ID: 56887
Title: Comment on "Surface deformation caused by April 6th 2009 earthquake in L ' Aquila (Italy): A comparative analysis from ENVISAT ASAR, ALOS PALSAR and ASTER" by M.A. Goudarzi, T. Woldai, V A Tolpenkin
Author: Marco Chini, Christian Bignami, Salvatore Stramondo
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: DInSAR, Coseismic and postseismic deformatin, L ' Aquila earthquake
Abstract: The present work concerns some observations about the paper by Goudarzi et al (2011), related to the surface deformation analysis carried out for the earthquake that hit the city of L ' Aquila, Italy, on April 2009 and based on SAR Differential Interferometry (DInSAR) technique.
We have manly identified a criticality about the post-seismic deformation, named by the author post seismic relaxation. The analysis performed by Goudarzi et al. (2011) leads to misleading conclusion in terms of seismic hazard all over the epicentral region. Here, some considerations driven by literature and interferograms comparison demonstrate the incorrectness of their interpretation concerning the coseismic and post seismic surface deformation.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56886
Title: Efficient methods to convert LiDAR-derived ellipsoid heights to orthometric heights
Author: J L Perez, A T Mozas, A Lopez, F J Aguilar, J Delgado, I Fernandez, M A Aguilar
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, Orthometric height, Ellipsoidic height, Accuracy
Abstract: Nowadays cartographic products are usually obtained from data sources which provide large amount of data. LiDAR acquisition system is a good example of the great quantity of data obtained, such as points with spatial coordinates in a determined reference system. The height of these points is usually related to a global ellipsoid (e.g WGS84), but the local vertical reference system, and so the corresponding orthometric heights, are usually measured from a local geoid which is adjusted for a country or region. Orthometric height determination can be performed for each point by knowing the undulation value which relates the ellipsoid to the geoid for each position. However, this operation may not be necessary for all points if we take into account the LiDAR specifications. Thus we can use a simplification which minimizes the processing time for this calculation. In this paper we present the results obtained by applying several simplifications to drastically shorten the number of point-to-point computations to obtain the orthometric height from the raw LiDAR point cloud data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56885
Title: Mapping return levels of absolute NDVI variations for the assessment of drought risk in Ethiopia
Author: Francesco Tonini, Giovanna Jona Lasinio, Hartwig H Hochmair
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: Drought risk, SPOT-Vegetation, NDVI, Autocorrelation, Return levels, Extreme value distributions
Abstract: The analysis and forecasting of extreme climatic events has become increasingly relevant to plan effective financial and food-related interventions in third-world countries. Natural disasters and climate change, both large and small scale, have a great impact on non-industrialized populations who rely exclusively on activities such as crop production, fishing, and similar livelihood activities. It is important to identify the extent of the areas prone to severe drought conditions in order to study the possible consequences of the drought on annual crop production. In this paper, we aim to identify such areas within the South Tigray zone, Ethiopia, using a transformation of the Normalized Difference Vegetation Index (NDVI) called Absolute Differnce NDVI (ADVI). Negative NDVI shifts from the historical average can generally be linked to a reduction in the vigor of local vegetation. Drought is more likely to increase in areas where negative shifts occur more frequently and with high magnitude, making it possible to spot critical situations. We propose a new methodology for the assessment of drought risk in areas where crop production represents a primary source of livelihood for its inhabitants. We estimate ADVI return levels pixel per pixel by fitting extreme value models to independent monthly minima. The study is conducted using SPOT-Vegetation (VGT) ten-day composite (S10) images from April 1998 to March 2009. In all short-term and long-term predictions, we found that central and southern areas of the South Tigray zone are prone to a higher drought risk compared to other areas.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56884
