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.

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.

Retrospective analysis of two northern California wild-land fires via Landsat five satellite imagery and Normalized Difference Vegetation Index (NDVI)

Wild-land fires are a dynamic and destructive force in natural ecosystems. In recent decades, fire disturbances have increased concerns and awareness over significant economic loss and landscape change. The focus of this research was to study two northern California wild-land fires: Butte Humboldt Complex and Butte Lightning Complex of 2008 and assessment of vegetation recovery after the fires via ground based measurements and utilization of Landsat 5 imagery and analysis software to assess landscape change. Multi-temporal and burn severity dynamics and assessment through satellite imagery were used to visually ascertain levels of landscape change, under two temporal scales. Visual interpretation indicated noticeable levels of landscape change and relevant insight into the magnitude and impact of both wild-land fires. Normalized Burn Ratio (NBR) and delta NBR (DNBR) data allowed for quantitative analysis of burn severity levels. DNBR results indicate low severity and low re-growth for Butte Humboldt Complex “burned center” subplots. In contrast, DNBR values for Butte Lightning Complex “burned center” subplots indicated low-moderate burn severity levels.

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.

基于Sentinel-2A NDVI时间序列数据和随机森林方法的高山冷凉蔬菜识别

该研究基于Sentinel-2A卫星的归一化差值植被指数(NDVI)时间序列数据,结合随机森林(RF)分类方法,对高山冷凉蔬菜种植区域进行精准识别与分类。以西吉县为研究区,利用2023年覆盖高山冷凉蔬菜全生育期的Sentinel-2A遥感数据,构建10 m高空间分辨率的NDVI时间序列数据,结合田间实测数据,使用RF分类方法对高山冷凉蔬菜进行识别分类。结果表明文章提出的方法在高山冷凉蔬菜种植区域识别中表现出了较高的精度和稳定性,总体精度达93.52%,Kappa系数为0.89。

Spatiotemporal Changes in NDVI and Its Driving Factors in the Kherlen River Basin

Vegetation is an important factor linking the atmosphere,water,soil,and biological functions,and it plays a specific role in the climate change response and sustainable development of regional economies.However,little information is available on vegetation vulnerability and its driving mechanism.Therefore,studying temporal and spatial change characteristics of vegetation and their corresponding mechanisms is important for assessing ecosystem stability and formulating ecological policies in the Kherlen River Basin.We used Moderate-resolution Imaging Spectroradiometer(MODIS)normalized difference vegetation index(NDVI)remote sensing images from 2000 to 2020 to analyse temporal changes in NDVI with the autoregressive moving average model(ARMA)and the breaks for additive season trend(BFAST)in the basin and to assess natural,anthropogenic and topographic factors with the Geodetector model.The results show that:1)the long NDVI time series remained stable in the Kherlen River Basin from 2000 to 2020,with a certain significant mutation period from 2013 to 2017;2)the coefficient of variation(CV)in the analysis of the spatial NDVI was generally constant,mainly at the level of 0.01–0.07,and the spatial NDVI change was minimally impacted by external interference;and 3)temperature and precipitation are the key factors affecting the NDVI in the basin,and changes in local hydrothermal conditions directly affect the local NDVI.The results of this study could provide a scientific basis for the effective protection of the ecological environment and will aid in understanding the influence of vegetation change mechanisms and the corresponding factors.

基于MODIS NDVI的科尔沁沙地荒漠化动态监测

以MOD IS植被指数产品为数据源,利用归一化植被指数(NDVI)与植被盖度的高相关性,以NDVI为荒漠化评价的定量依据进行荒漠化程度划分,得出科尔沁沙地2000年与2007年的NDVI分级分布图,并分别统计出相应的不同程度荒漠化土地面积所占比例;最后,利用不同等级荒漠化土地面积所占比例和NDVI分级分布图所提供的空间分配状况来评价研究区荒漠化程度及动态变化状况。研究结果表明,2000年至2007年科尔沁沙地荒漠化程度总体上呈减少趋势。

