Microwave Remote Sensing in Forestry

Microwave Remote Sensing in Forestry BACKGROUND: Microwave remote sensing at wavelengths ranging from 1 cm to 1 m has gained a lot of importance over the past decade for a wide range of scientific applications with the availability of active radar imaging systems. Its potential in spatial applications has been scientifically established in various sectors like forestry, agriculture, land use and land cover, geology and hydrology. A variety of applications have been carried out world over using microwave data like discrimination of crop types, crop condition monitoring, soil moisture retrieval, delineation of forest openings, estimation of forest above ground biomass, forest mapping; forest structure and fire scar mapping, geological mapping, monitoring wetlands and snow cover, sea ice identification, coastal windfield measurement, wave slope measurement, ship detection, shoreline detection, substrate mapping, slick detection and general vegetation mapping (Kasischke et al., 1997). There is an emerging interest on microwave remote sensing, as microwave sensors can image a surface with very fine resolution of a few meters to coarse resolution of a few kilometers. They provide imagery to a given resolution independently of altitude, limited only by the transmitter power available. Fundamental parameters like polarization and look angle can be varied to optimize the system for a specific application. SAR imaging is independent of solar illumination as the system provides its own source of illumination. It can operate independently of weather conditions if sufficiently long wavelengths are chosen. It operates in a band of electromagnetic spectrum different from the bands used by visible and infrared (IR) imageries. Microwave applications in Forestry Applications of microwave remote sensing in forestry have also been reported during the recent past. Recent reviews on the application of radar in forestry show that SAR systems have a good capability in discriminating various types of (tropical) forest cover using multi-temporal and multi-frequency SAR data (Vander Sanden, 1997; Varekamp, 2001; Quinones, 2002; Sgrenzaroli, 2004). These studies showed that the biomass dependence of radar backscatter varies as a function of radar wavelength, polarization and incidence angle. Also recent studies have demonstrated that synthetic aperture radar (SAR) can be used to estimate above-ground standing biomass. To date, these studies have relied on extensive ground-truth measurements to construct relationships between biomass and SAR backscatter (Steininger, 1996; Rignot et al., 1997). Many studies demonstrated the use of Synthetic Aperture Radar (SAR) remote sensing to retrieve biophysical characteristics from forest targets (Richards, 1990). Although radar backscatter from forest is influenced by their structural properties (Imhoff, 1995), earlier studies derived useful relationships between backscattering coefficients and the above-ground biomass (Baker et., 1994; Le Toan et al., 1992; Dobson et el., 1992; Imhoff; 1995). These relationships may provide a method of monitoring forest ecosystems which play such a vital role in carbon storage and NPP. Microwave remote sensing has the advantage of all weather capability coverage overcoming the persistent problem of cloud cover in satellite images like in optical data. Optical remote sensing is being used very successfully in various applications related to earth resources studies and monitoring of the environment. However, optical remote sensing is not suitable for all atmospheric conditions. It cannot penetrate through clouds and haze. In many areas of the world, the frequent cloud conditions often restrain the acquisition of high-quality remotely sensed data by optical sensors. Thus, radar data has become the only feasible way of acquiring remotely sensed data within a given time framework because the radar systems can collect Earth feature data irrespective of weather or light conditions. Due to this unique feature of radar data compared with optical sensor data, the radar data have been used extensively in many fields, including forest-cover identification and mapping, discrimi nation of forest compartments and forest types, estimation of forest stand parameters and monitoring of forests. In areas where vegetation cover is dense, it visually covers the underlying formation and it is very difficult to detect structural limiting the use of optical sensors. Radar however, is sensitive enough to topographic variation that it is able to discern the structural expression reflected in the tree top canopy, and therefore the structure may be clearly defined on the radar imagery. Based on this background, the current thesis work has been carried out to explore the potential of microwave data in addressing core areas of tropical forestry viz., vegetation classification, above ground biomass estimation etc., and to provide the users/researchers a meaningful data base of SAR applications in tropical forestry, specifically over the India region. Research questions: Which SAR wavelength/frequency band is appropriate for vegetation classification in tropical forests? To what extent above ground biomass can be measured in tropical forests? Which frequency band and polarization are suitable for above ground biomass estimation? Is there any enhancement in vegetation classification with polarimetric / interferometric data than stand alone amplitude data? Research hypothesis: Based on the previous studies and earlier mentioned research questions, we understand that the backscatter increases with the increase in above ground biomass and depends on wavelength bands, polarizations used and on the study area, topographic variations and species composition. So, the present study attempts to derive the application potential of airborne and space borne SAR data in the quantification of the forest resources in tropical regions like India, both as a complementary and supplementary role to optical datasets. Different techniques such as Regression analysis, multi-sensor fusion, texture measures and interferometric coherence characterize different biomass ranges of the test sites and classification of major land cover classes. This study would facilitate scope for future research in tropical regions to explore the potentials of SAR data in land cover classification and above ground biomass estimation using the polarimetric and interferometric techniques. OBJECTIVES: Based on this background, the present study aims at the following objectives: Vegetation type classification using polarimetric and interferometric SAR data. Forest above-ground biomass estimation using multi-frequency SAR data and ground inventoried data. Vegetation classification is necessary to understand the diversity of species in a given area which gives above ground biomass with measured parameters. Hence, vegetation classification enhances the estimation of the above ground biomass. Forest biomass is a key parameter in understanding the carbon cycle and determining rates of carbon storage, both of which are large uncertainties for forest ecosystems. Accurate knowledge of biophysical parameters of the ecosystems is essential to develop an understanding of the ecosystem and their interactions, to provide input models of ecosystem and global processes, to test these models and to monitor changes in ecosystem dynamics and processes over time. Thus, it is a useful measure for assessing changes in forest structure, comparing structural and functional attributes of forest ecosystems across a wide range of environmental conditions. Knowing the spatial distribution of forest biomass is important as the knowledge of biomass is required for calculating the sources and sinks of carbon that result from converting a forest to cleared land and vice versa, to know the spatial distribution of biomass which enables measurement of change through time. Field sampling is the most followed conventional method