A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

Assessment of heavy metals and their interrelationships with some physicochemical parameters in eco-efficient rivers of Himalayan region

Most precious and world famed Himalayan rivers like Ganga, Yamuna, and their tributaries are originated from Uttarakhand state of India. Over the years, increased industrial activities and urban growth along the rivers and lakes have resulted in increased load over the water bodies. In the present study, a comparison of characteristics of water quality with respect to heavy metals (Fe, Zn, Cu, and Pb) and their interrelationships with some physiological parameters during different seasons of year 2010 has been made in the water bodies flowing through the two geographical regions, namely Garhwal and Kumaon regions of the Himalayan State of India. All observed values of Pb, 02 observation of the Cu, and 59 observations of Fe are found exceed with the WHO standard for drinking water; 83 observations of Pb, 110 observations of Cu, and 59 observations of Fe are found exceed with the Bureau of Indian Standards. However, none of the observation of Zn is found exceeding with the standard limit. Cu shows the highest concentration 7.30 mg/l among all observations and also its higher concentration in Kumaon rivers. All the metals show negative correlation with dissolved oxygen and pH. Fe in river Yamuna system and Zn in Kumaon rivers show significant temporal variations at 90 % level of significance (LOS). However, no significant temporal difference of remaining metals is observed even at 95 % LOS. All metals except Fe in river Yamuna system show very significant variation in spatial distribution in different river systems at 95 % LOS.     

Assessment of water quality parameters of the Harike wetland in India, a Ramsar site, using IRS LISS IV satellite data

This study aims at the classification and water quality assessment of Harike wetland (Ramsar site) in India using satellite images from the Indian Remote Sensing satellite, Resourcesat (IRS P6). The Harike wetland is a converging zone of two rivers, Beas and Sutlej. The satellite images of IRS Linear Imaging Self Scanner (LISS) IV multispectral sensor with three bands (green, red, and near infrared (NIR)) and a spatial resolution of 5.8 m were classified using supervised image classification techniques. Field points for image classification and water sampling were recorded using a Garmin eTrex Global Positioning System. The water quality parameters assessed were dissolved oxygen, conductivity, pH, turbidity, total and suspended solids (SS), chemical oxygen demand, and Secchi disk transparency (SDT). Correlations were established between turbidity and SS, SS and SDT, and total solids and turbidity. Using reflectance values from the green, red, and NIR bands, we then plotted the water quality parameters with the mean digital number values from the satellite imagery. The NIR band correlated significantly with the water quality parameters, whereas, using SDT values, it was observed that the green and the red reflectance bands were able to distinguish the waters from the two rivers, which have different water qualities.     

Bioavailable phosphorus transport from a hillslope cropland of purple soil under natural and simulated rainfall

To further understand the mechanism of bioavailable total P (BAP) and bioavailable dissolved P (BDP) transport by overland and subsurface flow, we exposed a runoff plot 4.5 m long × 1.5 m wide × 0.6 m deep to simulated and natural rainfall in order to study the effects of rainfall type, rainfall intensity, and vegetation cover on BAP and BDP transport. The results showed that vegetation cover could alleviate the discharge of overland flow and sediment transport and enhance subsurface flow. BAP transport significantly increased with elevated rainfall intensity. Vegetation cover reduced the BAP transport by overland flow and increased it by subsurface flow. BDP transport showed no significant relationship with vegetation cover and rainfall type. The bioavailable particulate P (BPP) transport by overland flow contributed to no less than 90% by weight of total BAP, and the BPP transport by subsurface flow contributed to no less than 60% by weight of total BAP. Short-time heavy rainfall caused more BAP transport and accelerated non-point source pollution.     