基于AVHRR和MODIS NDVI数据的黄土高原植被覆盖时空演变分析

黄土高原自退耕还林还草工程实施以来，区域植被覆盖发生了很大变化．为有效监测其变化程度，基于像元一元线性回归模型，利用该地区2001-2014年MODIS归一化植被指数fnormalized difference vegetation index，NDVI）数据对1982＋2006年GIMMSNDVI数据进行扩展．扩展数据通过了一致性检验，获得1982-2014年长时间序列植被NDVI数据集，分析该地区近33年植被NDVI的时空变化特征．研究结果显示：33年间黄土高原植被NDV1年际整体呈现显著的增加趋势，区域植被覆盖空间分布差异明显．其中南部和西部大部分地区植被覆盖轻微退化，中部地区植被覆盖基本不变，内蒙古边界、甘肃兰州以及陕西榆林等地区的植被覆盖均呈改善趋势．研究区各坡度等级植被覆盖良好，各坡度植被覆盖变化程度由强到弱依次为〉28°、20°-28°、14°-20°、9°-14°、4°-9°．其中黄土高原中部的坡地植被改善效果最为明显，甘肃与青海的交界处以及陕西南部、山西部分地区坡地植被覆盖呈轻微改善趋势．

基于MODIS NDVI的京津风沙源工程治理区荒漠化动态监测

以MODIS植被指数产品为数据源,利用归一化植被指数(NDVI)进行京津风沙源工程治理区荒漠化程度划分,得出2000年、2004年、2008年荒漠化等级分布图,在此基础上对研究区不同等级荒漠化进行对比分析。结果表明:京津风沙源工程治理区荒漠化程度总体上呈现减少趋势;荒漠化转移方向主要为严重荒漠化→重度荒漠化→中度荒漠化→轻度荒漠化→非荒漠化。

Attribution analysis and multi-scenario prediction of NDVI drivers in the Xilin Gol grassland,China

Grassland degradation is influenced by climate change and human activities,and has become a major obstacle for the development of arid and semi-arid areas,posing a series of environmental and socio-economic problems.An in-depth understanding of the inner relations among grassland vegetation dynamics,climate change,and human activities is therefore greatly significant for understanding the variation in regional environmental conditions and predicting future developmental trends.Based on MODIS(moderate resolution imaging spectroradiometer)NDVI(normalized difference vegetation index)data from 2000 to 2020,our objective is to investigate the spatiotemporal changes of NDVI in the Xilin Gol grassland,Inner Mongolia Autonomous Region,China.Combined with 12 natural factors and human activity factors in the same period,the dominant driving factors and their interactions were identified by using the geographic detector model,and multiple scenarios were also simulated to forecast the possible paths of future NDVI changes in this area.The results showed that:(1)in the past 21 a,vegetation cover in the Xilin Gol grassland exhibited an overall increasing trend,and the vegetation restoration(84.53%)area surpassed vegetation degradation area(7.43%);(2)precipitation,wind velocity,and livestock number were the dominant factors affecting NDVI(the explanatory power of these factors exceeded 0.4).The interaction between average annual wind velocity and average annual precipitation,and between average annual precipitation and livestock number greatly affected NDVI changes(the explanatory power of these factors exceeded 0.7).Moreover,the impact of climate change on NDVI was more significant than human activities;and(3)scenario analysis indicated that NDVI in the Xinlin Gol grassland increased under the scenarios of reduced wind velocity,increased precipitation,and ecological protection.In contrast,vegetation coverage restoration in this area was significantly reduced under the scenarios of unfavorable climate conditions and excessive human activities.This study provides a scientific basis for future vegetation restoration and management,ecological environmental construction,and sustainable natural resource utilization in this area.