for vegetation type classification. The identification of different species in field yields good results in the estimation of the above ground biomass. It is very time consuming, expensive and very complicated. With the use of multiple sensors, varied data collection and interpretation techniques, remote sensing is a versatile tool that can provide data about the surface of the earth to suit any need (Reene et al, 2001). Remote sensing approach for vegetation classification is cost effective and also time effective. Though the identification of the tree species is possible only from the aerial imagery, major forest types can be identified from the airborne and the spaceborne remote sensing data. Visual image interpretation provides a feasible means of vegetation classification in forests. The image characteristics of shape, size, pattern, shadow, tone and texture are used by interpreters in tree species identification. Phenological correlations are useful in tree species identification. Changes in the appearance of trees in different seasons of the year some times enable discrimination of species that are indistinguishable on single dates. The use of multi-temporal remote sensing data enabl es the mapping of the different forest types. SAR has shown its potential for classifying and monitoring geophysical parameters both locally and globally. Excellent works were carried out on the classification using several approaches such as polarimetric data decomposition (Lee et al., 1998), knowledge based approaches considering the theoretical backscatter modeling and experimental observations ( Ramson and Sun , 1994) ; Backscatter model-related inversion approaches ( Kurvonen et al., 1999), neural networks and data fusion approaches ( Chen et al., 1996). Dong et al. (2001) have shown that the classification accuracy of 95% for the vegetation classes could be achieved through the segmentation and classification of the SAR data using Gaussian Markov Random Field Model (GMRF). Many methods have been employed for classification of polarimetric SAR data, based on the maximum likelihood (ML) (Lee et al. 1994), artificial neural network (NN) (Chen et al. 1996, Ito and Omatu, 1998), support vector machines (SVMs) (Fukuda et al. 2002), fuzzy method (Chen et al. 2003, Du and Lee 1996), or other approaches (Kong et al. 1988, Lee and Hoppel 1992, van Zyl and Burnette 1992, Cloude and Pottier 1997, Lee et al. 1999, Alberqa 2004) Among these methods, the ML classifier (Lee et al. 1994) can be employed for obtaining accurate classification results, but it is based on the assumption of the complex Wishart distribution of the covariance matrix. Assessing the total aboveground biomass of forests (biomass density when expressed as dry weight per unit area at a particular time) is a useful way of quantifying the amount of resource available for all traditional uses. It either gives the quantity of total biomass directly or the quantity by each component (e.g., leaves, branches, and bole) because their biomass tends to vary systematically with the total biomass. However, biomass of each component varies with total biomass by forest type, such as natural or planted forests and closed or open forests. For example, leaves contribute about 3-5% and merchantable bole is about 60% of the total aboveground biomass of closed forests. Many researchers have developed various methods based on field inventory and remote sensing approaches for the estimation of above ground biomass (Kira and Ogawa, 1971). Traditionally, field-measured approach is considered as the most accurate source for above-ground biomass estimation. It has been converted to volume, or biomass, using allometric equations that are based on standard field measurements (tree height and diameter at breast height). Different approaches, based on field measurement (Brown et al. 1989, Brown and Iverson 1992, Schroeder et al.. 1997, Houghton et al., 2001, Brown, 2002); remote sensing (Tiwari 1994, Roy and Ravan 1996, Tomppo et al., 2002, Foody et al., 2003, Santos et al., 2003, Zheng et al., 2004, Lu, 2005); and GIS (Brown and Gaston 1995) have been applied for AGB estimation. Traditional techniques based on field measurement are the most accurate ways for collecting biomass data. A sufficient number of field measurements is a prerequisite for developing AGB estimation models and for evaluating the AGB estimation results. However, these approaches are often time consuming, labour intensive, and difficult to implement, especially in remote areas and are generally limited to 10-year intervals. Also, they cannot provide the spatial distribution of biomass in large areas. For the above reasons, the perspectives of using remote sensing techniques to estimate forest biomass have gained interest. Remote sensing data available at different scales, from local to global, and from various sources, optical to microwave are expected to provide information that could be related indirectly, and in different manners, to biomass information. The possibility that aboveground forest biomass might be determined from space is a promising alternative to ground-based methods (Hese et al., 2005). The advantages of remotely sensed data, such as in repetivity of data collection, synoptic view, digital format that allows fast processing of large quantities of data, and the high correlations between spectral bands and vegetation parameters, make it the primary source for large area AGB estimation, especially in areas of difficult access. Therefore, remote sensing-based AGB estimation has increasingly attracted scientific interest. In general, AGB can be estimated using remotely sensed data with different approaches, such as multiple regression analysis, K nearest-neighbour, and neural network (Roy and Ravan 1996, Nelson et al. 2000a, Steininger 2000, Foody et al. 2003, Zheng et al. 2004), and indirectly estimated from canopy parameters, such as crown diameter, which are first derived from remotely sensed data using multiple regression analysis or different canopy reflectance models (Wu and Strahler 1994, Woodcock et al. 1997, Phua and Saito 2003, Popescu et al. 2003). Spectral signatures or vegetation indices are often used for AGB estimation in optical remote sensing. Many vegetation indices have been developed and applied to biophysical parameter studies (Anderson and Hanson 1992, Anderson et al. 1993, Eastwood et al. 1997, Lu et al. 2004, Mutanga and Skidmore 2004). Vegetation indices have been recommended to remove variability caused by canopy geometry, soil background, sun view angles, and atmospheric conditions when measuring biophysical properties (Elvidge and Chen 1995, Blackburn and Steele 1999). Radar remote sensing has potential to provide information on above ground biomass. The information content of SAR data in terms of the retrieval of biomass parameters will be assessed based on an understanding of the underlying scattering mechanisms, which in turn are derived from observations and modeling results. For this purpose, an analysis of data acquired by multiple frequency, incidence and polarisation systems and by interferometric systems is carried out. It has been proved that the sensitivity to biomass parameters differ strongly at different frequencies, polarisations and incidence angles. In general, long wavelength SAR backscatter (P and L band) is more sensitive to forest biomass than shorter wavelength C-band backscatter and the relationships saturate at certain biomass levels ( Imhoff 1995b). The strength of the relationships and the saturation levels are dependent on the type of forest being analysed (Ferrazoli et al. 1997). The saturation levels for the estimation of above ground biomass depend on the wavelengths (i.e. different bands, such as C, L, P), polarization (such as HV and VV), and the characteristics of vegetation stand structure and ground conditions. C-band can measure forestry biomass up to app. 50 tons/ha, L-band can measure up to 100 tons/ha and P-band can measure up to 