Carbon fluxes are essential indicators assessing vegetation carbon cycle functions. However, the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear. Here, we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor. The results showed that the annual average gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (Reco) in the Hexi Corridor oasis increased by 263.91 g C·m^-2·yr^-1, 118.45 g C·m^-2·yr^-1 and 122.46 g C·m^-2·yr^-1, respectively, due to the expansion of the oasis area by 3424.84 km² caused by human activities from 2000 to 2022. Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks. Compared to the non-oasis area, the carbon fluxes contributions of oasis area increased, ranging from 10.21% to 13.99% for GPP, 8.50% to 11.68% for NEP, and 13.34% to 17.13% for Reco. The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96% (7.09 Tg C yr^-1) for GPP, 29.57% (3.39 Tg C yr^-1) for NEP and 32.40% (3.58 Tg C yr^-1) for Reco. The changes in carbon fluxes in the oasis area were mainly attributed to human activities (oasis expansion) and temperature, whereas non-oasis area was mainly due to climate factors. Moreover, the future increasing trends were observed for GPP (64.99%), NEP (66.29%) and Reco (82.08%) in the Hexi Corridor. This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.

The northern high latitudes have warmed by about 0.8°C since the early 1970s, but not all areas have warmed uniformly [Hansen et al., 1999]. There is warming in most of Eurasia, but the warming rate in the United States is smaller than in most of the world, and a slight cooling is observed in the eastern United States over the past 50 years. These changes beg the question, can we detect the biotic response to temperature changes? Here we present results from analyses of a recently developed satellite‐sensed normalized difference vegetation index (NDVI) data set for the period July 1981 to December 1999: (1) About 61% of the total vegetated area between 40°N and 70°N in Eurasia shows a persistent increase in growing season NDVI over a broad contiguous swath of land from central Europe through Siberia to the Aldan plateau, where almost 58% (7.3×106 km2) is forests and woodlands; North America, in comparison, shows a fragmented pattern of change in smaller areas notable only in the forests of the southeast and grasslands of the upper Midwest, (2) A larger increase in growing season NDVI magnitude (12% versus 8%) and a longer active growing season (18 versus 12 days) brought about by an early spring and delayed autumn are observed in Eurasia relative to North America, (3) NDVI decreases are observed in parts of Alaska, boreal Canada, and northeastern Asia, possibly due to temperature‐induced drought as these regions experienced pronounced warming without a concurrent increase in rainfall [Barber et al., 2000]. We argue that these changes in NDVI reflect changes in biological activity. Statistical analyses indicate that there is a statistically meaningful relation between changes in NDVI and land surface temperature for vegetated areas between 40°N and 70°N. That is, the temporal changes and continental differences in NDVI are consistent with ground‐based measurements of temperature, an important determinant of biological activity. Together, these results suggest a photosynthetically vigorous Eurasia relative to North America during the past 2 decades, possibly driven by temperature and precipitation patterns. Our results are in broad agreement with a recent comparative analysis of 1980s and 1990s boreal and temperate forest inventory data [United Nations, 2000].

研究不同气候区植被覆盖的时空变化及气候因子与植被生长的关系,对生态环境建设与治理具有重要意义。基于1982—2015年GIMMS NDVI 3g数据集,运用均值法、Sen+Mann-Kendall趋势分析、偏相关系数、多元线性回归模型+残差法等方法,分析了黄河流域不同气候区生长季植被时空变化特征及气候因子与人类活动对植被变化的影响。结果表明:①1982—2015年黄河流域及不同气候区归一化植被指数(NDVI)年际变化呈缓慢上升趋势,干旱区变化波动平稳,半湿润区变化较明显。②34 a来各气候区大部分地区植被呈显著增加,半干旱区所占面积比例最大,不显著减少主要分布在半湿润区西南部及南部。③各气候区降水、气温、日照时数对NDVI表现出正影响,且日照影响最大;在半干旱区降水对NDVI影响最大,在半湿润区影响最小,在半湿润区气温对NDVI影响最大,在干旱区影响最小。④34 a来,人类活动对各气候区植被的积极影响明显大于消极影响。

