植被覆盖状况影响中国地表气温变化的观测事实

利用NOAA/AVHRR归一化植被指数（NDVI）及观测气温与再分析地表气温的差值（Observation Minus Reanalysis, OMR）分析了植被覆盖状况对中国地表气温变化的影响.结果表明,地表气温OMR趋势值与NDVI在空间上呈现出显著的负相关关系,植被覆盖状况差（NDVI小于0.1）的区域地表升温较为显著,气温OMR趋势值超过0.2℃/10a,而植被覆盖度高（NDVI大于0.5）的区域气温OMR趋势值则变化不大,甚至出现降温.气温OMR趋势值对植被的季节变化还有着敏感的响应.不同区域植被覆盖状况的差异可能导致中国地表气温变化对全球变暖的响应不同,预测中国未来气候变化需要考虑植被覆盖状况及其动态变化的影响.     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau(1981―2006):Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.     

Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.     

应用MODIS数据监测千岛湖流域植被覆盖动态(2001-2013年)

流域植被覆盖状况对于水源地生态环境保护具有重要的指示作用.当前的水质目标管理不仅要着眼于湖库水质参数控制,更应该从整个流域的角度维系生态平衡.在此背景下,依托长时间序列MODIS遥感数据对千岛湖流域2001-2013年植被覆盖状况进行监测,采用最小二乘法趋势分析和Mann-Kendall显著性检验方法分析了千岛湖流域植被的空间分布特征、时间变化特征与长期变化趋势.研究表明该方法能够有效地监测流域植被覆盖的时空动态变化:1)从空间分布上来看,千岛湖流域植被覆盖状况整体较好,但同时也发现受人为干扰较大的地域如河、湖附近的城镇建设用地、农业用地以及园地,其NDVI值明显低于自然林地;2)从时间变化特征上看,2001-2013年千岛湖流域植被年际NDVI在0.69~0.73之间波动,且近年来有增长趋势,年内季节性NDVI动态分析表明高时间分辨率的MODIS数据能够用来区分常绿植被与落叶植被的物候特征,以分析不同植被类型对流域氮、磷流失的风险差异;3)从变化趋势上看,2001-2013年植被覆盖状况改善的区域远大于退化的区域,其中改善区域约占流域面积的55.90%,呈现出一定退化状态的区域约占29.60%(严重退化区域仅占3.97%),而相对稳定不变区域约占14.51%.经与气温与降水等气候因子进行相关性分析表明,植被NDVI与气温呈显著正相关,而降水则不敏感,说明气温是研究区植被生长的主导气候因子.同时发现,人类活动对局部植被变化影响较大.研究结果可为流域水资源与生态环境保护提供空间数据支撑.     

Long‐term hydrological response to reforestation in a large watershed in southeastern China

The long‐term hydrological response to reforestation is critical to regional water management, especially in areas where large‐scale reforestation has been practiced. In this study, we investigated the long‐term hydrological response to reforestation in the 579 km² basin in southeastern China through ground‐based monitoring of water yield, sedimentation, vegetation cover and climate in the basin. The vegetation dynamics were also examined by remote sensing data (MSS, Landsat and AVHRR NDVI). We found that forest cover increased 23% or 13 593 ha from 1975 to 2002. Meanwhile, annual water yield decreased 86–88 mm from 1971–1983 (i.e. pre‐reforestation) to 1984–2009 (i.e. post‐reforestation). These decreases were significant statistically according to both regression and double mass analyses. Time series analysis demonstrated that there was a clear decline in annual sediment yield and an increase in annual evapotranspiration (ET) over the period from 1971 to 2009. We concluded that reforestation could significantly reduce annual water yield and sediment yield in the basin because of the forest cover change and forest growth. This conclusion is consistent with findings from widely paired‐watershed studies and literatures published on the impact of reforestation in large watersheds. Our results also have important strategic implications and provide insight into more sustainable forest management practices for the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981–2006): Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981–2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981–1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990–1998; (3) vegetation cover declined rapidly during 1999–2001; and (4) vegetation cover increased rapidly during 2002–2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology. Supported by the National Natural Science Foundation of China (Grant No. 40671019) and the Knowledge Innovation Project of the Institute of Geographical Sciences and Natural Resources Research of Chinese Academy of Sciences     

Spatiotemporal Characteristics of Evapotranspiration and Driving Factors in the Bosten Lake Watershed,China

