ID: 58143
Title: Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula
Author: B Martinez, F Camacho, A Verger, F J Garcia-Haro, M A Gilabert
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Intercomparison, FAPAR, Forests, Iberian Peninsula, Gross primary production
Abstract: The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58142
Title: Forest cover trends from time series Landsat data for the Australian continent
Author: Eric A Lehmann, Jeremy F Wallace, Peter A Caccetta, Suzanne L Furby, Katherine Zdunic
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Vegetation density index, Forest monitoring, Remote senisng, Landsat time series, Natural resource management, Data visualisation
Abstract: In perennial and naturla vegetation systems, monitoring changes in vegetation over time is of fundamental interest for idenifying and quantifying impacts of management and natural processes. Subtle changes in vegetation cover can be identified by calculating the trends of a vegetation density index over time. In this paper, we apply such an index-trends approach, which has been developed and applied to time series Landsat imagery in rangeland and woodland environments, to continental-scale monitoring of disturbances within forested regions of Australia. this paper describes the operationsl methods used for the generation of National Forest Trend (NFT) information, whidh is a time-series summary providing visual indicationof within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution. This result is based on a national archive of calibrated Landsat TM/ETM+ data from 1989 to 2006 produced for Australia ' s National Carbon Accounting System (NCAS). The ACAS was designed in 1999 initially to provide consistent fine-scale classifications for monitoring forest cover extent and changes (ie. land use change) over the Australia continent using time series Landsat imagery. NFT information identifies more subtle changes within forested areas and provides a capacity to identify processes affecting forests which are of primary interest to ecologists and land managers. The NFT product relies on the identification of an appropriate Landsat-based vegetation cover index (defined as a linear combination of spectral image bands) that is sensitive to changes in forest density. The time series of index values of a location, derived from calibrated imagery, represents a consistent surrogate to track density changes. To produce the trends summary information, statistical summaries of the index response over time (such as slope and quadratic curvature) are calculated. These calculated index responses of woody vegetation cover are then displayed as maps where the different colours indicate the approximte timing, direction (decline or increase), magnitude and spatial extent of the changes in vegetation cover. These trend images provide a self-contained and easily interpretable summary of vegetation change at scales that are relevant for natural resource management (NRM) and environmental reporting.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58141
Title: Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations
Author: Sam B Coggins, Nicholas C Coops, Thomas Hilker, Michael A Wulder
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Landsat, Forest inventory, Mountain pine beetle, susceptibility, Geometric optical modelling, Western Canada, Lodgepole pine, Forest health
Abstract: Assessment of the susceptibility of forests to mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation is based upon an understanding of the characteristics that predispose the stands to attack. These assessments are typically derived from conventional forest inventory data; however, this information often represents only managed forest areas. It does not cover areas such as forest parks or conservation regions and is often not regularly updated resulting in an inability to assess forest susceptability. To address these shortcomings, we demonstrate how a geometric optical model (GOM) can be applied to Landsat-5 Thematic Mapper (TM) imagery (30 m spatial resolution) to estimate stand-level susceptability to moutain pine beetle attack. Spectral mixture analysis was used to determine the proportion of sunlit canopy and background, and shadow of each Landsat pixel enabling per pixel estimates of attributes required for model inversion. Stand structural attributes were then derived from inversion of the geometric optical model and used as basis for susceptibility mapping. Mean stand density estimated by the geometric optical model was 2753 (standard deviation + 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation+ 0.11) metres. When compared to equivalent forest inventory attributes, model predictions of stems per hectare and crown radius were shown to be reasonably estimated using a Kruskal-Wallis ANOVA (p<0.001). These predictions were then used to create a large area map that provided an assessment of the forest area susceptible to moutain pine beetle damage.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58140