Studying the temporal and spatial changes of vegetation coverage in different climatic regions and the relation between climatic factors and vegetation growth is of great significance to the construction and governance of ecological environment. Based on the GIMMS NDVI 3g dataset from 1982 to 2015, we examined the temporal and spatial changes of vegetation coverage in growth season in different climatic regions of the Yellow River Basin using the mean method, Sen+Mann Kendall trend analysis, partial correlation coefficient, multiple linear regression model plus residual method. We also analyzed the impacts of climatic factors and human activities on vegetation changes. Results demonstrated that: 1) The interannual change of NDVI in the Yellow River Basin and different climatic regions showed a slow upward trend from 1982 to 2015. The changes in arid region were steady, while the changes in semi-humid areas were more obvious. 2) In the past 34 years, vegetation increased remarkably in most of the climatic regions, of which the semi-arid region accounted for the largest proportion, whereas the southwest and south part of the semi-humid region mainly subjected to slight reduce. 3) Precipitation, temperature, and sunshine time in various climatic regions had positive impacts on NDVI, among which sunshine time had the greatest impact; in semi-arid region precipitation had the greatest impact on NDVI, whereas in semi-humid region the least impact; in semi-humid region temperature had the greatest impact on NDVI, while in arid region the least impact. 4) In the past 34 years, human activities exerted far more positive impact on vegetation than negative impact.

陕西省是落实黄河流域生态保护和高质量发展战略的重要区域。本研究基于表征植被生长的卫星遥感数据,结合气象栅格数据、数字高程数据,采用趋势分析、偏相关分析、变异系数、残差分析及相对作用分析方法,探讨了2001—2020年黄河流域陕西段植被生长时空格局及其驱动因子。结果表明: 研究期间,黄河流域陕西段植被归一化植被指数(NDVI)和植被总初级生产力(GPP)均呈显著波动上升趋势,增速分别为0.066·(10 a)^-1和133.610 g C·m^-2·(10 a)^-1,空间上分别有78.0%和92.1%的区域显著增加,大部分区域植被生长稳定。植被NDVI和GPP随海拔先减少后增加,在坡度>20°时达到最高值,阴坡植被稍优于阳坡,同时,两者在海拔750～1250 m和坡度2°～10°范围内增速最大,西坡、西南坡和东坡的NDVI增速较大,各坡向的GPP变化幅度相近。植被NDVI与平均气温在空间分布上的正、负相关区域相当,17.0%的区域与降水量呈显著正相关,5.6%的区域与日照时数呈显著负相关。植被GPP与平均气温、降水量在空间分布上分别有6.1%和12.3%的显著正相关区域,与日照时数呈显著相关的区域则零星分布。黄河流域陕西段86.3%区域的植被生长受气候变化和人类活动共同驱动并呈改善趋势,在植被改善区,人类活动相对作用达到84.5%,尤其在实施退耕还林还草工程的核心区域,在植被退化区,人类活动相对作用超过80%的区域占比接近3成,主要集中在关中平原城市群。

基于中国603个气象站的地表气温和降水观测资料以及GIMMS NDVI3g数据,采用变化趋势分析和多元回归残差分析等方法研究了1982—2015年中国植被NDVI变化特征及其主要驱动因素（即气候变化和人类活动）的相应贡献。结果表明：① 1982—2015年中国植被恢复明显,在选择的32个省级行政区中,山西、陕西和重庆的生长季NDVI增加最快,仅上海生长季NDVI呈减小趋势。② 气候变化和人类活动的共同作用是中国植被NDVI呈现整体快速增加和巨大空间差异的主要原因,其中气候变化对各省生长季NDVI变化的影响在-0.01×10 ^-3~1.05×10 ^-3 a ^-1之间,而人类活动的影响在-0.32×10 ^-3~1.77×10 ^-3 a ^-1之间。③ 气候变化和人类活动分别对中国近34年来植被NDVI的增加贡献了40%和60%;人类活动贡献率超过80%的区域主要集中在黄土高原中部、华北平原以及中国东北和西南等地;人类活动贡献率大于50%的省份有22个,其中贡献率最大的3个地区为上海、黑龙江和云南。研究结果建议应更加重视人类活动在植被恢复中的作用。

