ID: 52552
Title: Mapping Cholera Vulnerability in Delhi: An Ecosocial Perspective
Author: Rajib Dasgupta
Editor: V.Subramanian
Year: 2010
Publisher: Capital Publishing Company, Vol 7, No 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Water, Environment and Pollution
Keywords: Cholera, Delhi, Vulnerability, health, ecosocial perspective
Abstract: In the city-state of Delhi, the decade of the 1990s was marked by large scale in-migration, growth of industries, proliferation of slums and unauthorised colonies, shortage of water and electricity and pollution of air and water. Simultaneously, there has been a marked rising trend in cholera, particularly among migrant population. This paper examines the epidemiological situation of cholera in Delhi through the 1990s when large scale public health measures were put into operation following a major cholera epidemic in 1988. The vulnerable zones within Delhi have been mapped in detail and the epidemiological complexities identified in this paper. While some problems are technological, others are administrative and managerial. Inadequacies of safe water supplies in vulnerable colonies, sources of potential contamination and the community ' s reliance on alternative sources (much of which is contaminated groundwater) emerge as critical issues. Some areas with deep tubewell (municipal) water supply emerged as cholera foci since chlorinators were not operated properly by the Delhi Jal Board (DJB). Other endemic belts were located either close to sanitary landfill sites or the river Yamuna, where in the absence of piped supplies communities accessed highly contaminated groundwater. However, marked decline in cholera has also been demonstrated in socio-economically disadvantaged areas with reasonabel quantities of piped supply by the DJB.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52551
Title: Good Evidences, Bad Linkages: A Review of Water and Health in South Asia
Author: Jayati Chourey and Anjal Prakash
Editor: V.Subramanian
Year: 2010
Publisher: Capital Publishing Company, Vol 7, No 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Asian Journal of Water, Environment and Pollution
Keywords: Water and health, water and sanitation, pollution, water-associated diseases, challenges, South Asia
Abstract: This review paper investigates the status of water and health in South Asia. Millions of people in South Asia lack access to safe water adn sanitation. Increasing population, rapid urbanization, unsustainable agricultural and industrial developments have degraded freshwater resources. Although countries seem to have worked on the Millennium Development Goals to create infrastructure concerning water supply and sanitation, it is still questionable whether these measures have led to increased access to adequate safe water and proper sanitation at all. The preventable water-associated diseases contribute to the top ten causes of death in the region. Mortality due to these diseases has decreased in the past 10 years, but morbidity is on rise. Diarrhoea remains a primary cause for majority of deaths. Besides infections diseases, chemical contamination of surface and ground water also create a great threat. The arsenic and fluoride contamination are emerging public health challenges. Although, countries have progressed in controlling water-associated diseases but achievements have been limited. The relationship between water and health is not linear, and is governed by various interlinked socioeconomic, political and cultural factors. This paper also discusses major complexities and challenges faced in the sector. The literature provides ' good ' enough ' evidences ' of lack of safe water leading to heavy burden of water associated diseases in South Asia. The existing goverance system aims to provide good health, but fails to appreciate and address its link with safe water and sanitation. The paper recommends a more integrated and demand driven approach to conquer water-related health hazards.
