ID: 56872
Title: External geo-information in the segmentation of VHR imagery improves the detection of imperviousness in urban neighborhoods
Author: Klaartje Verbeeck, Martin Hermy, Jos Van Orshoven
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: OBIA, QuickBird, Image segmentation, classification, Large scale reference database, Hydrology
Abstract: Object -based image analysis (OBIA) has become an established way to detect imperviousness and other land cover classes from very high resolution (VHR) multispectral imagery. Data fusion with LiDAR derived digital surface models (DSM) and large scale vectorial datasets containing building footprints and road boundaries have the potential to significantly improve this method However, the individual contribution of the large scale vectorial dataset reamins unclear. In this paper, we studied the improvement of segmentation and classification results when including a vectorial dataset in the OBIA. Two slightly different segmentation methods making use of the vectorial dataset (boundary suggestion method and absolute boundary method) are compared with each other, with a per-pixel classification of the image and an OBIA segmentation without the input of a vectorial dataset. The performance of all four segmentation methods was assessed both for per-pixel image classification and for segmentation accuracy. The classification accuracy was highest for the segmentation method where the vectorial boundaries were absolute (overall accuracy 82%). However, the boundary suggestion method, where segments were smaller than the reference polygons, had the highest segmentation quality. Although differences between the two methods were clear, the differences with the results of the object-based analysis which did not use the vectorial dataset, were even larger. This indicates that the explicit inclusion of a large scale vectorial dataset is beneficial for the segmentation and classfication of imperviousness in an urban enviornment.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56871
Title: Monitoring agricultural drought in the lower Mekong basin using MODIS NDVI and land surface temperature data
Author: N T Son, C F Chen, C R Chen, L Y Chang, V Q Minh
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: MODIS, TVDI, Agricultural drought, Lower Mekong Basin
Abstract: Drought is a complex natural phenomenon, and its impacts on agriculture are enormous. Drought has been a prevalent concern for farmers in the Lower Mekong Basin (LMB) over the last decades; thus, monitoring drought is important for water planning and management to mitigate impact on agriculture in the region. This study explored the applicability of monthly MODIS normalized difference vegetation index (NDVI) and land surface temperature (LST) data for agricultural drought monitoring in LMB in the dry season from November 2001 to April 2010. The data were processed using the temperature vegetation dryness index (TVDI), calculated by parameterizing the relationship between the MODIS NDVI and LST data. The daily volumetric surface soil moisture from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and monthly precipitation from the Tropical Rainfall Measuring Mission (TRMM) were collected and used for verification of the results. In addition , we compared the efficiency of TVDI with a commonly used drought index, the crop water stress index (CWSI), derived from the MODIS LST alone. The results achieved from comparisons between TVDI and AMSR-E soil moisture data indicated acceptable correlations between the two datasets in most cases. There was close agreement between TVDI and TRM precipitation data through the season, indicating that TVDI was sensitive to precipitation. The TVDI compared to CWSI also yileded close correlations between both datasets. The TVDI was, however, more sensitive to soil moisture stress than CWSI. The results archived by anlaysis of TVDI indicated that the moderate and severe droughts were spatially scattered over the region from November to March, but more extensive in northeast Thailand and Cambodia. The larger area of severe drought was especially observed for the 2003-2006 dry seasons compared to other years. The results achieved from this study could be important for drought warnings and irrigation scheduling.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56870
Title: High-resolution satellite data reveal an increase in peak growing season gross primary production in a high-Arctic wet tundra ecosystem 1992-2008
Author: Torbern Tagesson, Mikhail Mastepanov, Mikkel P Tamstorf, Lars Eklundh, Per Schubert, Anna Ekberg, Charlotte Sigsgaard, Torben R Christensen, Lena Strom
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Light use efficiency, NDVI, Remote sensing, Climate change, FAPAR, GPP