Title: Nonlinear intensity difference correlation for multi-temporal remote sensing images
Author: Shunping Ji, Tong Zhang, Qingfeng Guan, Junli Li
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Non-linear intensity difference correlation, Multi-temporal, Multi-sensor, Image matching, Ground control points
Abstract: Compared to geometric distortions exhibited in remote sensing images, radiometric deformations are less addressed in the literature and linear variations are usually assumed during image matching or registration. This paper proposes a novel robust and automatic image matching apporach for multi-temporal and multi-sensor remote sensing images which usually present non-linear radiometric changes. We introduce a non-linear intensity difference correlation (NIDC) algorithm that aims to reduce the impacts of non-linear intensity differences during image matching. Differences of illumination intensity are accounted for and modeled in the NIDC algorithm through the extension of traditional feature-based matching techniques. Our proposed approach has been tested with typical multi-temporal and multi-sensor images characterized by either dense or sparse ground control points (GCPs). Experimental results demonstrate that our matching approach outperforms common image matching techniques sukch as cross correlation (CC), scale-invariant feature transform (SIFT), and speed-up robust features (SURF) with respects to matching success rate and robustness in test data.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58139
Title: Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView -2 panchromatic images
Author: Manuel A Aguilar, Maria del Mar Saldana, Fernando J Aguilar
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: very high resolution satellite images, Sensor model, Rational functions, Geopositioning accuracy, Orthorectification
Abstract: GeoEye-1 and WorldView -2 are the commercial very high resolution (VHR) satellites more innovative, unexplored and presenting the highest available resolutions nowadays. The attainable geopositioning accuracies from GeoEyp-1 and WorldView-2 single panchromatic images, both along the sensor orientation and orthorectification phases, are analyzed at the same study area and by using exactly the same ancillary data. The accuracy assessment was carried out depending on the following factors: (i) type of input satellite image (GeoEye-1 Geo, WorldView -2 Ortho Ready Standard and WorldView-2 Basic ), (ii) sensor orientation model used (rigorous and based on rational function), (iii) number of well-distributed ground control points (GCPs) used in the triangulation process, (iv) off-nadir viewing angle, and finally (v) vertical accuracy of the DEm employed to conduct the orthorectification process.
Regardless of satellite or product, the best horizontal geopositioning accuracies were always attained by using third order 3D rational functions with vendor ' s rational polynomial coefficients data refined by a zero order polynomial adjustment (RPCD). Focusing on WorldView-2 products, worse accuracies were yielded from Basic images than from Ortho Reddy Standard level ones.
As a general rule, and for attaining sub-pixel planimetric accuracies for the orthorectified GeoEye-1 Geo and WorldView-2 Ortho Ready Standard images and using RPCO model with 7 GCPs, users should avoid off-nadir higher than 200 and use a very accurate DEM.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58138
Title: Spatial statistical analysis of tree deaths using airborne digital imagery
Author: Ya-Mei Chang, Adrian Baddeley, Jeremy Wallace, Michael Canci
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Covariate effect, Kernel estimation, morphological image analysis, partial residual, spatial point pattern, tree location detection, point process, logistic regressin, leverage, influence
Abstract: High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation wer eidentified using morphological image analysis techniques. Methods of spatial process statistics were then applied to estimate the spatially - varying tree death risk, and to show that is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008)]. The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on three death risk was investigated using spatial statistical (graphical exploratory methods, spatial point patterns modelling and diagnostics).
