ID: 58113
Title: A statistical simulation model for positional error of line features in Geographic Information Systems (GIS)
Author: Xiaohua Tong, Tong Sun, Junyi Fan, Michael F Goodchild, Wenzhong Shi
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: Positional error, Line feature, Probability, Simulation, GIS
Abstract: This paper presents a new error band model, the statistical simulation error model, for describing the positional error of line features by incorporating both analytical and simulation methods. In this study, line features include line segments, polylines, and polygons. In existing error models, an infinite number of points on the line segment are considered as the stochastic variables and the error band of a line segment is obtained from the union of all intermediate points on the line segment, while that of a polyline/polygon is obtained from the union of all error bands of the composite line segments. Our proposed error band model, however, regards the entire line feature (line segment/polyline/polygon) as the stochastic variable, instead of the infinite number of points on the line segment. Based solely on the statistical characteristics of the endpoints of the line feature and the predefined confidence level, our proposed error model is created by a simulation method that integrates a population of line segments/polylines/polygons computed from the entire solution set of the error model ' s defining equation.
A comprehensive comparison of the proposed and existing error band models is carried out through both simualted and practical experiments. The experimental results show the following: (1) For line segments, the proposed standard statistically simulated error band matches that of exisiting error models (for example, the G-band). Further, it is found that a scaled G-band with a specific scale factor (e.g., Square rootr of X24 (?)) matches the proposed statistically simulated error band with probability (1- ?)x 100%. (2) For polylines and polygons, if we correlate the errors of all the endpoints of the polyline/polygon, there is a marked different between the proposed statistically simulated error band and existing error bands. The reason for the difference is explained as follows. The existing error model defines the error band of a polyline/polygon as the union of all error bands of the composite line segments, thereby only accounting for the correlation between the two endpoints of each composite line segment. However, our proposed error band model considers the entire polyline/polygon as a whole by accounting for the variance-covariance matrix of all vertices of the polyline/polygon when constructing the statistically simulated error band.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58112
Title: Evaluating SAR polarization modes at L-band for forest classification purposes in Eastern Amazon, Brazil
Author: Veraldo Liesenberg, Richard Gloaguen
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: Polarization modes, Secondary forest, Successional forest, ALOS/PALSAR, SVM, Eastern Amazon
Abstract: Single, interferometric dual, and quad-polarization mode data were evaluated for the characterization and calssification of seven land use classes in an area with shifting cultivation practices located in the Eastern Amazon (Brazil). The Advanced Land-Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data were acquired during a six month interval. A clear-sky Landsat-5/TM image acquired at the same period was used as additional ground reference and as ancillary input data in the calssification scheme. We evaluate backscattering intensity, polarimetric features, interferometric coherence and texture parameters for classification purposes using support vector machines (SVM) and feature selection. Results showed that the forest classes were characterized by low temporal backscattering intensity variability, low coherence and high entropy. Quad polarization mode performed better than dual and single polarizations but overall accuracies remain low and were affected by precipitation events on the data and prior SAR data acquisition. Misclassification were reduced by integrating Landsat data and an overall accuracy of 85% was attained. The integration of Landsat to both quad and dual polarization modes showed similarity at the 5% significance level. SVM was not affected by SAR dimensionality and feature selection technique reveals that co-polarized channels as well as SAR derived parameters such as Alpha-Entropy decomposition were important ranked features after Landsat ' near-infrared and green bands. We show that in absence of Landsat data, polarimeteric features extracted from quad-polarization L-band increase classification accuracies when compared to single and dual polarization alone. We argue that the joint analysis of SAR and their derived parameters with optical data performs even better and thus encourage the further development of joint techniques under the Reducing Emissions from Deforestation and Degradation (REDD) mechanism.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58111
Title: Predicting Thaumastocoris peregrinus damage using narrow band normalized indices and hyperspectral indices using fiedl spectra resampled to the Hyperion sensor
Author: Z Oumar, O Mutanga, R Ismail
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: Thaumastocoris peregrinus, PLS regression, Normalized indices, Hyperspectral indices