Abstract: Artic ecosystems play a key role in the terrestrial carbon cycle. Our aim was to combine satellite-based normalized difference vegetation index (NDVI) with field measurements of CO2 fluxes to investigate changes in gross primary production (GPP) for the peak growing seasons 1992-2008 in Rylekaerene, a wet tundra ecosystem in the Zackenberg valley, north-eastern Greenland. A method to incorporate controls on GPP through satellite data is the light use efficiency (LUE) model, here expressed as GPP = ? peak x PARin x FAPARgreen-peak ; where ? peak was peak growing season light use efficiency of the vegetation, PARin was incoming photosynthetically active radiation, and FAPARgreen-peak was peak growing season fraction of PAR absorbed by the green vegetation. The ? peak was measured for seven different high-Artic plant communities in the field, and it was on average 1.63 g CO2 M-1. We found a significant linear relationship between FAPARgreen-peak was entered into the LUE-model. It was shown that when several empirical models are combined, propagation errors are introduced, which results in considerable model uncertainties. The LUE-model was evaluated against field-measured GPP and the model captured field-measured GPP well (RMSE was 192 mg CO2 m-2h-1). The model showed an increase in peak growing season GPP of 42 mg CO2 m-2h-1y1 in Rylekaerene 1992-2008. There was also a strong increase in air temperature (0.150Cy-1), indicating that the GPP trend may have been climate driven.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56869
Title: High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm
Author: Onisimo Mutanga, Elhadi Adam, Moses Azong Cho
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Above ground biomass, Red edge bands, Savanna wetlands, Random forest regression algorithm, variable importance
Abstract: The saturation problem associated with the use of NDVI for biomass estimation in high canopy density vegetation is a well known phenomenon. Recent field spectroscopy experiments have shown that narrow band vegetation indices computed from the red edge and the NIR shoulder can improve the estimation of biomass in such situations. However, the wide scale unavailability of high spectral resolution satellite sensors with red edge bands has not seen the up-scaling of these techniques to spaceborne remote sensing of high density biomass. This pape explored the possibility of estimate biomass in a density vegetated wetland area using normalized difference vegetation index (NDVI) computed from WorldView - 2 imagery, which contains a red edge band centred at 725 nm. NDVI was calculated from all possible two band combinations of WorldView -2. Subsequently, we utilized the random forest regression algorithm as variable selection and a regression method for predicting wetland biomass. The performance of random forest regression in predicting biomass was then compared against the widely used stepwise multiple linear regression. Predicting biomass on an independent test data set using the random forest algorithm and 3 NDVIs computed from the red edge and NIR bands yielded a root mean square error of prediction (RMSEP) of 0.441 kg/m2 (12.9 % of observed mean biomass) as compared to the stepwise multiple linear regression that produced an RMSEP of 0.5465 kg/m2 (15.9% of observed mean biomass). The results demonstrate the utility of WorldView-2 imagery and random forest regression in estimating and ultimately mapping vegetation biomass at high density-a previously challenging task with broad band satellite sensors.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56868
Title: An integrated approach for updating cadastral maps in Pakistan using satellite remote sensing data
Author: Zahir Ali, Arbind Tuladhar, Jaap Zevenbergen
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Cadastral surveying, Discipline-oriented approach, Methodology -oriented integrated approach, RS imagery, GPS data, Participatory -GIS (PGIS)
Abstract: Updating cadastral information is crucial for recording land ownership and property division changes in a timely fashioned manner. In most cases, the existing cadastral maps do not provide up-to-data information on land parcel boundaries. Such a situation demands that all the cadastral data and parcel boundaries information in these maps to be updated in a timely fashion. The existing techniques for acquiring cadastral information are discipline-oriented based on different disciplines such as geodesy, surveying and photogrammetry. All these techniques require a large numbe of manpower, time, and cost when they are carried out separately. There is a need to integrate these techniques for acquiring cadastral information to update the existing cadastral data and (re) produce cadastral