Based on the observed daily temperature and precipitation of the land surface of 603 meteorological stations in China, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) 3rd generation dataset, the changing patterns of NDVI in China during 1982-2015 were investigated and the corresponding contributions of the main driving forces, climatic change and human activities, to these changes were distinguished using the methods of trend analysis and multiple regression residuals analysis. The results showed that vegetation recovered in whole China in research period significantly. Shanghai was the single case with a decrease in growing season NDVI in the selected 32 provincial-level administrative regions, while the growing season NDVI in Shanxi, Shaanxi, and Chongqing increased much faster compared with other regions. The climatic change and human activities drove the NDVI change jointly as main forces in China and induced both a rapid increasing trend on the whole and a huge spatial difference. The impacts of climatic change on NDVI change in the growing-season ranged from -0.01×10 ^-3 a ^-1 to 1.05×10 ^-3 a ^-1, while the impacts of human activities changed from -0.32×10 ^-3 a ^-1 to 1.77×10 ^-3 a ^-1. The contributions of climatic change and human activities accounted for 40% and 60%, respectively, to the increase of NDVI in China in the past 34 years. The regions where the contribution rates of human activities were more than 80% were mainly distributed in the central part of the Loess Plateau, the North China Plain, and the northeast and the southwest of China. There were 22 provincial-level regions where the contributions of human activities were more than 50%, and the shares of contribution induced by human activities in Shanghai, Heilongjiang, and Yunnan were much greater than those of any other regions. The results suggest that we should focus more on the role of human activities in vegetation restoration in the whole country.

温度植被干旱指数（TVDI）是利用光学遥感进行干旱监测常用的遥感指数。但前人更多的是利用单时次的遥感数据计算TVDI，这使不同时间TVDI的可比性不高。利用历史遥感数据构建了NDVI-LST（LST，地表温度）、EVI（增强植被指数）-LST、SAVI（土壤调整植被指数）-LST 3种特征空间，讨论了TVDI方法在甘肃省陇东地区的适用性。结果表明：（1）特征空间法可用于甘肃省陇东地区土壤水分的监测，EVI-LST特征空间构建的TVDI与土壤相对湿度RSM的相关性更高；（2）DEM（数字高程模型）对特征空间法有一定的改进作用，LST经过DEM订正后，一方面特征空间干、湿边的拟合程度提高，另一方面TVDI与RSM的相关性得到一定程度的提高；（3）利用历史遥感数据建立的特征空间提高了TVDI的时空可比性：TVDI能够较好的指示出研究区每年RSM的空间分布特征及不同年份间RSM的差异。

Clear principle and concise physical meanings make Temperature Vegetation Dryness Index (TVDI) be a wildly used method in drought monitoring. It was not temporal comparable that building feature space by using single time remote sensing data in most former studies. In this paper, NDVI-LST, EVI-LST and SAVI-LST feature space is building by history MODIS data and the applicability is discussed. The results showed that: (1) In over all, TVDI method can be used to monitoring the Relative Soil Moisture (RSM) status in Longdong area. The correlation between TVDI calculated by EVI-LST space and RSM is highest. (2) Land Surface Temperature (LST) corrected by DEM improved TVDI method. In one hand, goodness of fitting of the dry and wet edge is improved. On the other hand, the correlation between TVDI and RSM is improved in a manner. (3) Building feature space though history remote sensing data is a reasonable and feasible method. Temporal and spatial comparable are enhanced by this method. TVDI indicated the history RSM spatial distribution every single year well and the variance of RSM in different year well too.