基于GIMMS NDVI的青藏高原植被指数时空变化及其气温降水响应

青藏高原植被生态系统脆弱,是研究全球气候变化陆地植被生态系统响应的理想场所。以GIMMS NDVI、气温和降水及植被类型数据为基础,利用一元线性回归模型、相关系数、偏相关系数及t检验方法,分析了青藏高原1982-2015年NDVI时空变化及其气温降水响应特征,结果表明:1982-2015年青藏高原NDVI时间变化过程总体表现为不显著的增加过程,空间变化以显著增加为主,占总面积的63.26%,分布在高原北部、西部和南部;显著减少集中分布在高原中东部和东南部,仅占总面积的3.45%。青藏高原主要植被类型NDVI平均值表现为:阔叶林>针叶林>灌丛>草甸>高山植被>草原>荒漠,其中草原、高山植被和荒漠植被NDVI呈显著线性增加过程,灌丛、针叶林和阔叶林植被的NDVI呈不显著的减少过程。青藏高原NDVI与气温相关系数空间上呈南北向分布,具有纬度地带性特征,显著正相关分布在高原中北部,显著负相关分布在高原中南部;NDVI与降水的相关系数呈东西向分布,具有干湿度地带性特征,显著正相关分布在高原中部,显著负相关分布在高原东西两侧。研究认为1982-2015年青藏高原北部水热条件缺乏区域NDVI出现显著增加趋势,而高原东南部水热条件充足地区NDVI呈现出显著减少趋势。深入开展植被类型NDVI气候响应的差异性研究,有助于深入理解全球气候变化影响的区域差异及科学制定植被生态保护政策。

A Simple Method to Extract Tropical Monsoon Forests Using NDVI Based on MODIS Data:A Case Study in South Asia and Peninsula Southeast Asia

Distribution of monsoon forests is important for the research of carbon and water cycles in the tropical regions. In this paper, a simple approach is proposed to map monsoon forests using the Normalized Difference Vegetation lndex （NDVI） derived from the Moderate Resolution Imaging Spectroradiometer （MODIS） data. Owing to the high contrast of greenness between wet season and dry season, the monsoon forest can be easily discriminated from other forests by combining the maximum and minimum annual NDVI. The MODIS-based monsoon forest maps （MODMF） from 2000 to 2009 are derived and evaluated using the ground-truth dataset. The MODMF achieves an average producer accuracy of 80.0% and the Kappa statistic of 0.719. The variability of MODMF among different years is compared with that calculated from MODIS land cover products （MCD 12Q 1）. The results show that the coefficient of variation of total monsoon forest area in MODMF is 7.3%, which is far lower than that in MCD12Q1 with 24.3%. Moreover, the pixels in MODMv which can be identified for 7 to 9 times between 200l and 2009 account for 53.1%, while only 7.9% ofMCD12QI pixels have this frequency. Additionally, the monsoon forest areas estimated in MODMF, Global Land Cover 2000 （GLC2000）, MCDI2Q1 and University of Maryland （UMD） products are compared with the statistical dataset at national level, which reveals that MODMv has the highest R^2 of 0.95 and the lowest RMSE of 14 014 km^2. This algorithm is simple but reliable for mapping the monsoon forests without complex classification techniques.

The Application of Continuous Spatial Scaling Model of NDVI in Validation and Its Sensibility Analysis to Various Image Characteristics

Based on the fractal theory, this study establishes a Continuous Spatial Scaling Model （CSSM） of the Normalized Difference Vegetation Index （NDVI） to address issues arising with spatial up-scaling in quantitative remote sensing. This model is able to quantitatively describe transformation relationships of the NDVI on continuous scales. Then the following experiments are accomplished： （1） the validation of ETM＋ NDVI imagery is implemented based on the GEOEYE-1 image and its NDVI CSSM, and the following conclusion is obtained： because of bad stripes in the ETM＋ image and the limited effect of destriping, the ETM＋ NDVI image had a rather large error, and the error for the entire experimental imagery is about 25%, so the ETM＋ NDVI product is not suitable for direct practical application; （2） Shatian Byland （Beihai City, China） is taken as the experimental area, and four images （two ETM＋ images with wider and smaller coverage, respectively, a GEOEYE-1 image, and an HJ-1B CCD1 image） are studied. The most suitable scale levels are computed and compared for the four images, and a better understanding is obtained of the impact of various image characteristics （area of coverage, spatial resolution, and imaging quality） on determining the scale level for the NDVI CSSM.

