Vegetation fractional coverage change in a typical oasis region in Tarim River Watershed based on remote sensing

Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM＋ images of 1989, 2001, and 2006, and supported by Geographic Information System （GIS） spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSl （vegetation, bare soil and shadow indices） suitable for TM/ETM＋ irrlages, constructed with FCD （forest canopy density） model principle and put forward by ITTO （International Tropical Timber Organization）, was used, and it was applied to estimate the VFC. The estimation accuracy was later prow^n to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover diigital images to deeply analyze the reason behind the variation.

Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area

The estimation of fractional vegetation cover(FVC) is important for identifying and monitoring desertification, especially in arid and semiarid regions. By using regression and pixel dichotomy models, we present the comparison of Sentinel-2A(S2) multispectral instrument(MSI) and Landsat 8(L8) operational land imager(OLI) data regarding the retrieval of FVC in a semi-arid sandy area(Mu Us Sandland, China, in August 2016). A combination of unmanned aerial vehicle(UAV) high-spatial-resolution images and field plots were used to produce verified data. Based on a normalized difference vegetation index(NDVI) regression model, the results showed that, compared with that of L8, the coefficient of determination(R2) of S2 increased by 26.0%, and the root mean square error(RMSE) and the sum of absolute error(SAE) decreased by 3.0% and 11.4%, respectively. For the ratio vegetation index(RVI) regression model, compared with that of L8, the R2 of S2 increased by 26.0%, and the RMSE and SAE decreased by 8.0% and 20.0%, respectively. When the pixel dichotomy model was used, compared with that of L8, the RMSE of S2 decreased by 21.3%, and the SAE decreased by 26.9%. Overall, S2 performed better than L8 in terms of FVC inversion. Additionally, in this paper, we develop a verified scheme based on UAV data in combination with the object-based classification method. This scheme is feasible and sufficiently robust for building relationships between field data and inversion results from satellite data. Further, the synergy of multi-source sensors(especially UAVs and satellites) is a potential effective way to estimate and evaluate regional ecological environmental parameters(FVC).

Investigation of Uncertainties of Establishment Schemes in Dynamic Global Vegetation Models

In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.

Effects of ecological projects on vegetation in the Three Gorges Area of Chongqing, China

The construction of the Three Gorges Reservoir and the resettlement project have caused increasing contradictions between human and land,and led to the deterioration of the ecological environment. In order to ameliorate ecological environment of the Three Gorges Area, the government carried out several ecological restoration projects to improve the vegetation coverage from 1990 s. This paper aims to quantitatively analyze the impact of ecological projects on the vegetation in the Three Gorges Area of Chongqing, China. Landsat and MODIS data from 1992 to 2015 were used to estimate vegetation coverage. In addition, the land cover data of the European Space Agency(ESA) was used to explore the impact of ecological projects on land cover change. The cropland accounted for about 62% and the forestland accounted for about 34% of the total area. There was more than 90% of the study area covered with high or very high vegetation coverage.From 1992 to 2015, a total of 272.7 km;croplands were converted into forestland in the Ecological Migration Project(EMP), 795.6 km;in the Grain for Green Project(GGP), and 13.77 km;in the Ecological Restoration Zone Project(ERZP). Among the three projects, the GGP was the most powerful measure,with a contribution rate of 1.6%. The implementation of the ecological projects improved vegetation coverage, which indicated that the ecological projects measures were effective in ecological restoration.

Preliminary Assessment of the Common Land Model Coupled with the IAP Dynamic Global Vegetation Model

The Common Land Model(CoLM) was coupled with the IAP Dynamic Global Vegetation Model(IAPDGVM), and the performance of this combined CoLMIAP model was evaluated. Offline simulations using both the original Common Land Model(CoLM-LPJ) and CoLM-IAP were conducted. The CoLM-IAP coupled model showed a significant improvement over CoLMLPJ, as the deciduous tree distribution decreased over temperate and boreal regions, while the distribution of evergreen trees increased over the tropics. Some biases in CoLM-LPJ were preserved, including the overestimation of evergreen trees in tropical savanna, the underestimation of boreal evergreen trees, and the absence of boreal shrubs. However, most of these biases did not exist in a further coupled simulation of IAP-DGVM with the Community Land Model(CLM), for which the parameters of IAP-DGVM were optimized. This implies that further improvement is needed to deal with the differences between CoLM and CLM in parameterizations of landbased physical and biochemical processes.