利用NOAA卫星AVHRR遥感资料,对甘肃省陇东地区1997-2001年地表植被指数的空间分布和年变化进行了分析,并对相应时段内的降水量与植被指数之间的关系,以及降水对该地区植被的影响进行了分析。结果表明,该5年陇东地区平均植被有减小趋势,但北部有所增加;降水量的多少对地表植被的月变化起重要作用,特别是对农作物区植被的影响;对于林区植被,降水的年际变化对地表植被的影响比较小,森林区植被指数最高;2000年及2001年的1~6月,尤其是2001年植被指数最低。

Using the NOAA satellite data of AVHRR, the spatial distribution and annual changes of surface vegetation index in Northeast Gansu region from 1997 to 2001 was studied and the relationship between precipitation and vegetation index and the impact of precipitation on vegetation index in this region were analyzed as well. The results showed that the averaged vegetation has decreasing trend in the recent 5 years, but it has some increasing one in the north of this region. The precipitation played an important role in the monthly changes of surface vegetation and especially in the agricultural area. The vegetation in forest area, in which has the highest vegetation index, the impact of annual change of precipitation on surface vegetation was slight. The lowest vegetation index occurred in January~June 2000 and 2001, especially in 2001.

探究三江源地区植被覆盖变化、驱动机制及生态脆弱性对其生态可持续发展具有重要意义。基于归一化植被指数（NDVI）、核归一化差异植被指数（kNDVI），采用Theil-Sen Median趋势分析、Mann-Kendall显著性检验法和地理探测器，探究植被覆盖时空变化及驱动机制，并运用“敏感-恢复-压力”模型评价生态脆弱性。结果表明：（1） 2001—2020年三江源地区植被NDVI和kNDVI均呈波动上升趋势，空间上，改善区域主要在东北部和西部，分别占73.70%和79.79%，退化区域主要在中部和南部，分别占23.23%和18.18%。（2） 降水量、海拔和气温是主导因素，因子间交互作用为双因子增强或非线性增强，降水量在573~675 mm、海拔在3447~3850 m范围内更适宜植被生长。（3） 生态脆弱性程度从东南部向西北部呈递增趋势，空间差异显著，该地区生态脆弱性较高，NDVI和kNDVI代表的重度、极度脆弱性区域分别占总面积的35.38%和36.85%。

三江源作为我国重要的生态安全屏障区,区域植被覆盖度的变化直接反映生态系统的健康状况,因此,监测区域植被覆盖变化并分析其驱动因素,有利于实现三江源生态环境的可持续发展。本文基于2000—2022年MODIS NDVI数据集,结合年均气温和年均降水数据,利用像元二分法、Sen+Mann-Kendall趋势分析法和偏相关系数分析法,探讨了三江源近23年间植被覆盖度时空演变特征及其与气候驱动的关系。结果表明:①三江源植被覆盖度在空间分布上表现为东南高、西北低的分布格局,2000—2022年三江源植被覆盖度呈线性增长趋势显著,增长率为0.001/a;②23年来三江源植被覆盖度增加区域为55.06%,减少区域为31.36%,植被覆盖度增加区域明显高于减少区域,总体植被覆盖度处于逐渐恢复的阶段;③偏相关分析表明,区域植被覆盖度与年均气温、年均降水均呈正相关性,与年均气温的相关性为0.02,与年均降水的相关性为0.29,降水为区域植被覆盖度增加的主要因素。本文研究揭示了23年来三江源植被覆盖度动态变化和分布格局,可为区域生态保护修复提供科学依据。

