广东省NDVI时空变化特征及其对气候因子的响应

广东省植被类型丰富、气候条件复杂,开展气候因子对植被的影响研究,对于全省保护生态环境、应对气候变化具有重要意义。利用MODIS NDVI数据和地面气象观测数据,基于变化趋势分析、空间自相关分析、相关性分析等方法,研究广东省NDVI时空分布特征及其对气温、降水、日照时数等气候因子的响应。结果表明,2000—2018年广东省NDVI平均值为0.62,总体呈上升趋势,平均年增长值为0.005 3,正增长区面积占比达94.50%。全省73.72%的区域植被呈现显著空间集聚性,其中高值集聚区面积占比48.19%,低值集聚区面积占比25.53%。不同类型植被的NDVI均呈增加趋势,其中常绿阔叶林、常绿针叶林、混交林的NDVI平均值最大,而农田、矮树灌木、混交林平均年增长值最大。NDVI具有明显的季节变化规律,夏季NDVI值最大、年增长值最小,冬季NDVI值最小、年增长值最大。年内NDVI最低值出现在2月,最高值出现在9月。月平均NDVI与气温、降水、日照时数相关性显著,其最大相关系数分别为0.863 7、0.639 4、0.605 7。NDVI对日照时数的响应不存在滞后,对气温存在1个月的滞后,对降水存在1—2个月的滞后。日照时数对NDVI的影响仅持续1个月左右,温度、降水对NDVI的影响可持续4—5个月。     

黄河源区植被生长季NDVI时空特征及其对气候变化的响应

利用黄河源区MODIS/NDVI数据、1∶100万植被类型图和气象资料,分析了该区不同植被类型生长季NDVI时空特征以及与气候因子的关系。结果表明,1）2000—2011年,黄河源区植被生长呈改善趋势,生长季NDVI年际变化率每10 a为＋2.75%,高寒草原、高寒草甸、高寒灌丛生长季NDVI年际变化率分别为每10 a＋2.84%、＋2.65%、＋2.77%。2）黄河源区植被改善面积占全区总面积的29.39%,主要分布在卡日曲和玛曲上游、扎曲流域、布青山南麓、扎陵湖北部和鄂陵湖周边地区。植被退化面积仅占全区总面积的0.98%,主要分布在约古宗列曲东南部山地和卡日曲北部山地。受水热条件控制,植被改善表现为：①植被改善面积南坡大于北坡;②植被改善面积随海拔升高先增加后减小;③植被改善面积随坡度增加迅速减小。3）黄河源区植被生长季NDVI与同期气温和降水分别存在显著正相关性,其中高寒草原和高寒草甸生长受降水影响更为明显,而高寒灌丛生长受气温影响更为明显。气候的暖湿化趋势可能是促使黄河源区植被生长改善的主要原因。     

基于SPOT—VGT的黄河流域植被覆盖时空演变

植被是土地覆盖中的最主要部分,是连接土壤、大气和生物等要素的自然“纽带”。植被覆盖动态变化对全球能量循环和物质循环具有重要影响,是全球变化研究的重要内容之一。黄河流域作为我国重要的粮食生产基地,其环境变化直接影响到流域经济的可持续发展。为了快速准确地提取地表植被状况,了解黄河流域生态环境,利用1998—2011年的SPOT-VGT遥感数据,结合地理信息技术,采用均值法和趋势分析法对黄河流域植被NDVI时空分布特征和变化趋势进行了动态监测。结果表明,（1）黄河流域14年NDVI均值的空间分布整体特征是东南部平原、盆地和西部山地植被状况要好于北部地区。其次,黄河流域属于干旱半干旱地区,植被发育主要依赖于水文条件,所以沿黄河干流和支流区域也具有较高的植被NDVI值。（2）黄河流域植被NDVl年均值近14年间整体呈缓慢增长趋势,1998--2000年呈现急剧减少态势,2001--2003年出现了较为快速的增长,2004--2011年又出现了较长时间的连续增长过程。（3）黄河流域植被NDVI基本不变的区域约占研究区总面积的71．13％;植被NDVI轻微改善的区域约占流域总面积的27．30％,且主要分布于流域东南部的盆地、平原和西部的山地、丘陵地区,植被NDVI退化的区域面积约占流域总面积的0．98％。黄河流域自1998年以来,植被NDVI整体在不断提高,生态环境在不断改善。     