基于Landsat时间序列遥感影像的合肥市FVC时空演化与分析

文章基于Landsat时间序列遥感影像,采用像元二分模型反演合肥市2008—2019年植被覆盖度(fractional vegetation cover,FVC),并利用马尔可夫转移矩阵与差值图像算法,定量分析2008—2019年合肥市不同等级FVC变化特征。研究结果表明:2008年、2011年、2013年、2015年、2017年、2019年合肥市平均FVC分别为60.9%、48.4%、56.0%、48.0%、63.0%、61.2%,年均FVC波动较大,但总体呈上升趋势;合肥市FVC变化以稳定区为主,主城区的外围FVC出现退化趋势,而长丰县、主城区及庐江县FVC增长明显;各等级FVC总体变化趋势为良性,未来FVC预计以增加为主;2008—2019年合肥市气温呈升高趋势,而降水量呈下降趋势,总体表现为“暖干化”,且这种趋势对合肥市FVC增加具有促进作用,其中年均气温是影响FVC演化的主要因子。

Evaluating the Impact of Different Vegetation Types on NEE: A Case Study of Banni Grasslands, India

Estimation of NEE of Grasslands ecosystems becomes mandatory as these grasslands with their wide spread (almost 40% of land of the earth) and high plant diversity play a major role in global carbon balances and NEE at both local and global scale. The present study has been focused on understanding the role of different plant species responsible for variation in NEE of the Banni Grasslands of India. These grasslands form a belt of arid grassland having low growing forbs, graminoids and scattered tree cover. Due to its wide spread and inaccessibility of Banni, this study utilized spatial approach for evaluating carbon emissions and NEE. Landsat data was utilized for vegetation type classification and SMAP data for extraction of NEE values proved their potential for categorising vegetation type and generating NEE values precisely. Three major plant types were identified from the study area viz., Grasslands, Land with Acacia and Land with Prosopis. Grasses were dominant covering 77% and the rest of the area was occupied by the other two classes, i.e. Acacia and Prosopis. The NEE values were higher for the grasses when compared to the other two plant species proving to be the active sinks when compared to other plants. The differential contribution of NEE by species has been depicted in the present work.

黄土高原极端降水变化及其对植被覆盖度影响

全球变暖背景下,黄土高原极端降水事件频发,对社会经济及植被生态产生了重要影响,研究黄土高原极端降水变化特征及其对植被覆盖度(fractional vegetation cover,FVC)影响,可为生态环境保护和区域可持续发展提供科学支撑。基于2000—2020年黄土高原64个气象站点逐日降水数据和MODIS NDVI数据,采用趋势分析、相关分析等方法,分析了黄土高原地区极端降水和FVC时空变化特征及极端降水对FVC的影响。结果表明:2000—2020年黄土高原地区总降水量P_(RCPTOT)、中雨日数R_(10mm)、大雨日数R_(20mm)、强降水日数R_(25mm)和降水强度S_(DII)均呈显著上升趋势(P<0.05),区域西部和北部强降水总体增加,但区域南部呈干旱化。2000—2020年黄土高原FVC总体呈显著上升趋势(P<0.05),集中分布在区域中东部,占区域总面积的32.00%;显著下降趋势主要分布在南部少部分地区,仅占区域总面积的4.91%。2000—2020年黄土高原地区FVC与中雨日数R_(10mm)、大雨日数R_(20mm)、强降水日数R_(25mm)和降水强度S_(DII)以正相关关系为主,其中呈显著正相关的区域占比分别为22.33%、48.19%、14.36%和24.37%,主要分布在中部地区。研究认为近20年黄土高原极端降水和FVC同步增加,表现为极端降水促进植被生态改善的作用,但应注意极端降水研究中的时间尺度效应问题,即年尺度数据可能掩盖了短时间尺度上极端降水对FVC的破坏作用。

“胡焕庸线”两侧植被覆盖度地域分异的时空特征分析

探究“胡焕庸线”两侧植被覆盖度的地域分异对于生态环境保护与自然资源的可持续管理具有重要意义。本研究根据MODIS-NDVI遥感数据及相关研究资料,运用像元二分法量化了2000至2020年间植被覆盖的变化情况,并结合斜率分析、空间自相关分析、转移矩阵及相关分析法,系统分析了“胡焕庸线”东西两侧植被覆盖度的动态及降水对其的潜在影响。研究发现,中国植被覆盖度在“胡焕庸线”两侧展现出显著的空间异质性,西部地区普遍低于东部;冷点主要分布于线西,热点主要分布于线东。尽管过去21年间全国植被覆盖度经历了局部年度波动,但从整体趋势看呈上升态势,约有45%的地区植被覆盖水平实现了由低向高的转变。具体而言,“胡焕庸线”以西区域的年均植被覆盖度增长率约为0.0035/a,而线东地区则达到0.0059/a,且在各自区域内,植被显著增长的区域占比分别为53.22%和59.81%。此外,年降水量与年际间植被覆盖度的相关性在“胡焕庸线”两侧表现出空间上的差异化特征,即东部地区呈负相关,而西部则为正相关。综上所述,以“胡焕庸线”为界,中国的植被覆盖度在时间和空间上的分布特征凸显了其独特的地域分异性。本研究为理解我国植被生态系统的动态变化提供了重要依据。

