ID: 54817
Title: Some Issues Related with Sub-pixel Classification using HYSI Data from IMS-1 Satellite
Author: A. Kumar . A. Saha . V. K. Dadhwal
Editor: Prof. B. L. Deekshatulu
Year: 2010
Publisher: Indian Society of Remote Sensing, Vol 38, No 2, June 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Society of Remote Sensing
Keywords: Sub-pixel . Support vector machine . Sub-pixel confusion-uncertainty matrix (SCM) . Uncertainty.
Abstract: The mixed pixels are treated as noise or
uncertainty in class allocation of a pixel and
conventional hard classification algorithms may thus
produce inaccurate classification outputs. Thus
application of sub-pixel or soft classification methods
have been adopted for classification of images
acquired in complex and uncertain environment. The
main objective of this research work has been to study
the effect of feature dimensionality using statisticallearning classifier - support vector machine (SVM with
sigmoid kernel) while using different single and
composite operators in fuzzy-based error matrixes
generation. In this work mixed pixels have been used
at allocation and testing stages and sub-pixel
classification outputs have been evaluated using
fuzzy-based error matrixes applying single and
composite operators for generating matrix. As subpixel
accuracy assessment were not available in
commercial software, so in-house SMIC (Sub-pixel
Multispectral Image Classifier) package has been used.
Data used for this research work was from HySI sensor
at 506 m spatial resolution from Indian Mini Satellite-1
(IMS-1) satellite launched on April 28, 2008 by Indian
Space Research Organisation using Polar Satellite
Launch Vehicle (PSLV) C9, acquired on 18th May 2008
for classification output and IRS-P6, AWIFS data for
testing at sub-pixel reference data. The finding of this
research illustrate that the uncertainty estimation at
accuracy assessment stage can be carried while using
single and composite operators and overall maximum
accuracy was achieved while using 40 (13 to 52 bands)
band data of HySI (IMS-1).
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 54816
Title: Design and Development of Field Radiometers for Ground Truth Data Collection at Antarctica
Author: S.S. Manjul ? P. Narayanbabu ? D.R.M. Samudraiah
Editor: Prof. B. L. Deekshatulu
Year: 2010
Publisher: Indian Society of Remote Sensing, Vol 38, No 2, June 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Society of Remote Sensing
Keywords: Radiometers
Abstract: Four types of low-cost, multi-band,
ground-truth radiometers have been indigenously
developed at Space Applications Centre,
Ahmedabad, for data collection at Antarctica. These
instruments are easy to operate and portable. They
are designed so as to incorporate a set of
interference filters with desired spectral
characteristics in the spectral region from 400 nm to
3000 nm. It is possible to tune these instruments for
various types of remote sensing applications. The
instruments have been calibrated in the absolute
quantities of spectral radiance (w/cm2-sr-?) and
spectral irradiance (w/cm2-?). The total radiometriccalibration uncertainty including the uncertainty of
standard source is of the order of ?3.5% for spectral
irradiance and is of the order of ?7.5% for spectral
radiance. All the instruments were tested and
operated at Antarctica and voluminous radiometric
ground truth data has been collected during 26th
Indian Scientific Expedition to Antarctica.
Measurements were carried out in terms of following
parameters: a) spectral reflectance measurement of
ice and fresh snow surfaces, b) terrestrial solar
spectral irradiance: direct and global components.
This paper gives salient features, specifications,
theory of operation and description of these
instruments. Some of the test results of the measured
data collected at Antarctica are also presented.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 54815
Title: Entropy-based Fuzzy Classification Parameter Optimization using uncertainty variation across Spatial Resolution
Author: A. Kumar . V. K. Dadhwal
Editor: Prof. B. L. Deekshatulu
Year: 2010
Publisher: Indian Society of Remote Sensing, Vol 38, No 2, June 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Indian Society of Remote Sensing
Keywords: Sub-pixel confusion uncertainty matrix (SCM) . Fuzzy c-means (FCM) . Entropy
Abstract: In the past researchers have suggested
hard classification approaches for pure pixel remote
sensing data and to handle mixed pixels soft
classification approaches have been studied for land
cover mapping. In this research work, while selecting
fuzzy c-means (FCM) as a base soft classifier entropy
parameter has been added. For this research work
Resourcesat-1 (IRS-P6) datasets from AWIFS, LISSIII
and LISS-IV sensors of same date have been used.