Abstract: Thaumastocoris peregrinus (T. peregrinus) is a sap sucking insect that feeds on Eucalyptus leaves. It poses a threat to the forest industry by reducing the photosynthetic ability of the tree, resulting in stunted growth and even death of severely infested trees. Remote sensing techniques offer the potential to detect and map T. pereginus infestations in plantation forests using current operational hyperspectral scanners. This study resampled field spectral data measured from a field spectrometer to the band settings of the Hyperion sensor in order to assess its potential in predicting T. peregrinus damage. Normalized indices based on NDVI ratios were calculated using the resamples visible and near-infrared bands of the Hyperion sensor to assess its utility in predicting T. peregrinus damage using Partial Least Squares (PLS) regression. The top 20 normalized indices were based on specific biochemical absorption features that predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.63 on an independent test dataset. The top 20 indices were located in the near-infrared region between 803.3 nm and 894.9 nm. Twenty three previously published hyperspectral indices which have been used to assess stress in vegetation were also used to predict T. peregrinus damage and resulted in a mean bootstrapped R2 value of 0.59 on an independent test dataset. The datasets were combined to assess its collective strength in predicting T. peregrinus damage and significant indices were chosen based on variable importance scores (VIP) and were then entered into a PLS model. The indices chosen by VIP predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.71 on an independent test dataset. A greedy backward variable selection model was further tested on the VIP selected indices in order to find the best subset of indices with the best prodictive accuracy. The greedy backward variable selection model identified 3 indices and performed the best by predicting damage with an R2 value of 0.74 with the lowest RMSE of 1.30% on an independent test dataset. The best three indices identified include the anthocyanin reflectance index, carotenoid reflectance index and the normalized index calculated at 864.4 and 884.7nm. Individual relationships between these indices and T. peregrinus damage indicate that high correlations are obtained with the inclusion of a few severely interested tress in the sample size. When the severely infested trees were removed from the study, the normalized index (864.4 and 884.7 nm) and the anthocyanin reflectance index still yielded significant correlations at the 99% confidence interval. This study indicates the significant correlations at the 99% confidence interval. This study indicates the significant of normalized indices and spectral indices calculated from the visible and near-infrared bands in hyperspectral data for the prediction of T. peregrinus damage.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58110
Title: A visible band index for remote sensing leaf chlorophyll content at the canopy scale
Author: E Raymond Hunt Jr, Paul C Doraiswamy, James E McMurtrey, Craig S T Daughtry, Eileen M Perry, Bakhyt Akhmedov
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: Spectral indices, Triangular greenness index (TGI), Airborne Visible/Infrared iimaging, Spectrometer (AVIRIS), PROSPECT, SAIL, Landsat Thematic Mapper (TM), Nitrogen fertilization, Zea mays
Abstract: Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. The triangular greenness index (TGI) was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at (670 nm, R670), (550 nm, R550), and (480 nm, R480), where R? is the spectral reflectance at wavelength of 670, 550 and 480, respectively. The equation is TGI = -0.5[(670-480) ( R670 - R550) - (670-550) (R670 - R480 )]. In 1999, investigators funded by NASA ' s Earth Observations Commercialization and Applications Program collaborated on a nitrogen experiment with irrigated maize in Nebraska. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and Landsat 5 Thematic Mapper (TM) data were acquired along with leaf chlorophyll meter and other data on three dates in July during late vegetative growth and early reproductive growth. TGI was consistently correlated with plot-averaged chlorophyll - meter values at the spectral resolutions of AVIRIS, Landsat TM, and digital cameras. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, leaf area index (LAI) and soil type at low crop LAI, whereas high LAI and canopy closure, TGI was only affected by leaf chlorophyll content. Therefore, TGI may be the best spectral index to detect crop nitrogen requirements with low-cost digital cameras mounted on low-altitude airborne platforms.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58109
Title: Assessing urbanisation effects on rainfall-runoff using a remote sensing supported modelling strategy
Author: B Verbeiren, T Van De Voorde, F Canters, M Binard, Y Cornet, O Batelaan
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: Consistent urban trajectories, sealed surface estimates, Rainfall-runoff modelling, Multi-temporal EO parameterisation
Abstract: This paper aims at developing a methodology for assessing urban dynamics in urban catchments and the related impact on hydrology. Using a multi-temporal remote sensing supported hydrological modelling approach an improved simulation of runoff for urban areas is targeted. A time-series of five medium resolution urban masks and corresponding sub-pixel sealed surface proportions maps was generated from Landsat and SPOT imagery. The consistency of the urban mask and sealed surface proportion timeseries was imposed throiugh an urban change trajectory of remote sensing derived information of detailed urban land use and sealed surface characteritics.
