ID: 56841
Title: Effect of the sampling design of ground control points on the geometric correction of remotely sensed imagery
Author: Jianghao Wang, Yong Ge, Gerard B M Heuvelink, Chenghu Zhou, Dick Brus
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Geometric correction, spatial coverage sampling, Universal kriging, Variogram, Model-based sampling
Abstract: The acquirement of ground control points (GCPs) is a basic and important step in the geometric correction of remotely sensed imagery. In particular, the spatial distribution of GCPs may affect the accuracy and quality of image correction. In this paper, both a simulation experiment and actual-image analyses are carried out to investigate the effect of the sampling design for selecting GCPs on the geometric correction of remotely sensed imagery. Sampling designs compared are simple random sampling, spatial coverage sampling, and universal kriging model-based sampling. The experiments indicate that the sampling design of GCPs strongly affects the accuracy of the geometric correction. The universal kriging model-based sampling design considers the spatial autocovariance of regression residuals and yields the most accurate correction. This method is highly recommended as a new GCPs sampling design method for geometric correction of remotely sensed imagery.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56840
Title: Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data
Author: Pavel Propastin
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Geographically and altitudinal weighted, regression, spatial non-stationarity, Aboveground biomass, tropical rainforest, vegetation index, Sulawesi
Abstract: The present study uses a local regression approach for estimation of aboveground biomass (AGB) in a tropical rainforest area with highly diverse terrain conditions from remote sensing -based multi-spectral vegetation indices (VI). By incorporating altitudinal effects inot the spatial weighting matrices of the common geographically weighted regression (GWR), an extended GWR model, geographically and altitundinal weighted regression (GAWR), has been developed to deal with both spatial (horizontal) and altitudinal (vertical) non-stationarity in the data set. Unlike the common GWR model, the presented GAWR approach captures both horizontal and altitudinal drifts in the relationships between aboveground biomass and remote sensing data. In order to test its improved performance, the GAWR method was compared with the traditional GWR technique and global ordinary least squares regression (OLS) in a region of mountainous tropical rainforest in Sulawesi, Indonesia. The relationships between AGB and VIs were found to be significantly spatially variable. The results hsowed that ther were substantial benefits in capturing both horizontal and vertical non-stationarity simultaneously. The GAWR method significantly improved AGB prediction in all simulations relative to both the traditional GWR and OLS methods, as indicated by accuracy and precision statistics. From the results of empirical tests, it seems proper to say that for this data set, the GAWR model is better than the traditional GWR model.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56839
Title: Flood mapping of Danube River at Romania using single and multi-date ERS2-SAR images
Author: T Y Gan, F Zunic, C C Kuo, T Strobl
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Flooding of Danube River, ERS2-SAR images, Permanent water, flooded aera, dry land, single-image un-supervised, contextual, PCA and isodata classifications
Abstract: Several flood mapping classification techniques, applied to single-date and multi-date SAR images of ERS2, based on the Danube River flooding of 2006 in Romania are compared, as part of an effort to explore the feasibility of mapping flooded areas by SAR images acquired through radar sensors. Among 7 SAR images analyzed for the same site located around Bistret of Romania, several represent "dry" and several "wet" conditions, where the latter represent the major Danube flooding event of 2006. The images were classified into (1) permanent water (Danube River and lakes), (2) flooded area, and (3) dry land, using single image, pixel-based classification, frequency -based contextual classification, and prinicipal component analysis (PCA) combined with Isodata classification. The flooded aeas delineated from the above procedures for the study site at Bistret are visually compared with that of Landsat-TM images and MODIS mosaic and digitally compared with referenced flooded area produced by the DEM data of SRTM. Apparently there is no one technique that is clearly better partly because of the nature of SAR data (radar echoes) and partly because of data noise even though the images were first subjected to speckle filtering and geometric corrections, and partly because SAR images could appear dark not only because of flooding but also because of smooth surfaces, target sizes, etc. However, if multi-date SAR images of both DRY and WET (flooding) conditions are available, it seems that PCA combined with the Isodata classifier would give better defined flooded areas of the Danube River than the simple single image, pixel-based classification or the contextual classification.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56838
Title: Remote sensing of geomorphological and ecological change in response to saltmarsh managed realignment, The Wash, UK
Author: D A Friess, T Spencer, G M Smith, I Moller, S M Brooks, A G Thomson
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Aerial photography, DSAS, Freiston Shore, Multispectral, Restoration, Salt marsh, Shoreline change, Surface elevation change