The Bosten Lake watershed investigated in this study has seen significant land cover and climate change. The spatiotemporal relationship between evapotranspiration (ET) and environmental factors remain unclear. In this study, trend analysis and correlation methods are applied to analyze the spatiotemporal characteristics of ET and the relationship between ET and its driving factors using remotely sensed ET data and measured climate data between 2001 and 2018. During the study period, high values of ET primarily occurr in the wetlands of the plain area and the mid‐elevation mountain areas. The ET values show a significantly increasing trend in the different vegetation types due to climate change and other factors. The ET change trend in the study area is in the range of ?13.4 to ≈35.9 mm per year; the desert area exhibits a significant decrease and most of the mountain areas show a significantly increasing trend. ET is significantly correlated with land surface temperature, normalized difference vegetation index (NDVI), and solar radiation. The dominant factor affecting ET is NDVI, accounting for 15.2% of the study area. The results of this study highlight the need for appropriate land‐use strategies for managing water resources in arid land ecosystems.     

The response of vegetation cover and dune activity to rainfall,drought and fire observed by multitemporal satellite imagery

The stable longitudinal dunes in the northern Simpson Desert, Australia, were observed in satellite imagery to become more active after vegetation cover was reduced by fire and drought. Subsequent rainfall events also resulted in significant vegetation regrowth and dune stabilization. These switches between more active and stable conditions have not been previously described in the largely vegetated dune fields of central Australia. The observations, made on 12 dune sites, relied on high spatial resolution satellite imagery to observe dune crest activity, and seasonal Landsat fractional cover imagery to observe vegetation cover changes. The non-photosynthetic vegetation (NPV) component of the fractional vegetation cover images revealed significant changes in hummock grass cover on the dunes between 1988 and 2018, with a positive relationship with the three-year cumulative rainfall, disrupted by two periods of patchy burning. Only those sites that had burnt became active, and only after vegetation cover had remained low (NPV < 16%) during the ‘Millennium Drought’. There is no threshold in vegetation cover, below which dune crests become active, but active dune features require four-years of low NPV cover (< 16%) to develop. The large rainfall event that ended the drought increased NPV cover, stabilizing the dunes. Similar hummock grass covered dunes are present across large areas of the arid zone, and are likely to respond in similar ways, given that fire and drought are common occurrences in Australia. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.     

The dynamic of vegetation coverage and its response to climate factors in Inner Mongolia, China

Normalized Difference Vegetation Index (NDVI) is widely recognized as a good indicator of vegetation productivity. Diagnosing the NDVI trend and understanding climatic factors influences on NDVI can predict the productivity changes under different climatic scenarios. This paper examined NDVI dynamic and its response to climate factors during a 10 year period (1998–2008) in Inner Mongolia. The main findings are as follows: (1) The NDVI multi-scale characters can be revealed well by wavelet transform, and the average NDVI and the NDVI amplitude show a gradually decreased trend from northeast to southwest in Inner Mongolia during the past 10 years, furthermore, this trend is consistent with the heat and water distribution caused by latitude difference in north–south direction and Asia monsoon effect in east–west direction. (2) The relation between NDVI and temperature is the most close, followed by precipitation, sunshine hours and relative humidity. Different vegetation cover types show different strengths in correlation between NDVI and climate variables with the correlation values decreasing from forest, meadow steppe to desert steppe in whole. (3) The precipitation and temperature have the same change cycle, both nearly 290 days in the 20 selected stations. The NDVI has the same change cycle with the precipitation and temperature or either 10 days earlier or later than precipitation and temperature, which supports the significant correlation between NDVI and its climatic factors from a new perspective. The nearly 290 days change cycle implies that the vegetation growth cycle is nearly 10 months and there are no obvious differences change cycles in different vegetations. (4) Vegetation dynamic is significantly correlated to the temperature and precipitation at the time scale of 10, 20, 40, 80, 160, and 320-day, respectively, and the S3 scale (i.e., the time scale of 80-day), nearly 3 months (one season), is most significant and suitable for evaluating the vegetation dynamic to climatic factors.     

