variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component(PC1, explaining 94.5%of variance) loadings, as expected, were significantly correlated with the temporal dynamics of the PV(r =0.94), which was mainly governed by regional climate The temporal loadings of PC2 and PC3(0.8% and0.6% of variance, respectively) were significantly correlated with the temporal dynamics of the PV of forests(r = 0.72) and the farmlands(r = 0.80),respectively. The low-order components(PC4 and PC5, 0.3% and 0.2% of variance, respectively) were closely related to the occurrence of drought(r = 0.49)and to irregular ENSO associated climate anomalies(r =-0.54), respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index(SOI) with one to three months of time lags(r =-0.35 ^-0.43, respectively), revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to largescale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios.

Cultivation Systems Using Vegetation Cover Improves Sustainable Production and Nutritional Quality of New Rice for Africa in the Tropics

Little is known about the impact of direct sowing under vegetation cover on the production and quality of New Rice for Africa （NERICA） on poor oxisol. In this study, two NERICA varieties （NERICA 3 and NERICA 8） were grown under tropical oxisol soil with very low nutrient contents. Four cultivation systems were used in completely randomized block design, including plowing （control）, unplowed soil with dead vegetation cover （DVC）, unplowed soil with live vegetation cover （LVC） and unplowed soil with mixed vegetation cover （MVC）. DVC significantly improved the exponential growth of NERICAs. NERICA 3 was the more productive （2.16–3.05 t/hm2） compared with NERICA 8 （0.71–1.21 t/hm2）. Cultivation systems improved the nutritional quality of NERICAs. The total protein content of NERICA 3 under DVC and MVC was 84.8% and 75.0% higher than control, respectively. The total soluble carbohydrate contents of NERICA 8 under LVC and MVC was 73.2% and 57.3% higher than control, respectively. These results suggested that conservative approach like direct sowing on unplowed soil with vegetation cover systems can improve the nutritional quality of rainfed NERICAs and their sustainable production under poor oxisol soil in sub-Saharan Africa.

Response of Vegetation Cover Change to Drought at Different Time-scales in the Beijing-Tianjin Sandstorm Source Region,China

Dominated by an arid and semiarid continental climate,the Beijing-Tianjin Sandstorm Source Region(BTSSR)is a typical ecologically fragile region with frequently occurring droughts.To provide information for regional vegetation protection and drought prevention,we assessed the relations between vegetation cover change(measured by the Normalized Difference Vegetation Index,NDVI)and the Standardized Precipitation Evapotranspiration Index(SPEI)at different time-scales,in different growth stages,in different subregions and for different vegetation types based on the Pearson's correlation coefficient in the BTSSR from 2000 to 2017.Results showed that 88.19%of the vegetated areas experienced increased NDVI in the growing season;48.3%of the vegetated areas experi-enced significantly increased NDVI(P<0.05)and were mainly in the south of the BTSSR.During the growing season,a wetter climate contributed to the increased vegetation cover from 2000 to 2017,and NDVI anomalies were closely related to SPEI.The maximum correlation coefficient in the growing season(Rmax)was significantly positive(P<0.05)in 97.84%of the total vegetated areas.In the vegetated areas with significantly positive Rmax,pixels with short time-scales(1-3 mon)accounted for the largest proportion(33.9%).The sensitivity of vegetation to the impact of drought rose first and then decreased in the growing season,with a peak in July.Compared with two subregions in the south,subregions in the north of the BTSSR were more sensitive to the impacts of drought variations,especially in the Xilingol Plateau and Wuzhumuqin Basin.All four major vegetation types were sensitive to the effects of drought variations,especially grasslands.The time-scales of the most impacting droughts varied with growth stages,regions,and vegetation types.These results can help us understand the relations between vegetation and droughts,which are important for ecological restoration and drought prevention.

Change of Vegetation Cover and Its Relationships with Climatic Factors in Large-area Eucalyptus Introduced Region of Yunnan