AWIFS and LISS-III datasets have been used forclassification and LISS-III and LISS-IV data were used
for reference data generation, respectively. Soft
classified outputs from entropy based FCM classifiers
for AWIFS and LISS-III datasets have been evaluated
using sub-pixel confusion uncertainty matrix (SCM).
It has been observed that output from FCM classifier
has higher classification accuracy with higher
uncertainty but entropy-based classifier with optimum
value of regularizing parameter generates classified
output with minimum uncertainty.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 54814
Title: Dynamics of chromophoric dissolved organic matter in Mandovi and Zuari estuaries - A study through in situ and satellite data
Author: Harilal B Menon, Nutan P Sangekar, Aneesh A Lotliker, P Vethamony
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Chromophoric dissolved organic matter (CDOM), Mandovi and Zuari estuaries, Monsoons, Salinity, Optical remote sensing
Abstract: The spatial and temporal distribution of absorption of chromophoric dissolved organic matter at 440 nm (aCDOM (440)) in the Mandovi and Zuari estuaries situated along the west coast of India, has been analysed. The study was carried out using remotely sensed data, obtained from the Ocean Colour Monitor (OCM) on board the Indian Remote Sensing satellite - P4, together with insitu data during the period January to December 2005. Satellite retrieval of CDOM absorption was carried out by applying an algorithm developed for the site. A good correlation (R = 0.98) was obtained between satellite derived CDOM and in situ data. Time series analysis revealed that spatial distribution of CDOM has a direct link with the seasonal hydrohynamics of the estuaries. The effect of remnant fresh water on CDOM distribution could be analysed by delineating a plume in the offshore region of the Zuari estuary. Though fresh water flux from terrestrial input plays a major role in the distribution of CDOM throughout the Mandovi estuary, its role in the Zuari estuary is significant up to the middle zone. Other processes responsible for feeding CDOM in both the estuaries are coastal advection, in situ production and resuspension of bottom settled sediments. The highest value of aCDOM (440) was observed in the middle zone of the Mandovi estuary during the post-monsoon season. The relation between aCDOM (440) and S (spectral slope coefficient of CDOM) could differentiate CDOM introduced in to estuaries through multiple sources. The algorithm developed for the Mandovi estuary is S = 0.003 [aCDOM (440)-0.7091] while for the Zuari estuary, S = 0.0031 [ aCDOM (440)-0.777], respectively.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54813
Title: A boosted genetic fuzzy classifier for land cover classification of remote sensing imagery
Author: D G Stavrakoudis, J B Theocharis, G C Zalidis
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: AdaBoost, Genetic fuzzy rule-based classification systems (GFRBCS), Local feature selection, Textural and spatial features, Multispectral image classification
Abstract: A Boosted Genetic Fuzzy Classifier (BGFC) is proposed in this paper, for land cover classification from multispectral images. The model comprises a set of fuzzy classification rules, which resemble the reasoning employed by humans. Fuzzy rules are generated in an itneractive fashion, incrementally covering subspaces of the feature space, as directed by a boosting algorithm. Each rule is able to select the required freatures, further improving the interpretability of the obtained model. After the rule generation stage, a genetic tuning stage is employed, aiming at improving the cooperation among the fuzzy rules, thus increasing the classification performance attained after the first stage. The BGFC is tested using an IKONOS multispectral VHR image, in a lake-wetland ecosystem of international importance. For effective classification, we consider advanced feature sets, containing spectral and textual feature types. Comparative results with well-known classifiers, commonly employed in remote sensing tasks, indicate that the proposed system is able to handle multi-dimensional feature spaces more efficiently, effectively exploiting information from different feature sources.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54812
Title: Automatic interpretation of digital maps
Author: Volker Walter, Fen Luo
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Interpretation, Classification, Spatial data mining, Analysis, Recognition
Abstract: In the past, the availability and /or the acquisition of spatial data were oftne the main problems of the realization of spatial applications. Meanwhile this situation has changed: on one hand, comprehensive spatial datasets already exist and on the other hand, new sensor technologies have the ability to capture fast and with high quality large amounts of spatial data. More and more responsible for the increasing accessibility of spatial data are also collaborative mapping techniques which enable users to create maps by themselves and to make them available in the internet. However, the potential of this diversity of spatial data can only hardly be utilized. Especially maps in the internet are represented very often only with graphical elements and no explicit information about the map ' s scale, extension and content is available. Nevertheless, humans are able to extract this information and to itnerpret maps. For example, it is possible for a human to distinguish between rural and industrial areas only by looking at the objects ' geometries. Furthermore, a human can easily identify and group map objects that belong together. Also the type, scale and extension of a map can be identified under certain conditions only by looking at the objects ' geometries. All these examples can be subsumed under the term " map interpretation". In this paper it is discussed how map interpretation can be automated and how automatic map interpretation can be used in order to support other processes. The different kinds of automatic map interpretation are discussed and two approaches are shown in detail.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54811