Location: 241
Literature cited 1: None
Literature cited 2: None
ID: 52550
Title: Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge
Author: Mourad Bouziani, Kalifa Goita, Dong-Chen He
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Change detection, Urban, QuickBird, Ikonos, Knowledge base
Abstract: The updating of geodatabases (GDB) in urban environments is a difficult and expensive task. It may be facilitated by an automatic change detection method. Several methods have been developed for medium and low spatial resolution images. This study proposes a new method for change detection of buildings in urban environments from very high spatial resolution images (VHSR) and using existing digital cartographic data. The proposed methodology is composed of several stages. The existing knowledge on the buildings and the other urban objects are first modelled and saved in a knowledge base. Some change detection rules are defined at this stage. Then, the image is segmented. The parameters of segmentation are computed thanks to the integration between the image and the geodatabase. Thereafter, the segmented image is analyzed using the knowledge base to localize the segments where the change of building is likely to occur. The change detection rules are then applied on these segments to identify the segments that represent the changes of buildings. These changes represent the updates of buildings to be added to the geodatabase. The data used in this research concern the city of Sherbrooke (Quebec, Canada) and the city of Rabat (Morocco). For Sherbrooke, we used an Ikonos image acquired in October 2006 and a GDB at the scale of 1:20,000. For Rabat, a QuickBird image acquired in August 2006 has been used with a GDB at the scale of 1:10,000. The rate of good detection is 90%. The proposed method presents some limitations on the detection of the exact contours of the buildings. It could be improved by including a shape post-analysis of detected buildings. The proposed method could be integrated into a cartographic update process or as a method for the quality assessment of a geodatabase. It could be also be used to identify illegal building work or to monitor urban growth.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52549
Title: Augmented reality and photogrammetry: A synergy to visualize physical and virtual city environments
Author: Cristina Portales, Jose Luis Lerma, Santiago Navarro
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Augmented reality, Model, Multisensor, Tracking, Navigation, Real time
Abstract: Close-range photogrammetry is based on the acquisition of imagery to make accurate measurements and, eventually, three-dimensional (3D) photo-realistic models. These models are a photogrammetric product per se. They are usually integrated into virtual reality scenarios where additional data such as sound, text or video can be introduced, leading to multimedia virtual environments. These environments allow users both to navigate and interact on different platforms such as desktop PCs, laptops and small hand-held devices (mobile phones or PDAs). In very recent years, a new technology derived from virtual reality has emerged: Augmented Reality (AR), which is based on mixing real and virutal environments to boost human interactions and real-life navigations. The synergy of AR and photogrammetry opens to new possibilities in the field of 3D data visualization, navigation and interaction far beyond the traditional static navigation and interaction in front of a computer screen. In this paper we introduce a low-cost outdoor mobile AR application to integrate buildings of different urban spaces. High-accuracy 3D photo-models derived from close-range photogrammetry are integrated in real (physical) urban worlds. The augmented environment that is presented herein requires for visualization a see-through video head mounted display (HMD), whereas user ' s movement navigation is achieved in the real world with the help of an inertial navigation sensor. After introducing the basics of AR technology, the paper will deal with real-time orientation and tracking in combined physical and virtual city environments, merging close-range photogrammetry and AR. There are, however, some software and complex issues, which are discussed in the paper.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52548
Title: Performance evaluation of automated approaches to building detection in multi-source aerial data
Author: Kourosh Khoshelham, Carla Nardinocchi, Emanuele Frontoni, Adriano Mancini, Primo Zingaretti '
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Building detection, Automation, Classification, LiDAR, Map updating
Abstract: Automated appraoches to building detection in multi-source aerial data are important in many applications, including map updating, city modeling, urban growth analysis and monitoring of informal settlements. This paper presents a comparative analysis of different methods for automated building detection in aerial images and laser data at different spatial resolutions. Five methods are tested in two study areas using features extracted at both pixel level and object level, but with the strong prerequisite of using the same training set for all methods. The evaluation of the methods is based on error measures obtained by superimposing the results on a manually generated reference map of each area. The results in both study areas show a better performance of the Dempster-Shafer and the AdaBoost methods, although these two methods also yield a number of unclassified pixels. The method of thresholding a normalized DSM performs well in terms of the detection rate and reliability in the less vegetated Mannheim study area, but also yields a high rate of false positive errors. The Bayesian methods perform better in the Memmingen study area where buildings have more or less the same heights.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52547