Assessing vegetation dynamics and their relationships with climatic variability in northern China

In this study, the vegetation dynamics and their correlations with climate variability in northern China were evaluated based on the normalized difference vegetation index (NDVI) and meteorological datasets from 1982 to 2006. The NDVI showed that vegetation cover had a tiny increasing trend for whole study area in the past 25 years. However, the interannual changes of NDVI were different in each season. The part of spring and autumn NDVI values increased significantly, while the summer NDVI increased no significantly. And the interannual variations of the NDVI showed obvious spatial differentiations. The annual max NDVI increased were mainly distributed in most areas of grassland and farmland, whereas the annual max NDVI decreased were mainly distributed in forest areas. The annual NDVI and temperature had more important relationships. Thus, as compared to precipitation, the correlation between NDVI with temperature was stronger than the precipitation in northern China. NDVI and climatic variables were different in each season. The NDVI trends exhibited a close correspondence to climatological variations in region and season. In Addition, human activities also had profound effect to the NDVI trends in some regions. All these findings will make humans know more about the knowledge of the natural forces that influence vegetation change and supply a scientific basic resource to for the environmental management in northern China.     

Vegetation pattern of Istanbul from the Landsat data and the relationship with meteorological parameters

This paper discusses the preliminary results of a study on the vegetation pattern and its relationship with meteorological parameters in and around Istanbul. The study covers an area of over 6800 km² consisting of urban and suburban centers, and uses the visible and near-infrared bands of Landsat. The spatial variation of the Normalized Difference Vegetation Index (NDVI) and meteorological parameters such as sensible heat flux, momentum flux, relative humidity, moist static energy, rainfall rate and temperature have been investigated based on observations in ten stations in the European (Thracian) and Anatolian parts of Istanbul. NDVI values have been evaluated from the Landsat data for a single day, viz. 24 October 1986, using ERDAS in ten different classes. The simultaneous spatial variations of sensible heat and momentum fluxes have been computed from the wind and temperature profiles using the Monin-Obukhov similarity theory. The static energy variations are based on the surface meteorological observations. There is very good correlation between NDVI and rainfall rate. Good correlation also exists between: NDVI and relative humidity; NDVI, sensible heat flux and relative humidity; NDVI, momentum flux and emissivity; and NDVI, sensible heat flux and emissivity. The study suggests that the momentum flux has only marginal impact on NDVI. Due to rapid urbanization, the coastal belt is characterized by reduced NDVI compared to the interior areas, suggesting that thermodynamic discontinuities considerably influence the vegetation pattern. This study is useful for the investigation of small-scale circulation models, especially in urban and suburban areas where differential heating leads to the formation of heat islands. In the long run, such studies on a global scale are vital to gain accurate, timely information on the distribution of vegetation on the earth’s surface. This may lead to an understanding of how changes in land cover affect phenomena as diverse as the atmospheric CO² concentrations, the hydrological cycle and the energy balance at the surface-atmosphere interface.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics

Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field-based measures can quantify species composition; however, the extent to which these different measures are duplicative or complementary is important to understand when planning monitoring programmes with limited resources. In this study, we analysed riparian vegetation growth in the delta of the Colorado River in response to an experimental pulse flow. Our goal was to compare ground-based measurements of vegetation structure and composition with satellite-based Landsat radiometric variables, such as the normalized difference vegetation index (NDVI). We made this comparison in 21 transects following the delivery of 131.8 million cubic meters (mcm) of water in the stream channel during the spring of 2014 as a pulse flow and 38.4 mcm as base flows. Vegetation cover increased 14% and NDVI increased 0.02 (15%) by October 2015, and both variables returned to pre-pulse flow values in October 2016. Observed changes in vegetation structure and composition did not persist after the second year. The highest increase in vegetation cover in October 2014 and October 2015 resulted from species that could respond rapidly to additional water such as reeds (Arundo donax and Phragmites australis), cattail (Typha domingensis), and herbaceous plants. Dominant shrubs, saltcedar (Tamarix spp.) and arrowweed (Pluchea sericea), both indicative of nonrestored habitats showed variable increases in cover, and native trees (Salicaceae family) presented low increases (1%). The strong NDVI–vegetation cover relationship indicates that NDVI is appropriate to detect changes at the riparian corridor scale but needs to be complemented with ground data to determine the contributions by different species to the observed trends.     