maps in an efficient manner. To reduce the time and cost involved in cadastral data acquisition, this study develops an integrated approach by integrating global position system (GPS) data, remote sensing (RS) imagery, and existing cadastral maps. For this purpose, the panchromatic image with 0.6m spatial resolution and the corresponding multispectral image with 2.4 m spatial resolution and 3 spectral bands from QuickBird satellite were used. A digital elevation model (DEM) was extracted from SPOT - 5 stereopairs and some ground control points (GCPs) were also used for ortho- rectifying the QuickBird images. After ortho-rectifying these images and registering the multi-spectral image to the panchromatic image, fusion between them was attained to get good quality multi-spectral images of these two study areas with 0.6m spatial resolution. Cadastral parcel boundaries were then identified on QuickBird images of the two study area via visual interpretation using particularly - GIS (PGIS) technique. The regions of study are the urban and rural areas of Peshawar and Swabi district sin the Khyber Pakhtunkhwa province of Pakistan. The results are the creation of updated cadastral maps with a lot of cadastral information which can be used in updating the existing cadastral data with less time and cost.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56867
Title: Hyperspectral retrieval of phycocyanin in potable water sources using genetic algorithm-partial least squares (GA-PLS) modeling
Author: Kaishan Song, Lin Li, Shuai Li, Lenore Tedesco, Bob Hall, Zuchuan Li
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: AISA, Cyanobacteria, GA-PLS, Hyperspectral, Phycocyanin, Semi-empirical model
Abstract: Eagle Creek, Morse and Geist reservoirs, drinking water supply sources for the Indianapolis, Indiana, USA metropolitan region, are experiencing nuisance cyanobacterial blooms. Hyperspectral remote sensing has been proven to be an effective tool for phycocyanin (C-PC) concentration retrieval, a proxy pigment unique to cyanobacteria in freshwate ecosystems. An adaptive model based on genetic alogorithm and partial least squares (GA-PLS), together with three-band algorithm (TBA) and other ratio algorithms were applied to hyperspectral data acquired from in situ (ASD spectrometer) and airborne (AISA sensor) platforms. The results indicated that GA-PLS achieved high correlation between measured and estimated C-PC for GR (RMSE = 16.3 ug/L, RMSE% = 18.2; range (R): 2.6- 185.1 ug/L), MR (RMSE = 8.7 ug/L, RMSE% = 15.6; R: 3.3-371.0 ug/L) and ECR (RMSE = 19.3 ug/L, RMSE% =26.4; R: 0.7 - 245.0 ug/L) for the in situ datasets. TBA also performed well compared to other band ratio algorithms due to its optimal band tuning process and the reduction of backscattering effects through the third band. GA -PLS (GR: RMSE = 24.1 ug/L, RMSE% = 25.2, R: 25.2 - 185.1 ug/L; MR: RMSE = 15.7 ug/L, RMSE% = 37.4, R: 2.0 -135.1 ug/L) and TBA (GR: RMSE = 28.3 ug/L, RMSE% = 30.1; MR: R<SE = 17.7 ug/L, RMSE% = 41.9) methods results in somewhat lower accuracy using AISA imagery data, which is likely due to atmospheric correction or radiometric resolution. GA-PLS (TBA) obtained an RMSE of 24.82 ug/L (35.8 ug/L), and RMSE% of 31.24 (43.5) between measured and estimated C-PC for aggregated datasets. C-PC maps were generated through GA-PLS using AISA imagery data. The C-PC concentration had an average value of 67.31+44.23 ug/L in MR with a large range of concentration, while the GR had a higher average value 103.17+ 33.45 ug/L
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56866
Title: Multitemporal analysis of hydrological soil surface characteristics using aerial photos: A case study on a Mediterranean vineyard
Author: Christina Corbane, Frederic Jacob, Damien Raclot, Jean Albergel, Patrick Andrieux
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Hydrological soil surface characteristics (H-SSC), Mediterranean vineyards, Expert knowledge, H-SSC evolutions, Multitemporal classification, Aerial photos
Abstract: Soil surface characteristics (SSC) constitute an important land surface property that drives the partitioning between infiltration and runoff. Therefore, knowledge of SSC is crucial for runoff-forecasting in hydrology. However, the difficulties in measuring spatial variabilities and temporal dynamics of SSC have limited the use of this property in operational hydrology at the catchment extent. Recent progresses have permitted to characterize hydrological SSC classes (H-SSC) with distinct infiltration rates, by implementing monotemporal classifications along with aerial photos. However, when dealing with Mediterranean vineyards, some classes still are difficult to discriminate on the basis of remotely sensed spectral and spatial information only.
