关岭-贞丰石漠化治理示范区植被覆盖变化及其对气候因子的响应

为揭示喀斯特石漠化治理示范区植被覆盖变化以及气候因子对植被覆盖变化的影响,利用2006—2015年Landsat 30 m/16 d分辨率影像数据,采用最大合成法、NDVI差值指数和相关、偏相关分析法,系统分析示范区归一化植被指数的时空变化特征及其与气候因子的关系。结果表明:(1)2006—2015年最大NDVI平均值为0.39,NDVI较高覆盖区域在示范区南北边界,而较低覆区域以花江南岸为主;(2)2006年以来示范区极低(-1.210)、低(-0.669)和中等(-0.729)植被覆盖度呈减少趋势,高(1.359)和极高(1.247)植被覆盖度增加,整体上呈显著增加趋势;(3)本月NDVI与本月、上月、上上月降雨量和气温的相关性均通过显著水平0.05检验,且本月NDVI与本月降雨量相关性高于本月气温(RNDVI降雨 =0.782),本月NDVI与上月气温相关性高于上月降雨量(RNDVI气温 =0.771);(4)在月尺度上,示范区植被生长对降雨量无滞后期,而对气温存在1个月的滞后期。      

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.     

Assessing soil salinity using WorldView-2 multispectral images in Timpaki,Crete, Greece

Salinization is one of the major soil degradation threats occurring worldwide. This study evaluates the feasibility of operational surface soil salinity mapping based on state-of-the-art Earth Observation (EO) products captured by sensors on-board WorldView-2 (WV2) and Landsat 8 satellites. The proposed methods are tested in Timpaki, south-central Crete,Greece, where brackish water irrigation puts soil health at risk of soil salinization. In all cases, EO products are calibrated against soil samples collected from bare soil locations. Results indicate a moderate correlation of observed EC_e values with the investigated remote sensing parameters. Regarding sensitivity to saline soil, the yellow band displays higher values. Comparison between methods used in the literature shows that those developed specifically for soil salinity, and especially index S5, perform better. The proposed ‘detection index’ and 3D PCA transformation methodology perform reasonably well in detecting areas with high EC_e values and provide a simple and effective operational alternative for saline topsoil detection and mapping.     

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.     

Late Pleistocene and Holocene Afromontane vegetation and headwater wetland dynamics within the Eastern Mau Forest,Kenya

The Mau Forest Complex is Kenya's largest fragment of Afromontane forest, providing critical ecosystem services, and has been subject to intense land use changes since colonial times. It forms the upper catchment of rivers that drain into major drainage networks, thus supporting the livelihoods of millions of Kenyans and providing important wildlife areas. We present the results of a sedimentological and palynological analysis of a Late Pleistocene–Holocene sediment record of Afromontane forest change from Nyabuiyabui wetland in the Eastern Mau Forest, a highland region that has received limited geological characterization and palaeoecological study. Sedimentology, pollen, charcoal, X-ray fluorescence and radiocarbon data record environmental and ecosystem change over the last ~16 000 cal a bp. The pollen record suggests Afromontane forests characterized the end of the Late Pleistocene to the Holocene with dominant taxa changing from Apodytes, Celtis, Dracaena, Hagenia and Podocarpus to Cordia, Croton, Ficus, Juniperus and Olea. The Late Holocene is characterized by a more open Afromontane forest with increased grass and herbaceous cover. Continuous Poaceae, Cyperaceae and Juncaceae vegetation currently cover the wetland and the water level has been decreasing over the recent past. Intensive agroforestry since the 1920s has reduced Afromontane forest cover as introduced taxa have increased (Pinus, Cupressus and Eucalyptus).     