Abstract: An integrated remote sensing approach quantified saltmarsh dynamics in response to a sudden change in surface elevation due to a saltmarsh restoration scheme. The biogeomorphological relationship between surface elevation and saltmarsh presence occurs over the long-term so can be difficult to observe, though the ' managed realignment ' of coastal defences provides a unique experimental opportunity to study this relationship. Realignment at Freiston Shore, Lincolnshire, UK in August 2002 caused a sudden and high-magnitude sediment input into the local coastal system, significantly increasing the intertidal surface elevation. The resulting impacts on the external, fronting saltmarsh were quantified by aerial photography and airborne multispectral imagery. Algal and pioneer saltmarsh boundary positions were calculated from 1984 to 2006, with the latter zone migrating slowly seaward pre-realignment (3.8 ma-1), but advancing significantly post-realignment (21.3 ma-1). Classification of five-year mutlispectral imagery accurately showed subtle changes in vegetation community composition within these boundaries. The realignment site was also colonized rapidly compared to other restoration sites, due to its high starting surface elevation. This study shows how, with sufficient sediment input and accommodation space, coastal management decisions can release intertidal surfaces from physical constraints to saltmarsh colonization.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56837
Title: Investigation of the biophysical processes over the oligotrophic waters of South Indian Ocean subtropical gyre, trigerred by cyclone Edzani
Author: Babula Jena, Debadatta Swain, Kumar Avinash
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Gyre, Aqua-MODIS, Chlorophyll-a, SST, Mixed layer, ASCAT, Upwelling
Abstract: The biophysical effects of a strom in the most oligotrophic waters of the South Indian Ocean (SIO) subtropical gyre have been investigated by conjunctive analyses using space-borne sensors and in situ observations. The most oligotrophic waters of SIO are identified using more than 8- years of chlorophyll-a images derived from Aqua-Moderate Resolution Imaging Spectroradiometer (Aqua - MODIS). Earlier studies revealed that the source of oceanic primary production enhancement in these oligotrophic waters has remained inconclusive. However, the present study succeeded in attributing the cyclone, name Edzani, which passed over these waters and to be responsible for enriching the chlorophyll-a pigment, lowering of sea surface temperature (SST) ad deepening of mixed layer. Analyses of MODIS Chlorophyll-a and SST images during the cyclone and pre-cyclone period shows lowering of SST values up to 2.230C and chlorophyll-a enrichment up to 0.062 mg/m3 from the pre-strom values along the cyclone track. Argo floats in the region recorded 10 m deepening of mixed layer with an average mixed layer cooling of ~1.340C and 0.14% incrase in salinity. These changes controlled by the physical processes have been examined using wind stress, wind stress curl and upwelling velocity derived from the new Advanced Scatterometer (ASCAT). The results provide a significant evidence to suggest that the frequent storms could possibly modify the prevaililng oligotrophic conditions of the SIO subtropical gyres into a relatively productive environment, thus leading to regulate the global carbon cycle which is an essential component of climate change.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56836
Title: Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan using LiDAR data
Author: Karin Kronseder, Uwe Ballhorn, Viktor Bohm, Florian Siegert
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: LiDAR, Tropical forest, Above ground biomass, Reduced emissions from deforestation and forest degradation, Forest inventory, Indonesia
Abstract: The quantification of tropical forest carbon stocks is a key challenge in creating a basic methodology for REDD (reducign emissions from deforestation and degradation in developing countries) projects. Small footprint LiDAR (light detection and ranging) systems have proven to successfullly correlate to above ground biomass (AGB) estimates in boreal and temperate forests. Their applicability to two different tropical rainforest types (lowlnad dipterocarp and peat swamp forest) in Central Kalimantan, Indonesia, was tested by developing multiple regression models at plot level using full waveform LiDAR point cloud characteristics. Forest inventory data is barely available for Central Kalimantan ' s forests. In order to sample a high number of field plots the angle count method was applied which allows fast sampling. More laborious fixed-area plots (three nests of circular shape) were used as a control and approved the use of the angle count method. AGB values, calculated by using existing allometric models, were in the range of 15-547 Mg ha-1 dependign on forest type, degradation level and the model used for calculation. As expected, logging resulted in significant AGB losses in all forest types. AGB-prediction models were established for each forest type using statistical values of the LiDAR point clouds and the forest inventory plots. These regression models were then applied to six LiDAR tracks (altogether with a size of 5241 ha) covering unlogged, logged and burned lowland dipterocarp and peat swamp forest. The regression analysis showed that the 45th and 65th percentiles and the standard error of the mean explain 83% of the variation in lowland dipterocarp forest plots (RMSE + 21.37%). The best model for peat swamp forest could only explain 32% of the AGB variation (RMSE = 41.02%). Taking both forest types together explained 71% (RMSE = 33.85%). Calculating AGB for whole LiDAR tracks demonstrated the ability of this approach to quantify not only deforestation but also especially forest degradation and its spaital variability in terms of biomass change in different forest ecosystems using LiDAR transects. Concluding it can be stated that the combined approach of extensive field sampling and LiDAR point cloud anlysis have high potential to significantly improve current estimates of carbon stocks across different forest types and degradation levels and its spatial variation in highly inaccessible tropical rainforests in the framework of REDD.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56835
Title: Downscaling land surface temperatures with multi-spectral and multi-resolution data
Author: Wenfeng Zhan, Yunhao Chen, Jinfei Wang, Ji Zhou, Jinling Quan, Wenyu Liu, Jing Li
