ID: 53032
Title: Assessment of vegetation vulnerability to ENSO warm events over Africa
Author: Pavel Propastin, Lucien Fotso, Martin Kappas
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: El-Nino, Remote sensing, Vegetation vulnerability, Africa
Abstract: The study investigates the vulnerability of vegetation over Africa to El-Nino Southern Oscillation (ENSO) events using the moving window statistical correlation analysis technique. The correlation anlaysis was done between Normalized Difference Vegetation Index (NDVI) data from Advanced Very High Resolution Radiometer (AVHRR) and an ENSO index, namely Multivariate ENSO Index (MEI). The study develops a new monitoring approach (ENSO vulnerability assessment system) to quantify the relationships between monthly maximum NDVI anomalies and their month-to-month correlations with the ENSO indices for the vegetative land areas of Africa. The data used in this study was for the period 1982-2006. The new monitoring approach was used in the assessment of the long-time vegetation sensitivity to the ENSO warm events that occurred during the study period. A map of Africa indicating the vegetation vulnerability to ENSO is produced. Different areas of vegetation vulnerability are identified within the main vegetation cover classes. For the African vegetative land, 16% of the total area was characterized by moderate vulnerability of vegetation to El-Nino, whereas 1.18% showed high vulnerability. Results suggest that the vulnerability of vegetative land surfaces across Africa to climate extremes, such as ENSO depends considerably on the vegetation type. In particular, results show that areas of equatorial rainforest are more resistant to drought stress than the wooded and non-wooded vegetation categories.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53031
Title: Multispectral remote sensing for rainfall detection and estimation at the source of the Blue Nile River
Author: Alemseged Tamiru Haile, Tom Rientjes, Ambro Gieske, Mekonnen Gebremichael
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Rainfall detection, Rainfall estimation, MSG-2, TRMM PR, Blue Nile
Abstract: Most remote sensing based rainfall products have spatial resolutions > 0.250 and temporal resolutions > 1 day which are coarser than what is typically needed in hydrology. In this study, satellite data obtained from the precipitation radar (PR) of the Tropical Rainfall Measuring Mission (TRMM) which acquires data at 5 km resolution once or twice a day and from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) of the Meteosat Second Generation (MSG-2) which acquires data at 3 km resolution at 15 min interval. We evaluated three MSG-2 channels for rainfall detection in the Upper Blue Nile area in Ethiopia by the following indices: (1) 10.8 ?m brightness temperature, (2) rate of change of the 10.8 ?m brightness temperature, (3) space gradient of the 10.8 ?m brightness temperature, (4) brightness temperature difference (BTD) at the 10.8 and 6.2 ?m and (5) BTD at the 10.8 and 12.0 ?m channels. The evaluation was made through categorical statistics that are bias, probability of detection, false alarm ratio and Heidke skill score. In this work also, an exponential model was developed for thermal infrared based rainfall estimation. The model was evaluated using observations from a rain guage network that we installed at the source of the Blue Nile River in Ethiopia.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53030
Title: Spatio-temporal analyses of correlation between NOAA satellite RFE and weather stations ' rainfall record in Ethiopia
Author: Ephrem Gebremariam Beyene, Bernd Meissner
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: RFE validation, Satellite and weather stations ' Rainfall Data, Monitoring food security using remotely sensed data
Abstract: The study analysed monthly satellite RFE (rainfall estimates ) from NOAA (National Atmospheric and Oceanic Administration) and monthly rainfall records (January 1996- December 2006) collected from weather stations by NMA (National Meterological Agency of Ethiopia). Can the RFE data be used reliably to analyse seasonal rainfall variability? After doing spatio-temporal analyses of the two datasets, a significant correlation during the important rainy seasons, summer and spring and a low correlation during winter was shown. In conclusion the RFE images can be used reliably for early warning systems in the country and to empower decision makers on the consequences caused by the changes in teh magnitude, timing, duration, and frequency of rainfall deficits on different spatial and temporal scales.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53029
Title: Image mining for drought monitoring in eastern Africa using Meteosat SEVIRI data
Author: Coco M. Rulinda, Wietske Bijker, Alfred Stein
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Image mining, NDVI, Vegetation monitoring, Drought, Meteosat SEVIRI, Eastern Africa