Impacts of ecological water conveyance on groundwater dynamics and vegetation recovery in the lower reaches of the Tarim River in northwest China

The ecological water conveyance project (EWCP) in the lower reaches of the Tarim River provided a valuable opportunity to study hydro-ecological processes of desert riparian vegetation. Ecological effects of the EWCP were assessed at large spatial and temporal scales based on 13 years of monitoring data. This study analyzed the trends in hydrological processes and the ecological effects of the EWCP. The EWCP resulted in increased groundwater storage—expressed as a general rise in the groundwater table—and improved soil moisture conditions. The change of water conditions also directly affected vegetative cover and the phenology of herbs, trees, and shrubs. Vegetative cover of herbs was most closely correlated to groundwater depth at the last year-end (R?=?0.81), and trees and shrubs were most closely correlated to annual average groundwater depth (R?=?0.79 and 0.66, respectively). The Normalized Difference Vegetation Index (NDVI) responded to groundwater depth on a 1-year time lag. Although the EWCP improved the NDVI, the study area is still sparsely vegetated. The main limitation of the EWCP is that it can only preserve the survival of existing vegetation, but it does not effectively promote the reproduction and regeneration of natural vegetation.     

Spatial distribution and concentration of sulfur in relation to vegetation cover and soil properties on a reclaimed sulfur mine site (Southern Poland)

This work aims to assess the spatial distribution and concentration of sulfur in the topsoil layer and to determine the relationships between sulfur concentration, soil pH, soil electrical conductivity, and plant cover at the reforested site of the former sulfur mine (Southern Poland). Soil samples were collected from 0 to 20 cm (topsoil) from a total of 86 sampling points in a regular square grid with sides of 150 m. Plant cover was assayed in circular plots with an area of 100 m², divided into a woody plant layer and herbaceous plant layer. Soil properties such as particle size distribution, pH in KCl and H₂O, soil electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (N_T), and total sulfur (S_T) were determined. The degree of soil contamination with sulfur was assessed based on the guidelines of the Institute of Soil Science and Plant Cultivation (IUNG), Poland. The results indicate that remediation and application of lime were not fully effective in spatial variation, because 33 points with sulfur contamination above 500 mg kg^?1 were observed. These spots occurred irregularly in the topsoil horizons. This high sulfur concentration in the soil did not result in severe acidification (below 4.5) in all cases, most likely due to neutralization from the application of high doses of flotation lime. High vegetative cover occurred at some points with high soil sulfur concentrations, with two points having S concentration above 40,000 mg kg^?1 and tree cover about 60%. Numerous points with high soil EC above 1500 μS cm^?1 as well as limited vegetation and high soil sulfur concentrations, however, indicate that the reclamation to forest is still not completely successful.     

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

Assessing and monitoring semi-arid shrublands using object-based image analysis and multiple endmember spectral mixture analysis

Arid and semi-arid shrublands have significant biological and economical values and have been experiencing dramatic changes due to human activities. In California, California sage scrub (CSS) is one of the most endangered plant communities in the US and requires close monitoring in order to conserve this important biological resource. We investigate the utility of remote-sensing approaches—object-based image analysis applied to pansharpened QuickBird imagery (QBPS/OBIA) and multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery (SPOT/MESMA)—for estimating fractional cover of true shrub, subshrub, herb, and bare ground within CSS communities of southern California. We also explore the effectiveness of life-form cover maps for assessing CSS conditions. Overall and combined shrub cover (i.e., true shrub and subshrub) were estimated more accurately using QBPS/OBIA (mean absolute error or MAE, 8.9 %) than SPOT/MESMA (MAE, 11.4 %). Life-form cover from QBPS/OBIA at a 25?×?25 m grid cell size seems most desirable for assessing CSS because of its higher accuracy and spatial detail in cover estimates and amenability to extracting other vegetation information (e.g., size, shape, and density of shrub patches). Maps derived from SPOT/MESMA at a 50?×?50 m scale are effective for retrospective analysis of life-form cover change because their comparable accuracies to QBPS/OBIA and availability of SPOT archives data dating back to the mid-1980s. The framework in this study can be applied to other physiognomically comparable shrubland communities.     