A first scenario compares the original land-use class based approach for hydrological parameterisation with a remote sensing sub-pixel based approach. A second scenario assess the impact of urban growth on hydrology. Study area is the Tolka River basin in Dublin, Ireland.
The grid-based approach of WetSpa enables an optimal use of the spatially distributed properties of remote sensing derived input.
Though change trajectory analysis remains little used in urban studies it is shown to be of utmost importance in case of time series analysis. The analysis enabled to assign a rational trajectory to 99% of all pixels. The study showed taht consistent remote sensing derived land-use maps are preferred over alternative sources (such as CORINE) to avoid over-estimation errors, interpretation inconsistencies and assure enouigh spatial detail for urban studies. Scenario 1 reveals that both the class and remote sensing sub-pixel based approaches are able to simulate discharges at the catchment outlet in an equally satisfactory way, but the sub-pixel approach yields considerably higher peak discharges. The result confirms the importance of detailed information on the sealed surface proportion for hydrological simulations in urbanised catchments. In addition a major advantage with respect ot hydrological parameterisation using remote sensing is the fact that it is site-and period-specific. Regarding the assessment of the impact of urbanisation (scenario 2) the hydrological simulations revealed that the steady urban growth in the Tolka basin between 1988 and 2006 had a considerable impact on peak discharges. Additionally, the hydrological response is quicker as a result of urbanisation. Spatially distributed surface runoff maps identify the zones with high runoff production.
It is evident that this type of information is important for urban water management and decision makers. The results of the remote sensing supported modelling approach do not only indicate increased volumes due to urbanisation, but also identifies the locations where the most relevant impacts took place.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58108
Title: Retrieval of leaf area index in alpine wetlands using a two-layer canopy reflectance model
Author: Binbin He, Xingwen Quan, Minfeng Xing
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: Leaf area index, ACRM radiative transfer model, Look -up table algorithm, Sensitive analysis of key model parameters classification, Regularization techniques
Abstract: In this paper, we focussed on the retrieval of the LAI in an alpine wetland located in western part of China in late August and early July 2011. A two-layer canopy reflectance model (ACRM) was used to establish the relationships between the LAI and the refelctance of near-infrared (NIR) and red (RED) wavebands. The reflectance data were derived from Landsat TM L1T product and the Terra and Aqua MODIS 16-day and 8-day composite reflectance products (MOD/MYD09) at 250 m resolution . Due to the lack of the information about some major input parameters for ACRM, which are sensitive to model outputs in the reflectance of NIR and RED wavebands, the inverse problem was ill-posed. To overcome this problem, a method of increasing the sensitivity of the LAI while reducing the influence of other model free parameters based on the study of free parameters ' sensitivity to the ACRM outputs and the region ' s features was studied. The area of interest was divided into two parts using the approximately statistic normalized difference vegetation index (NDVI) value around 0.5. One part was sparse vegetation (0.1<NDVI<0.5), which is more sensitive to soil background effects and less sensitive to the canopy biophysical and biochemical variables. The other part was dense vegetation (0.5 <NDVI < 1.0), which is less sensitive to soil background effects and more sensitive to plant canopies and leaf parameters. Then, the relationships of ?nir- LAI and ?red - LAI were established using a look-up table algorithm for the two parts. Furthermore, a regularization technique for fast pixel-wise retrieval was introduced to reduce the elements of LUT sets while maintaining a relatively high accuray. The results were very promising compared to the field measured LAI values that the correlation (R2) of the measured LAI values and retrieved LAI valkues reached 0.95, and the root-mean-square deviation (RMSD) was 0.33 for lagte August 2011, while the R2 reached 0.82 and RMSD was 0.25 for early July 2011.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58107
Title: Modeling BVOC isoprene emissions based on a GIS and remote sensing database
Author: Man Sing Wong, Md. Latifur Rahman Sarker, Janet Nichol, Shun-cheng Lee, Hongwei Chen, Yiliang Wan, P W Chan
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: Biogenic volatile organic compounds, Foliar density, Leaf area index, Photosynthetically active radiation, Satellite image