Taking Lancang County as a study area with a large area of eucalyptus introduction in Yunnan, spatiotemporal change characteristics of vegetation cover, as well as the relationships between Enhanced Vegetation Index（EVl） and climatic factors （temperature and precipitation） were analyzed by using the data of MODIS-EVI from 2005 to 2010. The results indicated that： （1） The vegetation cover was overall good, and the annual average values of EVl were greater than 0.395 and showed a slow increasing trend from 2005 to 2010 in study area; the monthly average values of EVl ranged from 0.296 to 0.538, and seasonal variability was obvious. Monthly average values of EVl usually fell to the lowest level in February and March, and reached the peak in July and August. From the perspective of space, average EVl over the years significantly varied in different towns of Lancang County. During 2005 -2010, in 92.534% area of total, vegetation coverage change were not obvious; in 7.25% area of total, vegeta- tion becoming better; only in 0.02% area of total, vegetation cover were getting worse. （2） Monthly average values of EVl were significantly correlated with monthly average rainfall in Lancang County. The maxima of monthly average EVI and rainfall appeared in August on summer, while the minima of monthly average EVl and rainfall appeared in February and January on winter respectively. （3） Monthly average EVl was somewhat relative with monthly average temperature. The maxima of monthly average EVl and temperature appeared in June and August respectively, while the minima appeared in January and February respectively.

Examining Rate of Built-Up Areas on the Vegetation Cover along River Riara Riparian within Kiambu Town, Kenya

Urban river riparian spaces and their natural systems are valuable to urban dwellers;but are increasingly affected and ruined by human activities and in particular, urbanization processes. In this research, land sat and sentinel satellite imagery apt for change detection in vegetation cover, both landsat and sentinel imagery, covering the period between 1970 and 2021 in epochs of 1973, 1984, 1993, 2003, 2015 and 2021 years were used to establish the correlation between vegetation cover and built-up area along River Riara river reserve. The images were analysed to extract the built-up areas along the river reserve, including the buildings, and the rate of human settlements, which influenced vegetation cover. Normalized Difference Built-Up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) were computed using the Short-Wave Infrared (SWIR) and the Near Infra-Red (NIR) bands to show the rate of change over the years. Results indicate NDVI values were high, compared to NDBI values along river Riara in the years 1973 and 1993 implying that there was more vegetation cover then. However, in the year 2021, the NDVI indicated the highest value at 0.88, with the complementary NDBI indicating the highest NDBI value at 0.47. This represents a significant increase in built-up areas since 2015 more than in previous epochs. Either, there was a significant increase in NDBI values, from 0.24 in 1993 to 0.47 in 2021. More so, the R-squared value at 0.80 informed 80% relationship between NDBI and NDVI values indicating a negative correlation.

Analysis on Change of the Vegetation Cover in Poyang Lake Area from 1991 to 2005

[Objective] The reseamh aimed to analyze variation of the vegetation cover in Poyang Lake area from 1991 to 2005. [Method] Based on Landsat TM remote sensing images of 1991 and 2005 in Poyang Lake area, NDVI dimidiate pixel model was used to calculate vegetation cover- age. By transfer matrix, temporal-spatial change of the vegetation cover grade in the area was analyzed. [ Result] Vegetation cover in this region overall presented increase trend from 1991 to 2005, and forestry area increased somewhat. But at the same time, farmland area decreased to some extent. Sandlot and bare land also increased slightly. [ Conclusion] Governments and relevant departments should reasonably allocate land re- sources and protect natural ecology environment.

Variability of urban fractional vegetation cover and its driving factors in 328 cities in China

Urban green space promotes the health of urban residents,enhances urban ecosystem biodiversity,mitigates environmental pollution,and attenuates urban heat island effect.However,urban vegetation cover is highly heterogeneous and difficult to quantify.In this study,the variation of urban fractional vegetation cover(FVC)in 328 cities in China from 1990 to2022 was quantified based on Landsat satellite data at a 30-m resolution.It was found that from 1990 to 2005,due to increases in building density and impervious surfaces in cities,the national mean urban vegetation cover decreased from 0.38 to 0.35.After2005,urban vegetation cover began to reverse,reaching 0.45 in 2022.This increasing trend was most pronounced in newly built urban districts.The decrease in average urban vegetation cover before 2005 was mainly due to the expansion of low vegetation cover areas,while the increase in urban vegetation cover after 2005 manifested as the expansion of high vegetation cover areas.The reversal in the trend of urban vegetation cover change after 2004 is related to the gradual implementation of national policies requiring increased urban green space coverage.The urban gross domestic product(GDP)showed the highest correlation with changes in urban vegetation cover.For large and medium-sized cities,the top three factors influencing vegetation cover were GDP,urban population,and temperature.However,for cities in arid/semi-arid regions,changes in vegetation cover were more sensitive to climatic factors(such as precipitation).Although the urban vegetation cover in China has substantially increased in recent years,the urban green space in small-sized cities and in the old urban districts of large-sized cities still have room to improve.