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58137
Title: Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data
Author: Cheng Sun, Zhi-feng Wu, Zhi-qiang Lv, Na Yao, Jian-bing Wei
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Urban growth types, change dynamic, spatial metrics, object-oriented classification
Abstract: There is a widespread concern about urban sprawl. It has negative impacts on natural resources, economic health, and community character. Without a universal definition of urban sprawl, its quantification and modeling is difficult. Traditionally, urban sprawl was descrbied using qualitatie terms, and landscape patterns. Quantitative methods aer required to help local, regional and state land use planners to better identify, understand and address it. In this study, an integrated approach of remote sensing and GIS was used to identify three urban growth types of infilling growth, outlying growth and edge-expansion growth at the city of Guangzhou, China. Spatial metrics were used to characterize long-term trends and patterns of urban growth. Result shows that hte proposed method can identify and visulize different urban growth types. Infilling growth is the dominant expansion types. Infilling growth is the dominant expansion type. Edge-expansion is concentrated at suburban areas. Outlying growth mainly occurs relatively far from the urban core. The analysis shows that initially the urban area expands mainly as outlying growth, causing increased fragmentation and dispersion of urban areas. Next, growth filled in vacant non-urban area inwards, resulting into a more compact and aggregated urban pattern. The study shows an improved understanding of urban growth and helps to provide an effective way for urban planning.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58136
Title: Classification method, spectral diversity, band combination and accuracy assessment evaluation for urban feature detection
Author: A Erener
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Classification, spectral diversity, band combination, accuracy assessment, future detection
Abstract: Automatic extractionof urban features from high resolution satellite images is one of the main applications in remote sensing. It is useful for wide scale applications, namely: urban planning, urban mapping, disaster management, GIS (geographic information systems) updating, and military target detection. One commonapproach to detecting urban features from high resolutionimages is to use automatic classification methods. This paper has four main objectives with respect to detecting buildings. The first objective is to compare the performance of the most notable supervised classification algorithms, including the maximum likelihood classifier (MLC) and the support vector machine (SVM). In this experiment the primary consideration is the impact of kernel configuration on the performance of the SVM. The second objective of the study is to explore the suitability of integrating additional bands, namely first principal component (1st PC) and the intensity image, for original data for multi classification approaches. The performance evaluation of classification results is doen using two different accuracy assessment methods:pixel based and object based approaches, which reflect the third aim of the study. The objective here is to demonstrate the differences in the evaluation of accuracies of classification methods. Considering consistency, the same set of ground truth data which is produced by labeling the building boundaries in the GIS environment is used for accuracy assessment. Lastly, the fourth aim is to experimentally evaluate variation in the accuracy of classifiers for six different real situations in order to identify the impact of spatial and spectral diversity on results. The method is applied to Quickbird images for various urban complexity levels; extending from simple to complex urban patterns. The simple surface type includes a regular urban area with low density and systematic buildings with brick rooftops. The complex surface type involves almost all kinds of challenges, such as high dense build up areas, regions with bare soil, and small and large buildings with different rooftops, such as concrete, brick and metal.
Using the pixel based accuracy assessment it was shown that the percent building detection (PBD) and quality percent (QP) of the MLC and SVM depend on the complexity and texture variation of the region. Generally, PBD balues range between 70% and 90% for the MLC and SVM, respectively. No substantial improvements were observed when the SVM and MLC classifications were developed by the addition of more variables, instead of the use of only four bands. In the evaluation of object based accuracy assessemt, it was demonstrated that while MLC and SVM provide higher rates of correct detection, they also provide higher rates of false alarms.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58135
Title: Global and local indicators of spatial association between points and polygons: A study of land use change
Author: Luo Guo, Shihong Du, Robert Haining, Lianjun Zhang
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Cross K-function, Spatial association, Land-use change, religious culture, spatial data analysis