Abstract: We propose an image mining approach to monitor drought using Meteosat Spinning Enhanced Visible and InfraRed Imager (SEVIRI) image data. SEVIRI image data provide frequent Normalized Difference Vegetation Index (NDVI) time series which are important to assess the evolution of drought conditions. Vegetation condition is characterized in space by the deviation of the current NDVI observations at locations from their temporal mean values. In this paper we assume a gradual evolution of vegetation stress caused by drought and hence address this aspect with the use of a membership function applied to vegetation stress values to model drought. Our approach is implemented on subset image data of eastern Africa. Vegetated sites in a drought prone area of the region serve as an illustration using the drought spell at the end of 2002. This stuyd shows that the use of a membership function allows capturing the spell at the end of 2005. This study shows that the use of a membership function allows capturing the gradual evolution of drought and can be used to model drought from observed vegetation condiitons.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53028
Title: Diurnal cycle of convective activity over the west of Central Africa based on Meteosat images
Author: Derbetini A. Vondou, Armand Nzeukou, F. Mkankam Kamga
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Cloud fraction, Convection, Diurnal cycle, Meteosat
Abstract: The diurnal cycle of deep convective activity over the West of Central Africa was investigated using Meteosat 7 data over a period of 5 years (1998-2002). An index of deep convective activity was built by thresholding to brightness temperatures less than 235 K to detect deep convective activity. It was found that deep convection over the ocntiguous study area has large diurnal variations with considerable regional features. Convective activity over the land exhibits a coherent diurnal cycle characterized by a rapid afternoon buildup, and a more gradual nighttime decrease. Over the sea, the diurnal cycle is weak and peaks around noon. The results of the study suggest that both topography and surface conditions are critical factors in the spatial and temporal patterns of the diurnal cycle of convection.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53027
Title: Estimation of sugarcane leaf nitrogen concentraion using in situ spectroscopy
Author: Elfatih M. Abdel-Rahman, Fethi B. Ahmed, Maurits Van den Berg
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: In situ spectroscopy, Hyperspectral, Sugarcane, Nitrogen
Abstract: The aim of this study was to explore the use of in situ spectroscopy for estimating sugarcane leaf nitrogen (N) concentration. Leaf spectral reflectance was measured using a field spectroradiometer in the 350-2500 nm range from sugarcane variety N19 crops of 6-7 months old under on-farm conditions. Lab-determined leaf N concentrations of the samples taken ranged from 1.00% to 1.55%. Vegetation indices based on simple ratio (SR); viz. SR (743, 1316), SR (743, 1317) and SR (741, 1323) generated from first-order derivatives of leaf reflectance showed the best correlation with leaf N concentration, with r2 values of 0.76 (P<0.01), 0.75 (P<0.01) and 0.74 (P<0.01), respectively. The root mean square errors of prediction (RMSEP) using a leave-one-out cross validation method were 0.089% (P<0.01) for SR (743, 1316), 0.092% (P<0.01) for SR (743,317) and 0.084% (P<0.01) for SR (741, 1323). These results suggest that the in situ spectroscopy has potential use in predicting sugarcane leaf N.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53026
Title: A comparison of regression tree ensembles: Predicting Sirex noctilio induced water stress in Pinus patula forests of KwaZulu-Natal, South Africa
Author: R. Ismail, O. Mutanga
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Regression trees, Ensembles, Random forest, Sirex noctilio
Abstract: In this study we compared the performance of regression tree ensembles using hyperspectral data. More specifically, we compared the performance of bagging, boosting and random forest to predict Sirex noctilio induced water stress in Pinus patula trees using nine spectral parameters derived from hyperspectral data. Results from the study show that the random forest ensemble achieved the best overall performance (R2 = 0.73) and that the predictive accuracy of the ensemble was statistically different (p<0.001) from bagging and boosting. Additionally, by using random forest as a wrapper we simplified the modeling process and identified the minimum number (n=2) of spectral parameters that offered the best overall predictive accuracy (R2=0.76). The water index ad Ratio 975 had the best ability to assay the water status of S,. noctilio infested trees thus making it possible to remotely predict and quantify the severity of damage caused by the wasp.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53025
Title: Development and implementation of an interactive Spatial Decision Support System for decision makers in Benin to evaluate agricultural land resources-Case study:AGROLAND
Author: Rainer Laudien, Mathias Pofagi, Julia Roehrig
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: SDSS, Multicriteria analysis, Software development, Agricultural marginality, Food security
Abstract: The sustainable use of agricultural land resources with concern to food security is essential, particularly in developing countries, where yields depend primarily on the biophysical conditions. To support decision making concerning national agricultural land usage, a computer based Spatial Decision Support System (SDSS) was developed. Within this SDSS, named AGROLAND, decision makers are able to visualise and evaluate biophysical agricultural land resources based on a marginality index for agricultural land use (MI). Data derived from remote sensing like MODIS or SRTM are thereby interesting and embolden sources to derive natural constraints. MI is calculated by using a fuzzy logic determination algorithm within the interactive SDSS. In AGROLAND, possibilities of user interactions during runtime as well as advanced model-based raster analyses are implemented to generate MI. This paper explicates (i) the development of AGROLAND for Benin, and (ii) the system implementation in institutions optimizing management strategies on the national scale.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53024