基于MODIS数据的珠三角地区NDVI时空变化特征及对气象因素的响应

珠江三角洲是广东省经济密度最大、人为活动最强烈的区域,随着工业化和城市化的迅速发展,该区域出现了各种生态环境问题。通过对2001-2017年覆盖珠三角地区的MODIS/NDVI数据进行月时间序列重构和年时间序列合成,利用趋势分析方法和空间自相关分析方法对珠三角地区NDVI的时间变化趋势和空间格局特征进行研究,同时结合气象站点观测资料,基于相关系数方法分析NDVI对气象因素的响应。结果表明,(1)在过去的17年中,珠三角地区NDVI在年际变化上呈现波动增长趋势,总体年平均增长速率为0.005 1。(2)在空间分布上,珠三角范围内有90.84%区域的植被呈增长趋势,而在珠三角核心地带的城市群集区域存在植被退化现象,占全区面积的9.16%。(3)珠三角地区NDVI具有高空间集聚特性,受地形和城区分布影响,低植被覆盖集聚区和高植被覆盖集聚区分布格局显著且变化稳定,在多年平均NDVI的局部空间自相关分析中分别占全区面积的28.77%和33.69%。(4)珠三角地区NDVI和气温、降水及日照时数在月变化上显著相关,NDVI对气温和降水的响应分别存在1个月和1-2个月的滞后效应,并且这种滞后效应在空间分布上也体现出"西南-东北"方向的区域差异,而NDVI对日照时数的响应不存在滞后。(5)在年尺度上,珠三角地区NDVI与气象因素之间的相关性不显著。研究结果对珠三角地区恢复植被和修复生态具有重要的参考价值和现实意义     

内蒙古地区近25年植被对气温和降水变化的影响

利用1982—2006年内蒙古地区GIMMS-NDVI和降水量、气温数据,分析了不同植被类型对气温和降水变化趋势的影响。结果表明：近25年来内蒙古地区气温整体上呈上升趋势,降水量呈微弱降低趋势,西部荒漠区呈暖湿化趋势,中东部草原、森林等植被类型区呈暖干化趋势;从不同植被类型NDVI与平均气温和降水量的变化趋势率相关分析表明,NDVI值越低,升温趋势越明显,其中春季和秋季各植被类型间NDVI与季均气温升高趋势率呈显著和较显著的相关,夏、冬季关系不明显;植被NDVI越高,降水量减少趋势越明显。基于栅格的NDVI与气温升高幅度、降水变化趋势相关分析表明,年均气温升高幅度基本随NDVI的增加而降低,其中春、夏和秋季的季均气温升高幅度均随NDVI的增加而显著降低,冬季趋势不明显;而年降水量减小趋势率随植被NDVI的增加而显著增加,其中春季和冬季NDVI变化对降水的变化几乎没有影响;夏季和秋季均表现为随NDVI的增加,降水减小趋势率呈增加趋势。     