200 tons/ha (Floyd et al., 1998). The combination of multiple channels and polarizations provides greater advantage for estimating total biomass (Harry Stern, 1998). RELEVANCE OF THE STUDY: The present study is the part of Radar Imaging satellite Joint Experiment Programme (RISAT-JEP) for forestry applications undertaken by Forestry and Ecology Division of National Remote Sensing Centre (NRSC), as a pilot campaign with specific objectives of above ground biomass estimation and vegetation type classification using airborne DLR (German Aerospace Center) carrying ESAR (Experimental Synthetic Aperture Radar) data for Rajpipla (Gujarat) study site and space borne ENVISAT (Environmental Satellite) carrying Advanced Synthetic Aperture Radar (ASAR) data for three test sites viz., Rajpipla (Gujarat), Dandeli (Karnataka) and Bilaspur (Chattisgarh), India. SCOPE OF THE STUDY: The specific objectives of the present study are above ground biomass estimation and vegetation type classification using airborne DLR (German Aerospace Center) carrying ESAR (Experimental Synthetic Aperture Radar) data for Rajpipla (Gujarat) study site and space borne ENVISAT (Environmental Satellite) carrying Advanced Synthetic Aperture Radar (ASAR) data; ALOS (Advanced Land Observing Satellite) carrying Phased Array L-band Synthetic Aperture Radar (PALSAR) for three test sites viz., Rajpipla (Gujarat), Dandeli (Karnataka) and Bilaspur (Chattisgarh), India. Different techniques such as Regression analysis, multi-sensor fusion, texture measures and interferometric coherence were used to characterize different biomass ranges of the test sites and to classify the major land cover classes using spaceborne C-band ENVISAT-ASAR data and L-band ALOS- PALSAR data. Polarimetric signatures, polarimetric decompositions, multi-sensor fusion techniques etc. were used for the classification of different vegetation types in the Rajpipla study area using the airborne DLR-ESAR data. The study has its uniqueness and gains importance in the application potential of SAR interferometry over tropical regions like India, both in terms of an alternate/substitute to optical data sets due to persisting cloud cover and to the lack of availability of any earlier scientific work over the study region. This study is useful for the applications of to be launched Radar Imaging Satellite (RISAT) in 2010. The study has amply demonstrated the application potential of airborne and space borne SAR data in the quantification of the forest resources in tropical regions like India, both as a complementary and supplementary role to optical datasets. The study would facilitate future research in tropical regions to explore the potentials of SAR data in land cover classification and above ground biomass estimation using the polarimetric and interferometric techniques. LITERATURE SURVEY: During the last decade, many potential applications of SAR in different frequency bands have been studied for forestry applications using data acquired by both airborne and space-borne systems. Various techniques like Polarimetry, Interferometry and Polarimetric-Interferometry enhanced the use of SAR data in forestry applications. The backscatter from vegetation is used to infer information about amplitude data for forest cover mapping and estimation of above ground biomass in regenerating forests. Use of SAR polarimetric data delineated vegetation classes within the forest and also enhanced the capability in estimating the above ground biomass. The use of repeat pass interferometric data enables to calculate the forest stand height and also used for the land cover classification. The emerging Pol-InSAR technique is used to derive the three dimensional forest structures. Forest cover maps were prepared for the boreal, temperate and tropical forests using SAR data. Forest was separated from non-forest regions using multi-temporal C-band ERS SAR data on the test sites of United Kingdom, Poland and Finland (Quegan et al., 2000). The study applied a threshold value to separate forest from other classes. Tropical rainforest of Borneo was mapped from SIR-B data of different incidence angles (Ford and Casey, 1988). Different vegetation covers along with wetlands and clear-cut areas were distinguished. Forest cover mapping was done with JERS-1 SAR data on the coastal regions of Gabon (Simard et al., 2000). The study used decision tree method utilizing both radar amplitude and texture information. Forest cover map was prepared for Southern Chittagong using JERS-1 SAR data (Rahman and Sumantyo, 2007) and the study separated forest, degraded forest, shrubs, coastal plantations, agriculture, shrimp-farms, urban and water. Although radar backscatter from forest is influenced by their structural properties (Imhoff, 1995a), many studies have demonstrated useful relationships between backscattering coefficients and the areal density of above-ground biomass within particular types of forest (Baker et., 1994; Le Toan et al., 1992; Dobson et al., 1992; Imhof et al; 1995b). Many airborne and spaceborne SAR systems have been used to carry out a large amount of experiments for investigating the forest ecosystems. The airborne systems, such as the NASA/JPL AIRSAR, DLR-ESAR, etc., operating at P, L and C band, has been flown over many forest sites (Zebker et al., 1991; Le Toan et al, 1992; Beaudoin et al., 1994; Rignot et al.; 1994; Skriver et al., 1994; Ranson et al., 1996). The experiments of the Canadian CV-580, as well as the European airborne system, mainly operating at C and X band also have been carried out in North America and Europe (Drieman et al., 1989; Hoekman, 1990). Spaceborne SAR is being used from regional to global monitoring in a periodic basis. The spaceborne systems, such as the Seasat SAR, SIR-B, SIR-C/X-SAR and ERS-1, ERS-2, ENVISAT-ASAR, RADARSAT etc., were used for investigations of boreal, temperature and sub-tropical forestry test sites (Ford et al., 1988; Dobson et al., 1992; Ranson et al., 1995; Stofan et al., 1995; Rignotet al., 1995). These experiments and studies have shown that radar is sensitive to forest structural parameters such as diameter at breast height (dbh) and tree mean height including above-ground biomass (Dobson et al., 1992; Pulliainen et al., 1994; Skriver et al., 1994; Ferrazzoli et al., 1995; Ranson et al., 1996). Earlier studies has shown the potential of radar data in estimating AGB (Hussin et al. 1991, Ranson and Sun 1994, Dobson et al. 1995, Rignot et al. 1995, Saatchi and Moghaddam 1995, Foody et al. 1997, Harrell et al. 1997, Ranson et al. 1997, Luckman et al. 1997, 1998, Pairman et al. 1999, Imhoff et al. 2000, Kuplich et al. 2000, Castel et al. 2002, Sun et al. 2002, Santos et al. 2003, Treuhaft et al. 2004). Kasischke et al. (1997) reviewed radar data for ecological applications, including AGB estimation. Lucas et al. (2004) and Kasischke et al. (2004) reviewed SAR data for AGB estimation in tropical forests and temperate and boreal forests, respectively. Different wavelength radar data have their own characteristics in relating to forest stand parameters. Backscatter in P and L bands is highly correlated with major forest parameters, such as tree age, tree height, DBH, basal area, and AGB (Leckie 1998). In particular, SAR L-band data have proven to be valuable for AGB estimation (Sad er 1987, Luckman et al. 1997, Kurvonen et al. 1999, Sun et al. 2002). However, low or negligible correlations were found between SAR C-Band backscatter and AGB (Le Toan et al. 1992). Beaudoin et al. (1994) found that the HH return was related to both trunk and crown biomass, and the VV and HV returns were linked to crown biomass. Harrell et al. (1997) evaluated four techniques for AGB estimation in pine stands using SIR C- and L-Band multi-polarization radar data and found that the L-Band HH polarization data were the critical elements in AGB estimation. Kuplich et al. (2000) used L-band JERS-1/SAR data for AGB estimation of regenerating forests and concluded that these data had