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.

Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

Simple method for extracting the seasonal signals of photochemical reflectance index and normalized difference vegetation index measured using a spectral reflectance sensor

A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index, Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Impact of climate and human activity on NDVI of various vegetation types in the Three-River Source Region, China

The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.

Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world.Under the impacts of climate change and human activities,desertification is becoming increasingly severe on the Mongolian Plateau.Understanding the vegetation dynamics in this region can better characterize its ecological changes.In this study,based on Moderate Resolution Imaging Spectroradiometer(MODIS)images,we calculated the kernel normalized difference vegetation index(kNDVI)on the Mongolian Plateau from 2000 to 2023,and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test.We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis,and quantified the effects of climate change and human activities on kNDVI change by residual analysis.The results showed that kNDVI on the Mongolian Plateau was increasing overall,and the vegetation recovery area in the southern region was significantly larger than that in the northern region.About 50.99%of the plateau showed dominant climate-driven effects of temperature,precipitation,and wind speed on kNDVI change.Residual analysis showed that climate change and human activities together contributed to 94.79%of the areas with vegetation improvement.Appropriate human activities promoted the recovery of local vegetation,and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau.This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Response of vegetation variation to climate change and human activities in the Shiyang River Basin of China during 2001-2022

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

Drivers,Trends,and Patterns of Changing Vegetation-greenness in Nansha Islands,China from 2016 to 2022

Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how they relate to climate change and human activities.To resolve this limitation,we studied changes to the Normalized Difference Vegetation Index(NDVI)vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions.Trends of vegetation greenness were analyzed using Sen's slope and Mann-Kendall test at two spatial scales(pixel and island),and driving factor analyses were performed by time-lagged partial correlation analyses.These were related to impacts from human activities and climatic factors under normal(temperature,precipitation,radiation,and Normalized Difference Built-up Index(NDBI))and extreme conditions(wind speed and latitude of IRs)from 2016 to 2022.Results showed:1)among the 22 IRs,NDVI increased/decreased significantly in 15/4 IRs,respectively.Huayang Reef had the highest NDVI change-rate(0.48%/mon),and Zhongye Island had the lowest(–0.29%/mon).Local spatial patterns were in one of two forms:dotted-form,and degradation in banded-form.2)Under normal conditions,human activities(characterized by NDBI)had higher impacts on vegetation-greenness than other factors.3)Under extreme conditions,wind speed(R^(2)=0.2337,P<0.05)and latitude(R^(2)=0.2769,P<0.05)provided limited explanation for changes from typhoon events.Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations‘Ocean Decade’initiative.

Climate-Vegetation Coverage Interactions in the Hengduan Mountains Area, Southeastern Tibetan Plateau, and Their Downstream Effects

Little is known about the mechanism of climate-vegetation coverage coupled changes in the Tibetan Plateau(TP)region,which is the most climatically sensitive and ecologically fragile region with the highest terrain in the world.This study,using multisource datasets(including satellite data and meteorological observations and reanalysis data)revealed the mutual feedback mechanisms between changes in climate(temperature and precipitation)and vegetation coverage in recent decades in the Hengduan Mountains Area(HMA)of the southeastern TP and their influences on climate in the downstream region,the Sichuan Basin(SCB).There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA,which is most significant during winter,and then during spring,but insignificant during summer and autumn.Rising temperature significantly enhances local vegetation coverage,and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the atmosphere.The atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air pressure.The high pressure anomaly disperses downstream via the westerly flow,expands across the SCB,and eventually increases the SCB temperature.This effect lasts from winter to the following spring,which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring.These results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios,as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.

Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data

Variations in vegetation are closely related to climate change, but understanding of their characteristics and causes remains limited. As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index(NDVI) variations and find the potential causes in the source region of the Yangtze River. Based on four tree-ring width chronologies, the regional mean NDVI for July and August spanning the period 1665–2013 was reconstructed using a regression model, and it explained 43.9% of the total variance during the period 1981–2013. In decadal, the reconstructed NDVI showed eight growth stages(1754–1764, 1766–1783, 1794–1811, 1828–1838, 1843–1855, 1862–1873, 1897–1909, and 1932–1945)and four degradation stages(1679–1698, 1726–1753, 1910–1923, and 1988–2000). And based on wavelet analysis, significant cycles of2–3 yr and 3–8 yr were identified. In additional, there was a significant positive correlation between the NDVI and the Palmer Drought Severity Index(PDSI) during the past 349 yr, and they were mainly in phase. However, according to the results of correlation analysis between different grades of drought/wet and NDVI, there was significant asymmetry in extreme drought years and extreme wet years. In extreme drought years, NDVI was positively correlated with PDSI, and in extreme wet years they were negatively correlated.

Enhanced soil moisture improves vegetation growth in an arid grassland of Inner Mongolia Autonomous Region, China

Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI(normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region(northern China) during 1982–2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors,precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.

Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas

Climate warming is constantly causing hydro-meteorological perturbations,especially in high-altitude mountainous regions,which lead to the occurrences of landslides.The impact of climatic variables(i.e.,precipitation and temperature)on the distribution of landslides in the eastern regions of the Himalayas is poorly understood.To address this,the current study analyzes the relationship between the spatial distribution of landslide characteristics and climatic variables from 2013 to 2021.Google Earth Engine(GEE)was employed to make landslide inventories using satellite data.The results show that 2163,6927,and 9601 landslides were heterogeneously distributed across the study area in 2013,2017,and 2021,respectively.The maximum annual temperature was positively correlated with the distribution of landslides,whereas precipitation was found to have a non-significant impact on the landslide distribution.Spatially,most of the landslides occurred in areas with maximum annual precipitation ranging from 800 to 1600 mm and maximum annual temperature above 15℃.However,in certain regions,earthquake disruptions marginally affected the occurrence of landslides.Landslides were highly distributed in areas with elevations ranging between 3000 and 5000 m above sea level,and many landslides occurred near the lower permafrost limit and close to glaciers.The latter indicates that temperature change-induced freeze-thaw action influences landslides in the region.Temperature changes have shown a positive correlation with the number of landslides within elevations,indicating that temperature affects their spatial distribution.Various climate projections suggest that the region will experience further warming,which will increase the likelihood of landslides in the future.Thus,it is crucial to enhance ground observation capabilities and climate datasets to effectively monitor and mitigate landslide risks.

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.

Vegetation Change of Ecotone in West of Northeast China Plain Using Time-series Remote Sensing Data

Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.

Assessment of Human Impacts on Vegetation in Built-up Areas in China Based on AVHRR,MODIS and DMSP_OLS Nighttime Light Data,1992–2010

Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.

Variation of Thornthwaite Moisture Index in Hengduan Mountains, China

The Thornthwaite moisture index, an index of the supply of water （precipitation） in an area relative to the climatic demand for water （potential evapotranspiration）, was used to examine the spatial and temporal variation of drought and to verify the influence of environmental factors on the drought in the Hengduan Mountains, China. Results indicate that the Thornthwaite moisture index in the Hengduan Mountains had been increasing since 1960 with a rate of 0.1938/yr. Annual Thomthwaite moisture index in Hengduan Mountains was between -97.47 and 67.43 and the spatial heterogeneity was obvious in different seasons. Thomthwaite moisture index was high in the north and low in the south, and the monsoon rainfall had a significant impact on its spatial distribution. The tendency rate of Thomthwaite moisture index variation varied in different seasons, and the increasing trends in spring were greater than that in summer and autumn. However, the Thomthwaite moisture index decreased in winter. Thomthwaite moisture index increased greatly in the north and there was a small growth in the south of Hengduan Mountains. The increase of precipitation and decrease of evaporation lead to the increase of Thomthwaite moisture index. Thornthwaite moisture index has strong correlation with vegetation coverage. It can be seen that the correlation between Normalized Difference Vegetation Index （NDVI） and Thomthwaite moisture index was positive in spring and summer, but negative in autumn and winter. Correlation between Thornthwaite moisture index and relative soil relative moisture content was positive in spring, summer and autumn, but negative in winter. The typical mountainous terrain affect the distribu- tion of temperature, precipitation, wind speed and other meteorological factors in this region, and then affect the spatial distribution of Thomthwaite moisture index. The unique ridge-gorge terrain caused the continuity of water-heat distribution from the north to south, and the water-heat was stronger than that from the east to west part, and thus determined the spatial distribution of Thornthwaite mois- ture index. The drought in the Hengduan Mountains area is mainly due to the unstable South Asian monsoon rainfall time.