基于MODIS NDVI的辽河保护区成立前后植被覆盖时空动态研究

以2010年成立以自然生态恢复为主的辽河保护区为研究对象,基于中分辨率成像光谱仪(MODIS)获取的500米分辨率的归一化植被指数(NDVI)数据,研究了辽河保护区成立前(2000—2009年)和成立后(2010—2015年)植被覆盖时空动态。结果表明:(1)2000—2015年NDVI呈现持续增加趋势;2000—2009年NDVI的年际增加主要发生在夏季,2010—2015年NDVI的年际增加主要发生在春季和冬季。辽河保护区成立后春季NDVI的逐年增加有利于该区域防风固沙功能的提升。(2)季节尺度上,2000—2009年春季降水量与春季和夏季NDVI显著正相关,夏季气温与夏季NDVI显著负相关;2010—2015年仅夏季NDVI动态受春季气温和夏季日照时数变化的影响。(3)月尺度上,气温是影响辽河保护区NDVI变化的主要气候因素,2000—2015年NDVI动态对气温变化的响应存在1个月的滞后期;2000—2009年NDVI动态对降水变化的响应存在1个月的滞后期,2010—2015年则无滞后效应。(4)2000—2009年影响NDVI动态的人类活动主要为农田耕作;辽河保护区成立后,河岸带封育区内的自然恢复和小型人工湿地建设促进了NDVI增加,大型人工湿地建设和人工经营牧草地对NDVI动态无显著影响。

基于ESTARFM NDVI的察汗淖尔流域灌溉耕地提取方法研究

运用遥感精准识别技术提取灌溉耕地可以为区域内农业耗水管理提供关键数据支持,但受限于遥感数据的时空分辨率,对于光谱特性相似容易混淆的灌溉耕地作物识别有一定难度。为此,本研究通过增强型自适应反射率时空融合模型(Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model,ESTARFM)对MODIS和Landsat数据进行融合,得到察汗淖尔流域时间分辨率为8 d、空间分辨率为30 m的NDVI数据,并与同期真实Landsat NDVI进行对比验证,相关系数为0.94。利用HANTS滤波建立ESTARFN NDVI时间序列数据,选取灌溉耕地样本通过支持向量机进行灌溉耕地空间分布的提取,以弥补数据源、特征提取等限制因素对复杂灌溉耕地提取的空缺。结果表明:流域内灌溉耕地总面积为1958.24 km^(2),商都、兴和、尚义、康保和化德5县耕地总面积占流域耕地总面积的94%,灌溉耕地分别为616.67 km^(2)、337.36 km^(2)、409.85 km^(2)、290.93 km^(2)和239.38 km^(2),主要种植葵花、甜菜、马铃薯等生长季从4月初到9月底的长生育期作物和生长季从5月初到8月初的蔬菜;张北、察哈尔右翼前旗、后旗和镶黄旗耕地占流域耕地总面积为6%,4县灌溉耕地面积共64.05 km^(2)。最后,通过真实样本进行验证,总分类精度为93.18%,Kappa系数为0.91。结果表明,用该数据融合模型获得的NDVI时间序列能反映作物真实变化情况,并且使用支持向量机提取察汗淖尔流域灌溉耕地效果较好。

