Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.     

Remote sensing provides a progressive record of vegetation change in northern KwaZulu-Natal,South Africa,from 1944 to 2005

Remote sensing, together with geographic information systems (GISs), provide a powerful tool for monitoring environmental processes. Aerial and satellite photographs enable the analysis of an entire landscape and, using multi-temporal sets of photographs, one is able to follow processes over time. In our study, we used multi-temporal sets of aerial photographs, taken between 1944 and 2005, to observe the phenomenon of woody plant encroachment in four neighbouring study sites in northern KwaZulu-Natal, South Africa. We also analysed rainfall and temperature trends. Woody plant encroachment was evident in all sites. We suggest possible drivers behind the bush encroachment; in particular, climatic trends. However, encroachment did not relate directly to rainfall and temperature trends. We also speculate on the effects of herbivory and fire, as well as rising atmospheric CO₂ concentrations and its effect on C₃ and C₄ plants. We suggest that increasing atmospheric CO₂ concentrations could be the overriding driver of woody plant encroachment in our study area, with other drivers, such as rainfall, temperature, fire, herbivory, and land use, playing a modifying role.     

Understanding burn severity sensing in Arctic tundra: exploring vegetation indices,suboptimal assessment timing and the impact of increasing pixel size

Little is known about how satellite imagery can be used to describe burn severity in tundra landscapes. The Anaktuvuk River Fire (ARF) in 2007 burned over 1000 km² of tundra on the North Slope of Alaska, creating a mosaic of small (1 m²) to large (>100 m²) patches that differed in burn severity. The ARF scar provided us with an ideal landscape to determine if a single-date spectral vegetation index can be used once vegetation recovery began and to independently determine how pixel size influences burn severity assessment. We determine and explore the sensitivity of several commonly used vegetation indices to variation in burn severity across the ARF scar and the influence of pixel size on the assessment and classification of tundra burn severity. We conducted field surveys of spectral reflectance at the peak of the first growing season post-fire (extended assessment period) at 18 field sites that ranged from high to low burn severity. In comparing single-date indices, we found that the two-band enhanced vegetation index (EVI2) was highly correlated with normalized burn ratio (NBR) and better distinguished among three burn severity classes than both the NBR and the normalized difference vegetation index (NDVI). We also show clear evidence that shortwave infrared (SWIR) reflectivity does not vary as a function of burn severity. By comparing a Quickbird scene (2.4 m pixels) to simulated 30 and 250 m pixel scenes, we are able to confirm that while the moderate spatial resolution of the Landsat Thematic Mapper (TM) sensor (30 m) is sufficient for mapping tundra burn severity, the coarser resolution of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (250 m) is not well matched to the fine scale of spatial heterogeneity in the ARF burn scar.     

Remote sensing of vegetation dynamics in West Africa

Vegetation dynamics and the lives of millions of people in West Africa are closely interlinked with each other. The high annual variability of the phenological cycle considerably affects the agricultural population with late rainfalls and droughts, often resulting in serious food crises. On the other hand, the rapidly growing population has a great need for space due to expanding cities and a low agricultural efficiency. This situation, together with a changing climate, has had a strong impact on vegetation dynamics in West Africa and will play a major role in the future. The dynamic nature of vegetation in the region has attracted a lot of remote-sensing-based research in the past 30 years and has lead to heated discussions. This review article gives a comprehensive overview of the studies on remotely sensed vegetation dynamics in West Africa. After an introduction to the specific situation for vegetation dynamics in West Africa, the applied sensors and their suitability for the region are outlined. Research on the assessment of different plant parameters, on phenological metrics as well as on the monitoring of agricultural areas is outlined and discussed. Furthermore, a major part of this review is dedicated to the analyses undertaken to assess vegetation trends in West Africa over the past 30 years and their potential human and climatic causes. Finally, identified research gaps and challenges for future studies are discussed.     