植被覆盖度增加对辽宁地区气温变化的影响研究

植被覆盖度(Fractional Vegetation Coverage,简称FVC)是陆面参数中重要的参数之一,植被覆盖度变化直接影响地表能量的再分配进而影响区域乃至全球气候变化,研究植被覆盖度增加对区域气候的影响对未来区域气候变化的预估具有重要意义,这对适应和缓解全球气候变暖至关重要。本文利用2001~2018年中分辨率成像光谱仪(MODIS)产品的植被归一化指数(Normalized Difference Vegetation Index,简称NDVI)数据制作植被覆盖度,在辽宁地区分别进行了WRF模式默认植被覆盖度和实际植被覆盖度的长时间(2001~2018年)模式模拟试验,结论如下:(1)辽宁地区因植被覆盖度增加全省年平均气温降低了0.48℃,其中夏季降温幅度最大,降温0.71℃,春、秋两季平均降温0.35℃和0.66℃,冬季降温幅度最小0.2℃。植被覆盖度增加对日最高、最低气温也有明显的降温作用,其中日最低气温对植被覆盖度增加的响应大于最高气温,且植被覆盖度增加与气温降温的空间分布具有较好一致性。(2)2001~2018年年均和四季植被覆盖度的显著增加对年均和四季平均气温、日最高气温、日最低气温均有降温趋势,尤其是对日最低气温降温作用更明显。(3)植被覆盖度增加导致气温降低的主要原因是由于蒸散发的增加导致潜热通量增加,感热通量减少;而对于日最低气温降低,主要是由于植被覆盖度增加导致地表温度降低进而引起夜间向上长波辐射减少。总体而言,植被覆盖度增加越多降温效果越明显,进而减缓辽宁省气候变暖。

京津冀植被覆盖度时空演变及其对自然人为变化的响应

基于2001~2020年归一化差异植被指数(NDVI)数据,采用像元二分模型最大值合成FVC,通过Sen趋势分析、Mann-Kendall显著性检验、Hurst指数分析预测研究区植被覆盖时空变化,结合气象因子数据应用相关性分析与残差分析在开展植被变化响应分析的基础上新增量化影响因子相对贡献率.结果表明:近20年京津冀地区植被建设良好,全域平均覆盖度为64.5%,植被变化速率介于(-0.0597421~0.039797)/a,植被覆盖波动较大,呈现明显的地理差异变化;京津冀地区FVC时空变化受多因素共同影响,FVC与气温以负相关为主,分布区域贴合行政分区,与城市热岛效应相关;FVC与降水以正相关为主,分布范围贴合生态分区,主要受地理因子调控;人类活动平均残差为-0.00105,负向影响为主;自然与人为因素相对贡献率分别为31.33%和68.67%,人类活动是植被变化的主要驱动因素;未来FVC以改善趋势为主,但城市交界处FVC有下降趋势.研究成果可指导京津冀交界处FVC监测,开展正向人为干预,稳定京津冀环境质量,助推全域生态环境高质量发展.

青海湖流域植被动态变化驱动力及空间粒度效应

基于Landsat遥感影像分析1986~2020年青海湖流域植被覆盖度时空变化特征,结合多元线性回归和地理探测器,考虑气候、地表及人类足迹的影响,阐明时间和空间尺度下植被覆盖度变化的机制,并探讨空间粒度对驱动因素及其相对贡献的影响.结果表明:(1)近35年来青海湖流域植被状况整体改善,表现为中等、中高覆盖度植被面积增加,其中环青海湖东北部及布哈河上游植被覆盖度呈显著增加趋势;(2)时间尺度上,流域平均植被覆盖度变化受气候暖湿化和生态恢复工程驱动;(3)空间尺度上,植被覆盖度变化由气候、地形、植被和土壤控制,解释力较大因素为气温(0.41),高程(0.34)和降水(0.30).气候、地形和人为因素对植被覆盖度的影响存在交互增强效应,气温、高程对交互效用具有控制作用,其中气温与距水系距离、降水和人类足迹的交互较为显著;(4)空间粒度对植被覆盖度空间变化驱动因素的贡献具有显著影响,考虑气候、地表和人为因素交互作用时青海湖流域植被覆盖度空间变化最佳研究粒度为6km.