Title: Potentiality of optical and radar satellite data at high spatio-temporal resolutions for the monitoring of irrigated wheat crops in Morocco
Author: R. Hadria, B. Duchemin, L. Jarlan, G. Dedieu, F.Baup, S.Khabba, A. Olioso, T. Le Toan
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Remote sensing, FORMOSAT-2, ASAR, Semi-arid, Crop monitoring, wheat, Biomass water content
Abstract: The potential of FORMOSAT-2 and ENVISAT/ASAR for the monitoring of irrigated wheat crops over Tensift/Marrakech semi-arid plain in Morocco is investigated. The green leaf area index (GLAI) was obtained from time series of vegetation index acquired by the FORMOSAT-2 instrument with a 25% accuracy. This information was then incorporated into a canopy functioning model to provide spatial estimates of GLAI, aerial biomass and top-soil moisture. These outputs were evaluated by comparing them to ground data collected on eight wheat fields monitored during the 2005-2006 agricultural season. The model accurately simulates the time courses of GLAI and aerial biomass during the vegetative phase. Finally, we anlaysed the spatio-temporal variations of ASAR backscattering co-polarization ratio (?0HH/VV) as a function of biomass water content on the basis of simulations performed over 69 other wheat fields. The purpose of such analysis is to retrieve this last biophysical variable from ASAR images. The sensitivity of ASAR data to vegetation appears to be deteriorated by the sensitivity of ?0HH/VV to the variability of soil conditions encountered in the study area (roughness and moisture).
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53023
Title: Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms
Author: J.R. Otukei, T. Blaschke
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Decision trees, Support vector machines, Maximum likelihood classifier, Land cover change
Abstract: Land cover change assessment is one of the main applications of remote sensed data. A number of pixel based classification algorithms have been developed over the past years for the analysis of remotely sensed data. The most notable include the maximum likelihood classifier (MLC), support vector machines (SVMs) and the decision trees (DTs). The DTs in particular offer advantages not provided by other approaches. They are computationally fast and make no statistical assumptions regarding the distribution of data. The challenge to using DTs lies in the determination of the "best" tree structure and the decision boundaries. Recent developments in the field of data mining have however, provided an alternative for overcoming the above shortcomings. In this study, we analysed the potential of DTs as one technique for data mining for the analysis of the 1986 and 2001 Landsat TM and ETM+ datasets, respectively. The results were compared with those obtained using SVMs, and MLC. Overall, acceptable accuracies of over 85% were obtained in all the cases. In general, the DTs performed bette than both MLC and SVMs.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53022
Title: Predicting forest structural attributes using ancillary data and ASTER satellite data
Author: M.T.Gebreslasie, F.B.Ahmed, Jan A.N.Van Aardt
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: ASTER dataset, Spectral vegetation indices, Forest structural attributes
Abstract: This study assessed the suitability of both visible and shortwave infrared ASTER data and vegetation indices for estimating forest structural attributes of Eucalyptus species in the southern KwaZulu Natal, South Africa. The empirical relationships between forest structural attributes and ASTER data were derived using stepwise multiple regression analysis; Modified Soil Adjusted Vegetation Index (MSVI) and band 3 were selected for analysis as it showed best relationships with forest structural attributes. The ancillary data such as age and site index were also included in teh analysis. Although the results of this study have indicated statistically significant relationships between the forest structural attributes and the ASTER data in the plantation forests stands with adjusted R2-values for volume, basal area (BA), stem per hectare (SPHA), and tree height of 0.51, 0.67, 0.65 and 0.52, respectively, but these results are not suitable for operational purpose in a forest company. However, the structural forest attribute predictions were markedly improved after incorporating age and site index as predictor variable. R2-values for the stands increased by 42%, 20.2%, 16.8% and 42.2% for volume, basal area, SPHA, and tree height, respectively. These results imply that ASTER satellite data alone are not applicable to forest structural attribute estimation; however, ASTER data can provide useful information if it is used in conjunction with age and site index data for forest structural attribute estimation in plantation forests.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53021