the potential to estimate AGB for young, regenerating forests. Sun et al. (2002) found that multi-polarization L-Band SAR data were useful for AGB estimation of forest stands in mountainous areas. Castel et al. (2002) identified the significant relationships between the backscatter coefficient of JERS- 1/SAR data and the stand biomass of a pine plantation. The study observed the improvement in AGB estimation results for young stands, compared to estimation for old stands. Santos et al. (2002) used JERS-1 SAR data to analyse the relationships between backscatter signals and biomass of forest and savanna formations. This study concluded that forest structural-physiognomic characteristics and the radars volume scattering, double bounce scattering are two important factors affecting these relationships. The saturation levels of backscattering co-efficient with respect to AGB depend on the wavelengths (i.e. different Bands, such as C, L, P), polarization (such as HV and VV), and the characteristics of vegetation stand structure and ground conditions. Luckman et al. (1997) found that the longer-wavelength (L-Band) SAR image was more suitable to discriminate different levels of forest biomass up to a certain threshold, indicating that it is suitable for estimating biomass of regenerating forests in tropical regions. Austin et al. (2003) indicated that forest biomass estimation using radar data may be feasible when landscape characteristics are taken into account. The radar backscattering coefficient is correlated with forest biomass and stem volume (Le Toan et al. 1992, Israelsson et al. 1994, Kasischke et al. 1994, Dobson et al. 1995). The sensitivity of Synthetic Aperture Radar (SAR) data to forest stem volume increases significantly as the radar wavelength increases (Israelsson et al. 1997). The imaging process makes SAR suitable for mapping parameters related to forest biomass, like stem volume (Baker et al, 1999; Fransson et al, 1999; Hyyppa et al, 1997; Israelsson et al., 1997; Kurvonen et al, 1999; Pulliainen et al, 1996), total growing stock (Balzter et al, 2000; Schmullius et al, 1997), LAI (Imhoff et al, 1997), or above ground net primary productivity (Bergen et al, 1998). Le Toan et al., (1992) used multi-polarisation L- and P-band airborne radar data, and found that the dynamic range of the radar backscatter corresponded highly with forest growth stages and is maximum at P-band HV polarization. The analysis of P-band data indicated a good correlation between the radar backscatter intensity and the main forest parameters including trunk biomass, height, age, diameter at breast height (dbh), and basal area. Dobson et al., (1992) showed an increasing range of backscatter with changing biomass from C to P-band, as well as higher biomass levels at which backscatter relationships to biomass saturate. Hoekman, (1990) found poor relationships between X- and C-band backscatter and volume and other stand parameters. The spaceborne systems, such as the Seasat SAR, SIR-B, SIR-C/X-SAR and ERS-1, ERS-2, JERS, ENVISAT-ASAR and recently ALOS-PALSAR etc. were used for investigations of boreal, temperature and sub-tropical forestry test sites (Ford et al., 1988; Dobson et al., 1992; Ranson et al., 1995; Stofan et al., 1995; Rignot et al., 1995). These experiments and studies have shown that radar is sensitive to forest structural parameters including above-ground biomass (Dobson et al., 1992; Pulliainen et al., 1994; Skriver et al., 1994; Ferrazzoli et al., 1995; Ranson et al., 1996). Kasischke et al., (1997) reviewed radar data for ecological applications, including AGB estimation. It is being reported in literature that the radar backscatter in the P and L bands is highly correlated with major forest parameters, such as tree age, tree height, DBH, basal area, and AGB. In particular, SAR L-Band data have proven to be valuable for AGB estimation (Sader, 1987; Luckman et al., 1997; Kurvonen et al., 1999; Sun et al., 2002). Kuplich et al., (2000) used JERS-SAR data for AGB estimation of regenerating forests and concluded that these data had the potential to estimate AGB for young, regenerating forests. Luckman et al., (1997) found that the longer-wavelength (L-Band) SAR image was more suitable to discriminate different levels L-Band backscatter shows no sensitivity to increased biomass density after a certain threshold, such as 100 tons ha-1, indicating that it is suitable for estimating biomass of regenerating forests in tropical regions. The radar backscattering coefficient is correlated with forest biomass and stem volume (Le Toan et al. 1992; Israelsson et al., 1994; Kasischke et al., 1994, Dobson et al., 1995). The sensitivity of Synthetic Aperture Radar (SAR) data to forest stem volume increases significantly as the radar wavelength increases (Israelsson et al., 1997). The imaging process makes SAR suitable for mapping parameters related to forest biomass, like stem volume (Baker et al., 1999; Israelsson et al., 1997; Pulliainen et al., 1996), total growing stock (Balzter et al., 2000; Schmullius et al., 1997), LAI (Imhoff et al., 1997), or above ground net primary productivity (Bergen et al., 1998). The dependency of backscatter on above ground biomass was observed and related to the penetration of the radiation into the canopy and interaction with the trunk, where most of the volume, therefore, biomass of the vegetation is concentrated (Sader 1987, Le Toan et al. 1992, Dobson et al. 1992). HV polarization in longer wavelengths (L or P band) is the most sensitive to above ground biomass (Sader 1987, Le Toan et al. 1992, Ranson et al. 1997a) because it originates mainly from canopy volume scattering (Wang et al. 1995), trunk scattering (Le Toan et al. 1992) and is less affected by the ground surface (Ranson and Sun 1994). As forest backscatter in different wavelengths and polarizations originate from separate layers of a canopy, the use of multiple channels or multi-step approaches (e.g., Dobson et al. 1995) could be used to estimate total above-ground biomass (Kasischke et al. 1997). Sun and Ranson (1994) estimated biomass in mixed conifer temperate forest upto 250 Mg/ha. Band ratios (HH/HV and VV/VH) were also used for the above ground biomass estimation. However, Dobson et al. (1995) considered these band ratios too simplistic (as the corresponding backscatter will be much higher for the few tall trees than for the many short ones), although effective in estimating biomass at higher ranges. In spite of this, a combination of bands and polarizations in a multi-step approach made possible the mapping of biomass in a mixed temperate forest upto 250 Mg/ha (Dobson et al. 1995). Establishing a strong link between backscatter and forest variables is an important part of the successful estimation of forest biomass from backscatter. Models are often used to explain the relationship between forest variables, scattering mechanisms and SAR configuration parameters (Richards 1990, Kasischke and Christensen 1990). Another approach is the use of statistical analysis, where forest variables are related to SAR backscatter by regression models (Sader 1987, Le Toan et al. 1992, Rauste et al. 1994). The combination of the two approaches, in most cases to assess the results of the predicted biomass or backscatter via regression (Ranson and Sun 1994, Ferrazzoli et al. 1997, Franson and Israelson 1999). Statistical procedures such as stepwise regression analysis were also used to determine the best set of bands and polarizations to discriminate biomass levels (Ranson et al. 1997a). The three-band (C, L, and P) polarimetric AIRSAR sensor has been used in many forest biomass studies (e.g., Green, 1998; Kasischke et al., 1991, 1995; Moghaddam et al., 1994; Ranson Sun, 1997). The strongest correlation between SAR backscatter and forest biomass has been reported in P-band and the weakest in C-band (e.g., Beaudoin et al., 1992; Dobson et al., 1992; Israelsson et al., 1992; Rauste et al., 1992;

Why Did I Choose Wuthering Heights?