气候因子与植被的时滞相关分析——以广西为例

广西地区地下河发育,地表水缺乏,生态系统脆弱、抗干扰能力低,灾害频繁,森林生态系统严重退化,石漠化程度加剧,属于生态脆弱区域,而植被变化是生态系统对气候变化响应的指示器,其变化研究对该地区生态环境建设具有重要意义。文章基于1999--2010年气温与降水数据和GIMMS．NDVI（GlaobalInventoryModellingandMappingMtudies-NormalDifferenceVegetionIndex）数据集,研究近12年来广西地区植被覆盖时空特征。通过时滞相关分析法,分析研究区不同植被类型受气温和降水的影响,即植被NDVI对气温和降水的响应程度。结果表明,（1）植被NDVI与温度的时滞相关程度强于降水,而响应时间刚好相反,植被NDVI对降水的响应比对温度的响应程度要快。（2）植被NDvI与降水的时滞相关规律呈桂南较弱—桂中较强—桂北较弱,但响应时间刚好相反,即桂南较快一桂中较慢—桂北较快。（3）植被NDvI与温度的时滞相关性变化规律呈由南向北递减,响应时间由南向北变快。（4）植被NDVI与气候因子时滞相关越强,响应的时间就越迟缓,反之越快。（5）不同的植被类型对水热条件响应程度不同,与水热条件时滞相关越强的植被则滞后时间相对越久。     

灾害胁迫下建平县沙棘人工林的时空特性

辽宁省建平县沙棘衰退主要是干旱胁迫和沙棘术蠹蛾蛀食危害复合作用的结果,本文中统称沙棘灾害.选择建平县东北部作为实验区,利用5期TM遥感图像研究沙棘林的光谱反射特征,并计算样地的归一化植被指数(NDVI),得到了沙棘植被多年变化特征.结果表明,NDVI增加表明沙棘林生长状况良好,而下降则表明在灾害胁迫下沙棘人工林出现衰退.结合地而数据,初步明确了沙棘灾害程度的NDvI临界值,以NDVI下降幅度至≤0.1为轻度受灾区,NDVI下降幅度在<0.1≤0.25为中等受灾Ⅸ,NDVI下降幅度>0.25为严重受灾区.应用RS与GIS相结合方法,对研究区的遥感影像进行人机交瓦解译,得到5期土地利用类型分布以及面积统计.结果表明,1991～2004年间沙棘面积显著减少,主要向耕地、荒地与裸地转化.本研究结果为实时动态、大面积监测沙棘人工林灾害奠定了基础.图5表2参21     

雅砻江流域生长季植被时空变化特征及对气象因子的响应分析

在全球气候变化背景下,开展植被变化对气象因子的响应研究对流域生态环境保护和水土资源合理利用具有重要的现实意义。以雅砻江流域为研究区,基于1982—2015年GIMMS NDVI数据,首先采用多种数理统计方法揭示生长季NDVI的时空变化特征,基于滞后相关系数法分析NDVI对气象因子的时滞效应,在此基础上建立各像元NDVI与气象因子的主成分回归方程,分析影响NDVI变化的主要气象因子及其贡献率,进而揭示NDVI对各气象因子的响应变化特征。结果表明:雅砻江流域NDVI在年内呈单峰型变化,峰值出现在8月,生长季NDVI年际变化呈不显著下降趋势。流域NDVI自下游向上游逐渐减小,植被退化面积占30%,改善面积占24.28%,中游植被改善和退化面积占比最大,就各植被类型变化而言,针叶林改善比重相对较大,灌丛和草甸退化较为严重。导致流域植被变化的主控气象因子为降水和气温,其对植被变化的贡献率分别为27.68%和26.31%,其中,流域上游及中游北部地区植被变化主要受气象因素影响,中游南部及下游地区植被受气象因子与其他因子(如人类活动)的共同影响。各像元NDVI变化的主控气象因子存在显著差异,降水、平均气温和相对湿度是中上游植被变化的主控气象因子,而降水和日照时数是下游植被变化的主控气象因子。流域植被对各气象因子的响应存在一定的时滞效应,植被对各气象因子滞后响应面积大小顺序为:平均风速>降水>日照时数>平均气温>相对湿度。中上游植被对主控气象因子降水、平均气温和相对湿度的响应主要为当月及滞后1个月;下游植被对主控气象因子降水的响应主要为滞后1个月和滞后3个月,而对主控气象因子日照时数的响应主要为当月。     