Title: Experimentation of structured light and stereo vision for underwater 3D reconstruction
Author: F Bruno, G Bianco, M Muzzupappa, S Barone, A V Razionale
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Structured light, Underwater imaging, Photogrammetry, 3D reconstruction, Imaging in turbid medium
Abstract: Current research on underwater 3D imaging methods is mainly addressing long range applications like seafloor mapping or surveys of arecheological sites and shipwrecks. Recently, there is an increasing need for more accessible and precise close-range 3D acquisition technologies in some application fields like, for example, monitoring the growth of coral reefs or reconstructing underwater archaeological pieces that in most cases cannot be recovered from the seabed. This paper presents the first resutls of a research project that aims to investigate the possibility of using active optical techniques for the whole-field 3D reconstructions in an underwater environment. In this work we have tested an optical technique, frequently used for air acquisition, based on the projection of structured lighting patterns acquired by a stereo vision system. We describe the experimental setup used for the underwater tests, which were conducted in a water tank wih different turbidity conditions. The tests have evidenced that the quality of 3D reconstruction is acceptable even with high turbdity values, despite the heavy presence of scattering and absorption effects.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54810
Title: Angular effect of MODIS emissivity products and its application to the split-window algorithm
Author: Huazhong Ren, Guangjian Yan, Ling Chen, Zhaoliang Li
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: MODIS emissivity, Angular effects, Split-window algorithm
Abstract: The angular effects of emissivity are ignored in current land surface temperature (LST) products. As a result, the directionality of these LST products limits their further application in many fields. Accurate correction of the angular problem of LST products requires explicit understanding of the angular effects of emissivity at the pixel scale. Currently, nearly ten years of global emissivity products of MODIS are available. However, the pixel-scale directionality of emissivity has never been analyzed. By performing a statistical analysis of 5- year MODIS emissivity products over most of East Asia, we generated the empirical relationships between the directional emissivity, land cover, and seasonal variations. Two look-up tables (LUTs) of directional emissivity were created for typical land cover types and applied to the generalized split-window algorithm to modify the MODIS LST. The results showed that the angular effect of emissivity could introduce a singificant bias of -1-3 K to the 1 km resolution LST. Finally, the spatial effect of emissivity were analyzed, and it was found that the temperature differences caused by scale effects fell within +/- 0.5 K for most pixels if 5 km emissivity was used in 1 km LST retrieval. There fore, wide use of the LUTs can be expected.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54809
Title: Building roof modeling from airborne laser scanning data bsed on level set approach
Author: KyoHyouk Kima, Jie Shan
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: LiDAR (Light Detection And Ranging), Level set, Multiphase level set, Segmentation, Building reconstruction
Abstract: This paper presents a novel approach to building roof modeling, includine roof plane segmentation and roof model reconstruction, from airborne laser scanning data. Segmentation is performed by minimizing an energy function formulated as multiphase level set. The energy function is minimized when each segment corresponds to one or severl roof plans of the same normal vector. With this formulation, maximum n regions are segmented at a time by applying log2 n level set functions. The roof ridges or step edges are then delineated by the union of the zero level contours of the level set functions. In the final step of segmentation, coplanar and parallel roof segments are separated into individual roof segments based on their connectivity and homogeneity. To reconstruct a 3D roof model, roof structure points are determined by intersecting adjacent roof segments or line segments of building boundary and then connected based on their topological relations inferred from the segmentation result. As a global solution to the segmentation problem, the proposed approach determines multiple roof segments at the same time, which leads to topological consistency among the segment boundaries. The paper describes the principle and solution of the multiphase level set approach and demonstrates its performance and properties with two airborne laser scanning data sets.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54808