1. WHY DID I CHOOSE THIS BOOK? Since I started to be interested in English literature, I had always heard about Wuthering Heights and Emily Brontà «. Everybody I met used to say that even thought it is a really complex novel, it is a must. Likewise, I met many teachers whose devotion to this book was formidable; in terms of translation, literary criticism or just for the pleasure of reading, all of them coincided that it is a masterpiece. Due to all these facts, I looked for some information about it although it was useless, I could not understand the complicated plot just by means of an online summary, it was impossible. That is why I decided to buy this novel last summer. Even though I did not read it that summer, it was there, in my shelf, tantalizing me. Finally, I forgot it. In the early days of this semester, I discovered that for the new literature subject, we will have to choose a book and there it was, Wuthering Heights' opportunity. Without any doubt, from the first moment, I knew that it would be my ch oice. Now, after reading and analyzing this classic, I can truly say that all its renown is worthy. So that, I do not regret about having chose this masterpiece. Moreover, if I have to write another essay, I will do it on Wuthering Heights again. 2. BIOGRAPHY OF THE AUTHOR Literature was in Brontà «'s blood. Emily was born in Yorkshire on July, 1818. She was the fifth child of Patrick Brontà «, an Irish priest, and Maria Branwell, poet and painter. Since Emily was a child, she used to enjoy reading and creating stories with her sisters. After many travels trough Europe, she discovered her own poetic talent. Joint with her sisters, Anne and Charlotte, they decided to publish a collection of their poetry in 1846. In order to evade all the problems that publishing a book being a woman provoked, they adopted pseudonyms but retaining the first letter of their fist names: Emily as Ellis Bell, Anne as Acton Bell and Charlotte as Currer Bell. Analyzing the style of our author, it is undeniable the influence of Wordsworth, Walter Scott and Byron on Emily's poems. Of course, the fact that the three sisters were writers affected also her style. As a final point to Emily's biography, I would like to make a connection with the next section, her novel. Wuthering H eights was published almost a year before her death from tuberculosis at the age of thirty. 3. WUTHERING HEIGHTS: THE BOOK The context of this masterpiece takes us to the Victorian Age, and for a better understanding it should be convenient to understand the 19th-century fiction novels and the Victorian culture in which the novel was written and published. Novel became the most popular style in literature during the 19th-century in England. Most of the novels of the age were determined by the Gothic tradition, which marked these novels with the typical elements of the period such as a gloomy and ruined atmosphere or the supernatural. In the list of influenced novels, it is a must to mention, of course, Wuthering Heights and Jane Eyre by Charlotte Brontà «. Another issue to be taken into account is the Victorian's archetypes. In culture, the Victorians were defined by their focussing in appearance and by leaving behind disagreeables topics. Social decorum had to be kept all the time. Published in 1847, Wuthering Heights was not a really welcome novel. Not too many readers gave an opportunity to the book. It was considered against the Victorian guidelines due to to its inappropriate plot. Even though the book's narrative did not depicted any sexual nor blooded scenes, it was the topics of uncontrolled love and cruelty the ones which made the novel to be considered as disproportionated and improper for the age. However, after Brontà «'s death, the novel was reread and analyzed again by different generations of readers and that is when it started to be classified as a classic of the 19th century English literature. The storyline relates the life of Heathcliff, a mysterious character, from his childhood until his death. It is described his intense love with Catherine Earnshaw, her betrayal of him and how his revenge perdures until the day of the narration. 4. CHARACTERS' ANALYSIS In this section, the characters of the novel will be classified into different categories and analyzed. As a final part of the description, a brief interpretation of them will be added.4.1. The narratorsAs it is already known, Wuthering Heights is told by the use of multiple narrators. Although it is supposed to be the entire diary of Mr. Lockwood, it is interrupted by the use of reported speech by some characters, also the addition of written documents, such as Isabella's letter or Catherine's comments on her books. The embedded literature gives the reader a wide variety of opinions and points of view, although not all of them are believable. In this novel, we find two main narrators: Nelly Dean and Mr. Lockwood.Nelly Dean: As she grew up with Catherine Earnshaw and her brother, she is immersed in the story that she relates. In the time of the narration she is working as the housekeeper. As far a she is a passionate woman, her speech is infested of feelings. These feelings complicate her narration and sometimes they can alter it, that is the main reason why she is considered as an unreliable narrator in this novel. Mr. Lockwood: He started the story as a narrator, writing on his diary the moment when he arrived to Wuthering Heights. His narration conforms a complement to Nelly's and both of them tell the plot of the book. Lockwood's words are also considered as unreliable. The fact that he did not live the story from the beginning and his inexperience in love matters ensure that he is an untrustworthy narrator. All these facts are corroborated by Melissa Fegan, as she explains: The reader must wonder why Bronte deliberately constructed the narrative in such a way that the story is filtered through the two characters who seem least able to understand or empathize with it – two ‘unreliable' narrators. An analysis of the characters of Nelly and Lockwood suggests we must look carefully at all the evidence they provide about other characters – and themselves -and fill in the gaps where their comprehension is at fault. The burden of interpretation lies firmly with the reader. (2008: 30).4.2. The first generationNotwithstanding the importance of the first generation, during the novel they do not play a crucial role, except from Joseph. So that, this section will be very concrete and straightforward. Mr and Mrs Earnshaw: They are the parents of Catherine and Hindley, the four of them live in Wuthering Heights. One day, Mr Earnshaw brought an orphan to love with them, Heathcliff. During the narration, it is undeniable Mr Earnshaw' s preference for Heathcliff and the annoyance of Mrs Earnshaw. Mr and Mrs Linton: Thrushcross Grange's owners and parents of Edgar and Isabella Linton. In the novel, they are depicted as well-mannered and wealthy people. They both raise up their children in good manners and as sophisticated people. After taking Catherine to their house, Mrs Linton tried to teach her as a refined young girl. Joseph: A servant at Wuthering Heights during the whole novel. Stevie Davies stated: He is a gnarled root of the novel's authenticity. [†¦] He has always been there and he always will be, old as the hills, son of the Ancient of Days, with a mythic and timeless quality that does not conflict with his authenticity as a representative of the working class with its pride in hard graft and contempt for the affectations of gentility. (1994: 149).The importance of this character should not be underestimated. He has a strange power over the masters of Wuthering Heights.4.3. The second generationIn this section, the two principal characters will be presented: Catherine Earnshaw and Heathcliff. Even though Catherine and Heathcliff are the very principal, there are some others that also must be depicted for a better and correct understanding of the plot.Edgar Linton: He was Catherine's husband. In the novel he is described as handsome, and young, and cheerful (Brontà «, 2012, p.84). These are the qualities why Catherine married him. Since he is a child, we can perceive his hate towards Heathcliff, as a response of the way he had been educated. In his personality we can feel a tendency to be cold and a strong feeling of unforgiving when his dignity is hurt. Isabella Linton: Edgar's sister. She marries Heathcliff, but she didn't evaluate it before. This act and some others show us the spirit of Isabella. She is a shallow minded and a bit foolish. I could say that she ruined her life by falling in love with Heathcliff. Finally, the horror of