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征。结果表明,（1）研究区2000—2018年植被覆盖趋向改善,NDVI呈现增加趋势,增速为0.11/10a,2008年以后植被增长较为明显;NDVI在2018年中高等级（0.6—0.8）面积比2000年中高等级面积明显增加;中高等级集中于榆林市东部黄土丘陵区,中低等级（0.2—0.4）集中于榆林市西北部的风沙区,植被覆盖呈现东部高西北低的空间分布特征。（2）人口密度和气温因子较好地解释植被NDVI空间分异性,是影响NDVI空间分异性的主要因子,GDP、土地利用类型和坡度是次级影响因子,其他因子对NDVI空间分异存在间接影响;坡向、降水和土壤类型因子与其他自然、人文因素对植被空间分布影响存在显著性差异。（3）自然、人文因子对榆林市NDVI的影响存在交互作用,因子之间的交互...     

2001～2007年天山南坡中段不同植被类型NDVI变化分析——以新疆和静县为例

利用MODIS数据建立近7年和静县NDVI时间序列,通过采用均值法、最大合成法和一元线性回归法,分析了该区不同植被类型年内变化、年际变化趋势.结果表明,和静县植被季相变化明显,不同植被类型变化幅度差异显著;近7年大部分地区植被存在退化趋势,局部区域植被有所改善;不同植被类型退化程度从大到小为荒漠草原＞荒漠植被＞草原＞高山垫状植被＞高寒草原＞草甸 沼泽＞落叶阔叶林＞耕地;平原区植被NDVI的变化主要受人为活动的影响.山区植被NDVI除受季节性放牧影响外,更多的受气候变化的影响.     

青藏高原东北部气候变化的异质性及其成因

利用1961-2016年西宁等青藏高原东北部13个气象台站气温、降水等气象资料以及国家气候中心发布的南海季风指数、西伯利亚高压指数等大气环流特征量数据,分析近56年来气候变化与高原主体的差异性及其可能的气候成因。研究表明：近56年来青藏高原东北部气候变暖趋势十分显著,年平均气温气候倾向率高达0.39 ℃/10 a,呈现出三次明显的阶梯性增高态势,并于1994年前后发生了由冷到暖的突变,同时具有明显的空间差异性;年降水量及四季降水量均没有明显变化趋势,虽然经历了2002年左右由少到多的变化,但并未出现明显突变,年降水量具有3年、5年的准周期,而年降水日数微弱减少,降水强度呈增加趋势;该区域气候变化的年际波动主要受到东亚季风、高原季风和南海季风的年际振荡及其相互作用的影响,而西风环流的作用并不明显,植被覆盖的恢复既是对2002年以来降水量增加的具体反应,同时也对于气候变暖趋势起到了一定的缓和作用。     

归一化差值植被指数在土地覆盖遥感动态调查中的应用

以金沙江流域西南区为研究区，通过两个时相NDVI的比较判断地表植被的变化情况，生成差值图像，提取变化区域，处理判读结果。     

Measuring Protected‐Area Isolation and Correlations of Isolation with Land‐Use Intensity and Protection Status

Abstract: Protected areas cover over 12% of the terrestrial surface of Earth, and yet many fail to protect species and ecological processes as originally envisioned. Results of recent studies suggest that a critical reason for this failure is an increasing contrast between the protected lands and the surrounding matrix of often highly altered land cover. We measured the isolation of 114 protected areas distributed worldwide by comparing vegetation‐cover heterogeneity inside protected areas with heterogeneity outside the protected areas. We quantified heterogeneity as the contagion of greenness on the basis of NDVI (normalized difference vegetation index) values, for which a higher value of contagion indicates less heterogeneous land cover. We then measured isolation as the difference between mean contagion inside the protected area and mean contagion in 3 buffer areas of increasing distance from the protected‐area border. The isolation of protected areas was significantly positive in 110 of the 114 areas, indicating that vegetation cover was consistently more heterogeneous 10–20 km outside protected areas than inside their borders. Unlike previous researchers, we found that protected areas in which low levels of human activity are allowed were more isolated than areas in which high levels are allowed. Our method is a novel way to assess the isolation of protected areas in different environmental contexts and regions.     

Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data

Global warming and climate change have been identified as the most important challenges of the 21st century. Greenhouse Gases Observation Satellite (GOSAT) measures the concentrations of carbon dioxide (CO ₂) and methane (CH ₄) in the atmosphere column from the earth's surface to the upper atmosphere. In this research, GOSAT Thermal And Near Infrared Sensor for Carbon Observation – Fourier Transform Spectrometer (TANSO‐FTS) level 2 data and meteorological parameters were used in the assessment of changes in CO ₂ concentration (XCO ₂) from 2009 to 2015. We investigated the relationship between XCO ₂ and meteorological parameters (temperature and precipitation) obtained from weather stations and the Normalized Difference Vegetation Index (NDVI) in the year 2013 in Iran. The results reveal a steady increase in the mean atmospheric CO ₂ concentration, from 384.89 to 400.39 ppm. It was observed that the XCO ₂ varied significantly depending on the month, with the highest concentration of CO ₂ in April/May and the lowest concentration in August/September. The correlation between XCO ₂ and average monthly air temperature is negative, which means that a reduction in XCO ₂ with an increase in temperature is dependent on photosynthetic activities in the growing seasons. The highest and lowest correlation coefficient between the NDVI and XCO ₂ was obtained in the spring and in the fall, respectively. These findings are useful for recognizing factors that affect CO ₂ concentration in different seasons in arid and semi‐arid regions, and as an initial step toward sustainable management.     

近25年山西植被指数时空变化特征分析

在遥感及地理信息系统技术支持下,利用1982-2006年8 km×8 km的NASA/GIMMs植被指数(NDVI)数据,采用多种方法分析了山西高原近25 a来植被指数的时空动态变化规律.结果表明:①25 a来,山西省年均NDVI基本在0.33上下呈波动中上升趋势,表明山西高原植被活动在增强;②从季节变化来看,山西省春季和秋季的植被都在增加,冬季上升趋势较弱,夏季变化很小,呈现极弱的递减趋势;③空间上,植被指数南部好于北部,山区好于平原;④从植被变化趋势图中也可以看出植被呈现总体变好趋势,其中北部变好趋势明显,其次是南部;⑤植被年际变化表现出较为一致的变化趋势以及较为明显中部和南北反相的局地变化特征.     

基于时间序列MODIS数据的贵州省森林物候地域分异

森林物候是气候与环境变化的重要指示器,对于陆地植被生态环境监测具有重要的意义。以2011～2013年的MODIS NDVI(归一化植被指数)为时间序列数据,采用Savizky-Golay(S-G)滤波平滑和动态阀值法,提取出贵州省2012年森林物候的生长起始日期(SOS)、生长结束日期(EOS)、生长季长度(LOS)和生长季振幅(AOS)4个参数,分别将提取的森林物候参数与经度、纬度和海拔做相关性分析。研究结果显示:(1)贵州省森林物候参数与纬度相关性整体较弱,因此贵州省森林物候纬度地带性地域分异的不显著;(2)贵州省森林物候生长起始期、生长季长度与经度呈极显著相关,而森林物候生长结束期与经度呈低度相关,整体上贵州省森林物候参数海陆(经度)地带性地域分异显著;(3)贵州省森林物候生长起始期、生长结束期与海拔呈显著相关,而森林物候生长季长度与海拔呈极显著相关,因此贵州省森林物候参数垂直(海拔)地带性地域分异的十分显著。     

2000～2020年西南地区植被NDVI时空变化及驱动机制探究

基于2000～2020年MOD13A3 NDVI时间序列、1999～2020年气象数据以及2000年和2020年两期土地利用类型数据,采用Theil-Sen Median趋势分析、 Mann-Kendall显著性检验、多重共线性检验、残差分析和相对作用分析等方法,分析了西南地区植被NDVI时空变化特征及气候变化和人类活动对植被NDVI变化的驱动机制.结果表明,研究时段内西南地区整体及各地貌单元植被NDVI均呈上升趋势,其中,广西丘陵和云贵高原植被NDVI上升趋势最为显著,青藏高原植被NDVI上升趋势最为微弱.气候变化和人类活动影响下西南地区植被NDVI上升斜率分别为0.001 0 a^-1和0.000 6 a^-1.气候变化和人类活动的共同驱动是引起西南地区植被改善的主要原因.西南地区植被改善主要受区域气候条件的控制,植被退化主要受人类活动的影响.总体上,植被NDVI与最低气温、降水、最高气温、可能蒸散率和相对湿度呈正相关,与平均气温、气压、日照时数、温暖指数和湿度指数呈负相关.最低气温、日照时数和降水是影响西南地区植被NDVI变化的主要气象因子...     

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.