Title: Comparison of carbon assimilation estimates over tropical forest types in India based on different satellite and climate data products
Author: Shijo Joseph, Patrick E van Laake, A P Thomas, Lars Eklundh
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: Light use efficiency, Gross primary productivity, Vegetation photosynthesis Model, MODIS GPP product, Western Ghats
Abstract: Carbon assimilation defined as the eoverall rate of fixation of carbon through the process of photosynthesis is central to the climate change research. The present study compares the two well-known algorithms in satellite based carbon assimilation estimation, the Vegetation Photosynthesis Model (VPM) and the MOD 17A2 GPP Model, over the tropical forest types in India for a period of two years (September, 2006-August, 2008). The results indicate that the evergreen forest assimilate carbon at a higher rate while the rate is lower for montane grasslands. The comparison between the model results shows that there are large differences between these estimates, and that the spatial resolution of the input datasets plays a larger role than the algorithms of the models. The comparison exercise will be helpful for the refinement and development of the existing and future GPP models by incorporating the empirical environmental conditions.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56883
Title: A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery
Author: Zoltan Szantoi, Sparkle Malone, Francisco Escobedo, Orlando Misas, Scot Smith, Bon Dewitt
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: Hurricane debris, assessment, Edge detection, Color filtering, Urban forest management
Abstract: Coastal communities in the southeast United States have regularly experienced severe hurricane impacts. To better facilitate recovery efforts in these communities following natural disasters, state and federal agencies must respond quickly with information regarding the extent and severity of hurricane damage and teh amount of tree debris volume. A tool was developed to detect downed trees and debris volume to better aid disaster response efforts and tree debris removal. The tool estimates downed tree debris volume in hurricane affected urban areas using a Leica Airborne Digital Sensor (ADS40) and very high resolution digital images. The tool employs a Sobel edge detectin algorithm combined with spectral information based on color filtering using 15 different statistical combinations of spectral bands. The algorithm identified downed tree edges based on contrasts between tree stems, grass, and asphalt and color filtering was then used to establish threshold values. Colors outside these threshold values were replaced and excluded from the detection processes. Results were overlaid and an "edge line" was placed where lines or edges from longer consecutive segments and color values within the threshold were met. Where two lines were paired within a very short distance in the scene a polygon was drawn automatically and, in doing so, downed tree stems were detected. Tree stem diameter-volume bulking factors were used to estimate post-hurricane tree debris volumes. Images following Hurricane Ivan in 2005 and Hurricane Ike in 2008 were used to assess the error of the tool by comparing downed tree counts and subsequent debris volume estimates with post-hurricane photo-interpreted downed tree coutns and actual field measured estimates of downed tree debris volume. The errors associated with the use of the tool and potential applications are also presented.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56882
Title: Assessment of area favourable for crop sowing using AMSR-E derived soil Moisture Index (AMSR-E SMI)
Author: Abhishek Chakraborty, M V R Sesha Sai, C S Murthy, P S Roy, G Behera
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: AMSR-E, soil moisture, sown area, drought
Abstract: Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) soil moisture product was used to assess the progression of Area Favourable for Crop Sowing (AFCS) over Andhra Pradesh State of India during summer monsoon. The AMSR-E soil moisture data were normalized with respect to soil texture to calculate AMSR-E soil Moisture Index (AMSR-E SMI). The index had significant correlation (r value 0.7-0.8) with the amount of rainfall during early monsoon period. Progression of soil wetness condition was mapped week-wise by thresholding the AMSR-E SMI. Logical criteria were developed based on the surface soil moisture content, its persistence and the type of crop to classify AFCS. The estimated AFCS was found to have significant correlation (r = 0.92 and root mean squre error = 0.66) with the reported official sown area by Directorate of Economics & Statistics, Govt of Andhra Pradesh. The study demonstrated the potential use of AMSR-E SMI for assessment of agricultural drought during early monsoon season at regional level.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56881