Abstract: This paper presents a geographic information systems (GIS) model to relate biogenic volatile organic compounds (BVOCs) isoprene emissions to ecosystem type, as well as environmental drivers such as light intensity, temperature, landscape factor and foliar density. Data and techniques have recently become available which can permit new improved estimates of isoprene emissions over Hong Kong. The techniques are based on Guenther et al ' s (1993, 1999) model. The spatially detailed mapping of isoprene emissions over Hong Kong at a resolution of 100 m and a database has been constructed for retrieval of the isoprene maps from February 2007 to January 2008. This approach assigns emission rates directly to ecosystem types not to individual species, since unlike in temperate regions where one or two single species may dominate over large regions. Hong Kong ' s vegetation is extremely diverse with up to 300 different species in 1 ha. Field measurements of emissions by canister sampling obtained a range of ambient emissions according to different climatic conditions for Hong Kong ' s main ecosystem types in both urban and rural areas, and these were used for model validation. Results show the model-derviced isoprene flux to have high to moderate correlations with field observations (i.e. r2 = 0.77, r2 = 0.63, r2 = 0.37 for all 24 field measurements, subset for summer, and winter data, respectively) which indicate the robustness of the approach when applied to tropical forests at detailed level, as well as the promising role of remote sensing in isoprene in Hong Kong at detailed level. City planners and environmental authorities may use the derived models for estimating isoprene transportation, and its interaction with anthropogenic pollutants in urban areas.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58106
Title: Modelling the spectral response of the desert tree Prosopis tamarugo to water stress
Author: R O Chavez, J G P W Clevers, M Herold, M Ortiz, E Acevedo
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: Arid ecosystem, Radiative transfer model, Soil-leaf-Canopy, water stress, spectral reflectance, vegetation indcies, Remote sensing, Tamarugo, Atacama
Abstract: In this paper, we carried out a laboratory experiments to study changes in canopy reflectance of Tamarugo plants under controlled water stress. Tamarugo (Prosopis tamarugo Phil) is an endemic and endangered tree species adapted to the hyper-arid conditions of teh Atacama Desert, Northern Chile. Observed variation in reflectance during the day (due to leaf movements) as well as changes over the experimental period (due to water stress) were successfully modelled by using the Soil-Leaf-Canopy (SLC) radiative transfer model. Empirical canopy reflectance changes were mostly explained by the parameters leaf area index (LAI), leaf inclination distribution function (LIDF) and equivalent water thickness (EWT) as shown by the SLC simulations. Diurnal leaf movements observed in Tamarugo plants (as adaptation to decrease direct solar irradiation at the hottest time of the day) had an important effect on canopy reflectance and were explained by the LIDF parameter. The results suggest that remote sensing based assessment of this desert tree should consider LAI and canopy water content (CWC) as water stress indicators. Consequently, we tested fifteen different vegetation indices and spectral absorption features proposed in literature for detecting changes of LAI adn CWC, considering the effect of LIDF variations. A sensitivity analysis was carried ouit using SLC simulations with a broad range of LAI, LIDF variations. A sensitivity analysis was carried lout using SLC simulations with a broad range of LAI, LIDF, and EWT values. The Water Index was the most sensitive remote sensing feature for estimating CWC for values less than 0.036 g/cm2, while the area under the curve for the spectral range 910-1070 nm was most sensitive for values higher than 0.036 g/cm2. The red-edge chlorophyll index (CIred-edge) performed the best for estimating LAI. Diurnal leaf movements had an effect on all remote sensing features tested, particularly on those for detecting changes in CWC.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58105
Title: Evaluating post-disaster ecosystem resilience using MODIS GPP data
Author: Amy E Frazier, Chris S Renschler, Scott B Miles
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: Ecosystem resilience, Ecological capital, MODIS, GPP, ResilUS
Abstract: An integrated community resilience index (CRI) quantifies the status, exposure, and recovery of the physical, economic, and socio-cultural capital for a specific target community. However, most CRIs do not account for the recovery of ecosystem functioning after extreme events, even though many aspects of a community depend on the services provided by the natural environment. The primary goal of this study was to monitor the recovery of ecosystem functionality (ecological capital) using remote sensing -derived gross primary production (GPP) as an indicator of ' ecosystem-wellness ' and assess the effect of resilience of ecological capital on the recovery of a community via an integrated CRI. We developed a measure of ecosystem resilience using remotely sensed GPP data and applied the modeling prototype ResilUS in a pilot study for a four-parish coastal community in southwestern Louisiana. USA that was impacted by Hurricane Rita in 2005. The results illustrate that after such an extreme event, the recovery of ecological capital varies according to land use type and may take many months to return to full functionality. This variable recovery can potentially impact the recovery of certain businesses that rely heavily on ecosystem services such as agriculture, forestry, fisheries, and tourism.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58104