Biological response to physical processes in the Indian Ocean sector of the Southern Ocean: a case study in the coastal and oceanic waters

The spatial variation of chlorophyll a (Chl a) and factors influencing the high Chl a were studied during austral summer based on the physical and biogeochemical parameters collected near the coastal waters of Antarctica in 2010 and a zonal section along 60°S in 2011. In the coastal waters, high Chl a (>3 mg m^?3) was observed near the upper layers (～15 m) between 53°30′E and 54°30′E. A comparatively higher mesozooplankton biomass (53.33 ml 100 m^?3) was also observed concordant with the elevated Chl a. Low saline water formed by melting of glacial ice and snow, as well as deep mixed-layer depth (60 m) due to strong wind (>11 ms^?1) could be the dominant factors for this biological response. In the open ocean, moderately high surface Chl a was observed (>0.6 mg m^?3) between 47°E and 50°E along with a Deep Chlorophyll Maximum of ～1 mg m^?3 present at 30–40 m depth. Melt water advected from the Antarctic continent could be the prime reason for this high Chl a. The mesozooplankton biomass (22.76 ml 100 m^?3) observed in the open ocean was comparatively lower than that in the coastal waters. Physical factors such as melting, advection of melt water from Antarctic continent, water masses and wind-induced vertical mixing may be the possible reasons that led to the increase in phytoplankton biomass (Chl a).     

Assessment of land cover changes & water quality changes in the Zayandehroud River Basin between 1997–2008

Water quality of rivers is strongly influenced by landscape characteristics of their watershed, including land use /cover types, and their spatial configuration. This research evaluates the effects of land cover changes on the water quality of the Zayandehroud River, which is the most important river in the center of Iran. The main goal of this study was to quantify the change in rangelands, forests, and bare lands in the Zayandehroud river basin, which suffered intense human interference, in a period of 11 years (1997–2008), and to evaluate how landscape patterns (including the number of patches, edge density, percentage of rangelands, forests, and bare lands) influence on the 14 water quality indices (including BOD5, EC, NO3, P, and TDS) measured in 10 stations along the river. Results showed that from 1997 to 2008, bare lands increased from 5.8 to 20 %, while rangelands decreased from 70 to 55 % in the whole basin. The results indicated that water quality was significantly correlated with both the proportions and configuration of rangeland and bare land areas. The total edge (TE) of rangeland area had positive effects on water quality, especially on BOD5 and EC. Percentage of landscape (PLAND) and largest patch index (LPI) metrics of rangeland had positive effect on decreasing nutrient (NO₃, PO₄). The results showed that water quality was more likely degraded when there was high edge density (ED) of bare lands. Results of this study also revealed that degradation of rangeland lead to the degradation of water quality. Finding of this study highlights the importance of rangeland conservation in water quality management at landscape scale.     

Monitoring the formation of structures and patterns during initial development of an artificial catchment

The objective of this paper is to present observations, results from monitoring measurements, and preliminary conclusions about the development of patterns and structures during the first 5 years of development of an artificial catchment starting from point zero. We discuss the high relevance of initial system traits and external events for the system development and draw conclusions for further research. These investigations as part of a Collaborative Research Center, aim to disentangle and understand the feedback mechanisms and interrelationships of processes and their co-development with spatial and temporal structures and patterns by studying an initial, probably less complex ecosystem. Therefore, intensive measurements were carried out in the catchment with regard to the development of surface structures, hydrological patterns, vegetation dynamics, water chemistry, and element budgets. During the first 5 years, considerable changes within the catchment were observed. Both internal and external factors could be identified as driving forces for the formation of structures and patterns in the artificial catchment. Initial structures formed by the construction process and initial substrate characteristics were decisive for the distribution and flow of water. External factors like episodic events triggered erosion and dissection during this initial phase, promoted by the low vegetation cover, and the unconsolidated sandy substrate. The transformation of the initial geosystem into areas with evolving terrestrial or aquatic characteristics and from a very episodic to a more permanent stream network and discharge, together with the observed vegetation dynamics increased site diversity and heterogeneity with respect to water and nutrient availability and transformation processes compared with the more homogenous conditions at point zero. The processes and feedback mechanisms in the initial development of a new landscape may deviate in rates, intensity, and dominance from those known from mature ecosystems. It is therefore crucial to understand these early phases of ecosystem development and to disentangle the increasingly complex interactions between the evolving terrestrial and aquatic, biotic, and abiotic compartments of the system. Long-term monitoring of initial ecosystems may provide important data and parameters on processes and the crucial role of spatial and temporal structures and patterns to solve these problems. Artificially created catchments could be a suitable tool to study these initial developments at the landscape scale under known, designed, and defined boundary conditions.     