her relationship makes her to move out from Wuthering Heights. Hindley Earnshaw: He is Catherine's brother. Since Heathcliff is brought to Wuthering Heights, Hindley tortures him due to the favoritism given by Mr Earnshaw towards Heathcliff. He abuses Heathcliff during the whole novel. He got married with Frances and had a son. The dead of this last one drives him into alcoholism and hopelessness. He is one of the personification of revenge and insanity in the novel. Heathcliff: An enigmatic and mysterious character since the beginning of the narration. An orphan child who is brought to Wuthering Heights by Mr Earnshaw. He fell in a profound love with Catherine, his â€Å"sister†, but she declined and married with Edgar. During the novel he is humiliated by almost everybody. Many critics coincide that: [Heathcliff]exemplifies the effects which a life of continued injustice and hard usage may produce on a naturally perverse, vindictive, and inexorable disposition. Carefully trained and kindly treated, the black gipsy-cub might possibly have been reared into a human being, but tyranny and ignorance made of him a mere demon. (Barker 1997, p. 203).As Baker states before and I completely agree, the behavior of Heathcliff was built up by all the characters who were evil with him. The truth is that it must be so difficult to be a kind person if everybody is hurting you. All this anger discharges in a final character, who is driven by rancor and during his adulthood looks for revenge. Catherine Earnshaw: The daughter of Mr and Mrs Earnshaw. She falls in a passionate love with Heathcliff, this love will determine all her life. She found herself reflected into Heathcliff, the fact that they grew up being together and together makes her think her that they belongs to each other, as it is in written in the book, [†¦]he's more myself than I am. Whatever our souls are made of, his and mine are the same (p.87). Despite the fact that she loves him, her desire for social improvement and ambition made her to marry with Edgar Linton. Finally, this dispute between her wild love and her ambition brought misery to both of the men who loved her. Why Did I Choose Wuthering Heights? 1. WHY DID I CHOOSE THIS BOOK? Since I started to be interested in English literature, I had always heard about Wuthering Heights and Emily Brontà «. Everybody I met used to say that even thought it is a really complex novel, it is a must. Likewise, I met many teachers whose devotion to this book was formidable; in terms of translation, literary criticism or just for the pleasure of reading, all of them coincided that it is a masterpiece. Due to all these facts, I looked for some information about it although it was useless, I could not understand the complicated plot just by means of an online summary, it was impossible. That is why I decided to buy this novel last summer. Even though I did not read it that summer, it was there, in my shelf, tantalizing me. Finally, I forgot it. In the early days of this semester, I discovered that for the new literature subject, we will have to choose a book and there it was, Wuthering Heights' opportunity. Without any doubt, from the first moment, I knew that it would be my ch oice. Now, after reading and analyzing this classic, I can truly say that all its renown is worthy. So that, I do not regret about having chose this masterpiece. Moreover, if I have to write another essay, I will do it on Wuthering Heights again. 2. BIOGRAPHY OF THE AUTHOR Literature was in Brontà «'s blood. Emily was born in Yorkshire on July, 1818. She was the fifth child of Patrick Brontà «, an Irish priest, and Maria Branwell, poet and painter. Since Emily was a child, she used to enjoy reading and creating stories with her sisters. After many travels trough Europe, she discovered her own poetic talent. Joint with her sisters, Anne and Charlotte, they decided to publish a collection of their poetry in 1846. In order to evade all the problems that publishing a book being a woman provoked, they adopted pseudonyms but retaining the first letter of their fist names: Emily as Ellis Bell, Anne as Acton Bell and Charlotte as Currer Bell. Analyzing the style of our author, it is undeniable the influence of Wordsworth, Walter Scott and Byron on Emily's poems. Of course, the fact that the three sisters were writers affected also her style. As a final point to Emily's biography, I would like to make a connection with the next section, her novel. Wuthering H eights was published almost a year before her death from tuberculosis at the age of thirty. 3. WUTHERING HEIGHTS: THE BOOK The context of this masterpiece takes us to the Victorian Age, and for a better understanding it should be convenient to understand the 19th-century fiction novels and the Victorian culture in which the novel was written and published. Novel became the most popular style in literature during the 19th-century in England. Most of the novels of the age were determined by the Gothic tradition, which marked these novels with the typical elements of the period such as a gloomy and ruined atmosphere or the supernatural. In the list of influenced novels, it is a must to mention, of course, Wuthering Heights and Jane Eyre by Charlotte Brontà «. Another issue to be taken into account is the Victorian's archetypes. In culture, the Victorians were defined by their focussing in appearance and by leaving behind disagreeables topics. Social decorum had to be kept all the time. Published in 1847, Wuthering Heights was not a really welcome novel. Not too many readers gave an opportunity to the book. It was considered against the Victorian guidelines due to to its inappropriate plot. Even though the book's narrative did not depicted any sexual nor blooded scenes, it was the topics of uncontrolled love and cruelty the ones which made the novel to be considered as disproportionated and improper for the age. However, after Brontà «'s death, the novel was reread and analyzed again by different generations of readers and that is when it started to be classified as a classic of the 19th century English literature. The storyline relates the life of Heathcliff, a mysterious character, from his childhood until his death. It is described his intense love with Catherine Earnshaw, her betrayal of him and how his revenge perdures until the day of the narration. 4. CHARACTERS' ANALYSIS In this section, the characters of the novel will be classified into different categories and analyzed. As a final part of the description, a brief interpretation of them will be added.4.1. The narratorsAs it is already known, Wuthering Heights is told by the use of multiple narrators. Although it is supposed to be the entire diary of Mr. Lockwood, it is interrupted by the use of reported speech by some characters, also the addition of written documents, such as Isabella's letter or Catherine's comments on her books. The embedded literature gives the reader a wide variety of opinions and points of view, although not all of them are believable. In this novel, we find two main narrators: Nelly Dean and Mr. Lockwood.Nelly Dean: As she grew up with Catherine Earnshaw and her brother, she is immersed in the story that she relates. In the time of the narration she is working as the housekeeper. As far a she is a passionate woman, her speech is infested of feelings. These feelings complicate her narration and sometimes they can alter it, that is the main reason why she is considered as an unreliable narrator in this novel. Mr. Lockwood: He started the story as a narrator, writing on his diary the moment when he arrived to Wuthering Heights. His narration conforms a complement to Nelly's and both of them tell the plot of the book. Lockwood's words are also considered as unreliable. The fact that he did not live the story from the beginning and his inexperience in love matters ensure that he is an untrustworthy narrator. All these facts are corroborated by Melissa Fegan, as she explains: The reader must wonder why Bronte deliberately constructed the narrative in such a way that the story is filtered through the two characters who seem least able to understand or empathize with it – two ‘unreliable' narrators. An analysis of the characters of Nelly and Lockwood suggests we must look carefully at all the evidence they provide about other characters – and themselves -and fill in the gaps where their comprehension is at fault. The burden of interpretation lies firmly with the reader. (2008: 30).4.2. The first generationNotwithstanding the importance of the first generation, during the novel they do not play a crucial role, except from Joseph. So that, this section will be very concrete and