Title: Unsupervised image segmentation evaluation and refinement using a multi-scale approach
Author: Brian Johnson, Zhixiao Xie
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Object-based image analysis, Multi-scale segmentation, image segmentation evaluation, Under-segmentation, over-segmentation
Abstract: In this study, a multi-scale approach is used to improve the segmentation of a high spatial resolution (30 cm) color infrared image of a residential area. First, a series of 25 image segmentations are performed in Definiens Professional 5 using different scale parameters. The optimal image segmentation is identified using an unsupervised evaluation method of segmentation quality that takes into account global intra-segment and inter-segment heterogeneity measures (variance and Local Moran ' s I). The under- and over-segmented regions are refined by (1) further segmenting under-segmented regions at finer scales, and (2) merging over-segmented regions with spectrally similar neighbors. This process leads to the creation of several segmentations consisting of segments generated at three different segmentation scales. Comparison of single-and multi-scale segmentations shows that identifying and refining under- and over-segmented regions using local statistics can improve global segmentation results.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54807
Title: In situ estimation of water quality parameters in freshwater aquaculture ponds using hyperspectral imaging system
Author: Amr Abd-Elrahman, Matthew Croxton, Roshan Pande-Chettri, Gurpal S Toor, Scot Smith, Jeffrey Hill
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Chlorophyll-a, Hyperspectral, Submerged targets, Aquaculture, water quality
Abstract: Knowledge of water quality parameters is integral to sustainability of freshwater aquaculture operations that raise ornamental fish. Our objective in this study is to evaluate the ability of a mobile, groundbased hyperspectral (HS) imaging sensor to determine chlorophyll-a (Chl-a) concentrations in working aquaculture ponds, which represent manipulated, shallow, nutrient-rich systems, and to determine the effect of usign submerged reflectance targets on the accuracy of Chl-a estimation. We collected Chl-a measurements from aquaculture ponds raning from 0.8 to 494 ?g/L. Chl-a measurements showed a strong correlation with two-band and three-band spectral indices computed from the HS image reflectance. Coefficient of determination (R2) values of 0.975 and 0.982 were obtained for the two-and three-band models, respectively, using spectra captured from the submerged target at 10 cm depth. Using spectra captured from water (no submerged targets), R2 values were slightly lower at 0.833 and 0.862 for two- and three-band models. Data from the submerged target at 30 cm depth had the lowest correlation with measured chlorophyll-a concentrations, potenially due to variations in water column properties and shadows cast by the platform. Modeling total Phosphorous (P) and Nitrogen (N) concentrations of the collected samples with the spectral indices sensitive to Chl-a concentrations showed a moderate level of correlation. Removing a model outlier (observation with maximum N and P concentrations) led to a significant increase in the models ' coefficient of determination (e.g. from 0.478 to 0.823 for the P model using three-band index values), which highlighted the possibility of using HS imagery to estimate N and P concentrations and the need for more research to model the interrelationships between Chl-a and nutrient concentrations in aquaculture water systems.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54806
Title: User interactive multiple aerial view analysis for reconstructing a large number of 3D architectural models
Author: Sung Chun Lee, Ram Nevatia
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Building, Modeling, Urban, Architecture, Detection
Abstract: An effective 3D method incorporating user assistance for modeling complex buildings is described. This method utilizes the connectivity and similar structure information among unit blocks in a multi-component building structure, to enable the user to incrementally construct models of many types of buildings. The system attempts to minimize the complexity and the number of user interactions needed to assist an existing automatic system in this task. Several examples are presented that demonstrate significant improvement and efficiency, compared with other approaches and with purely manual systems.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54805
Title: The selection of appropriate spectrally bright pseudo-invariant ground targets for use in empirical line calibration of SPOT satellite imagery
Author: Barnaby Clark, Juha Suomalainen, Petri Pellikka
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Calibration, SPOT, radiometric, multispectral, Close range