Spatial and temporal variability of water quality in the coral reefs of Tayrona National Natural Park,Colombian Caribbean

Tayrona National Natural Park (TNNP) is a hotspot of coral reef biodiversity in the Colombian Caribbean, located between the city of Santa Marta (>455,000 inhabitants) and several smaller river mouths (Rio Piedras, Mendihuaca, Guachaca). The region also experiences a strong seasonal variation in physical parameters (temperature, salinity, wind, and water currents) due to alternating dry seasons with coastal upwelling and rainy seasons. However, the spatial and temporal effects on water quality parameters relevant for coral reef functioning have not been investigated. Therefore, inorganic nutrient, chlorophyll a, and particulate organic carbon (POC) concentrations along with biological O₂ demand (BOD), pH, and water clarity directly above local coral reefs (~10 m water depth) were monitored for 25 months in four bays along a distance gradient (12–20 km) to Santa Marta in the southwest and to the first river mouth (17–27 km) in the east. This is by far the most comprehensive coral reefs water quality dataset for the region. Findings revealed that particularly during non-upwelling, chlorophyll a and POC concentrations along with BOD significantly increased with decreasing distance to the rivers in the east, suggesting that the observed spatial water quality decline was triggered by riverine runoff and not by the countercurrent-located Santa Marta. Nitrate, nitrite, and chlorophyll a concentrations significantly increased during upwelling, while pH and water clarity decreased. Generally, water quality in TNNP was close to oligotrophic conditions adequate for coral reef growth during non-upwelling, but exceeded critical threshold values during upwelling and in relation to riverine discharge.     

A new approach for crop identification with wavelet variance and JM distance

This paper develops a new crop mapping method through combined utilization of both time and frequency information based on wavelet variance and Jeffries–Matusita (JM) distance (CIWJ for short). A two-dimensional wavelet spectrum was obtained from datasets of daily continuous vegetation indices through a continuous wavelet transform using the Mexican hat and the Morlet mother wavelets. The time-average wavelet variance (TAWV) and the scale-average wavelet variance (SAWV) were then calculated based on the wavelet spectrum of the Mexican hat and the Morlet wavelet, respectively. The class separability based on the JM distance was evaluated to discriminate the proper period or scale range applied. Finally, a procedure for criteria quantification was developed using the TAWV and SAWV as the major metrics, and the similarity between unclassified pixels and established land use/cover types was calculated. The proposed CIWJ method was applied to the middle Hexi Corridor in northwest China using 250-m 8-day composite moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) time series datasets in 2012. The CIWJ method was shown to be efficient in crop field mapping, with an overall accuracy of 83.6 % and kappa coefficient of 0.7009, assessed with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data. Compared with methods utilizing information on either frequency or time, the CIWJ method demonstrates tremendous potential for efficient crop mapping and for further applications. This method could be applied to either coarse or high spatial resolution images for agricultural crop identification, as well as other more general or specific land use classifications.     

