A new concept for estimating the influence of vegetation on throughfall kinetic energy using aerial laser scanning     

Johannes Antenor Senn  Fabian Ewald Fassnacht  Jana Eichel  Steffen Seitz  Sebastian Schmidtlein 《地球表面变化过程与地形》2020,45(7):1487-1498

Soil loss caused by erosion has enormous economic and social impacts. Splash effects of rainfall are an important driver of erosion processes; however, effects of vegetation on splash erosion are still not fully understood. Splash erosion processes under vegetation are investigated by means of throughfall kinetic energy (TKE). Previous studies on TKE utilized a heterogeneous set of plant and canopy parameters to assess vegetation's influence on erosion by rain splash but remained on individual plant- or plot-levels. In the present study we developed a method for the area-wide estimation of the influence of vegetation on TKE using remote sensing methods. In a literature review we identified key vegetation variables influencing splash erosion and developed a conceptual model to describe the interaction of vegetation and raindrops. Our model considers both amplifying and protecting effect of vegetation layers according to their height above the ground and aggregates them into a new indicator: the Vegetation Splash Factor (VSF). It is based on the proportional contribution of drips per layer, which can be calculated via the vegetation cover profile from airborne LiDAR datasets. In a case study, we calculated the VSF using a LiDAR dataset for La Campana National Park in central Chile. The studied catchment comprises a heterogeneous mosaic of vegetation layer combinations and types and is hence well suited to test the approach. We calculated a VSF map showing the relation between vegetation structure and its expected influence on TKE. Mean VSF was 1.42, indicating amplifying overall effect of vegetation on TKE that was present in 81% of the area. Values below 1 indicating a protective effect were calculated for 19% of the area. For future work, we recommend refining the weighting factor by calibration to local conditions using field-reference data and comparing the VSF with TKE field measurements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   

Numerical study for vegetation effects on coastal wave propagation by using nonlinear Boussinesq model     

《Applied Ocean Research》2018

The vegetation has important impacts on coastal wave propagation. In the paper, the sensitivities of coastal wave attenuation due to vegetation to incident wave height, wave period and water depth, as well as vegetation configurations are numerically studied by using the fully nonlinear Boussinesq model. The model is based on the implementation of drag resistances due to vegetation in the fully nonlinear Boussinesq equation where the drag resistance is provided by the Morison’s formulation for rigid structure induced drag stresses. The model is firstly validated by comparing with the experimental results for wave propagation in vegetation zones. Subsequently, the model is used to simulate waves with different height, period propagating on vegetation zones with different water depth and vegetation configurations. The sensitivities of wave attenuation to incident wave height, wave period, water depth, as well as vegetation configurations are investigated based on the numerical results. The numerical results indicate that wave height attenuation due to vegetation is sensitive to incident wave height, wave period, water depth, as well as vegetation configurations, and attenuation ratio of wave height is increased monotonically with increases of incident wave height and decreases of water depth, while it is complex for wave period. Moreover, more vegetation segments can strengthen the interaction of vegetation and wave in a certain range.  相似文献   

基于 MODIS 数据的吐鲁番盆地 2001—2017 年 植被变化及水热组合影响分析          下载免费PDF全文

庞冉  王文 《干旱区地理》2020,43(5):1242-1252

中国西北干旱地区的气候变化及其对植被的影响一直备受关注。以地形特殊的吐鲁番盆 地为研究对象，利用实测气象站点数据、再分析气象格点数据以及 MODIS 卫星遥感植被指数，采用 趋势检验、线性回归、偏相关分析等方法，探究了该地区 2001—2017 年间的植被变化及其与水热组 合特征之间的关系。结果表明：（1）吐鲁番盆地降水量整体没有显著变化，但北部山区降水增长较 多，气温总体呈显著上升趋势，尤其是盆地底部中心区域增温较大。（2）全区域植被指数（NDVI）总 体呈极显著上升趋势，山区及中心区域 NDVI 增长率较大。（3）受水汽来源和日照时长的影响，吐鲁 番盆地周边山区高程 3 000 m 左右 NDVI 值最高，山区植被最好的坡向是西北坡。（4）吐鲁番盆地水 热组合复杂，水分条件是大部分地区植被生长的主要限制因素，降水与 NDVI 有较好的正相关，在 山区和荒漠区热量增加不利于植被生长，但中心区域受地下水和人类活动影响，水分的供给相对 稳定，热量增加利于植被生长。  相似文献   