As an important ecological security barrier area in China, regional vegetation cover changes directly reflect the health of the ecosystem, so monitoring regional vegetation cover changes and analyzing their driving factors are conducive to realizing the sustainable development of the Three Rivers Headwaters region ecosystem. This study is based on the MODIS NDVI dataset from 2000 to 2022, combined with the mean annual temperature and mean annual precipitation data, and explores the spatial and temporal evolutionary characteristics of vegetation cover and its relationship with the climate driver during the last 23 years in the Three Rivers Headwaters region by using the image element dichotomy, Sen+Mann-Kendall trend analysis, and bias correlation coefficient analysis. Results show that: ①The vegetation cover of the Three Rivers Headwaters region show a high spatial distribution in the southeast and a low distribution pattern in the northwest. The vegetation cover show a significant linear growth trend from 2000 to 2022, with a growth rate of 0.001/a. ②Over the past 23 years, the vegetation cover of the Three Rivers Headwaters region has increased by 55.06% and decreased by 31.36%, with the increase in vegetation cover significantly higher than that of the decrease, and the overall vegetation cover is in the stage of gradual recovery.③The partial correlation analysis showe that the regional vegetation cover is positively correlated with the average annual temperature and average annual precipitation, with the correlation with the average annual temperature of 0.02 and the correlation with the average annual precipitation of 0.29, and precipitation is the main factor for the increase of vegetation cover. This study reveals the dynamic change and distribution pattern of vegetation cover in the Three Rivers Headwaters region over the past 23 years, which can provide a scientific basis for regional ecological protection and restoration.

为探究2001—2020年川西高原植被物候时空变化及其对气候变化的响应,利用MODIS NDVI数据、植被区划数据、数字高程数据以及气象数据,通过Savitzky-Golay滤波以及动态阈值法,提取了川西高原2001—2020年植被生长季始期(SOS)、生长季末期(EOS)以及生长季长度(LOS), 结合月平均气温与降水量,探讨了植被物候与气候因子(月平均气温、降水量)之间的关系。结果表明:①川西高原植被SOS主要集中在第90—第130天, EOS主要集中在第260—第290天,LOS主要为130~190 d;随着海拔不断升高,植被SOS呈提前趋势、EOS呈推迟趋势、LOS呈延长趋势。②植被SOS呈提前趋势的面积占60.56%;植被EOS呈推迟趋势的面积占51.21%;植被LOS呈延长趋势的面积占60.75%,其中7.19%呈显著延长趋势。③川西高原植被SOS与春季2—4月份平均气温呈负相关, 且存在较大的时空差异性;植被EOS与10月份平均温度、11月份降水量呈显著正相关;6月份平均气温和8月份降水对LOS的正向影响较大。整体来说,川西高原植被物候在不同植被区划具有明显的分布规律。研究成果可为高原地区植被物候变化规律研究提供参考。

动态评估滦河流域植被覆盖变化及对生态因子的响应,对于保障区域生态安全和促进京津冀城市群的可持续发展具有重要意义。本研究将滦河流域划分为两个生态区(内蒙古高原生态区、华北山地生态区),利用Theil-Sen中值趋势分析、Mann-Kendall检验和最优参数地理探测器模型,系统分析了2000—2019年流域植被时空变化特征,量化了自然和人为因素对植被变化的驱动作用。结果表明: 2000—2019年,滦河流域归一化植被指数(NDVI)总体呈波动上升趋势,多年均值为0.72,增长速率为0.0051·a^-1。上游高原生态区的NDVI增长速率较快但稳定性较差,而中下游山地生态区植被稳定性较高。年降水量、年日照时数和土地利用类型转换是NDVI变化的关键驱动因子,其解释力(q值)分别为0.22、0.18和0.17,其中,年降水量与土壤类型的交互作用最为显著(q=0.32)。土地利用变化显著促进了植被改善,研究期间生态工程实施区NDVI平均增加0.16。本研究揭示了自然与人为因素对植被覆盖变化的协同作用机制,为滦河流域生态保护与土地管理政策提供了科学依据。