西南喀斯特地区植被变化及其与气候因子关系研究

受气候变化和退耕还林还草工程实施的影响,植被分布产生一定的变化,厘清气候因子与植被生长的关系,可以为生态维护与治理提供参考依据,为生态保护成效评估提供科学基础。选择环江喀斯特区,以中分辨率卫星成像光谱仪(MODIS)卫星遥感250m空间分辨率植被指数NDVI,分析2000-2017年该地区植被变化趋势,利用多元线性回归分析累积降水、温度、辐射等气候因子的影响范围和程度,以残差趋势法厘定植被变化中的人为贡献。结果表明,(1)2000-2017年,环江地区87%的地区植被年均NDVI呈现不同程度的增加趋势,增长率为0.4%a~(-1);主要植被类型农田、森林、草地年均NDVI持续改善,其中森林的改善状况最好。(2)环江地区气候变化整体呈冷湿化。温度、累积降水、辐射对植被年均NDVI的影响情况不同,就环江地区而言,温度、辐射对年均NDVI表现出正影响,且温度影响最大;累积降水与年均NDVI呈负相关。(3)不同植被类型受气候因素的影响不同,在气候因素对植被年均NDVI的解释度较高的地区,农田主要受温度影响,森林和草地主要受辐射和温度的共同影响。(4)环江地区气候因素可以解释8.5%的年均NDVI的变化情况。(5)环江地区除气候因素以外的其他因素对NDVI影响更大。     

基于SPOT-VGT的黄河流域植被覆盖时空演变

植被是土地覆盖中的最主要部分,是连接土壤、大气和生物等要素的自然"纽带"。植被覆盖动态变化对全球能量循环和物质循环具有重要影响,是全球变化研究的重要内容之一。黄河流域作为我国重要的粮食生产基地,其环境变化直接影响到流域经济的可持续发展。为了快速准确地提取地表植被状况,了解黄河流域生态环境,利用1998—2011年的SPOT-VGT遥感数据,结合地理信息技术,采用均值法和趋势分析法对黄河流域植被NDVI时空分布特征和变化趋势进行了动态监测。结果表明,(1)黄河流域14年NDVI均值的空间分布整体特征是东南部平原、盆地和西部山地植被状况要好于北部地区。其次,黄河流域属于干旱半干旱地区,植被发育主要依赖于水文条件,所以沿黄河干流和支流区域也具有较高的植被NDVI值。(2)黄河流域植被NDVI年均值近14年间整体呈缓慢增长趋势,1998—2000年呈现急剧减少态势,2001—2003年出现了较为快速的增长,2004—2011年又出现了较长时间的连续增长过程。(3)黄河流域植被NDVI基本不变的区域约占研究区总面积的71.13%;植被NDVI轻微改善的区域约占流域总面积的27.30%,且主要分布于流域东南部的盆地、平原和西部的山地、丘陵地区,植被NDVI退化的区域面积约占流域总面积的0.98%。黄河流域自1998年以来,植被NDVI整体在不断提高,生态环境在不断改善。     

基于LandsatTM影像的武汉市热岛效应研究

采用定量遥感与GIS相结合的方法,利用武汉市2006年TM遥感影像,定量分析武汉市植被指数和热岛效应的关系和空间分布。在空间剖面上,研究了植被指数（NDVI）与地表辐射温度的关系并对植被指数（NDVI）与地表辐射温度进行了回归拟合。在此基础上,研究了武汉市热岛空间分布,解释了武汉市热岛等级空间分布的特点。研究结果表明：植被指数（NDVll与地表辐射温度存在着明显的负相关性;随着植被覆盖的变化,城市建设用地的地表辐射温度明显比其他土地类型敏感;城市中工业区和人口活动密集的商业区热岛强度高;水体和绿地对于分割城市热岛和缓解热岛效应有显著作用。该研究可为城市生态规划、用地合理布局等提供参考。     

Temporal-spatial dynamics of vegetation variation on non-point source nutrient pollution