Impact of climatic factors on vegetation dynamics in the upper Yangtze River basin in China

It is necessary to understand vegetation dynamics and their climatic controls for sustainable ecosystem management.This study examines the vegetation dynamics and the effect of climate change on vegetation growth in the pristine conditions of 58 woodland National Nature Reserves(NNRs)located in the upper Yangtze River basin(UYRB)in China which are little influenced by human activities.Changes in the normalized difference vegetation index(NDVI),precipitation,and temperature in the selected NNRs were observed and analyzed for the period between 1999 and 2015.The relationship between time-lag effect of climate and changes in the NDVI were assessed using Pearson correlations.The results showed three major trends.1)The NDVI increased during the study period;this indicates an increase in the amount of green vegetation,especially due to the warmer climate during the growing season.The NDVIs in March and September were significantly affected by the temperature of the previous months.Spring temperatures increased significantly(P<0.05)and there was a delay between climatic factors and their effect on vegetation,which depended on the previous season.In particular,the spring temperature had a delayed effect on the NDVI in summer.2)The way in which vegetation responds to climatic factors varied significantly across the seasons.Temperature had a greater effect on the NDVI in spring and summer and the effect was greater at higher altitudes.A similar trend was observed for precipitation,except for altitudes of 1000–2000 m.3)Temperature had a greater effect on the NDVI in spring and autumn at higher altitudes.The same trend was observed for precipitation in summer.These findings suggest that the vegetation found in NNRs in the upper reaches of the Yangtze River was in good condition between 1999 and 2015 and that the growth and development of vegetation in the region has not been adversely affected by climate change.This demonstrates the effectiveness of nature reserves in protecting regional ecology and minimizing anthropogenic effects.

Spatial-temporal Changes of Vegetation Cover in Guizhou Province, Southern China

Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION(1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index(NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country(0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area(0.030/10 yr) is faster than that in non-karst area(0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.

Mapping rice cropping systems using Landsat-derived Renormalized Index of Normalized Difference Vegetation Index （RNDVI） in the Poyang Lake Region, China

Mapping rice cropping systems with optical imagery in multiple cropping regions is challenging due to cloud contamination and data availability; development of a phenology-based algorithm with a reduced data demand is essential. In this study, the Landsat-derived Renorma- lized Index of Normalized Difference Vegetation Index （RNDVI） was proposed based on two temporal windows in which the NDVI values of single and early （or late） rice display inverse changes, and then applied to discriminate rice cropping systems. The Poyang Lake Region （PLR）, characterized by a typical cropping system of single cropping rice （SCR, or single rice） and double cropping rice （DCR, including early rice and late rice）, was selected as a testing area. The results showed that NDVI data derived from Landsat time-series at eight to sixteen days captures the temporal development of paddy rice. There are two key phenological stages during the overlapping growth period in which the NDVI values of SCR and DCR change inversely, namely the ripening phase of early rice and the growing phase of single rice as well as the ripening stage of single rice and the growing stage of late rice. NDVI derived from scenes in two temporal windows, specifically early August and early October, was used to construct the RNDVI for discriminating rice cropping systems in the polder area of the PLR, China. Comparison with ground truth data indicates high classification accuracy. The RNDVI approach highlights the inverse variations of NDVI values due to the difference of rice growth between two temporal windows. This makes the discrimination of rice cropping systems straightforward as it only needs to distinguish whether the candidate rice typeis in the period of growth （RNDVI 〈 0） or senescence （RNDVI 〉 0）.