Title: Assessment of terrain elevation derived from satellite laser altimetry over mountains forest areas using airborne lidar data
Author: Qi Chen
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: GLAS, Gaussian decomposition, Elevation, Lidar
Abstract: Gaussian decomposition has been used to extract terrain elevation from waveforms of the satellite lidar GlAS (Geoscience Laser Altimeter System), on board ICESat (Ice, Cloud, and land Elevation Satellite). The common assumption is that one of the extracted Gaussian peaks, especially the lowest one, corresponds to the ground. However, Gaussian decomposition is usually complicated due to the broadened signals from both terrain and objects above over sloped areas. It is a critical and pressing research issue to quantify and understand the correspondence between Gaussian peaks and ground elevation. This study uses ~2000 km2 airborne lidar data to assess the lowest two GLAS Gaussian peaks for terrain elevation estimation over mountainuous forest areas in North Carolina. Airborne lidar data were used to extract the only ground elevation, but also terrain and canopy features such as slope and canopy height. Based on the analysis of a total of ~500 GLAS shots, it was found that (1) the lowest peak tends to underestimate ground elevation; terrain steepness (slope) and canopy height have the highest correlation with the underestimation, (2) the second to the lowest peak is, on average, closer to the ground elevation over mountainous forest areas, and (3) the stronger peak among the lowest two is closet to the ground for both open terrain and mountainous forest areas. It is expected that this assessment will shed light on future algorithm improvements and /or better use of the GLAS products for terrain elevation estimation.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52546
Title: Modelling vertical error in LiDAR-derived digital elevation models
Author: Fernando J.Aguilar, Jon P.Mills, Jorge Delgado, Manuel A. Aguilar, J.G.Negreiros, Jose L.Perez
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: LiDAR, Vertical accuracy assessment, Spatial modelling, Topographic mapping
Abstract: A hybrid theoretical -empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200 x 200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, South of Almeria province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856; p<0.001). In validation, Bristol observed vertical errors, corresponding to different LiDAR point densities, offered a reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings presented in this article could be used as a guide for the selection of appropriate operational parameters (essentially point density in order to optimize survey cost), in projects related to LiDAR survey in non-open terrain, for instance those projects dealing with forestry applications.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52545
Title: Terrestrial laser scanner self-calibration: Correlation sources and their mitigation
Author: Derek D.Lichti
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Laser scanning, Calibration, Error, Modelling, Correlation
Abstract: Instrument calibration is recognised as an important process to assure the quality of data captured with a terrestrial laser scanner. While the self-calibration approach can provide optimal estimates of systematic error parameters without the need for specialised equipment or facilities, its success is somewhat hindered by high correlations between model variables. This paper presents the findings of a detailed study into the sources of correlation in terrestrial laser scanner self-calibration for a basic additional parameter set. Several pertinent outcomes, resulting from experiments conducted with simulated data, and 12 real calibration datasets captured with Faro 880 terrestrial laser scanner, are presented. First, it is demonstrated that panoramic-type scanner self-calibration from only two instrument locations is possible so long as the scans have orthogonal orientation in the horizontal plane. Second, the importance of including scanner tilt angle observations in the adjustment for parameter de-correlation is demonstrated. Third, a new network measure featuring an asymmetric distribution of object points that does not rely upon a priori observation of the instrument position is proposed. It is shown to be an effective means to reduce the correlation between the rangefinder offset and the scanner position parameters. Fourth, the roles of several other influencing variables on parameter correlation are revealed. The paper concludes with a set of recommended design measures to reduce parameter correlation in terrestrial laser scanner self-calibration.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52544
Title: Seam-line determination for image mosaicking: A technique minimizing the maximum local mismatch and the global cost
Author: Jaechoon Chon, Hyongsuk Kim, Chun-Shin Lin
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Image mosaicking, Seamless mosaic, Optimal path finding, Dijkstra ' s algorithm