基于FVC的新疆植被覆盖度时空变化

【目的】对新疆植被覆盖变化的空间自相关性进行分析,研究植被覆盖的时间变化特征、空间分布特征及变化趋势等,为改善区域生态环境提供参考。【方法】利用新疆1998—2012年NDVI数据,采用像元二分法获取植被覆盖指数(FVC)数据,在此基础上运用Sen+Mann-Kendall趋势分析和空间自相关分析方法,研究新疆植被覆盖的变化趋势特征和空间分布的聚集性特点。【结果】1)15年间新疆植被覆盖度略有下降趋势,山地和平原均呈下降趋势,山地较平原变化大。2)Sen+Mann-Kendall趋势分析可反映新疆FVC变化趋势的空间分布特点,全疆植被改善区域占25%,退化区域占28%,47%的区域变化不大,其中明显改善区域和严重退化区域所占比例均为10%左右。植被改善区域主要分布在天山北坡一带,退化区域主要分布在山地和平原的交错带,伊犁地区退化程度尤为严重。植被覆盖度极低地区基本不变,退化区域主要分布在植被低覆盖度区域周围。3)空间自相关分析进一步验证了Sen+Mann-Kendall趋势分析结果,新疆植被有明显的聚集现象。全局自相关性分析表明,当距离大于3 km后,空间自相关影响不大。局部相关性分析表明,新疆植被覆盖以"高-高聚集"和"低-低聚集"为主。【结论】植被盖度相对较高的地区植被覆盖越易改善,盖度较低或无覆盖的地区越难改善,而且退化越明显。根据植被盖度的聚集性可以看出,植被覆盖呈现明显的"高-高聚集"和"低-低聚集"格局,这与区域气候、水资源分布及人类活动的影响有着潜在的联系。今后可重点分析植被覆盖变化的影响因素,以了解干旱区植被覆盖变化的驱动机制。由于人类活动在短时期内对植被覆盖变化的影响比较显著,因此在空间上分析人类活动对植被覆盖变化的影响可为改善干旱区植被覆盖提供相应指导。【其他】本文从植被覆盖的空间聚集性解释了植被覆盖变化特点,一方面是对Sen+Mann-Kendall趋势分析的验证,另一方面为整体分析植被的变化特征提供了依据。

黄河柳园口湿地植被时空变化及驱动因素分析

柳园口湿地是我国省级自然保护区,其保护与治理对于维护城市生态环境具有重要意义。基于Landsat影像,采用像元二分模型、转移矩阵法和一元线性回归模型分析植被覆盖度时空变化特征,运用皮尔逊相关系数法进行其与年均气温、年均降水的驱动因素分析。结果表明:2000—2020年植被覆盖度呈缓慢上升趋势,湿地的改善区域大于退化区域,年均气温对植被覆盖度的影响大于年均降水。研究结果可为开展湿地生态保护和制定湿地生态修复规划提供科学支撑。

基于可见光影像的木里矿区排土场植被覆盖度提取研究

为了快速准确提取木里矿区排土场的植被覆盖度,基于无人机可见光影像,选择过绿指数、过绿减过红指数、可见光波段差异植被指数和归一化绿红差异指数,将植被指数时序图交点法和样本统计法相结合进行阈值分割,从而提取植被覆盖度,并对提取结果的精度进行验证。结果表明:可见光波段差异植被指数的提取精度最高,达到95.83%,Kappa系数为0.92。由此可见,利用可见光波段差异植被指数,将植被指数时序图交点法和样本统计法相结合的方法适用于提取木里矿区排土场的植被覆盖度且精度较高。研究结果可为高寒矿区排土场植被覆盖度的精确提取提供一定的参考。

基于空间自相关分析和FVC指数的克拉玛依地区植被覆盖时空变化

以新疆克拉玛依地区为研究区,基于GIS平台和2000—2013年NOAA/AVHRR影像的FVC数据,在1km×1km空间分辨率下,对研究区的FVC指数进行空间自相关分析,从时间和空间两个维度探讨其植被覆盖变化的时空变化特征。研究结果表明:1)2000—2013年来研究区FVC指数变化明显,克拉玛依地区绿洲主要分布在南部的克拉玛依区,北部的乌尔禾区绿洲相对较少,中部的白碱滩区只有零星分布,绿洲面积显著扩大,扩大方向主要在克拉玛依区,然而白碱滩区和乌尔禾区绿洲面积有所减小。2)沙漠无植被区主要分布在研究区的北部和中部,研究期内沙漠化有所扩大,白碱滩区和乌尔禾区是沙漠化扩大的主要地区,其沙漠腹地的绿洲面积缩小,有些绿洲已经彻底消失。3)绿洲—荒漠过渡带主要分布在研究区南部的克拉玛依区,呈减小的变化趋势。全面、客观地分析克拉玛依地区近十几年来的FVC指数变化特征,对促进研究区经济、社会、环境的可持续发展具有重要参考价值。