The objective of the current study was to propose a multitemporal classification that integrates a priori information about possible H-SSC evolutions, such as it is possible improving their characterization. H-SSC evolutions could be either natural, depending on rainfall events, or anthropogenic, driven by soil management practices. Knowledge of possible H-SSC evolutions was translated in the form of decision rules. It was applied to a time series of H-SSC class maps derived from a monotemporal classification of monthly aerial photos. As compared to the monotemporal classification, the multitemporal classification had two advantages for the identification of H-SSC classes. First, it allowed improving the discrimination of classes related to crusting processes, with increased performances between 35 and 48% relative. Second, it was able to detec-H-SSC temporal evolutions in relation to soil management practices.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56865
Title: Land cover mapping with emphasis to burnt area delineation using co-orbital ALI and Landsat TM imagery
Author: George P. Petropoulos, Charalambos C Kontoes, Iphigenia keramitsoglou
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Burnt area mapping, Landsat TM, EO-1 Advanced Land Imager (ALI), Support Vector Machines, Artificial Neural Networks, Maximum Likelihood, Greece
Abstract: In this study, the potential of EO-1 Advanced Land Imager (ALI) radiometer for land cover and especially burnt area mapping from a single image analysis is investigated. Co-orbital imagery from the Landsat Thematic Mapper (TM) was also utilized for comparison purposes. Both images were acquired shortly after the suppression of a fire occurred during the summer of 2009 North-Est of Athens, the capital of Greece. The Maximum Likelihood (ML), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) classifiers were parameterised and subsequently applied to the acquired satellite datasets. Evaluation of the land use/cover mapping accuracy was based on the error matrix statistics. Also, the McNemar test was used to evaluate the statistical significance of the differences between the approaches tested. Derived burnt area estimates were validated against the operationally deployed Services and Applications For Emergency Response (SAFER) Burnt Scar Mapping service.
All classifiers applied to either ALI or TM imagery proved flexible enough to map land cover and also to extract the burnt area from other land surface types. The highest total classification accuracy and burnt area detection capability was returned from the application of SVMs to ALI data. This was due to the SVMs ability to identify an optimal separating hyperplane for best classes separation that was able to better utilise ALI ' s advanced technological characteristics in comparison to those of TM sensor. This study is to our knowledge the first of its kind, effectively demonstrating the benefits of the combined application of SVMs to ALI data further implying that ALI technology may prove highly valuable in mapping burnt areas and land use/cover if it is incorporated into the development of Landsat 8 mission, planned to be launched in the coming years.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56864
Title: Insights to urban dynamics through landscape spatial pattern analysis
Author: Ramachandra T V, Bharath H Aithal, Durgappa D Sanna
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Urbanisation, Urban sprawl, Landscape metrices, spatial metrics, Remote sensing
Abstract: Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of and use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good goveranance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growht in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973 - 1992), 129.56% (during 1992 -1999), 106.7% (1999 - 2002), 114.51% (2002 -2006) and 126.19% from 2006 to 2010. The study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levles. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon ' s entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon ' s entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about hte sprawl. Principal component analysis helped in prioritizing the metrics for detailed analyses. The results clearly indicates that whole landscape is aggregating to a large patch in 2010 as compared to earlier years which was domianted by several small patches. The large scale conversion of small patches to large single patch can be seen form 2006 to 2010. In the year 2010 patches are maximally aggregated indicating the that the city is becoming more compact and more urbanised in recent years. Bangalore was the most sought after destination for its climatic condition and the availability of various facilities (land availability, economy, political factors) compared to other cities. The growth into a single urban patch can be attributed to rapid urbanisation coupled with the industrialisation. Monitoring of growht through landscape metrics helps to maintain and manage the natural resources.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56863
Title: Using a modified invasive weed optimization algorithm for a personalized urban multi-criteria path optimization problem
Author: Parham Pahlavani, Mahmoud R Delavar, Andrew U Frank
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Personalized urban multi-criteria path, optimization problem, Invasive weed optimization algorithm, genetic algorithm