Abstract: This paper presents a novel algorithm that selects seam-lines for mosaicking image patches. This technique uses Dijkstra ' s algorithm to find a seam-line with the minimal objective function. Since a segment of seam-line with significant mismatch, even if it is short, is more visible than a lengthy one with small differences, a direct summation of the mismatch scores is inadequate. Limiting the level of the maximum difference along a seam-line should be part of the objective in the seam-line selection process. Our technique first determines this desired level of maximum difference, then applies Dijkstra ' s algorithm to find the best seam-line. A quantitative measure to evaluate a seam-line is proposed. The measure is defined as the sum of a fixed number of top mismatch scores. The proposed algorithm is compared with other techniques quantitively and visually about various types of images.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52543
Title: Statistical information of ASAR observations over wetland areas: An interaction model interpretation
Author: F.Grings, M.Salvia, H.Karszenbaum, P.Ferrazzoli, P.Perna, M.Barber, J.Jacoba Berlles
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Statistics, SAR, Ecology, Floods, Hydrology
Abstract: This paper presents the results obtained after studying the relation between the statistical parameters that describe the backscattering distribution of junco marshes and their biophysical variables. The results are based on the texture analysis of a time series of Envisat ASAR C-band data (APP mode, VV + HH polarizations) acquired between October 2003 and January 2005 over the Lower Parana River Delta, Argentina. The image power distributions were analyzed, and we show that the k distribution provides a good fitting of SAR data extracted from wetland observations for both polarizations. We also show that the estimated values of the order parameter of the k distribution can be explained using fieldwork and reasonable assumptions. In order to explore these results, we introduce a radiative transfer based interaction model to simulate the junco marsh ?0 distribution. After analyzing model simulations, we found evidence that the order parameter is related to the junco plant density distribution inside the junco marsh patch. It is concluded that the order parameter of the k distribution could be a useful parameter to estimate the junco plant density. This result is important for basin hydrodynamic modeling, since marsh plant density is the most important parameter to estimate marsh water conductance.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52542
Title: Sensor modeling, self-calibration and accuracy testing of panoramic cameras and laser scanners
Author: Jafar Amiri Parian, Armin Gruen
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Terrestrial photogrammetry, Sensor modeling, Calibration, Accuracy test
Abstract: Terrestrial Linear Array CCD-based panoramic cameras have been used for purely imaging purposes, but they also have a high potential for use in high accuracy measurement applications. The imaging geometry and the high information content of those images make them suitable candidates for quantitative image analysis. For that a particular sensor model has to be established and the inherent accuracy potential has to be investigated. We developed a sensor model for terrestrial Linear Array-based panoramic cameras by means fo a modified bundle adjustment with additional parameters, which models substantial deviations of a real camera from the ideal one. We used 3D straight-line information in addition ot tie points to conduct a full calibration and orientation without control point information. Due to the similarity of the operation of laser scanners to panoramic cameras the sensor model of the panoramic cameras was extended for the self-calibration of laser scanners. We present the joint sensor model for panoramic cameras and laser scanners and the results of self-calibration, which indicate the subpixel accuracy level for such highly dynamic systems. Finally we demonstrate the systems ' accuracy of two typical panoramic cameras in 3D point positioning, using both a minimal number of control points and a free network adjustment. With these new panoramic imaging devices we have additional powerful sensors for image recording and efficient 3D object modeling.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52541
Title: Irrigated areas of India derived using MODIS 500m time series for the years 2001-2003
Author: V.Dheeravath, P.S.Thenkabail, G.Chandrakantha, P.Noojipady, G.P.O. Reddy, C.M.Biradar, M.K.Gumma, M.Velpuri
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Agriculture, Land use, crop, Hyperspectral, vegetation