Title: Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China
Author: Dehua Mao, Zongming Wang, Ling Luo, Chunying Ren
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: AVHRR GIMMS NDVI, MODIS NDVI, Temperatuer, Precipitation, Northeast China
Abstract: On the basis of AVHRR GIMMS NDVI and MODIS NDVI, we constructed montly NDVI sequences covering Northeast China from 1982 to 2009 using a per-pixel unary linear regression model. The expanded NDVI passed the consistency check and were well used for analysis. The monthly NDVI trends were highly correlated wtih climatic changes. Spatially averaged NDVI in summer exhibited a downward trend with increased temperature and significantly decreased precipitation in the 28 years. NDVI trens were spatially heterogeneous, corresponding with the regional climatic featrues of different seasons. NDVI for the 95 meteorological stations exhibited significant correlations with monthly mean temperature and monthly precipitation during the study period. The NDVI-temperature correlation was stronger than NDVI-precipitation correlation in most stations and for all vegetation types. Different vegetation types showed various spatial responses to cliamtic changes.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56880
Title: Downscaling Landsat 7 ETM+ thermal imagery using land surface temperature and NDVI images
Author: V Rodriguez-Galiano, E Pardo-Iquzquiza, M Sanchez - Castillo, M. Chica-Olmo, M Chica-Rivas
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: Landsat, Land surface temperature (LST), Thermal imagery, Downscaling Cokriging (DCK), Image sharpening
Abstract: Thermal infrared (TIR) satellite images and derived land surface temperatuer (LST) are variables of great interest in many remote sensing applications. However, the TIR band has a spatial resolution which is coarser than the other multispectral bands for a given satellite sensor (visible, near nad shortwave infrared bands): therefore, the spatial resolution of the retrieved LST from available satellite-borne sensors is not accurate enough to be used in certain applications.
The application of a method is shown here for obtaining LST images with enhanced spatial resolution using the LST at a coarser resolution and the Normalized Difference Vegetation Index (NDVI) of the same scene using Downscaling Cokriging (DCK). A LST image with perfect coherence was obtained by applying this method to a Landsat 7 ETM+ image. This implies that, if the downscaled LST image is degraded to its original resolution, the degraded image obtained is identical to the original. Hence high spatial resolution LST images were obtained without altering the original radiometry with the inclusion of artefacts. Moreover, the performance of DCK was compard with global and local TSHARP methods. The RMSE of the shapened images were 0.85, 0.92 and 1.1 K, respectively.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56879
Title: A hybrid visual estimation method for the collection of ground truth fractional coverage data in a humid tropical environment
Author: Paul L Delamater, Joseph P Messina, Jiaguo Qi, Mark A Cochrane
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: Fractional coverage, fc, percent vegetation cover, visual estimation, NDVI, Spectral mixture analysis
Abstract: A substantial body of research exists exploring the spectral unmixing of remotely sensed image data. Specifically, we refer to the attempts and successes to model the percent vegetatin cover (2-dimensional horizontal density) within a pixel, known as fractional coverage (fc). With this paper, we present a hybrid visual estimation method for fc field data collection in the complex landscapes found inhumid tropical environments. The method includes a scalable theoretical model of fc, integrates the visual estimation technique with hemispherical photography collection, and is conducted over a systematic ground collection area. We present results from a case study conducted in the humid tropical region of Ecuador. Specifically, we report on the relationship between fc data modeled using a linear NDVI transformation and observed fc data collected using our hybrid visual estimation method.