Abstract: The appropriate utilization of multi-temporal SPOT multispectral satellite imagery in quantitative remote sensing studies requires the removal of atmospheric effects. One widely used and potentially very accurate way of achieving absolute atmospheric correction is the calibration of at-satellite radiance data to field measures of the surface reflectance factor (ps). There are a number of variations in this technique, which are known collectively as empirical line (EL) approaches. However, the successful application of an EL spectral calibration requires the presence and careful selection of appropriate pseudo-invariant ground targets within each scene area. Real surfaces, even those that are man-made and vegetation-free, display non-Lambertian reflectance behaviour to some extent. Because of the + 310 off-nadir incidence angle range of the SPOT sensors, this is a crucial consideration. In favourable cirumstances, it may be possible to utilize a goniometer to collect multiangular ps measurements, but for widespread lower cost application of EL approaches currently, the use of a handheld spectrometer to measure nadir only ps is a more realistic proposition. In either case, the selection of targets that have more limited and stable multiangular reflectance behaviour is preferable. Details are given of the reflectance properties of a variety of spectrally bright potential calibration surface types, encompassing sands, gravel, asphalts, and managed and artificial grass turf surfaces, measured in the field using the Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO). Bright calibration site selection requirements for SPOT data are discussed and the physical mechanisms behind the varying reflectance characteristics of the surfaces are considered. The most desirable properties for useful calibration targets are identified. The results of this study will assist other workers in the identification of likely suitable EL calibration sites for medium and high resolution optical satellite data, and therefore help optimize efforts in the time consuming and costly process of measuring ps in the field.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54804
Title: B-spline deconvolution for differential target cross-section determination in full-waveform laser scanning data
Author: Andreas Roncat, Gunther Bergauer, Norbert Pfeifer
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Laer scanning, Full-waveform, Deconvolution, Linear estimation
Abstract: In full-waveform laser scanning, short laser pulses are emitted and travel towards Earth and object surfaces. The sensor samples the waveform of teh emitted pulse and its complete backscattered echo as a function of time. This technique allows for the three-dimensional reconstruction of the terrain, natural and man-made objects, and for the derivation of (geo-) physical quantities such as the differential target cross-section. The retrieval of the differential target cross-section requires deconvolution which is an ill-posed problem. In this study, we present a novel technique for the computation of the differential target cross-section using B-splines. This class of mathematical functions enables a well-posed linear approach for deconvolution. Furthermore, it is not dependent on the symmetry of the temporal profiles of the emitted laser waveform and the received echoes, as approaches previously suggested. In this paper, the algorithm for deconvolution is presented in detail and validated for both synthetic and real-world full-waveform laser scanner data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54803
Title: Water-removal spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations
Author: Abel Ramoelo, Andrew K Skidmore, Martin Schlerf, Renaud Mathieu, Ignas M A Heitkonig
Editor: George Vosselman
Year: 2011
Publisher: Elsevier, Vol 66, Issue 4, July 2011
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetry and Remote Sensing
Keywords: Nitrogen concentration, Phosphorus concentration, water removal, continuum removal, bootstrapping
Abstract: Information about the distributio of grass foliar nitrogen (N) and phosphorus (P) is important for understanding rangeland vitality and for facilitating the effective management of wildlife and livestock. Water absorption effects in the near-infrared (NIR) and shortwave-infrared (SWIR) regions pose a challenge for nutrient estimation using remote sensing. The aim of this study was to test the utility of water-removed (WR) spectra in combination with partial least-squares regression (PLSR) and stepwise multiple linear regression (SMLR) to estimate foliar N and P, compared to spectral transformation techniques such as first derivative, continuum removal and log-transformed (Log (1/R)) spectra. The study was based on a green house experiment with a savanna grass species (Digitaria eriantha). Spectral measurements were made using a spectrometer. The D. eriantha was cut, dried and chemically analyzed for foliar N and P concentrations. WR spectral were determined by calculating the residual from the modelled leaf water spectra using a nonlinear spectral matching technique and observed leaf spectra. Results indicated that the WR spectra yielded a higher N retrieval accuracy than a traditional first derivative transformation (R2 = 0.84, RMSE = 0.28) compared to R2 = 0.59, RMSE = 0.45 for PLSR. Similar trends were observed for SMLR. The highest P retrieval accuracy was derived from WR spectra using SMLR (R2 = 0.64, RMSE = 0.067), while the traditional first derivative and continuum removal resulted in lower accuracy. Only when using PLSR did the first derivative result in a higher P retrieval accuracy (R2 = 0.47, RMSE = 0.07) than the WR spectra (R2 = 0.43, RMSE = 0.070). It was concluded that the water removal technique is a promising technique to minimize the perturbing effect of foliar water content when estimating grass nutrient concentrations.
Location: 231
Literature cited 1: None
Literature cited 2: None