The temporal-spatial interaction of land cover and non-point source (NPS) nutrient pollution were analyzed with the Soil and Water Assessment Tool (SWAT) to simulate the temporal-spatial features of NPS nutrient loading in the upper stream of the Yellow River catchment. The corresponding land cover data variance was expressed by the normalized difference vegetation index (NDVI) that was calculated from MODIS images. It was noted that the temporal variation of land cover NDVI was significantly correlated with NPS nutrient loading. The regression analysis indicated that vegetation not only detained NPS nutrient pollution transportation, but also contributed to sustainable loading. The temporal analysis also confirmed that regional NDVI was an effective index for monthly assessment of NPS nitrogen and phosphorus loading. The spatial variations of NPS nutrient loading can be classified with land cover status. The high loadings of NPS nitrogen in high NDVI subbasins indicated that forestry and farmland are the main critical loss areas. Farmland contributed sustainable soluble N, but the loading of soluble and organic N from grassland subbasins was much lower. Most P loading came from the areas covered with dense grassland and forestry, which cannot directly discharge to local water bodies. However, some NPS phosphorus from suburban farmland can directly discharge into adjacent water bodies. The interactions among nutrient loading, NDVI, and slope were also analyzed. This study confirmed that the integration of NPS modeling, geographic information systems, and remote sensing is needed to understand the interactive dynamics of NPS nutrient loading. Understanding the temporal-spatial variation of NPS nutrients and their correlations with land cover will help NPS pollution prevention and water quality management efforts. Therefore, the proposed method for evaluating NPS nutrient loading by land cover NDVI can be an effective tool for pollution evaluation and watersheds planning.     

三江源地区基于植被生长季的NDVI对气候因子响应的差异性研究

采用1999—2008年NDVI和三江源地区及周边31个气象站点的温度和降水旬数据,在确定每年5月中旬至9月底作为三江源地区植被生长季（14旬）的基础上,分析NDVI对气候因子变化响应的区域差异。结果显示：以巴颜喀拉山为界,三江源西部生长季内NDVI指数对温度、降水的线性相关性明显比中东部普遍,同时,不同海拔地段响应程度存在着明显的差异,且海拔5300m左右为线性响应的最高限,NDVI对气候因子的线性响应主要表现为对温度正相关和降水负相关。因此,对三江源生长季内植被生长而言,水条件明显好于温度条件,并且温度对植被覆盖的影响通过直接正相关和降水负相关表现出来,温度是三江源地区植被生长的主导因子。     

植被覆盖度与沙尘暴形成条件分析

以归一化差值植被指数（Normalized Difference Vegetation Index,NDVI）为指标分析了我国1981年到1998年期间植被覆盖变化情况,给出了植被急剧减少产生新沙源的实例。通过对1998年4月强沙尘暴的分析,指出影响沙尘暴产生和运移的因素除了地形、风速、风向、大气稳定度外,当地植被覆盖和土壤因素也是关键因素之一。并通过对植被覆盖度（NDVI）与浮尘指数（Aerosol Index）进行定量分析,发现二者之间存在明显的负相关关系,表明植被的存在可以从一定程度上抑制浮尘现象的产生。因此,在沙尘运移路径上,采取封山封荒,植树种草,增加植被覆盖度以固结当地土壤和泥沙的措施,可以在一定程度上抑制沙尘暴灾害的发生。     

中国东部南北样带中南段典型植被类型NDVI变化分析

以IGBP第15条国际标准样带——中国东部南北样带中南段的植被为主要研究对象，对该区域应用NDVI(normalized difference vegetation index)数据进行植被类型划分，共划分为三大类35小类．在此基础上，选择6种不同气候区域典型的森林植被类型，对其NDVI变化进行分析，从而得出：NDVI随着纬度的降低变化逐渐减小；通过研究经向年内：NDVI变化，发现4月份研究区域南北：NDVI指数变化最明显；分析NDVI均值变化可知，从暖温带到北亚热带植被指数NDVI形成明显的阶跃，从而判定植被指数NDVI对短期气候变化具有明显的指示性，并发现通过植被指数NDVI的季节变化曲线，可以较为准确地判定森林、草原、农作物等大类型，图4表1参15。     