Abstract: The overarching goal of this research was to develop methods and protocols for mapping irrigated areas using a Moderate Resolution Imaging Spectroradiometer (MODIS) 500m time series, to generate irrigated area statistics, and to compare these with ground-and census-based statistics. The primary mega-file data-cube (MFDC), compariable to a hyper-spectral data cube, used in this study consisted of 952 bands of data in a single file that were derived from MODIS 500m, 7-band reflectance data acquired every 8-days during 2001-2003. The methods consisted of (a) segmenting hte 952-band MFDC based not only on elevation-precipitation-temperature zones but on major and minor irrigated command area boundaries obtained from India ' s Central Board of Irrigation and Power (CBIP), (b) developing a large ideal spectral data bank (ISDB) of irrigated areas for India, (c) adopting quantitative spectral matching techniques (SMTs) such as the spectral correlation similarly (SCS) R2-value, (d0 establishing a comprehensive set of protocols for class identification and labeling, and (e) comparing the results with the National Census data of India and field - plot data gathered during this project for determining accuracies, uncertainties and errors. The study produced irrigated area maps and statistics of India at the national and the subnational (e.g, state, district) levels based on MODIS data from 2001-2003. The Total Area Available for Irrigation (TAAI) and Annualized Irrigated Areas (AIAs) were 113 and 147 million hectares (MHa), respectively. The TAAi does not consider the intensity of irrigation, and its nearest equivalent is the net irrigated areas in the Indian Naitonal Statistics. The AIA considers intensity of irrigation and is the equivalent of "irrigated potential utilized (IPU)" reported by India ' s Ministry of Water Resources (MoWR). The field-plot data collected during this project showed that the accuracy of TAAi classes was 88% with a 12% error of omission and 32% of error of commission. Comparisons between the AIA and IPU produced an R2-value of 0.84. However, AIA was consistently higher than IPU. The causes for differences were both in traditional approaches and remote sensing. The causes of uncertainties unique to traditional approaches were (a) inadequate accounting of minor irrigation (groundwater, small reservoirs and tanks), (b) unwillingness to share irrigated aea statistics by the individual Indian states because of their stakes, (c) absence of comprehensive statistical analyses of reported data, and (d) subjectivity involved in obsrvation-based data collection process. The causes of uncertainties unique to remote sensing approaches were (a) irrigated area fraction estimate and related sub-pixel area computation and (b) resolution of the imagery. The causes of uncertainties common in both traditional and remote sensing approaches were definitions and methodological issues.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52540
Title: Motivation, development and validation of a new spectral greenness index: A spectral dimension related to foliage projective cover
Author: T.Moffiet, J.D.Armston, K.Mengersen
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Landsat, Multispectra, Land cover, Vegetation, Modelling
Abstract: A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three prinicpal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three prinicpal components, of diminishing significance with respect to the reference image, complete the set.
The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscape containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demostrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greeness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greeness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional -scale predictions of FPC could be gained over those based on spectral indices alone.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52539
Title: Urban aerosol mapping over Athens using the differential textural analysis (DTA) algorithm on MERIS-ENVISAT data
Author: Adrianos Retails, Nicolaos Sifakis
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Remote sensing, Atmosphere, Pollution, Urban, Retrieval
Abstract: Low and moderate spatial resolution satellite sensors (such as TOMS, AVHRR, SeaWiFS) have already shown their capability in tracking aerosols at a global scale. Sensors with moderate to high spatial resolution (such as MODIS and MERIS) seem also to be appropriate for aerosol retrieval at a regional scale. We investigated in this study the potential of MERIS-ENVISAT data to resolve the horizontal spatial distribution of aerosols over urban areas, such as the Athens metropolitan area, by using the differential textural analysis (DTA) code. The code was applied to a set of geo-corrected image to retrieve and map aerosol optical thickness (AOT) values relative to a reference image assumed to be clean of pollution with a homogeneous atmosphere. The comparison of satellite retrieved AOT against PM10 data measured at ground level showed a high positive correlation particularly for the AOT values calculated using the 5th MERIS ' spectral band (R2 = 0.83). These first results suggest that the application of the DTA code on cloud free areas of MERIS images can be used to provide AOT related to air quality in this urban region. The accuracy of retrieved AOT mainly depends on the overall quality, the pollution cleanness and the atmospheric homogeneity of the reference image.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52538
Title: Object based image analysis for remote sensing
Author: T.Blaschke
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, issue 1, January 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Object based image analysis, OBIA, GEOBIA, GIScience, Multiscale image analysis
Abstract: Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA-or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance fo ' grey ' literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA method are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.
Location: 231
Literature cited 1: None
Literature cited 2: None