Abstract: The existing indicators related to spatial association, especially the K function, can measure only the same dimension of vector data, such as points, lines and polygons, respectively. We develop four new indicators that can anlayze and model spatial association for the mixture of different dimensions of vector adata, such as lines and points, points and polygons, lines and polygons. The four indicators can measure the spatial association between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the assoication between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the association of temples and villages on land-use change at multiple distance scales in the Guoluo Tibetan Autonomous Prefecture in Qinghai Province, PR China. Global indicators show that temples are positively associated with land-use change at large spatial distances (e.g., >6000m), while the association between villages and land-use change is insignifiant at all distance scales. Thus temples, as religious and cultural centers, have a stronger association with land-use change than the places where people live. However, local indicators show that these associations vary significantly in different sub-areas of the study region. Furthermore, the association of temples with land-use change is also dependent on the specific type of land-use change. The case study demonstrates that the presented indicators are powerful tools for analyzing the spatial association between points and polygons.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58134
Title: Increasing the accuracy of nitrogen dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics
Author: D P Robinson, C D Lloyd, J M McKinley
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Geostatistics, GWR, SKIm, Nitrogen dioxide, Air pollution
Abstract: Nitrogen dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult ot map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by differetn laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKIm). SK and OK make use of the primary variable only. SKIm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was oxides of nitrogen (NOx) derived from dispersion modelling ouputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKIm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKIm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKIm was beneficial in this study.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58133
Title: Research on the influence of site factors on the expansion of construction land in the Pearl River Delta, China: By using GIS and remote sensing
Author: Yuyao Ye, Hongou Zhang, Kai Liu, Qitao Wu
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: site factor, construction land, The Pearl River delta, China, GIS, Remote sensing, TM
Abstract: Landsat TM images of the Pearl River Delta taken in 1988, 1998 and 2006 are used to explore the site factors that influence the construction land expansion in this study. Several site factors, including landscape types and the distances to roads, coastlines, or city centers, had significant impacts on the expansion of construction land, influencing the direction, scale and intensity of the expansion. The site factors serve as important natural and spatial indictors of the preferable locales for construction alnd expansion, describing tendencies to expand to locations in sururbs, plains and areas near roads or coastlines.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58132
Title: Determination of snow cover from MODIS data for the Tibetan plateau region
Author: Bo-Hui Tang, Basanta Shrestha, Zhao-Liang Li, Gaohuan Liu, Hua Ouyang Deo Raj Gurung, Amarnath Giriraj, Khun San Aung
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Snow cover, NDSI, NDCI, Atmospheric and topographic correction, MODIS
Abstract: This paper addresses a snow-mapping algorithm for the Tibetan Plateau region using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Accounting for the effects of the atmosphere and terrain on the satelilte observations at the top of the atmosphere (TOA), particularly in the rugged Tibetan Plateau region, the surface reflectance is retrieved from the TOA reflectance after atmospheric and topographic corrections. To reduce the effect of the misclassification of snow and cloud cover, a normalized difference cloud index (NDCI) model is proposed to discriminate snow/cloud pixels, separate from the MODIS cloud mask product MOD35. The MODIS land surface temperature (LST) product MOD11_L2 is also used to ensure better accuracy of the snow cover classification. Comparisons of the resulting snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover product MOD10_L2 for the Mount Everest region for different seasons in 2002, show that the MODIS snow cover product MOD10_L2 overestimates the snow cover with relative error ranging from 20.1% to 55.7%, whereas the proposed algorithm estimates the snow cover more accurately with relative error varying from 0.3% to 9.8%. Comparisons of the snow cover estimated with the proposed algorithm and those obtained from MOD10_L2 product with in situ measurements over the Hindu Kush-Himalayan (HKH) region for December 2003 and January 2004 (the snowy seasons) indicate that the proposed algorithm can map the snow cover more accuretly with greater than 90% agreement.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58131
Title: Discharge and suspended sediment flux estimated along the mainstream of the Amazon and the Madeira Rivers (from in situ and MODIS Satellite Data)
Author: S Mangiarotti J M Martinez, M P Bonnet, D C Buarque, N Filizola, P Mazzega