Abstract: The personalized urban multi-criteria quasi-optimum path problem (PUMQPP) is a branch of multi-criteria shortest path problems (MSPPs) and it is classified as a NP-hard problem. To solve the PUMQPP, by considering dependent criteria in route selection, there is a need for approaches that achieve the best compromise of possible solutions/routes. Recently, invasive weed optimization (IWO) algorithm is introduced and used as a novel algorithm to solve many continuous optimization problems. In this study, the modified algorithm of IWO was designed, implemented, evaluated, and compared with the genetic algorithm (GA) to solve the PUMQPP in a directed urban transportation network. In comparison with the GA, the results have shown the significant superiority of the proposed modified IWO algorithm in exploring a discrete search-space of the urban transportation network. In htis regard, the proposed modified IWO algorithm has reached better results in fitness function, quality metric and running-time values in comparison with those of the GA.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56862
Title: Integration of carbon conservation into sustainable forest management using high resolution satellite imagery: A case study in Sabah, Malaysian Borneo
Author: Andreas Langner, Hiromitsu Samejima, Robert C Ong, Jupiri Titin, Kanehiro Kitayama
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Borneo, Biomass, Forest degradation, Sustainable forest management, Remote sensing, Landsat
Abstract: Conservation of tropical forests is of outstanding importance for mitigation of climate change effects and preserving biodiversity. In Borneo most of the forests are classified as permanent forest estates and are selectively logged using conventional logging techniques causing high damage to the forest ecosystems. Incorporation of sustainable forest management into climate change mitigation measures such as Reducing Emissions from Deforestation and Forest Degradation (REDD+) can help to avert further forest degradation by synergizing sustainable timber production with the conservation of biodiversity. In order to evaluate the efficiency of such initiatives, monitoring methods for forest degradation and above-ground biomass in tropical forests are urgently needed. In this study we developed an index using Landsat satellite data to describe the crown cover condition of lowland mixed dipterocarp forests. We showed that this index cmbined with field data can be used to estimate above-ground biomass using a regression model in two permanent forest estates in Sabah. Malaysian Borneo, Tangkulap represented a conventionally logged forest estate while Deramakot has been managed in accordance with sustainable forestry principles. The results revealed that conventional logging techniques used in Tangkulap during 1991 and 2000 decreased the above-ground biomass by an annual amount of average-6.0 t C/ha (-5.2 to -7.0 t C/ha, 95% confidential interval) whereas the biomass in Deramakot increased by 6.1 t C/ha per year (5.3 - 7.2 t C/ha, 95% confidential interval) between 2000 and 2007 while under sustainable forest management. This indicates that sustainable forest management with reduced-impact logging helps to protect above-ground biomass. In absolute terms, a conservative amount of 10.5 t C/ha per year, as documented using the methodology developed in this study, can be attributed to the different management systems, which will be of interest when implementing REDD+ that rewards the enhancement of carbon stocks.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56861
Title: Mappign curbstones in airborne and mobile laser scanning data
Author: Liang Zhou, George Vosselman
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Feature extraction, Road detection, Sigmoid fitting, Laser scanning, Accuracy
Abstract: The high point densities obtained by today ' s laser scanning systems enable the extraction of various features which are traditionally mapped by photogrammetry or land surveying. While significant progress has been made in the extraction of buildings and trees from dense point clouds, little research has been performed on the extraction of roads. In this paper it is analysed to what extent road sides can be mapped in point clouds of high point density. In urban areas curbstones are often used to separate the road surface from the adjacent pavement. These curbstones are mapped in a three step procedure. First, the locations with small height jumps near the terrain surface are detected. Second, midpoints of high and low points on either side of the heigth jump are generated, put in a sequence to obtain a polygonal chain describing the approximate curbstone location. A sigmoidal function is then fitted to all points near the polygonal chain to increase the accuracy. Third, small gaps between nearby and collinear line segments are closed. GPS measurements were taken to analyse the performance of the road side detection. The analysis showed that the completeness in airborne laser scanning (ALS) data varying between 53% and 92% is higher than that in mobile laser scanning (MLS) data ranging from 54% to 83%, depending on the amount of parked cars occluding the curbstones. The RMS value in the comparison with the GPS points measured from ground survey was 0.11 m in ALS data and 0.06 m in MLS data, respectively.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56860