Detecting new Buffel grass infestations in Australian arid lands: evaluation of methods using high-resolution multispectral imagery and aerial photography

We assess the feasibility of using airborne imagery for Buffel grass detection in Australian arid lands and evaluate four commonly used image classification techniques (visual estimate, manual digitisation, unsupervised classification and normalised difference vegetation index (NDVI) thresholding) for their suitability to this purpose. Colour digital aerial photography captured at approximately 5 cm of ground sample distance (GSD) and four-band (visible–near-infrared) multispectral imagery (25 cm GSD) were acquired (14 February 2012) across overlapping subsets of our study site. In the field, Buffel grass projected cover estimates were collected for quadrates (10 m diameter), which were subsequently used to evaluate the four image classification techniques. Buffel grass was found to be widespread throughout our study site; it was particularly prevalent in riparian land systems and alluvial plains. On hill slopes, Buffel grass was often present in depressions, valleys and crevices of rock outcrops, but the spread appeared to be dependent on soil type and vegetation communities. Visual cover estimates performed best (r ² 0.39), and pixel-based classifiers (unsupervised classification and NDVI thresholding) performed worst (r ² 0.21). Manual digitising consistently underrepresented Buffel grass cover compared with field- and image-based visual cover estimates; we did not find the labours of digitising rewarding. Our recommendation for regional documentation of new infestation of Buffel grass is to acquire ultra-high-resolution aerial photography and have a trained observer score cover against visual standards and use the scored sites to interpolate density across the region.     

Vegetation response to hydrologic and geomorphic factors in an arid region of the Baja California Peninsula

Remotely sensed imageries were used to analyze the response of desert vegetation to physiographic factors and accumulated precipitation in drier and wetter years within a region of >16,500 km² sampled with 5,000 random pixels of 30 m. Vegetation development was indexed by the annual maximum values for greenness (SAVI) and canopy water content (NDII). Precipitation was interpolated from the 0.25° grid of the Tropical Rainfall Measurement Mission satellite-based estimates, showing a regional average of ～55 mm in the wetter year. The vegetation indices were only weakly related to total precipitation, often in a negative sense. Terrain factors that most often affected the vegetation indices, in multiple regression models, were Topographic Wetness Index, elevation, and slope gradient; these often had different signs for SAVI and for NDII. Models for NDII on intrusive igneous rocks gave better results than on extrusive igneous rocks. The strongest patterns in vegetation development were the contrast among Pacific coast, Cordillera, and Gulf coast subregions and the generally stronger results for NDII than SAVI.     

Monitoring and validating the temporal dynamics of interday streamflow from two upland head micro-watersheds with different vegetative conditions during dry periods of the growing season in the Bohemian Massif,Czech Republic

At present, dynamic land use, climate change, and growing needs for fresh water are increasing the demand on the ecosystem effects of forest vegetation. Mountainous areas are at the forefront of scientific interest in European forest ecology and forest hydrology. Although uplands cover a significant area of the Czech Republic and other countries and are often covered with forest formations, they do not receive an appropriate amount of attention. Therefore, two experimental upland head micro-watersheds in the Bohemian Massif were selected for study because they display similar natural conditions, but different vegetative conditions (forest versus meadow). During the 2011 growing season, short-term streamflow measurements were carried out at the discharge profiles of both catchments and were evaluated in relation to climatic data (rainfall and temperature). The basic premise was that the streamflow in a forested catchment must exhibit different temporal dynamics compared to that in treeless areas and that these differences can be attributed to the effects of woody vegetation. These conclusions were drawn from measurements performed during dry periods lasting several days. A decreasing streamflow trend during the day part of the day (0900–1900 hours) was observed in both localities. The decrease reached approx. 44 % of the initial morning streamflow (0.24 dm³ s^?1 day^?1) in the treeless catchment and approx. 20 % (0.19 dm³ s^?1 day^?1) in the forested catchment. At night (1900–0900 hours), the streamflow in the forested catchment increased back to its initial level, whereas the streamflow in the treeless catchment stagnated or slowly decreased. We attribute these differences to the ecosystem effects of woody vegetation and its capacity to control water loss during the day. This type of vegetation can also function as a water source for the hydrographic network during the night.     