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Suspended sediments, Remote sensing, Sediment transport, Amazonia Basin, Statistical modelling
Abstract: Water and suspended sediment fluxes are considering during the period 2000-2008 in a region including the full Amazon River from the confluence of the Negro River to Santarem, the end part of the Solimoes River, and the lower part of the Madeira River. Three types of data are used: water discharge estimated from field measurements, and suspended sediment obtained from field measurements and derived from MODIS satellite data. A generalized least square method including a propagating term is developed in order to propagate the signal upward and downward the river. The approach is introduced and tested. Several experiments are considered in order, first, to estimate the ability to propagate the signal from stations located before the confluences of Negro and Madeira Ribers to stations located on the Amazon River; second to investigate the possibility to propagate the signal along the Amazon River which dynamics is coupled with floodplains dynamics; and third produce optimal solutions of water and sediment fluxes. For each experiment, the influence of field and satellite data is compared. The approach is efficient in the upper part of the region of study where the Solimoes, the Negro and the Madeira Rivers meet and fails in the lower part of the region where interactions between Amazon River and floodplains play an important role on the fluxes ' dynamics. The optimal experiment includes in situ and satellite data from all the stations available and is used to analyse the recent evolution of suspended sediment flux along the Amazon River and its interaction with the large coupled floodplains. A high accumulation rate is observed during the 200-2002 period, followed by decreasing rates until 2005 and by increasing values in 2006 and 2007. Our results suggest that floodplains extending along a river reach of 390 km-long between Itacoatiara and Obidos trap about 15% of the suspended sediment flux passing at Obidos. The simulated deposition rate is of about 0.3 Mt km-1yr-1 correspondign to an accretion rate of about 27 mm yr-1.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58130
Title: Exploratory spatial data anlysis of global MODIS active fire data
Author: D Oom, J M C Pereira
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Spatial data analysis, Vegetation fires, Global, MODIS
Abstract: We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.50 resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p =0.001,? =0.05)for Moran ' s 1 indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58129
Title: Diurnal rainfall varaibility over the upper blue Nile basin: A remote sensing based approach
Author: Tom Rientjes, Alemseged Tamiru Haile, Ayele Almaw Fenta
Editor: F van der Meer
Year: 2013
Publisher: Elsevier, Vol 21, April 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Diurnal rainfall, TRMM TMI, TRMM PR, Upper Blue Nile
Abstract: In this study we aim to assess the diurnal cycle of rainfall across the Upper Blue Nile (UBN) basin using satellite observations from Tropical Rainfall measuring Mission (TRMM). Seven years (2002-2008) of Precipitation Radar (PR) and TRMM Microwave Imager (TM) data are used and analyses are based on GIS operations and simple statistical techniqes. Observations from PR and TMI reveal that over most parts of the basin area, the rainfall occurrence and conditional mean rain rate are highest between mid- and late-afternoon (15:00-18:00 LST). Exceptions to this are the south-west and south - eastern parts of the basin area and the Lake Tana basin where midnight and early morning maxima are observed. Along the Blue Nile River gorge the rainfall occurrence and the conditional mean rain rate are highest during the night (20:00 -23:00 LST). Orographic effects by largre scale variation of topography, elevation and the presence of the UBN river gorge were assessed taking two transects across the basin. Along transects from north to south and from east to west results indicate increased rainfall with increase of elevation whereas areas on hte windward side of the high mountain ranges receive higher amount of rainfall than areas on the leeward side. As such, mountain ranges and elevation affect the rainfall distribution resulting in rain shadow effect in the north-eastern parts of Choke-mountain and the ridges in the north-east of the basin. Moreover, a direct relation between rainfall occurrence and elevation is observed specifically for 17:00-18:00 LST. Further, results indicate that the rainfall distribution in the deeply incised and wide river gorge is affected with relatively low rainfall occurrence adn low mean rainfall rates in the gorge areas. Seasonal mean rainfall depth is highest in the south-west area and central highlands of the basin while areas in the north, north-east and along the Blue Nile gorge receive the least amount of rainfall. Statistical results of this work show that he diurnal cycle of rainfall occurrence from TRMM estimates show significant correlation with the ground observations at 95% confidence level. In the UBN basin, the PR conditional mean rain rate estimates are closer to the ground observations than the TMI. Analysis on mean wet season rainfall maount indicates that PR generally underestimates and TMI overestimates the ground observed rainfall.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None