Remote sensing of biomass of salt marsh vegetation in France

Abstract

Spectral data (gathered using a hand-held radiometer) and harvest data were collected from four salt marsh vegetation types in Brittany, France, to develop equations predicting live aerial biomass from spectral measurements. Remote sensing estimates of biomass of the general salt marsh community (GSM) and of Spartina alternifiora can be obtained throughout the growing season if separate biomass prediction equations are formulated for different species mixtures (for the GSM) and for different canopy types (for S. alternifiora). Results suggest that remote sensing will not be useful for predicting Halimione portulacoides biomass, but can be used to estimate Puccinellia maritima biomass early in the growing season.     

Remote sensing of vegetation change near Inco's Sudbury mining complexes

Abstract

Using LANDSAT data for different years between 1973 and 1983, vegetation change maps were produced for two areas in the vicinity of Inco's mining complexes. Field checking showed that for more than 80 per cent of the sites inspected, causes for the vegetation changes recorded on the maps could be determined. The system used provides a cost-effective method of monitoring major vegetation changes over a number of years, but it is not suitable for monitoring slow, progressive, vegetation changes over short periods.     

Remote sensing of land use and vegetation for mesoscale hydrological studies

In this paper, methods for mapping land use changes and vegetation parameters using remote sensing data are presentedin the context of hydrological studies. In the first part, a land use and land cover classification system (RUB-LUCS: Ruhr University Bochum - Land Use and Land Cover Classification System) is developed for providing distributed information for hydrological modelling and for detection of distributed land use changes. Applying this system to Landsat data, land use time series is created for hydrological modelling of effects of man-made changes in the Sauer River Basin. In the second part, equations are established for estimating leaf area indices using vegetation indices calculated from remote sensing data and a two stream approximation model for estimating leaf area indices is applied to the Sauer River Basin. Combining the two approaches, a method has been found for calculating leaf area indices for mesoscale river basins using remote sensing data.     

Remote sensing of savanna vegetation changes in Eastern Zambia 1972-1989

The use of the historical Landsat Multi-Spectral Scanner (MSS) archive to monitor changes in savanna vegetation between 1972 and 1989 in the South Luangwa National Park region, Eastern Zambia, was investigated. Land-cover types in the region were mapped and major changes in land cover from 1972 to 1989 were detected from MSS data. Woody canopy cover, which provides a quantitative measure of woodland structure, was estimated for woodland vegetation from MSS data using a linear relationship between woody canopy cover and red reflectance. The canopy cover changes estimated from MSS data agreed with those measured from multitemporal aerial photographs (r=0.94). Woody canopy cover changed significantly in the region from 1972 to 1989 and revealed strong spatial patterns of deforestation in Colophospermum mopane woodland on alluvial soils and vegetation regrowth of valley miombo vegetation and riverine woodland. This information on the spatial patterns of canopy cover change from 1972 to 1989 suggests certain criteria that any causative process must satisfy, and it provides a baseline for the National Park and Wildlife Services to manage the natural resources in the region. The canopy cover estimated from MSS data also provides an important input to biophysical and climatic process models for estimating the impact of vegetation structure on vegetation and climate processes.     

Remote sensing for detection and monitoring of vegetation affected by oil spills

This study is aimed at demonstrating the application of vegetation spectral techniques for detection and monitoring of the impact of oil spills on vegetation. Vegetation spectral reflectance from Landsat 8 data were used in the calculation of five vegetation indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), adjusted resistant vegetation index 2 (ARVI2), green-infrared index (G-NIR) and green-shortwave infrared (G-SWIR) from the spill sites (SS) and non-spill sites (NSS) in 2013 (pre-oil spill), 2014 (oil spill date) and 2015 (post-oil spill) for statistical comparison. The result shows that NDVI, SAVI, ARVI2, G-NIR and G-SWIR indicated a certain level of significant difference between vegetation condition at the SS and the NSS in December 2013. In December 2014 vegetation conditions indicated higher level of significant difference between the vegetation at the SS and NSS as follows where NDVI, SAVI and ARVI2 with p-value 0.005, G-NIR – p-value 0.01 and G-SWIR p-value 0.05. Similarly, in January 2015 a very significant difference with p-value <0.005. Three indices NDVI, ARVI2 and G-NIR indicated highly significant difference in vegetation conditions with p-value <0.005 between December 2013 and December 2014 at the same sites. Post-spill analysis shows that NDVI and ARVI2 indicated low level of significance difference p-value <0.05 suggesting subtle change in vegetation conditions between December 2014 and January 2015. This technique may help with the real time detection, response and monitoring of oil spills from pipelines for mitigation of pollution at the affected sites in mangrove forests.     