Dynamically assessing vegetation cover changes and their responses to ecological factors in the Luanhe River Basin is crucial for ensuring regional ecological security and promoting the sustainable development of the Beijing-Tianjin-Hebei urban agglomeration. In this study, the Luanhe River Basin was divided into two ecological zones (Inner Mongolia Plateau Ecoregion and North China Mountain Ecoregion). Using Theil-Sen median trend analysis, the Mann-Kendall test, and the optimal parameters-based geographical detector model, we systematically analyzed the spatiotemporal characteristics of vegetation change from 2000 to 2019 and quantified the effects of natural and anthropogenic factors. The results showed that the normalized difference vegetation index (NDVI) exhibited an overall increasing trend with fluctuations from 2000 to 2019, with a mean value of 0.72 and a growth rate of 0.0051·a^-1. The NDVI growth rate in the upstream plateau ecological zone was higher but less stable, whereas vegetation in the midstream and downstream mountain ecological zone exhibited greater stability. Annual precipitation, annual sunshine duration, and land-use type conversion were identified as key drivers of NDVI variation, with explanatory power (q-values) of 0.22, 0.18, and 0.17, respectively. Among them, the interaction between annual precipitation and soil type was the most significant (q=0.32). Land use changes significantly contri-buted to vegetation improvement, with an average NDVI increase of 0.16 in ecological restoration project areas. By revealing the synergistic mechanism of natural and anthropogenic factors on vegetation cover changes, our results provide scientific support for ecological conservation and land management policies in the Luanhe River Basin.

黄土高原因其易被流水侵蚀的土壤特性，经常遭受沟谷溯源侵蚀而造成耕地面积减小并诱发地质灾害等一系列问题。基于高精度遥感影像和DEM，提取了沟谷网络及其特征参数，分析了沟谷之间的相互影响关系和发育特征。通过计算流域沟谷的盒维数和沟沿线的边界维数，对沟谷侵蚀发育的复杂程度进行了综合评价。同时，基于盒维数和边界维数，研究了沟谷流域的发育过程及其侵蚀的空间分布规律。研究发现：（1） 在发育次一级的沟谷时，沟谷顺流方向单侧有110°的可发育区间。（2） a流域的侵蚀发育程度最复杂，b次之，c最小；b流域的沟沿线最复杂，a次之，c最简单；c流域的沟谷侵蚀发育程度从SW向NE递增。（3） 地质构造是影响着沟谷发育程度的主要因素之一；高程越高，黄土厚度越薄，植被越稀少，沟谷侵蚀发育程度越高。研究结果可为陇东地区水土保持治理提供指导建议。

The Loess Plateau, characterized by soil highly susceptible to erosion from flowing water, frequently experiences gully backward erosion, leading to reduced arable land and a series of geologic hazards. Using high-resolution remote sensing imagery and DEM, the gully network and its characteristic parameters were extracted to analyze the interaction relationships and development characteristics of gullies. The complexity of gully erosion and development was comprehensively evaluated through the box dimension of the watershed gully and the boundary dimension of the gully ridgeline. Additionally, the development process and spatial distribution patterns of erosion in the gully watershed were examined based on the box and boundary dimensions. The results demonstrated that: (1) In secondary-level valley development, there exists a 110° developable interval on one downstream side. (2) Watershed b exhibits the most complex erosion development, followed by watershed a, and then watershed c; along valley slopes, watershed b has the most intricate boundary dimension, followed by watershed a, and then watershed c. The degree of watershed gully erosion increases from southwest to northeast for watershed c. (3) Geological structure significantly influences the degree of gully development, with higher elevation, thinner loess thickness, sparser vegetation, and greater gully erosion. This study offers guiding recommendations for soil and water conservation management in eastern Gansu Province.

灌溉面积是有效实施农业节水所需的基础性数据,传统调查统计方式已经不能满足当前灌溉面积监测需要。融合GF-1与Sentinel-2卫星影像,构建作物生育期的样本光谱,基于像元尺度光谱匹配方法协同提取江苏省宿迁市皂河灌区2017—2022年作物种植结构及实际灌溉面积。结果显示:皂河灌区的主要种植模式为水稻小麦轮作;灌区2017—2022年实际灌溉面积分别为85.11、91.91、103.65、95.85、97.72、88.24 km²。基于样本点利用混淆矩阵对提取的实际灌溉面积结果进行精度验证,总体精度为89.71%,Kappa系数为0.80,监测结果精度较高且提取效果优于目前公开产品中精度较高的IrriMap_Syn产品及IWMI产品。该方法适用于南方灌区实际灌溉面积提取,可为灌区管理部门日常监管、优化水资源配置等提供技术与数据支持。