Our study found a significant, positive linear relationship (?=0.795, r2 >0.84, and p<0.001) between modeled and observed fc values. Because the accuracy of both modeled and observed values are unknown, a full validation of the proposed method of collection is not possible. Therefore, we conduct an error assessment, identifying limitations in the modeling method (e.g non-linear relationship between modeled and true values and potential for saturation) and hybrid ground-truth collection method (e.g., subjectivity of visual estimation and positional errors in the ground collection area) that explain the deviation from a 1:1 relationship. We believe the proposed method of ground truth data collection is a significant contribution towards efforts to validate biophysical information gained from remotely sensed data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56878
Title: Collinearity and orthogonality of endmembers in linear spectral unmixing
Author: Freek D Van der Meer, Xiuping Jia
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: Collinearity, Orthogonality, Endmembers, Linear spectral unmixing
Abstract: Contrary to image classification, spectral unmixing techniques allow to derive abundance/ fractional cover estimates for selected endmembers within the volume of a pixel. Mathematically the solution to the mixing problem is resolving a set of linear equations using least squares approaches. Practically this is done using singular value deconvolution of the endmember matrix inversion. This solution assumes orthogonality of the endmembers which determines the orthogonaly of the matrix. If endmembers are highly correlated (thus collinearity or multi-collinearity occurs), the matrix becomes non-orthogonal, the inversion unstable and the inverse or estimated fractions highly sensitive to random error (e.g. noise). In practice, collinearity almost always exists but it is typically overlooked or ignored, hence with this overview we wish to create awarness to the issue and offer approaches to deal with the problem. The first part of the paper highlights the problem using a numerical example. It is shown how collinearity amplifies the error in the endmember matrix inversion. In the next paragraph we propose measures to quantify the level of (multi) collinearity in the endmember matrix: a weighted multiple correlation measure, the variance inflation factor, the partial regression coefficient. The remainder of the paper is dedicated to approaches to mitigate the problem: excluding endmembers, decorrelating endmembers, iterative approaches for endmember selection and we propose an adjustment to the unmixing equation which could be further explored. In conclusion, collinearity hampers the use of fractional aboundance estimates. There is no single recipe to successfully combat this problem but in all mixtures models collinearity should be tested avoided as much as possible.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56877
Title: On the suitability of the SRTM DEM and ASTER GDEM for the compilation of topographic parameters in glacier inventories
Author: Holger Frey, Frank Paul
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: SRTM, ASTER GDEM, Glacier inventory, Topographic parameter, GLIMS
Abstract: Topographic parameters in glacier inventories are of vital importance for several subsequent applications. In combination with digital elevation models (DEMs) with near global coverage, such parameters can in principle be derived for all digital glacier outlines. In this study we investigate the suitability of the SRTM DEM and the ASTER GDEM for the compilation of seven glacier-specific topographic parameters for a sample of 1786 Swiss glaciers. Both DEMs were applied in two different resolutions, and the obtained parameter values were compared to values derived from the Swiss national DEM (DHM25), which served as the reference. The analysis revealed that large differences of the values can occur on individual glaciers, but they average out for larger glacier samples. Parameters that depend on a single DEM value (e.g minimum or maximum elevation) show a larger variability than parameters that are averaged over the entire glacier area (e.g mean elevation or mean slope). Besides artifacts, also changes due to different acquisition dates and techniques (radar, optical) have an influence on the inventory parameters. Although the SRTM DEM yielded slightly better results than the ASTER GDEM, both DEMs are suitable for the compilation of topographic parameters in glacier inventories.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56876
Title: Assessing vegetation changes in timberline ecotoen of Nanda Devi National Park, Uttarakhand
Author: Rupesh R Bharti, Bhupendra S Adhikari, Gopal S Rawat
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: Change detection, Nanda Devi NP, Timberline ecotone, Western Himalaya