Remote sensing of vegetation water content from equivalent water thickness using satellite imagery

Vegetation water content (VWC) is one of the most important parameters for the successful retrieval of soil moisture content from microwave data. Normalized Difference Infrared Index (NDII) is a widely-used index to remotely sense Equivalent Water Thickness (EWT) of leaves and canopies; however, the amount of water in the foliage is a small part of total VWC. Sites of corn (Zea mays), soybean (Glycine max), and deciduous hardwood woodlands were sampled to estimate EWT and VWC during the Soil Moisture Experiment 2005 (SMEX05) near Ames, Iowa, USA. Using a time series of Landsat 5 Thematic Mapper, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Wide Field Sensor (AWiFS) imagery, NDII was related to EWT with R² of 0.85; there were no significant differences among land-cover types. Furthermore, EWT was linearly related to VWC with R² of 0.87 for corn and 0.48 for soybeans, with a significantly larger slope for corn. The 2005 land-cover classification product from the USDA National Agricultural Statistics Service had an overall accuracy of 92% and was used to spatially distribute VWC over the landscape. SMEX05 VWC versus NDII regressions were compared with the regressions from the Soil Moisture Experiment 2002 (SMEX02), which was conducted in the same study area. No significant difference was found between years for corn (P = 0.13), whereas there was a significant difference for soybean (P = 0.04). Allometric relationships relate the size of one part of a plant to the sizes of other parts, and may be the result from the requirements of structural support or material transport. Relationships between NDII and VWC are indirect, NDII is related to canopy EWT, which in turn is allometrically related to VWC.     

Remote sensing the orographic effects of dry-hot valley on vegetation distribution in the southeast Tibetan Plateau

ABSTRACT

Mountains in the southeast Tibetan Plateau (TP) often intercept and precipitate abundant monsoon-transported vapours, but some deep valleys of this region are likely subjected to heavy water stress possibly related to orographic effects. Understanding the orographic effects of these dry-hot valleys (DHV) on vegetation distribution is crucial to project local ecological response to global warming. In the study, we used multiple satellite observations with limited in-situ records to investigate the links between vegetation cover and geomorphology in the southeast TP. We designed two types of transects to distinguish altitudinal properties of heat and vegetation between the DHV and non-DHV areas with satellite-retrieved enhanced vegetation index and land surface temperature (LST). Our results showed that the DHVs are characterized by the seemingly ‘abnormal’ decreasing of vegetation density from intermediate elevation simultaneously towards both ridge and valley. The significant increase in LST lapse rate with valley depth (1.8 × 10^?3°C km^?1 m^?1, p < 0.01) suggested the positive role of local valley wind system in the DHV development. Satellite observations revealed that there are, respectively, about 530, 420, and 300 km of DHVs developed in the Nujiang, Lancangjiang, and upper Yangtze rivers, and the DHVs are mostly deeper than 1600 m. Current global warming may lead to the altitudinal expansion of DHV dry and hot effects on local ecosystems, which should be carefully accounted in local ecosystem conservation and management.     

Remote sensing of salt marsh vegetation in the first four proposed Thematic Mapper bands

Abstract

The potential for using data collected in the first four bands of the proposed thematic mapper for monitoring intertidal salt marsh vegetation is assessed, using ground spectral data collected with a portable multiband radiometer. Results from a field study in Chichester Harbour, Southern England, show that certain species can be separated using transformations of these data. The estimation of above ground biomass from ground spectral data was not possible for Spartina × townsendii agg., due to the combined effects of mixtures of different substrate types and mixtures of live and dead vegetation within the field of view of the radiometer. However, biomass estimation was possible for both Zostera marina L. and Fucus vesiculosus L. The relationships between biomass and bidirectional reflectance for these species followed a similar pattern, despite Fucus vesiculosus having carotenoids rather than chlorophylls as the dominant leaf pigments.     