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Thermal remote sensing, Sharpening, Downscaling, Land surface temperature, Multi-resolution, Multi-spectral
Abstract: Land surface temperature (LST) plays an important roel in many fields. However, the limited spatial resolution of current thermal sensors impedes the utilization of LSTs. Based on a theoretical framework of thermal sharpening, this report presents an Enhanced Generalized Theoretical Framework (EGTF) to downscale LSTs using multi-spectral (MS) and multi-resolution images. MS proxy-sharpening and LST downscaling are combined under EGTF. Simulates images upscaled from Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data are produced for indirect validations. Validation of MS proxy-sharpening shows that EGTF is better than the Gram -Schmidt (GS) and the Principle Component (PC) methods, yielding a lower root mean square error (RMSE) and ERGAS (erreur relative globale adimensionnelle de synthese) and, thus, maintaining higher spectral similarity. For LST downscaling, validations show that EGTF has a higher accuracy than the Unmixing-Based Image Fusion (UBIF) method and indicate that the proxy-sharpening process improves the accuracy of downscaled LSTs. Further discussions regarding the selection of the moving-window size (MWS) demonstrate that the MWS could be determined by the range in a semi-variance anlaysis of scaling factor images.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56834
Title: An evaluation of ensemble classifiers for mapping Natura 2000 heathland in Belgium using spaceborne angular hyperspectral (CHRIS/Proba) imagery
Author: Jonathan Cheung-Wai Chan, Pieter Beckers, Toon Spanhove, Jeroen Vanden Borre
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Natura 2000 habitats, Hyperspectral imagery, Random forest, Adaboost, SVM, CHRIS/Proba, Angular imagery
Abstract: Natura 2000 habitats are priority habitats for nature conservation in Europe and need to be monitored closely. In this study, angular hyperspectral CHRIS/Proba imagery was tested for mapping a Natura 2000 heathland site in the north of Belgium. Two ensemble classifiers, Random Forest (RF) and Adaboost, were used and thier resutls compared with Support Vector Machines (SVM). Two classification scenarios were examined: (1) only the nadir images, and (2) both nadir and angular +360images. For accuracy assessments, a field dataset was randomly dividded into two equal halves, one for training and one for testing. To avoid possible bias, we repeated this random separation of training and testing samples ten times. The mean accuracy and accuracy distribution of each classifier were then analyzed. The averaged result out of ten trials is found to be a better characterization of the classifiers. When only the nadir image was used, SVM outperformed both RF and Adaboost by 3-4%. After angular image were added, both RF and Adaboost achieved comparable accuracy as SVM. In terms of ease-of-use, RF and Adaboost are earlier and faster to train than SVM because of less parameter tunning. Incorporating angular images benefitted RF and Adaboost with increases in accuracy by 2-8% and 2-5% respectively. For SVM, degraded accuracy (1-3%) was seen in five trails. Small sample size with relatively high dimensional input explains the poor performance of SVM. Another advantage of adding angular images is that the final classification maps have a better formation of habitat patches with less salt-and- pepper effects. Among the heathland types, Molinia-encroached heath has an acceptable accuracy (75-80%). While overall accuracies are low because of the spectral similarity of the heathland classes and the limited spectral range of CHRIS (0.4 - 1 um), our results point to the potential of hyperspectral sensors with an extended spectral range between 0.4 and 2.5 um and future hyperspectral missions that are equipped with angular viewing capacity.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56833
Title: Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence
Author: J M Barrios, W W Verstraeten, P Maes, J Clement, J M Aerts, J Farifteh, K Lagrou, M Van Ranst, P Coppin
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Borreliosis, Ixodes, MODIS, NDWI, Wavelets
Abstract: The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were teseted as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56832
Title: Resourcesat-2 L4FMX digital data 97 - 63 - A of 5/01/12
Author: None
Editor: None
Year: 2012
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Resourcesat-2 L4FMX digital data 97 - 63 - A of 5/01/12
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 56831
Title: Resourcesat-2 L4FMX digital data 97 - 62 - C of 5/01/12
Author: None
Editor: None
Year: 2012
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Resourcesat-2 L4FMX digital data 97 - 62 - C of 5/01/12
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 56830
Title: Resourcesat-2 L4FMX digital data 63 - B of 13 - Nov - 11
Author: None
Editor: None
Year: 2011
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Resourcesat-2 L4FMX digital data 63 - B of 13 - Nov - 11
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 56829
Title: Resourcesat-2 L4FMX digital data 96-62-D of 13 - Nov - 11
Author: None
Editor: None
Year: 2011
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Resourcesat-2 L4FMX digital data 96-62-D of 13 - Nov - 11
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 56828
Title: Resourcesat - 2 L4FMX digital data - Bangalore 5 mt data
Author: None
Editor: None
Year: 2012
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Resourcesat - 2 L4FMX digital data - Bangalore 5 mt data
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 56827
Title: Cartosat-1 stereo orthokit digital data: 546-335 30% of 19 -Jan-2012
Author: None
Editor: None
Year: 2012
Publisher: NRSC, Hyderabad
Source: Centre for Ecological Sciences
Reference: None
Subject: Cartosat-1 stereo orthokit digital data: 546-335 30% of 19 -Jan-2012
Keywords: None
Abstract: None
Location: 215
Literature cited 1: None
Literature cited 2: None