Title: A preliminary assessment of NigeriaSat-1 for sustainable mangrove forest monitoring
Author: Ayobami T. Salami, Joseph Akinyede, Alfred de Gier
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Mangrove assessment, Wetland, NigeriaSat-1, DMC, Sustainable monitoring
Abstract: Mangroves constitute an area of great ecological importance and regular assessment and monitoring of this ecosystem is an integral part of environmental management plan. The difficulty of access for ground survey has often limited the frequency of assessment of mangroves and remote sensing methods therefore provide a veritable means of assessment. However, accessibility to remotely sensed data as well as the cost have been major constraints for mangrove assessment in the developing countries. The launching of small satellites by some developing countries may therefore provide a solution to this problem. This paper is an attempt to evaluate the capability of NigeriaSat -1 which is one of the Disaster Management Constellation (DMC) small satellites for generation of baseline information on cover types and areal extents within the mangrove zone in Nigeria. This is important since cover information is always the first step for conservation and management. The study shows that the results obtained from NigeriaSat-1 have comparable accuracy with ASTER and Landsat ETM+. The findings documented in this paper could serve as a springboard for organized wetland management in Nigeria in particular and West Africa sub-region in general.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53020
Title: Patterns and dynamics of land-cover changes since the 1960s over three experimental areas in Mali
Author: Denis Ruelland, Florent Levavasseur, Antoine Tribotte
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Land-use/cover changes (LUCC), Remote sensing, Corona, Landsat, SPOT, Mali
Abstract: This paper addresses a critical need to provide a better quantitative understanding of how the Sudano-Sahelian environments actually been changing under the combined impacts of climate variability and the increasing pressure of human activity. Using Corona, Landsat and SPOT satellite images of three areas (90-250 km2) along the climatic gradient of a large catchment in Mali, significant land-cover changes since the 1960s were identified through visual interpretation of images following a common classification scheme. The pattern and trajectory of changes differed markedly between the three areas studied. Overall, the 40-year trends indicate:(i) in the Sahelian area, a steady increase in croplands and erosional surfaces with sparse vegetation and a corresponding drastic reduction in woody covers; (ii) in the Sudano-Sahelian area, a large increase in croplands and a moderate reduction in woody covers; (iii)in the Sudanian area, agricultural extension, deforestation, but also reforestation and land rehabilitation, due to alternating periods of exploitation and recolonization by natural vegetation. These patterns and dynamics can be parially explained by the differences in demographic pressure between the three areas. They also highlight differences in response to anthropogenic and climate forcings depending on the areas ' respective climatic and environmental endowments. This study is a first step towards an in-depth analysis of the various forces and processes driving these changes and the formulation of prospective environmental scenarious for the catchment in line with hydrological studies.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53019
Title: Vegetation cover degradation assessment in Madagascar savanna based on trend analysis of MODIS NDVI time series
Author: Anne Jacquin, David Sheeren, Jean-Paul Lacombe
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Supplement 1, February 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: MODIS, Time series, STL, Change, Trend, Savanna, Phenological indicator
Abstract: Like other African countries, Madagascar is concerned by vegetation cover degradation especially in savanna ecosystems. In this article, we describe an approach to quantify and localise savanna vegetation cover degradation. To this end, we analyse using STL decomposition method the trends measured between 2000 and 2007 of two phenological indicators which are derived from NDVI MODIS time series and characterizing vegetation activity during the growing season. Three types of trend were observed-null, positive or negative-over the study period with which we can associate a state of vegetation cover degradation. Future work will provide validation of this result. Next a comparison between the spatial variations of vegetation cover degradation and fire pressure for the same period should improve knowledge on the effect of fire on savanna vegetation activity. This information will be useful for local managers in order to implement savanna management strategies.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53018
Title: Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment
Author: K. Meusburger, N. Konz, M.Schaub, C. Alewell
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Soil erosion, Mountain, Remote sensing, Cs-137, USLE, PESERA, Erosion model
Abstract: The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scare forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha-1 a -1. In conclusion field measurements of Cs-137confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.
Location: 231
Literature cited 1: None
Literature cited 2: None