Title: Object-based sub-pixel mapping of buildings incorporating the prior shape information from remotely sensed imagery
Author: Feng Ling, Xiaodong Li, Fei Xiao, Shiming Fang, Yun Du
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Sub-pixel mapping, super-resolution, object-based, buildings, spatial pattern, scale
Abstract: Sub-pixel mapping (SPM) is a promising method to predict the spatial locations of land cover classes at the sub-pixel scale for remotely sensed imagery, using the fraction images generated by soft classification as input. At present, SPM treats all sub-pixels of differetn land cover classes in the same strategy by maximizing their spatial dependence. Although the maximal spatial dependence is a simple method to describe the spatial pattern of land cover classes and has been proved to be an effective principle for SPM. It does not reflect real-world situations. Given that spatial patterns are land cover class-or object - specific, each land cover class or object should be designated its own specific spatial pattern description when SPM is applied. In this paper, a novel based sub-pixel mapping (OBSPM) method was proposed to map buildings at the sub-pixel scale. On the basis of the prior information of the building shape (i.e., the building boundaries are parallel or perpendicular to the main orientation), a novel anisotropic spatial dependence model is adopted in the SPM procedure. The proposed OBSPM model includes three main steps: building segmentation, building feature extraction, and anisotropic SPM of buildings. The proposed model is evaluated with a simulated synthetic image and an actual AVIRIS image. The results show that OBSPM obtains more accurate building maps than do conventional SPM models, and the accuracy of fraction images and the spatial resolutions of remotely sensed images are two crucial factors that influence the OBSPM results. Furthermore, extending the OBSPM model to more lead cover classes to incorporate more specific prior information is a promising method in enhancing the applicability of SPM to practical situations.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56859
Title: Community detection in spatial networks: Inferring land use from a planar graph of land cover objects
Author: A J Comber, C F Brunsdon, C J Q Farmer
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: OBIA, Network, Community detection, Land cover to land use, Modularity
Abstract: This paper applies three algorithms for detecting communities within networks. It applies them to a network of land cover objects, identified in an OBIA, in order to indentify areas of homogenous land use. Previous research on land cover to land use transformations has identified the need for rules and knowledge to merge land cover objects. This research shows that Walktrap, Spinglass and Fastgreedy algorithms are able to identify land use communities but with different spatial properties. Community detection algorithms, arising from graph theory and networks science, offer methods for merging sub-objects based on the properties of the network. The use of an explicity geographical network also identifies some limitations to network partitioning mehtods such as Spinglass that introduce a degree of randomness in their search for community structure. The results show such algorithms may not be suitable for analysing geographic networks whose structure reflects topological relationships between objects. The discussion identifies a number of areas for further work, including the evaluation of different null statistical models for determining the modularity of geographic networks. The findings of this research also have implications for the many activities that are considering social networks, which increasingly have a geographical component.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 56858
Title: Comparison of surface heat balance in three cities in Taiwan using Terra ASTER and Formosat -2 RSI data
Author: Soushi Kato, Cheng-Chien Liu, Chen-Yi Sun, Po-Li Chen, Hsin-Yi Tsai, Yasushi Yamaguchi
Editor: Freek van der Meer
Year: 2012
Publisher: Elsevier, Vol 18, August 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: ASTER, Formosat-2, Surface heat balance, Urban heat island
Abstract: In order to investigate the influence of the city scale, usage, topography, and climate on surface heat balance, the authors compared the surface heat balance for three urban areas in Taiwan, namely, Kaohsiung City, Taichung City, and Tainan City, estimated using ASTER and Formosat - 2 data. The net radiation was in a similar range in all three study areas because the cities are in close proximity to each other. Tainan City released 60 -70% of the sensible heat flux of the other cities because of its smaller size. Taichung City, which is located in a basin, exhibited the largest sensible heat flux, due to the radiation cooling during the night before the observation. Anthropogenic heat discharge clearly decreased the storage heat flux in certain industrial areas in Kaohsiung City and Taichung City, while the small scale urban functions moderated the variation of storage heat flux in Tainan City. These results imply that the terrain around a given city as well as the scale of urban activity significantly affect the heat balance in the cities.
Location: 231
Literature cited 1: None
Literature cited 2: None