The effects of biotic and abiotic factors on the spatial heterogeneity of alpine grassland vegetation at a small scale on the Qinghai–Tibet Plateau (QTP), China

Understanding the complex effects of biotic and abiotic factors on the composition of vegetation is very important for developing and implementing strategies for promoting sustainable grassland development. The vegetation–disturbance–environment relationship was examined in degraded alpine grasslands in the headwater areas of three rivers on the Qinghai–Tibet Plateau in this study. The investigated hypotheses were that (1) the heterogeneity of the vegetation of the alpine grassland is due to a combination of biotic and abiotic factors and that (2) at a small scale, biotic factors are more important for the distribution of alpine vegetation. On this basis, four transects were set along altitudinal gradients from 3,770 to 3,890 m on a sunny slope, and four parallel transects were set along altitudinal gradients on a shady slope in alpine grasslands in Guoluo Prefecture of Qinghai Province, China. It was found that biological disturbances were the major forces driving the spatial heterogeneity of the alpine grassland vegetation and abiotic factors were of secondary importance. Heavy grazing and intensive rat activity resulted in increases in unpalatable and poisonous weeds and decreased fine forages in the form of sedges, forbs, and grasses in the vegetation composition. Habitat degradation associated with biological disturbances significantly affected the spatial variation of the alpine grassland vegetation, i.e., more pioneer plants of poisonous or unpalatable weed species, such as Ligularia virgaurea and Euphorbia fischeriana, were found in bare patches. Environmental/abiotic factors were less important than biological disturbances in affecting the spatial distribution of the alpine grassland vegetation at a small scale. It was concluded that rat control and light grazing should be applied first in implementing restoration strategies. The primary vegetation in lightly grazed and less rat-damaged sites should be regarded as a reference for devising vegetation restoration measures in alpine pastoral regions.     

Monitoring and assessing of landscape heterogeneity at different scales

In numerous studies, spatial and spectral aggregations of pixel information using average values from imaging spectrometer data are suggested to derive spectral indices and the subsequent vegetation parameters that are derived from these. Currently, there are very few empirical studies that use hyperspectral data, to support the hypothesis for deriving land surface variables from different spectral and spatial scales. In the study at hand, for the first time ever, investigations were carried out on fundamental scaling issues using specific experimental test flights with a hyperspectral sensor to investigate how vegetation patterns change as an effect of (1) different spatial resolutions, (2) different spectral resolutions, (3) different spatial and spectral resolutions as well as (4) different spatial and spectral resolutions of originally recorded hyperspectral image data compared to spatial and spectral up- and downscaled image data. For these experiments, the hyperspectral sensor AISA-EAGLE/HAWK (DUAL) was mounted on an aircraft to collect spectral signatures over a very short time sequence of a particular day. In the first experiment, reflectance measurements were collected at three different spatial resolutions ranging from 1 to 3 m over a 2-h period in 1 day. In the second experiment, different spectral image data and different additional spatial data were collected over a 1-h period on a particular day from the same test area. The differently recorded hyperspectral data were then spatially and spectrally rescaled to synthesize different up- and down-rescaled images. The normalised difference vegetation index (NDVI) was determined from all image data. The NDVI heterogeneity of all images was compared based on methods of variography. The results showed that (a) the spatial NDVI patterns of up- and downscaled data do not correspond with the un-scaled image data, (b) only small differences were found between NDVI patterns determined from data recorded and resampled at different spectral resolutions and (c) the overall conclusion from the tests carried out is that the spatial resolution is more important in determining heterogeneity by means of NDVI than the depth of the spectral data. The implications behind these findings are that we need to exercise caution when interpreting and combining spatial structures and spectral indices derived from satellite images with differently recorded geometric resolutions.