straightforward. Mr and Mrs Earnshaw: They are the parents of Catherine and Hindley, the four of them live in Wuthering Heights. One day, Mr Earnshaw brought an orphan to love with them, Heathcliff. During the narration, it is undeniable Mr Earnshaw' s preference for Heathcliff and the annoyance of Mrs Earnshaw. Mr and Mrs Linton: Thrushcross Grange's owners and parents of Edgar and Isabella Linton. In the novel, they are depicted as well-mannered and wealthy people. They both raise up their children in good manners and as sophisticated people. After taking Catherine to their house, Mrs Linton tried to teach her as a refined young girl. Joseph: A servant at Wuthering Heights during the whole novel. Stevie Davies stated: He is a gnarled root of the novel's authenticity. [†¦] He has always been there and he always will be, old as the hills, son of the Ancient of Days, with a mythic and timeless quality that does not conflict with his authenticity as a representative of the working class with its pride in hard graft and contempt for the affectations of gentility. (1994: 149).The importance of this character should not be underestimated. He has a strange power over the masters of Wuthering Heights.4.3. The second generationIn this section, the two principal characters will be presented: Catherine Earnshaw and Heathcliff. Even though Catherine and Heathcliff are the very principal, there are some others that also must be depicted for a better and correct understanding of the plot.Edgar Linton: He was Catherine's husband. In the novel he is described as handsome, and young, and cheerful (Brontà «, 2012, p.84). These are the qualities why Catherine married him. Since he is a child, we can perceive his hate towards Heathcliff, as a response of the way he had been educated. In his personality we can feel a tendency to be cold and a strong feeling of unforgiving when his dignity is hurt. Isabella Linton: Edgar's sister. She marries Heathcliff, but she didn't evaluate it before. This act and some others show us the spirit of Isabella. She is a shallow minded and a bit foolish. I could say that she ruined her life by falling in love with Heathcliff. Finally, the horror of her relationship makes her to move out from Wuthering Heights. Hindley Earnshaw: He is Catherine's brother. Since Heathcliff is brought to Wuthering Heights, Hindley tortures him due to the favoritism given by Mr Earnshaw towards Heathcliff. He abuses Heathcliff during the whole novel. He got married with Frances and had a son. The dead of this last one drives him into alcoholism and hopelessness. He is one of the personification of revenge and insanity in the novel. Heathcliff: An enigmatic and mysterious character since the beginning of the narration. An orphan child who is brought to Wuthering Heights by Mr Earnshaw. He fell in a profound love with Catherine, his â€Å"sister†, but she declined and married with Edgar. During the novel he is humiliated by almost everybody. Many critics coincide that: [Heathcliff]exemplifies the effects which a life of continued injustice and hard usage may produce on a naturally perverse, vindictive, and inexorable disposition. Carefully trained and kindly treated, the black gipsy-cub might possibly have been reared into a human being, but tyranny and ignorance made of him a mere demon. (Barker 1997, p. 203).As Baker states before and I completely agree, the behavior of Heathcliff was built up by all the characters who were evil with him. The truth is that it must be so difficult to be a kind person if everybody is hurting you. All this anger discharges in a final character, who is driven by rancor and during his adulthood looks for revenge. Catherine Earnshaw: The daughter of Mr and Mrs Earnshaw. She falls in a passionate love with Heathcliff, this love will determine all her life. She found herself reflected into Heathcliff, the fact that they grew up being together and together makes her think her that they belongs to each other, as it is in written in the book, [†¦]he's more myself than I am. Whatever our souls are made of, his and mine are the same (p.87). Despite the fact that she loves him, her desire for social improvement and ambition made her to marry with Edgar Linton. Finally, this dispute between her wild love and her ambition brought misery to both of the men who loved her.

Ebay Strategy

Short history of eBay Pierre Omidyar launched the first online auction in 1995 under the name ‘Auctionwatch’ under the domain name of www. eBay. com with the intention of creating a person- ­? to- ­? person trading community based on a democratized, efficient market where everyone could have equal access through the same medium, the Internet. The initial concept was to attract neighbours and other interested in the San Francisco Bay area residents to the site to buy and sell items of mutual interest. From there, the business grew to succession year after year. 1996: Jeffrey Skoll became co- ­? president and director of eBay. 997: Margaret Whitman became CEO of eBay. 2004: eBay acquired a share in Craigslist. 2005: eBay acquired Rent. com and Shopping. com. 2006: Acquisition of Skype. 2007: eBay acquired Stubhub. com. 2008: Margaret Whitman resigned as CEO. John Donahoe was her successor. During the years 2006- ­? 2008, eBay experienced a drop in gross merchandise sales to - ­? 12% and a reduction in number of auctions listed to - ­? 15%. This signalled a downturn in business for eBay, and a need to overcome the challenges which it now faced. Between 2006 and 2008 : eBay’s share of the US e- ­? commerce market had fallen from 19% to 17% (Amazon market hares, same period: from 3,7% to 5,3%). In 2008, John Donahoe took over the firm. Donahoe was a man who liked change. He believed that the firms marketplace sector had reached its maturity and a change in strategy was needed for the firm to move forward. In other words, he believed that the emphasis should no longer be put on the market place sector of eBay but on expanding the business by providing an array of other services. Question 1: Porters’ five forces: When eBay was first set up in 1995, it was the first business in the online auction industry. Since then, the industry has grown significantly. eBays competitors includeAmazon, uBid, Yahoo, and Google. Due to the incre asing interest in the online auction industry, eBay is now facing competition from a number of different rivals, most importantly Amazon. 1. Bargaining Power of buyers: Medium Buyers have the power to negotiate a price which suits them through setting their preferred bid. There is no pressure on buyers to surpass their preferred price limit. However, the number of buyers in the market is vast therefore their power is limited. 2. Bargaining Power of Sellers: Low As a result of endless number of sellers in the market, the bargaining power is low as there are many alternatives which an offer buyers good value and at a low price. Unless dealing with high end items or collectibles, which may be rare, the bargaining power of suppliers is low. 3. Existing Rivalry among competitors: Medium: The online auction industry is oligopolistic in the sense that there are a few large companies who own a large proportion of the market shares (eBay, uBid). However eBay is facing competition from severa l online retailers (Amazon, Overstock). 4. Threat of Substitutes: High Many consumers still prefer to use traditional methods for purchasing and selling items such as in- ­? store purchases. Consumers prefer to use this ype of purchase for many reasons. Firstly for security purposes, there is no risk in giving cash- ­? in- ­? hand to an establishment as opposed to giving credit card details online. Also, buyers have the opportunity to check the value of the good they wish to purchase. Many retail outlets have also extended their market to an online level. 