基于NDVI数据的陇南市植被覆盖度时空演变

为研究陇南市的植被覆盖变化,基于2001—2020年归一化差异植被指数数据,采用像元二分模型最大值合成植被覆盖度,通过趋势分析、显著性检验,Hurst指数等方法,系统地分析甘肃省陇南市近20年来植被覆盖度的时空演化特征,并对其发展趋势进行预测。结果表明:①陇南市植被覆盖度整体呈现出一个波动性的上升趋势,变化速率在(-0.0417208~0.0479985)/a;②不同地区的植被覆盖度稳定性存在明显的差异,其中植被覆盖稳定不变区域占比7.26%,明显改善区域占比31.12%,严重退化区域占比9.39%;③在植被覆盖演变过程中,持续性和反持续性呈现出交错的分布模式,总体上主要呈现为弱持续性的序列。研究结果可为陇南市生态环境的修复和保护工作提供参考依据。

基于Landsat遥感影像的湖南省新邵县植被覆盖度变化分析

植被覆盖度是植被的直观量化指标,能够反映植被的生长情况,对生态环境建设具有重要意义。为探讨2000-2021年间新邵县植被覆盖度的动态变化,以湖南省邵阳市新邵县为研究区,利用2000年和2021年两期Landsat遥感影像,采用归一化差异植被指数和像元二分模型估算不同时期新邵县的植被覆盖度,并进行差值分析。结果表明:自2000年到2021年,新邵县的植被覆盖度整体呈增长趋势,且西部、南部地区的植被覆盖度增加明显,这与当地封山育林、绿化造林等政策实施密切相关。这也反映出新邵县在2000-2021年期间注重生态保护建设,森林质量明显提升。

内蒙古植被覆盖时空变化特征及其对人类活动的响应

基于2000—2022年MOD13A1 NDVI数据计算内蒙古年最大植被覆盖度(FVC),了解内蒙古FVC时空分布状况及变化趋势,结合夜间灯光(NTL)和地表覆被数据,采用逐像元相关分析方法探究FVC对人类活动的响应模式。结果表明:(1)内蒙古FVC空间分布总体表现为由东北至西南逐渐减小的趋势,FVC以改善为主,增速为0.0039·a^(-1),大部分区域FVC变化表现为基本稳定(64.02%)和明显增加(31.64%),所有盟市年均FVC增长量均为正值;(2)FVC变化趋势主要表现为不显著变化,占比依次为:不显著变化(65.62%)、显著增加(17.36%)、极显著增加(13.43%)、显著减少(3.27%)和极显著减少(0.32%),显著减少和极显著减少的区域与新增建设用地在空间分布上存在较高的一致性;(3)在人类活动空间范围,内蒙古大部分区域(79.67%)人类活动不会对FVC变化产生显著影响,12.80%的区域人类活动对FVC变化起着积极作用,地表覆被主要为城区周边的草地和耕地区域,只有7.53%的区域人类活动对FVC变化起着消极作用,主要分布在地表覆被为耕地、由耕地转为建设用地和新增工矿用地区域。

利用Google Earth Engine云平台进行植被覆盖估算及等级划分

植被变化时空特征能够间接反映生态环境质量的变化,对一个地区的生态系统稳定、物种多样性和社会经济发展有着重要意义。借助谷歌地球引擎(GEE)云平台建立归一化植被指数(NDVI)、植被覆盖度(FVC)等指标对浙江省2011—2021年植被覆盖面积进行了估算和等级划分。结果表明:2011—2021年期间,浙江省植被覆盖总面积基本维持不变,平均植被覆盖面积为104233.87 km^(2),植被覆盖以高覆盖度为主,平均覆盖面积占总覆盖度面积的81.0%,2021年,高覆盖度、较高覆盖度植被面积分别占比82.90%、9.39%,而低覆盖度、较低覆盖度植被面积分别占比0.63%、1.59%。对植被覆盖面积时空变化的特征分析揭示了浙江省植被覆盖度变化存在空间尺度依赖性,同时其结果可为浙江省生态监测、环境保护及区域高质量发展提供科学依据和决策支持。