Remote sensing characterization of benthic habitats and submerged vegetation biomass in Los Roques Archipelago National Park,Venezuela

Remote sensing is a useful tool for characterizing submerged aquatic vegetation and other benthic habitats in shallow water areas with clear water transparency. In the present study, the visible bands of the Thematic Mapper (TM) sensor aboard Landsat 7 satellite were used in a supervised classification of benthic habitats and for the assessment of submerged vegetation biomass in Los Roques Archipelago National Park, Venezuela. Initially, the TM visible bands were log‐transformed and linearly combined to reduce the depth‐dependent variance in the bottom reflectance signal. The supervised classification had an overall accuracy of 74%. Eight bottom types could be spectrally separated: sand, dispersed communities over sand (shallow and deep), dense seagrass, dispersed seagrass meadows over sand, reef communities, mixed vegetation over muddy bottom, and lagoons. Regression analyses were performed between the depth‐invariant band combinations and field samples of vegetation biomass. The regression using the TM band 2 and 3 combination accounted for 64% of the variability of submerged vegetation biomass. According to these estimates, seagrass meadows with biomass between 64–96?g?m^?2 and 96–128?g?m^?2 predominate in the Los Roques Archipelago National Park.     

Remote sensing of temperature variations around major power plants as point sources of heat

Variations in land surface temperature (LST) around major point sources of heat were studied using the Tampa Bay region as a case study. LST in the Tampa Bay region, FL, USA, was retrieved from Landsat Thematic Mapper (TM) 6 and Enhanced Thematic Mapper Plus (ETM+) 6 high-gain thermal bands. The TM6 image data were obtained on 29 January (winter season) and 3 April 2007 (spring season). The ETM+6 data were obtained on 11 April 2007 (spring season). Spatial profiles of LST around four major fossil-fuelled power plants (FFPPs) were considered in this study. Temperatures were found to be highest at power plants and to decay to an average background temperature within 1.2–2.0 km from the FFPPs. The average background temperatures obtained in January and April were 17°C and 29°C, respectively. Results indicate that LST in close proximity to the FFPPs could be up to 10°C hotter than the surrounding areas. These findings suggest that FFPPs are significant heat sources and populations living within 1–2 km from an FFPP might be at significantly higher risk of heat-related illnesses and mortality.     

Remote sensing of coastlines: detection,extraction and monitoring

This paper reviews the current status of the use of remote sensing for the detection, extraction and monitoring of coastlines. The review takes the US system as an example. However, the issues at hand can be applied to any other part of the world. Visual interpretation of airborne remote sensing data is still widely and popularly used for coastal delineation. However, a variety of remote sensing data and techniques are available to detect, extract and monitor the coastline. The developed techniques have reached a level of maturity such that they are applied in operational settings.     

Remote sensing of cloud cover in the Arctic region from AVHRR data during the ARTIST experiment

In this paper we present a cloud detection algorithm developed for the Arctic region using Advanced Very High Resolution Radiometer (AVHRR) data. Our approach is a simplified version of the Ebert method to discriminate between clouds, ice and open water in the Arctic Sea. The algorithm is tuned to work on an AVHRR scene typical of the winter to spring transition period. The algorithm has been applied to 1 month (154 scenes) of NOAA-14 AVHRR images (from 16 March to 15 April 1998) covering the region of the Arctic Sea near the Svalbard Islands. The cloud detection results are analysed using various check procedures. The algorithm's pixel classification performance was verified by a satellite image expert. The misclassified pixels were digitalized on the image and counted by the expert in order to quantify the algorithm's accuracy. The cloud classification results are quite accurate: 70% of the images (109) have an error less than 5% and only 11% of the image results have an error greater than 10%. The method's performance is also tested against independent cloud and ice observations obtained, respectively, from the Ny-Ålesund meteorological base and from the Special Sensor Microwave/Imager (SSM/I) dataset. The comparison with these independent sources of data confirms the algorithm's good performance.     