Vegetation and topographic controls on sediment deposition and storage on gully beds in a degraded mountain area

Active gully systems developed on highly weathered or loose parent material are an important source of runoff and sediment production in degraded areas. However, a decrease of land pressure may lead to a return of a partial vegetation cover, whereby gully beds are preferred recolonization spots. Although the current knowledge on the role of vegetation on reducing sediment production on slopes is well developed, few studies exist on the significance of restoring sediment transport pathways on the total sediment budget of degraded mountainous catchments. This study in the Ecuadorian Andes evaluates the potential of vegetation to stabilize active gully systems by trapping and retaining eroded sediment in the gully bed, and analyses the significance of vegetation restoration in the gully bed in reducing sediment export from degraded catchments. Field measurements on 138 gully segments located in 13 ephemeral steep gullies with different ground vegetation cover indicate that gully bed vegetation is the most important factor in promoting short‐term (1–15 years) sediment deposition and gully stabilization. In well‐vegetated gully systems ( ≥ 30% of ground vegetation cover), 0.035 m³ m^–1 of sediment is deposited yearly in the gully bed. Almost 50 per cent of the observed variance in sediment deposition volumes can be explained by the mean ground vegetation cover of the gully bed. The presence of vegetation in gully beds gives rise to the formation of vegetated buffer zones, which enhance short‐term sediment trapping even in active gully systems in mountainous environments. Vegetation buffer zones are shown to modify the connectivity of sediment fluxes, as they reduce the transport efficiency of gully systems. First calculations on data on sediment deposition patterns in our study area show that gully bed deposition in response to gully bed revegetation can represent more than 25 per cent of the volume of sediment generated within the catchment. Our findings indicate that relatively small changes in landscape connectivity have the potential to create strong (positive) feedback loops between erosion and vegetation dynamics. Copyright © 2009 John Wiley & Sons, Ltd.     

The relative roles of climate variations and human activities in vegetation change in North China

Using SPOT-VEGETATION Normal Difference Vegetation Index (SPOT/NDVI) data from 1998 to 2011 and climate data obtained from 223 weather stations in or near North China, vegetation variation characteristics within North China were analyzed. Vegetation variation characteristics under the influence of climate variations and human activities were distinguished through a residual analysis. Based on the results of that analysis, the relative roles of climate variations and human activities in vegetation variation were calculated. The results showed that NDVI observed by remote sensing (SPOT/NDVI) increased from 1998 to 2011. The relative roles of climate variations and human activities in vegetation increase were 30.82% and 69.18%, respectively, indicating that human activities played a major role. And observed NDVI showed an increasing trend for different land cover types overall. While NDVI increase in shrub was mainly caused by climate variations, NDVI increases in forest, grassland, farmland, deserts and urban were all primarily caused by human activities. For areas with increasing vegetation, as identified by remote sensing observations in North China, the relative roles of climate variations and human activities in vegetation change were calculated at 14.85% and 85.15% respectively, again indicating that human activities played an important role in vegetation increase. For areas of decreasing vegetation, as identified by remote sensing observations in North China, the relative roles of climate variations and human activities in vegetation change were calculated at 87.72% and 12.28% respectively, indicating that climate variations had large negative effects on vegetation condition. In addition, the relative roles of climate variations and human activities on vegetation variation have obvious spatial differences in North China. Human activities played a positive role in vegetation growth in North China. However, we cannot ignore the function of human destruction on vegetation variation in some areas.     

Influences of catchment characteristics on nitrogen concentration in largely forested streams during the base flow period

Based on measured stream nitrogen concentrations at outlets of 12 small sub‐areas (1·3–54·7 km²) in a largely forested catchment during the base flow period, we investigated the influences of discharges and different catchment characteristics on stream nitrogen concentration. Our field surveys were carried out during the 11‐month's period from April 2001 to February 2002 and the correlations between nitrogen concentrations and catchment characteristics were studied. The results showed that the vegetation cover was strongly correlated to total nitrogen (TN) and nitrate + nitrite ? nitrogen (NO_x‐N) concentrations. That is, the TN and NO_x‐N concentrations had positive correlations with mean normalized difference vegetation cover index (NDVI) of each sub‐area during dormant seasons (mean NDVI < 0 · 70) and had negative correlations during the growing season (mean NDVI ≥ 0 . 70). The significance of catchment characteristics to TN and NO_x‐N concentrations was ranked as vegetation cover > soil > topography > land use, and the best models can account for 55–64% of the variance of TN and NO_x‐N concentrations. Copyright © 2006 John Wiley & Sons, Ltd.     

Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery

The age of past lava flows is crucial information for evaluating the hazards and risks posed by effusive volcanoes, but traditional dating methods are expensive and time‐consuming. This study proposes an alternative statistical dating method based on remote sensing observations of tropical volcanoes by exploiting the relationship between lava flow age and vegetation cover. First, the factors controlling vegetation density on lava flows, represented by the normalized difference vegetation index (NDVI), were investigated. These factors were then integrated into pixel‐based multi‐variable regression models of lava flow age to derive lava flow age maps. The method was tested at a pixel scale on three tropical African volcanoes with considerable recent effusive activity: Nyamuragira (Democratic Republic of Congo), Mt Cameroon (Cameroon) and Karthala (the Comoros). Due to different climatic and topographic conditions, the parameters of the spatial modeling are volcano‐specific. Validation suggests that the obtained statistical models are robust and can thus be applied for estimating the age of unmodified undated lava flow surfaces for these volcanoes. When the models are applied to fully vegetated lava flows, the results should be interpreted with caution due to the saturation of NDVI. In order to improve the accuracy of the models, when available, spatial data on temperature and precipitation should be included to directly represent climatic variation. Copyright © 2017 John Wiley & Sons, Ltd.     

Rock crevices determine woody and herbaceous plant cover in the karst critical zone

The study of the critical zones(CZs) of the Earth link the composition and function of aboveground vegetation with the characteristics of the rock layers, providing a new way to study how the unique rock and soil conditions in karst regions affect the aboveground vegetation. Based on survey results of the rocks, soils and vegetation in the dolomite and limestone distribution areas in the karst area of central Guizhou, it was found that woody plant cover increases linearly with the number of cracks with a width of more than 1 mm, while the cover of herbaceous plants shows the opposite trend(p0.01). The dolomite distribution area is characterized by undeveloped crevices, and the thickness of the soil layer is generally less than 20 cm, which is suitable for the distribution of herbaceous plants with shallow roots. Due to the development of crevices in the limestone distribution area, the soil is deeply distributed through the crevices for the deep roots of trees, which leads to a diversified species composition and a complicated structure in the aboveground vegetation. Based on moderate resolution imaging spectroradiometer(MODIS) remote sensing data from 2001 to 2010, the normalized differentiated vegetation index(NDVI) and annual net primary productivity(NPP) results for each phase of a 16-day interval further indicate that the NDVI of the limestone distribution area is significantly higher than that in the dolomite distribution area, but the average annual NPP is the opposite. The results of this paper indicate that in karst CZs, the lithology determines the structure and distribution of the soil, which further determines the cover of woody and herbaceous plants in the aboveground vegetation. Although the amount of soil in the limestone area may be less than that in the dolomite area, the developed crevice structure is more suitable for the growth of trees with deep roots, and the vegetation activity is strong. At present, the treatment of rocky desertification in karst regions needs to fully consider the rock-soilvegetation-air interactions in karst CZs and propose vegetation restoration measures suitable for different lithologies.     

Variability and trends in the annual snow‐cover cycle in Northern Hemisphere land areas, 1972–2000

This study investigated variability and trends in the annual snow‐cover cycle in regions covering high‐latitude and high‐elevation land areas in the Northern Hemisphere. The annual snow‐cover cycle was examined with respect to the week of the last‐observed snow cover in spring (WLS), the week of the first‐observed snow cover in autumn (WFS), and the duration of the snow‐free period (DSF). The analysis used a 29‐year time‐series (1972–2000) of weekly, visible‐band satellite observations of Northern Hemisphere snow cover from NOAA with corrections applied by D. Robinson of Rutgers University Climate Laboratory. Substantial interannual variability was observed in WLS, WFS and DSF (standard deviations of 0·8–1·1, 0·7–0·9 and 1·0–1·4 weeks, respectively), which is related directly to interannual variability in snow‐cover area in the regions and time periods of snow‐cover transition. Over the nearly three‐decade study period, WLS shifted earlier by 3–5 days/decade as determined by linear regression analysis. The observed shifts in the annual snow‐cover cycle underlie a significant trend toward a longer annual snow‐free period. The DSF increased by 5–6 days/decade over the study period, primarily as a result of earlier snow cover disappearance in spring. The observed trends are consistent with reported trends in the timing and length of the active growing season as determined from satellite observations of vegetation greenness and the atmospheric CO₂ record. Copyright © 2002 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.