Title: Monitoring basin-scale land cover changes in Kagera Basin of Lake Victoria using ancillary data and remote sensing
Author: John E Wasige, Thomas A Groen, Eric Smaling, Victor Jetten
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: Historical analysis, Data integration, Land use/land cover changes, land degradation, GIS/remote sensing, eutrophication, Lake Victoria basin
Abstract: The Kagera Basin is a high value ecosystem in the Lake Victoria watershed because of the hydrological and food services it provides. The basin has faced large scale human induced land use and land cover changes (LUCC), but quantitative data is to date lacking. A combination of ancillary data and satellite imagery were interpreted to construct LUCC dynamics for the last century. This study is an initial step towards assessing the impact of LUCC on sustainable agriculture and water quality in the watershed. The results show that large trends of LUCC have rapidly occurred over the last 100 years. The most dominant LUCC process were grains in farmland areas (not detectable in 1901 to 60% in 2010) and a net reduction in dense forest (7% to 2.6%), woodlands (51% to 6.9%) and savannas (35% to 19.6%) between 1901 and 2010. Forest degradation rapidly occurred during 1974 and 1995 but the forest re-grew between 1995 and 2010 due to forest conservation efforts. Afforestation efforts have resulted in plantation forest increases between 1995 and 2010. The rates of LUCC observed are higher than those reported in Sub Saharan Africa (SSA) and other parts of the world. This is one of the few studies in SSA at a basin scale that combines multisource spatio-temporal data on land cover to enable long-term quantification of land cover changes. In the discussion we address future research needs for the area based on the results of this study. These research needs include quantifying the impacts of land cover change on nutrient and sediment dynamics, soil organic carbon stocks, and changes in biodiversity.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58103
Title: Methodology for estimating availability of cloud-free image composites: A case study for Southern Canada
Author: Fuqun Zhou, Aining 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: Cloud cover, Cloud fraction product, cloud-free images, cloud-free composite availability
Abstract: Image composites are often used for earth surface phenomena studies at regional or national level. The compromise between residual clouds and the length of compositing period is a necessary corollary ot the choice of satellite optical data for monitoring earth surface phenomena dynamics. This paper introduced a methodology for estimating availability of cloud-free image composites for optical sensors with various revisiting intervals, using MODIS MODO6 L2 cloud fraction product in the period of 2000-2008. The methodology starts with downscaling of the cloud fraction product to 1 km x 1km cloud cover binary images. The binary images are then used for the exploration of spatial and temporal characteristics of cloud dynamics, and subsequently for the simulation of cloud-free composite availability with various revisiting intervals of optical sensors. Using Canada ' s southern provinces as an application case, the study explored several factors important for the design of environmental monitoring system using optical sensors of earth observation, in particular, cloud dynamics and its inter-annual variability, sensor ' s revisiting intervals, and cloud-free threshold for targeting composites, While the cloud images used in the analysis are at 1 km x 1 km resolution, our anlaysis suggests that the simulated availabilities of cloud-free image composites may also provide reasonable estimates for optical sensors with higher than 1km x 1km resolution, though the closer to 1 km x 1km resolution the optical sensor, the more pertinent the application. Also, the methodology can be parameterised to different temporal period and different spatial region, depending on applications.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58102
Title: Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa
Author: Gaia Vaglio Laurin, Veraldo Liesenberg, Qi Chen, Leila Guerriero, Fabio Del Frate, Antonia Bartolini, David Coomes, Beccy Wilebore, Jeremy Lindsell, Riccardo Valentini
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, West Africa, Forests, SAR, Landsat AVNIR-2, texture