Remote sensing and GIS for detecting changes in the aquatic vegetation of a rehabilitated lake

Remote sensing and geographical information system (GIS) methods combined with ground estimations were used to assess the effects of rehabilitation on the aquatic vegetation of a shallow, eutrophic lake in Finland. Aerial photograph interpretation was used to study the distribution of aquatic vegetation before (1953, 1996) and after (2001) rehabilitation in 1997. A digital elevation model was derived to relate the change in the aquatic vegetation to water depth. In addition, changes in the biomass of the most abundant species of the lake, Common Club-rush (Schoenoplectus lacustris), were studied by means of a regression analysis relating the ground estimations to the reflectance values (R ²=0.889, p@lt;0.001). The results indicated that the objective of the rehabilitation--to stop the overgrowth process--has at least temporarily been achieved. After rehabilitation the most noticeable change had taken place in the area covered by floating-leaved vegetation. Greater proportional changes in the aquatic vegetation areas had occurred in the deep rather than in the shallow areas. A decrease in biomass of Common Club-rush was estimated to be 30% due to rehabilitation. The use of remote sensing and GIS provided valuable information on temporal and spatial changes in the aquatic vegetation, and the methods could be applied more extensively for lake monitoring purposes.     

Remote sensing of vegetation principles,techniques, and applications,edited by Hamlyn G. Jones and Robin A. Vaughn

In South African grasslands, rangeland management is strongly related to land tenure. Communal farms are reported to exhibit less desirable vegetation conditions for livestock than commercial farms. Time series of high spatial and temporal resolution imagery may be useful for improved evaluation of these rangelands as they provide information at a spatial scale similar to the typical scale of field assessments and may thus overcome the limited spatio-temporal representativeness of field measurements. A time series of 13 RapidEye images over one growing season (2010–2011) was used to explore spectral differences between and within two management systems (commercial vs. communal). Isomap ordination was applied to map continuous spectral dissimilarities of sample plots. Using regression with simultaneous autoregressive models (SAR), dissimilarities were subsequently related to ecological variables of plant and soil, including indicators for grazing effects. The largest differences were found between sample plots of communal and commercial farms. Vegetation attributes were significantly related to dissimilarities in reflectance, both from the growing season and the dormant period. However, these relationships did not suggest vegetation degradation on communal farms. They further suggest that a management-related pattern of grazing disturbance in the summer months led to spectral differences between farms but could have impaired the detailed characterization of spectral dissimilarities related to differences in vegetation composition.     

Manipulating subjective realism and its impact on presence: Preliminary results on feasibility and neuroanatomical correlates

The feeling of presence has been shown to be an important concept in several clinical applications of virtual reality. Among the factors influencing presence, realism factors have been examined extensively from the angle of objective realism. Objective realism has been manipulated by altering numerous technological characteristics such as pictorial quality, texture and shading, or by adding more sensory information (i.e., smell, touch). Much less studied is the subjective (or perceived) realism, the focus of the two pilot studies reported in this article. In Study 1, subjective realism was manipulated in order to assess the impact on the feeling of presence. Method: Presence was measured in 31 adults after two immersions in virtual reality. Participants were immersed in a neutral/irrelevant virtual environment and subsequently subjected to the experimental manipulation. Participants in the experimental condition were falsely led to believe that they were immersed live in real time in a “real” room with a “real” mouse in a cage. In the control condition, participants believed they were immersed in a replica of the nearby room. All participants were actually immersed in the exact same virtual environment. Results: A manipulation check revealed that 80% of the participants believed in the deception. A 2 Times by 2 Conditions repeated measure ANOVA revealed that leading people to believe they were seeing a real environment digitized live in virtual reality increased their feeling of presence compared to the control condition. In Study 2, the same experimental design was used but with simultaneous functional magnetic resonance imaging (fMRI) in order to assess brain areas potentially related to the feeling of presence. fMRI data from five participants were subjected to a within subject fixed effect analysis to verify differences between the experimental immersion (higher presence) and the control immersion (lower presence). Results revealed a statistically significant difference in left and right parahippocampus areas. Conclusion: Results are discussed according to layers of presence and consciousness and the meaning given to experiences occurring in virtual reality. Some suggestions are formulated to target core presence and extended presence.