不同覆盖措施对高寒地区剥离的草皮块堆放温湿度及成活的影响

重大工程建设会扰动高寒草地,法规要求扰动区草皮层应予以剥离,待工程建设后再用于恢复原生植被,当前对剥离草皮堆放成活的影响研究较少。试验设计遮阳网与穿孔膜两种覆盖条件,探讨分析其对剥离的草皮块堆放与铺植利用后土壤温湿度及草皮块返青覆盖度的影响,研究结果表明：遮阳网覆盖堆体较自然地表日均土壤温度显著降低,同时各深度层极大延长冻结期,降水对土壤水分的补充效应延后,并造成堆放期水分大量损失;穿孔膜覆盖堆体较自然地表提高了土壤温度,阻碍了降水对土壤水分的补充,并造成堆放后土壤吸持水能力降低。遮阳网覆盖的草皮块返青覆盖度显著高于穿孔膜覆盖的返青覆盖度,堆放期日平均土壤温度>0 ℃的堆放日数与草皮块返青覆盖度的线性拟合较好。工程建设中应尽量缩短堆放时长,采用透水透气类覆盖材料,增加土壤与空气热量交换,以维持更长的冻结期,并适时补充水分,提高草皮块铺植的恢复成效。     

The relationship between groundwater and natural vegetation in Qaidam Basin

To accurately evaluate ecological risks trigged by groundwater exploitation, it must be clarified the relationship between vegetation and groundwater. Based on remote sensing data sets MOD13Q1, groundwater table depth (WTD) and total dissolved solids (TDS), the relationship between groundwater and natural vegetation was analyzed statistically in the main plain areas of Qaidam Basin. The results indicate that natural vegetation is groundwater-dependent in areas where WTD is less than 5.5 m and TDS is less than 7.5 g/L. Aquatic vegetation, hygrophytic vegetation and hygrophytic saline-alkali tolerant vegetation are mainly distributed in areas with WTD <1.1 m. Salt-tolerant and mesophytic vegetation mainly occur in areas with WTD of 1.4-3.5 m, while the xerophytic vegetation isprimarily present in areas where WTD ranges from 1.4 m to 5.5 m. Natural vegetation does not necessarily depend on groundwater in areas with WTD >5.5 m. For natural vegetation, the most suitable water TDS is less than 1.5 g/L, the moderately suitable TDS is 1.5-5.0 g/L, the basically suitable TDS is 5.0-7.5 g/L, and the unsuitable TDS is more than 7.5 g/L.     

USING A COMBINED SLOPE HYDROLOGY/STABILITY MODEL TO IDENTIFY SUITABLE CONDITIONS FOR LANDSLIDE PREVENTION BY VEGETATION IN THE HUMID TROPICS

The susceptibility of cut slopes to landsliding can be reduced in certain circumstances by the establishment of a vegetation cover. However, the hydrological implications of allowing a cover to develop may offset the mechanical benefits of soil reinforcement by roots. The balance between hydrological and mechanical effects is critical on slopes which are susceptible to the development of an infiltration-induced transitory perched water table, a common cause of landslides in deep, tropical residual soils. This balance is likely to change both between slopes of different types as well as temporally on any given slope. The net effect of a vegetation cover must be predicted either before natural vegetation covers are allowed to encroach on bare slopes, or if engineers are considering the use of trees as a protective measure. This paper presents a method of calculating the impact of a vegetation cover on slope stability. Simulations carried out on a wide range of slope types suggest that where failure is most likely to be triggered by infiltration rather than ground water rise, large-scale vegetation covers may contribute to instability. Whether vegetation had a positive or negative impact on slope stability was controlled by the permeability of the soil matrix, whilst the magnitude of impact was controlled by the soil strength and the slope height.     

珠穆朗玛峰自然保护区植被变化分析

利用1981～2001 年美国NASA Pathfinder NOAA/NDVI 数据, 以1∶100 万植被图为基础, 结 合气温降水资料、DEM数据和2000 年人口空间化数据, 研究了珠穆朗玛峰自然保护区植被变化 空间格局和海拔梯度特征及其影响因素。结果表明: ①1981～2001 年珠峰自然保护区植被变化以 稳定为主, 有5.09%的区域发生严重退化, 13.34%的区域发生退化, 54.31%的区域保持稳定, 26.31%的区域变好以及0.95%的区域植被显著变好。退化和严重退化区域主要分布在保护区南 部, 国境沿线; 植被变好地区集中分布在保护区北部, 雅鲁藏布江南岸。稳定区域位于退化区域和 变好区域之间。植被退化区域主要分布在海拔2400m ~ 4000m 带上。②针叶林、针阔混交林和灌 丛构成了区域植被退化的主体。③从空间上看, 主要是气温变化对植被变化有影响。在海拔梯度 上, 气温变化和坡度共同影响植被变化。④在珠峰自然保护区内, 人类不合理的资源利用方式造 成了部分地区的植被退化。