Abstract: Changes in the timberline ecotone vegetation of Nanda Devi Naitonal Park (NDNP) was studied over a period of 30 years (1980-2010). Our study based on remote sensing analysis of Landsat MSS and TM images suggest no geographical shift in the upper limit of timberline, while the subalpine forest ' s canopy has increased substantially. Decrease in heterogeneous reflectance pattern near upper boundary of timberline ecotone (above 3600 m asl) suggest more homogenous growth at this elevation. Though the scale of the study is not sufficient to detect minor changes our objective here is to know if the timberline vegetation of NDNP has gone under rapid change in last three decades. Two different methods post classification comparison and vegetation index differencing, used in this study have widely been used for vegetation change detection but very few studies have reported the performance of these methods for highly rugged terrain. Our approach in this study is to test the applicability of these methods in the specific enviornment of western Himalaya. Given the fact that the findings of the study could be the result of incorporation of various methodological errors we analyzed the descriptive statistis (mean and standard deviation) of vegetation index to interpret the nature of change.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56875
Title: Comparison of different methods for corn LAI estimation over northeastern China
Author: Fei Yang, Jiulin Sun, Hongliang Fang, Zuofang Yao, Jiahua Zhang, Yunqiang Zhu, Kaishan Song, Zongming Wang, Maogui Hu
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: Comparison, corn, estimation, LAI, PCA
Abstract: Leaf area index (LAI) is a crucial variable in all kinds of ecosystem, climate and crop yield models, describing the fluxes of energy, mass and momentum between the surface and the planetary boundary layer. To accurately determine the corn LAI, several methods of LAI estimation have been evaluated in this investigation, including vegetation indices, principal component analysis (PCA), the neural network method (NN), the look-up table (LUT) inversion from PROSAIL model and the Hybrid model. Comparisons were conducted based on field-measured corn canopy hyperspectral reflectance and LAI data over northeastern China. In order to fairly compare the LAI estimation performance of different methods, the ground measured data were separated into two sets (modeling data and validation data), except the LUT and hybrid methods of PROSAIL-based. The results indicated that the PCA method delivered the best performance for corn LAI estimation (with maximum R2 = 0.814 and minimum RMSE = 0.501) in this study. The hybrid model and EVI provided moderate results. Comparatively, the LUT and NN methods were less successful and NDVI provided the worst corn LAI estimation performance in this study. The PCA method shows great potential for performing well on corn LAI estimation from hyperspectral information. PCA can avoid the reflectance saturation defect of dense canopy in a certain extent, can utilize hyperspectral reflectance data much more effectively than other methods, and is not limited by the band numbers, it can also reduce noise and provide an great correlation with LAI from the hyper-bands or the multi-bands reflectance.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56874
Title: Estimating aboveground biomass in interior Alaska with Landsat data and field measurements
Author: Lei Ji, Bruce K Wylie, Dana R Nossov, Birgit Peterson, Mark P Waldrop, Jack W McFarland, Jennifer Rover, Teresa N Hollingsworth
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: Aboveground biomass, Spectral vegetative index, Landsat, Lidar, Alaska, Yukon flats ecoregion
Abstract: Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectal variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bioas error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar datast acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56873
Title: Evaluation and parameterization of ARCOR3 topographic correction method for forest cover mapping in mountain areas
Author: Vincent Balthazar, Veerle Vanacker, Eric F Lambin
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: Topographic correction, Mountains, Remote sensing, Forest, Landsat , ATCOR
Abstract: A topographic correction of optical remote sensing data is necesary to improve the quality of quantitative forest cover change analysis in mountainous terrain. The implementation of semi-empirical correction methods requires the calibration of model parameters that are empirically defined. This study develops a method to improve the performance of topographic corrections for forest cover change detection in mountainous terrain through an iterative tuning method of model parameters based on a systematic evaluation of the performance of the correction. The latter was based on: (i) the general matching of reflectances between sunlit and shaded slopes and (ii) the occurrence of abnormal reflectance values, qualified as statistical outliers, in very low illuminated areas. The method was tested on Landsat ETM+data for rough (Ecuadorian Andes) and very rough mountainous terrain (Bhutan Himalays). Compared to a reference level (no topographic correction), the ATCOR3 semi-empirical correction method resulted in a considerable reduction of dissimilarities between reflectance values of forested sites in different topographic orientations. Our results indicate that optimal parameter combinations are depending on the site, sun elevation and azimuth and spectral conditions. We demonstrate that the results of relatively simple topographic correction methods can be greatly improved through a feedback loop between parameter tuning and evaluation of the performance of the correction model.
Location: 231
Literature cited 1: None
Literature cited 2: None