FY-3C VIRR和Terra MODIS NDVI产品在湘赣地区的一致性

卫星遥感是监测大范围植被动态变化最有效的手段。随着中国遥感技术的发展,国产风云卫星也逐渐应用于植被变化研究,但有关国产风云卫星刻画植被动态变化表现方面仍不明晰。比较了国产风云卫星(FY-3C VIRR)和美国Terra卫星(MODIS)的归一化植被指数(normalized difference vegetation index,NDVI)产品在湖南省和江西省的时空一致性。结果表明:①两种卫星NDVI产品的空间分布与年、季、月的变化特征在湘赣地区有较好的一致性,江西省NDVI整体高于湖南省;②FY-3C和MODIS年均NDVI都呈现出2018年高于2017年和2019年的情况,基于MODIS的湘赣地区三年的年均NDVI(0.58)高出FY-3C(0.36)约60%;③FY-3C NDVI在各季节都整体低于MODIS NDVI,其中冬季差异最大,基于MODIS NDVI均值(0.42)约是FY-3C(0.21)的2倍,其余季节MODIS高出FY-3C约50%;④FY-3C NDVI与MODIS NDVI月变化趋势基本一致,二者年最大NDVI差异变化不大且较为稳定,年最小NDVI差异方面更明显且差异较大(MODIS年最小NDVI高出FY-3C约100%)。研究结果可为国产风云卫星检测典型地区植被动态变化特征的能力提供科学参考。

Quantification of driving factors on NDVI in oasis-desert ecotone using geographical detector method

Within oasis-desert ecotone regions,the normalized difference vegetation index(NDVI)is an important parameter for evaluating the growth of vegetation.An accurate quantitative study between NDVI and environmental and anthropogenic factors is critical for understand the driving factors of vegetation growth in oasis-desert ecotone.In 2016,four periods Landsat 8 OLI_TIRS images,relevant climatological parameters data(air temperature,air relative humidity,wind velocity and accumulated temperature),land cover type data and soil data were selected as proxies.In order to quantify the explanatory power for NDVI spatial and temporal distribution in the southern edge of Dunhuang City and northern side of the Mingsha Mountain,the geographical detector model was used to explain the potential influences of factors versus the spatial distribution of NDVI,and each explanatory variable's relative importance can be calculated.The factor detector results disclose that the spatial distribution of NDVI is primarily dominated by land cover type.The risk detector results show that,high NDVI region is located within woodland.The mean value of NDVI displays an increase and then decrease trend with air temperature increase.With the increase of wind velocity and decrease of air relative humidity,the NDVI value shows a decrease trend.The interactive q values between the two factors are higher than any q value of separated factors.Results also indicate that the strongest interactive effects of NDVI are different in distinct seasons.Consequently,anthropogenic activity is more important than environmental factors on NDVI in oasis-desert ecotone.We also demonstrate that air relative humidity rather than air temperature have played a greater role in NDVI spatial distribution.

基于MODIS NDVI数据的广西植被覆盖时空变化遥感诊断

【目的】对广西2006—2016年植被覆盖变化特征及其变化关键因素进行遥感诊断,为掌握广西地区植被覆盖的时空变化提供科学监测结果和诊断依据。【方法】基于250 m分辨率16天合成的MOD13Q1产品,利用趋势分析法获得11年间广西植被覆盖整体变化情况;结合气象数据,运用回归因子分析法得到植被覆盖变化与温度和降水之间的关系;采用遥感影像差异法对不同时期MODIS土地覆盖类型数据进行分析,探讨人类活动对植被覆盖变化的影响。【结果】2006—2016年11年间广西植被覆盖在波动中呈上升趋势;归一化差值植被指数(NDVI)2—3月呈最低状态,9月最高。全区植被增加面积大于退化面积,其中面积增加最大的区域包括河池、百色、南宁东南部和桂林东部,退化面积最大的区域包括崇左、百色中部、南宁西部和桂林中部,退化程度最高的北海区域退化面积占全区面积的28.9%。11年间,广西植被覆盖类型变化巨大,林地面积显著上升,农用地面积下降明显。【结论】温度和降水与植被覆盖呈正相关关系,二者与植被覆盖在月尺度上的正相关性较年尺度更为显著,且降水对植被的影响高于温度对植被的影响;MODIS土地覆盖类型数据反映出的人类活动表明,林地面积显著增加是广西NDVI上升的主要原因。