Abstract: The classification of tropical fragmented landscapes and moist foreted areas is a challenge due to the presence of a continuum of vegetation successional stages, persistent cloud cover and the presence of small patches of a continuum of vegetation sucessional stages, persistent cloud cover and the presence of small patches of different land cover types. To classify one such study area in West Africa we integrated the optical sensors Landsat Thematic Mapper (TM) and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) with the Phased Arrayed L-band SAR (PALSAR) sensor, the latter two on-board the Advanced Land Observation Satellite (ALOS), using traditional Maximum Likelihood (MLC) and Neural Networks (NN) classifiers. The impact of texture variables and the use of SAR to cope with optical data unavailability were also investigated. SAR and optical integrated data produced the best classification overall accuracies using both MLC and NN, respectively equal to 91.1% and 92.7% for TM and 95.6% and 97.5% for AVNIR-2. Texture information dervied fromoptical images was critical, improving results between 10.1% and 13.2%. In our study area, PALSAR alone was able to provide valuable information over the entire area: when the three forest classes were aggregrated, it achieved 75.7% (with MCL) and 78.1% (with NN) over all classification accuracies. The selected classification and processing methods resulted in fine and accurate vegetation mapping in a previously untested region, exploiting all available sensors synergies and highlights the advantages of each dataset.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58101
Title: Diverse responses of vegetation production to interannual summer drought in North America
Author: Chaoyang Wu, Jing M Chen
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: Summer drought, Soil moisture, forests, vegetation production, climate change
Abstract: Droughts are projected to occur more frequently with future climate change of rising temperature and low precipitation. However, its impact on regional and global vegetation production is not well understood, which in turn contributes to uncertainties to model carbon sequestration under drought scenarios. Using long-term continuous eddy covariance measurements (168 site-year). we present an analysis of the influences of interannual summer drought on vegetation production across 29 sites representing diverse ecoregions and plant functional types in NOrth America. Results showed that interannual summer drought, which was evaluated by the increase in summer temperature or decrease in soil moisture, would cause reductions of both summer gross primary production (GPP) and net ecosytem production (NEP) in non-forest sites (e.g grasslands and crops). On the contrary, forest ecosystems presented a very different pattern. For evergreen forests, lower summer soil moisture decreased both GPP and NEP; however, higher summer temperature only reduced NEP with no apparent impacts on GPP. Furthermore, summer drought did not show evident impacts on either summer GPP or NEP in deciduous forest, suggesting a better potential of deciduous forests in resisting summer drought and accumulating carbon form atmosphere. These observations imply diverse responses of vegetation production to interannual summer drought and accumulating carbon from atmosphere. These observations imply diverse responses of vegetation production to interannual summer drougt and such features would be useful to improve the strengths and weaknesses of ecosystem models to better comprehend the impacts of summer drought with future climate change.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58100
Title: Development of a coordinate transformation method for direct georeferencing in map projection frames
Author: Haitao Zhao, Bing Zhang, Changshan Wu, Zhengli Zuo, Zhengchao Chen
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 77, March 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of photogrammetry and Remote Sensing
Keywords: Coordinate transformation, GPS/INS, local tangent frame, Map projection frame, orientation angles, direct georeferencing
Abstract: This paper develops a novel Coordinate Transformation method (CT-method), with which the orientation angles (roll, pitch, heading) of the local tangent frame of the GPS/INS system are transformed into those (omega, phi, Kappa) of the map projection frame for direct georeferencing (DG). Especially, the orientation angles in the map projection frame were derived from a sequence of coordinate transformations. The effectiveness of orientation angles transformation was verified through comparing with DG results obtained from conventional methods (Legat method1 and POSPac method2) using empirical data. Moreover, the CT-method was also validated with simulated data. One advantage of the proposed method is that the orientation angles can be acquired simultaneously while calculating position elements of exterior orientation (EO) prameters and auxillary points coordinates by coordinate transformation.