2007-2016年四川省土壤干旱时空动态分析     

陈艾琳  戴晓爱  张诗琪  周旋 《山地学报》2020,38(1):31-41

四川作为农业大省,旱灾是导致农业减产最主要的因素。通过遥感和GIS手段进行四川省土壤干旱程度的时空分析,提高干旱的空间可视化程度,加强干旱监测的时效性尤为重要。本研究基于四川省2007—2016年逐季度的MODIS数据和1961—2011年40个气象站的月降水资料,采用温度植被干旱指数(TVDI)计算得到四川省干旱等级分布情况,辅以标准化降雨指数(SPI)进行相关性分析,并通过线性回归、反距离权重空间插值、GIS空间分析模型重建等方法,分析近十年来四川省地区以季度为时间尺度的土壤干旱时空变化特征,制作各时相土壤干旱分布图展示其微变化。结果表明:(1)在月时间尺度上,SPI-1与TVDI呈中等至强负相关关系,即TVDI值越小,SPI值越大,干旱程度越轻;验证结果表明TVDI都能够较好地对四川省的干旱空间分布状况进行反映。(2)四川省各区域、各季节干旱分布不均:空间上,干旱频发的区域集中在四川盆地及攀西南部区域。时间上,在春季,四川盆地区域的土壤干旱程度大致呈现加剧—持续—减缓的趋势;夏季,四川盆地的干旱变化趋势是加剧—减缓—加剧;秋季,四川盆地的干旱变化趋势是加剧—减缓—持续减缓;冬季,全川干旱程度变化不明显。本文的研究结果对四川省开展农业防灾减灾,引导农业灌溉具有指导意义。  相似文献   

A comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere     

Qing Chang  Wenzhe Jiao  Fengmei Yao 《国际地球制图》2018,33(1):1-20

Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr^–1.  相似文献   

Characteristics and variation law of wind-blown sand delivered to the Ningxia-Inner Mongolia reach of the Yellow River under a changing environment     

Zhichun Yue  Ximin Yuan  Lugan Cao  Fuchang Tian  Chao Han  Hongwu Zhang 《国际泥沙研究》2022,37(2):188-201

Wind-blown sand is one of the key factors affecting the evolution of sediment transport,erosion,and deposition in rivers crossing desert areas.However,the differences and complex variations in the spatial and temporal distribution of the underlying surface conditions are seldom considered in research on the river inflow of wind-blown sand over a long time period.The Yellow River contains a large amount of sediment.The Ningxia-Inner Mongolia reach of the Yellow River was selected as the research ...  相似文献   

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India     

《地学前缘(英文版)》2022,13(2):101312

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.  相似文献   

Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa     

《International Journal of Applied Earth Observation and Geoinformation》2015

Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000–2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000–2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.  相似文献   

Evaluating the relationship between biomass,percent groundcover and remote sensing indices across six winter cover crop fields in Maryland,United States     

《International Journal of Applied Earth Observation and Geoinformation》2015

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r² = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r² = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.  相似文献   

Reducing background effects in orchards through spectral vegetation index correction     

《International Journal of Applied Earth Observation and Geoinformation》2015

Satellite remote sensing provides an alternative to time-consuming and labor intensive in situ measurements of biophysical variables in agricultural crops required for precision agriculture applications. In orchards, however, the spatial resolution causes mixtures of canopies and background (i.e. soil, grass and shadow), hampering the estimation of these biophysical variables. Furthermore, variable background mixtures obstruct meaningful comparisons between different orchard blocks, rows or within each row. Current correction methodologies use spectral differences between canopies and background, but struggle with a vegetated orchard floor. This background influence and the lack of a generic solution are addressed in this study.Firstly, the problem was demonstrated in a controlled environment for vegetation indices sensitive to chlorophyll content, water content and leaf area index. Afterwards, traditional background correction methods (i.e. soil-adjusted vegetation indices and signal unmixing) were compared to the proposed vegetation index correction. This correction was based on the mixing degree of each pixel (i.e. tree cover fraction) to rescale the vegetation indices accordingly and was applied to synthetic and WorldView-2 satellite imagery. Through the correction, the effect of background admixture for vegetation indices was reduced, and the estimation of biophysical variables was improved (ΔR² = 0.2–0.31).  相似文献