5. Threat of new entrants: Medium The threat from new entrants is medium. As a result of low barriers of entry into the market, it is not difficult for businesses to be created. Businesses find it difficult to generate regular customers, as they must build up a reputation of having a safe nd secure website. In this sense, eBay has a competitive advantage as it has created a strong, trusted environment for its customers. Risin g competition in the market will, in turn, cause improvements in product quality and innovation. Also in order to generate good profits, eBay must focus on the sector of suppliers which regulates the most profits, this being the suppliers of high end items such as collectible products. EBay can differentiate by specialising in the market for collectible goods. Question 2: PEST Analysis:  §? Political: The internet is a tax free environment. EBay is not affected by the governments’ laws on axes. However, eBay is affected by certain policies considering the sale of certain products in different countries. For example, the CNIL in France. Economical: As a result of the economic crisis, consumer behaviour is changing. Consumers have less disposable income to spend caused by problems associated with the economic downturn such as rising unemployment rates, inflation rates etc. Sociological: Consumer behaviour has changed dramatically in recent years. Consumers want a quick and co nvenient way to source their products/services; the internet provides this through online retailers and auctions. The number of internet sers has amplified (insert statistics later? ). Technological: The internet has revolutionised, its range of activities has expanded with time. Along with offering search engines to quickly find products/ services, internet now makes it possible to quickly make transactions between buyers and sellers (PayPal).  §?  §?  §? The combined aspects of political, social, economic and technological will strengthen competition in the industry. In reference to economical, the economic crisis will cause companies to differentiate and work harder to find a competitive advantage over its rivals. In relation to technological, the use of e- ­? ommerce is becoming more and more popular; it has transformed the market place. Changing demographics has meant the internet and e- ­? commerce has become a more prominent force in the lives of consumers. E- ­? commerce is appealing as a more attractive industry as opposed to traditional retail outlets. It is less expensive for companies to create a business online as they can avoid the cost of employing a sales workforce. Also, as technology progresses, there will be the opportunity for firms to globalize, therefore expanding their market reach into different countries, and increasing their consumer base. Online businesses ill be able to target a larger number of consumers worldwide. In the current economic crisis, people need to increase their cash flow. This is an advantage for online auctions such as eBay as people can sell items that they no longer use. It creates a larger market for second- ­? hand items such as worn- ­? once clothing. Question 3: Key Success Factors: Online auctions and retailers †¢ †¢ †¢ †¢ †¢ These key success factors apply to both online retailers and online auctions. However, in the case of the online auctions, a key success factor w ould be the necessity to create a community of trusted buyers and sellers. Online auctions uch as eBay emphasise the importance of good values among their users such as honesty and trustworthiness. A second key success factors for online auctions is the importance of attracting and keeping sellers as without sellers supplying the items, the market would not exist. It is essential that online auctions are made attractable to sellers. This can be done by offering suppliers the option to set a minimal price for their products, further advertisements of their products e. g. eBay will display sellers products on their homepage for a minimal fee. As shown, there are specified key success factors for online auctions. †¢ Necessity to create a community Necessity to attract suppliers Expertise in technology Brand name Generate traffic to the site: by attracting and keeping customers Overcome internet users nervousness about using the internet for e- ­? commerce Security of payment Que stion 4: Our strategic map conveys that this is an oligopolistic market. There are two main competitors who hold strong positions in the market, those being eBay and Amazon. Both businesses have a strong reputation in the market combined with a wide variety of auctions/product categories. EBay is a household name when it comes to online auctions. The map shows hat eBay holds the strongest position in the market. Amazon lacks in number/variety of auctions compared to eBay but it still managed to hold a strong position in the market through its well- ­? established brand name. In comparison with eBay, Yahoo holds a weak position in the market. It lacks in brand recognition as an online business. Yahoo also has a limited variety of auctions paralleled with the market giants eBay and Amazon. Question 5: Swot Analysis  §?  §?  §?  §? Strengths: Global brand for online auctions (Brand awareness). Quality and Quantity of products. Community spirit. Payment security (Paypal). Oppo rtunities:Acquisition of new business. Develop a market in emerging countries (India, Brazil†¦). Increase in online shopping.  §?  §?  §? Weaknesses: Model opened to fraudulent activities. System breakdowns. Increasing customer demands Threats: Substitute products (stores, online shopping web sites†¦). Success attracts competition. Interest and foreign currency exchange rates. Consumers’ fear of fraudulence  §?  §?  §?  §?  §?  §?  §? The SWOT analysis reveals that eBays strengths outweigh its weaknesses. eBays most promising strength is its globally known brand name. EBay has been established as a household name with its continued success in the - ­? commerce industry. It is still possible for eBay to expand and grow in this industry due to the increasing interest in online shopping. A notable weakness of the online commerce industry would be its systems openness to fraudulence. This has been faced by many businesses in the market including eB ay. Even though eBay was subject to controversy over this problem it has still emerged in a strong position nevertheless. Question 6: After computing the current ratio, we found that the company is able to pay its liabilities with its assets. 2005 2006 2007 Current Assets Current Liabilities 3990993 1266792 4970586 2518395 7122505 099579 Current ratio = current 3,15 1,97 2,30 assets /current liabilities It means that in 2007, the company can reimburse its liabilities with its assets 2 times. We noticed that the net income is decreasing (- ­? 70%). In fact, the gross merchandise sales are decreasing (- ­? 20%) and the auction listed too (- ­? 14%). The working capital shows us that eBay has enough cash available for the firm day to day operations. Working capital = current assets- ­? current liabilities 2005 2006 2007 2724201 2452191 4022926 The average collection period in 2007 is about 22 days. That means the company wait just 22 days before receiving the

The Contempt and Bitterness of Virginia Woolf Exposed in...

The Contempt and Bitterness of Virginia Woolf Exposed in A Room of Ones Own Virginia Woolf refuses the role society prescribes her. She stands up against glass ceilings, separate spheres, and double standards-cultural institutions that create and uphold a weaker sex. In her writing, specifically A Room of Ones Own, she manifests her contempt and bitterness by advocating it is necessary [for women] to have five hundred [pounds] a year and a lock on the door if you are to write fiction or poetry (769). However, to break and step above the institutions she criticizes, Woolf knows she cannot simply complain about her brothers years at Oxford while she stayed home with tutors-that would lead an audience to believe she has an axe†¦show more content†¦Marys skills let her do what Woolf cannot: perform. Mary is not against the social order--quite the opposite: Mary is a master of society, commander of its every minutia. At the grand social gala Mary radiates with effortless grace, rallying envy and dazzling spectators, for she knows this performance her par t-very well; whereas at the same occasion Woolf feels uncomfortable, even angry because functions like these keep women in their place. Marys extensive ballet instruction has prepared her well for the socializing world by teaching her complacence. Her highly skilled maestros have taught her to obey orders from superiors, follow what is expected, and to stay graceful and beautiful at all times-at all costs, Thus, Mary has the restrained character expected of academic men, and all the burdens of a shackled woman. Creating Mary gives Woolf the ability to execute the performance she otherwise could not; at the same time it enables her to present herself as an every woman, so to speak. The Mary-mask covers Woolfs individuality with a common name and stereotypically female qualities including naivety and disguised anger--echoing the practice of countless women. By employing this mask, Woolf creates a bond between herself and all women, attempting to establish trust and creating a shared experience with them. As author Adrienne Rich describes Mary: I recognized that tone. I had heard it often enough, in myself and in other women. It is the tone