These three methods were demonstrated and compared using empirical data. Empirical results show that the CT-method is both as sound and effective as Legat method. Compared with POSPac method, the CT-method is more suitable for calculating EO parameters for DG in map projection frames. DG accuracy of the CT-method and Legat method are at the same level. DG results of all these three methods have systematic errors in height due to inconsistent length projection distortion in the vertical and horizonal components, and these errors can be significantly reduced using the EO height correction technique in Legat ' s approach. Similar to the results obtained with empirical data, teh effectivenss of the CT-method was also proved with simulated data.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None
ID: 58099
Title: Remote sensing of seasonal variability of fractional vegetation cover and its object-based spatial pattern analysis over mountain areas0
Author: Guijun Yang, Ruiliang Pu, Jixian Zhang, Chunjiang Zhao, Haikuan Feng, Jihua Wang
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier, Vol 77, March 2013
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of photogrammetry and Remote Sensing
Keywords: FVC, topographic and atmospheric effect, segmentation, landscape analysis, Landsat TM image, patch analysis
Abstract: Fractional vegetation cover (FVC) is an important indicator of mountain ecosystem status. A study on the seasonal changes of FVC can be benficial for regional eco-environmental security, which contributes to the assessment of mountain ecosystem recovery and supports mountain forest planning and landscape reconstruction around megacities, for example, Beijing, China. Remote sensign has been demonstrated to be one of the most powerful and feasible tools for the investigation of mountain vegetation. However, topographic and atmospheric effects can produce enormous errors in the quantitative retrieval of FVC data from satellite images of mountainous areas. Moreover, the most commonly used analysis approach for assessing FVC seasonal fluctuations is based on per-pixel analysis regardless of the spatial context, which results in pixel-based FVC values that are feasible for landscape and ecosystem applications. To solve these problems, we proposed a new method that incorporates theuse of a revised physically based (RPB) model to correct both atmopsheric and terrain-caused illumination effects on Landsat images, an improved vegetation Index (VI)-based technique for estimating the FVC and an adaptive mean shift approach for object-based FVC segmentation. An array of metrics for segmented FVC analyses, including a variety of area metrics, patch metrics, shpae metrics and diversity metrics, was generated. On the basis of the individual segmented FVC values and landscape metrics from multiple images of different dates, remote sensing of the seasonal variabilityof FVC was conducted over the mountainous area of Beijing, China. The experimental results indicate that (a) the mean value of the RPB-NDVI in all seasons was increased by approximately 10% compared with that of the atmospheric correction-NDVI; (b) a strong consistency was demonstrated between ground - based FVC observations and FVC estimated through remote sensing technology (R2 = 0.8527, RMSE = 0.0851); and c) seasonal changes in the landscape characteristics existed, and the landscape diversity reached its in May and June in the study area.
Location: TE12, New Biological Sciences, IISc
Literature cited 1: None
Literature cited 2: None