Scale-dependent relations in land cover biophysical dynamics

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations. In particular, the analysis is focused on the spatial organization of some phenological parameters including deterministic variations (seasonal range, interannual variability, jump discontinuities) and stochastic components (plant memory, spatial correlations). The analysis is performed using MODIS-based Normalized Difference Vegetation Index (NDVI) 16-day composites for the period from March 2000 to December 2006 over Italy at different levels of spatial aggregation (1-8 km). Scale-dependences of the statistical moments of the phenological parameters are quantified through simple power laws for five distinct vegetated land covers. Results suggest that some biophysical characteristics, especially deterministic components, show no preferential spatial scale for important coverage. In particular, broad-leaved forests and natural grasslands are characterized by deterministic and low-distance spatial components well explained by scale relationships, which are modulated by possible spatiotemporal dynamics of climatic drivers. Agricultural lands show high scale-dependent relations on short-term biophysical memory sources and low-distance spatial components of phenology likely related to hierarchical interactions of anthropogenic and ecological processes; whereas mixed patterns of croplands and natural areas generally present no consistent scaling relations.     

Thirty years of vegetation change in the coastal Santa Cruz Mountains of Northern California detected using landsat satellite image analysis

The Santa Cruz Mountains is a coastal landscape with a history of extensive forest logging, and a future with projected climate warming that may alter vegetation cover and surface water runoff in new ways. Results from Landsat satellite image time-series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90 % of the (predominantly second-growth) evergreen forest locations sampled. The cumulative distribution of NDVI values in 2013 was significantly different and higher overall from the cumulative distribution of NDVI values in 1983. The extreme drought year of 2013 (and other previous years of low precipitation) did not affect average NDVI growth rates in most drainage basins of the study area, with the exception of four relatively small basins that had less than 30 % forested land cover. Notably different patterns of NDVI change were detected in areas burned by wildfires in recent years. Within the perimeters of the 2008 Summit Fire and the 2009 Lockheed Fire, NDVI showed notable declines from pre-fire levels to those calculated in 2013 Landsat imagery. In contrast to these recent fires, the burned area from the 1985 Lexington Fire showed the highest rate of NDVI increase (over 27 years of regrowth) of any relatively large contiguous area within the Santa Cruz Mountains.     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.     

Recovery of forest structure and spectral properties after selective logging in lowland Bolivia.

Effective monitoring of selective logging from remotely sensed data requires an understanding of the spatial and temporal thresholds that constrain the utility of those data, as well as the structural and ecological characteristics of forest disturbances that are responsible for those constraints. Here we assess those thresholds and characteristics within the context of selective logging in the Bolivian Amazon. Our study combined field measurements of the spatial and temporal dynamics of felling gaps and skid trails ranging from <1 to 19 months following reduced-impact logging in a forest in lowland Bolivia with remote-sensing measurements from simultaneous monthly ASTER satellite overpasses. A probabilistic spectral mixture model (AutoMCU) was used to derive per-pixel fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil. Results were compared with the normalized difference in vegetation index (NDVI). The forest studied had considerably lower basal area and harvest volumes than logged sites in the Brazilian Amazon where similar remote-sensing analyses have been performed. Nonetheless, individual felling-gap area was positively correlated with canopy openness, percentage liana coverage, rates of vegetation regrowth, and height of remnant NPV. Both liana growth and NPV occurred primarily in the crown zone of the felling gap, whereas exposed soil was limited to the trunk zone of the gap. In felling gaps >400 m2, NDVI, and the PV and NPV fractions, were distinguishable from unlogged forest values for up to six months after logging; felling gaps <400 m2 were distinguishable for up to three months after harvest, but we were entirely unable to distinguish skid trails from our analysis of the spectral data.     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用.以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特...