ID: 55791
Title: Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area
Author: Xin Tian, Zhongbo Su, Erxue Chen, Zengyuan Li, Christiaan van der Tol, Jianping Guo, Qisheng He
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: k-NN method, Regression method, Above-ground biomass, configuration
Abstract: Remote sensing is a valuable tool for estimating forest biomass in remote areas. This study explores retrieval of forest above-ground biomass (AGB) over a cold and arid region in Northwest China, using two different methods (non-parametric and parametric), field data, and three different remote sensing data: a SPOT-5 HRG image, multi-temporal dual - polarization ALOS PALSAR and airborne LiDAR data. The non-parameteric method was applied in 300 different configurations, varying both the mathematical formualtion and the data input (SPOT-5 and ALOS PALSAR), and the quality of the performance of each configuration was evaluated by Leave One Out (LOO) cross-validation agianst ground measurements. For the parametric method (The multivariate linear regression), the same remote sensing data were used, but is one additional configuration the airborne LiDAR data were used for stepwise multiple regression. The result of the best performing non-parameteric configuration was satisfactory (R = 0.69 and RMSE = 20.7 tons/ha). The results for the parametric method were notoriously inaccurate, except for the case where airborne LiDAR data were included. The regression method with airborne low density LiDAR point cloud data was the best of all tested methods (R = 0.84 and RMSE = 15.2 tons/ha). A cross comparison of the two best results showed that the non-parametric method performs nearly as well as the parametric method with LiDAR data, except for some areas where forests have a very heterogeneous structure. It is concluded that the non-parametric method with SPOT data is able to map forest AGB operatively over the cold and arid region as an alterntive to the more expensive airborne LiDAR data.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55790
Title: Respond of Upper ocean during passage of MALA cyclone utilizing ARGO data
Author: Naresh Krishna Vissa, A N V Satyanarayana, B Prasad Kumar
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Upper ocean, Mixed layer, MALA cyclone, ARGO data, Sea surface cooling
Abstract: In the present study an attempt has been made to study the response of the upper ocean atmospheric interactions during the passage of a very severe cyclonic storm (VSCS) ' MALA ' formed over the Bay of Bengal (BOB) on 24 April 2006. Deepening of mixed layer depth (MLD), weakening of barrier layer thickness (BLT) associated with a deeper 260C isotherm level (D26) is observed after the MALA passage. Tropical cyclone heat potential (TCHP) and depth averaged temperature (T?100) exhibit a good degree of correlation for higher values. The passage of MALA cyclone also resulted in cooling the sea surface temperature (SST) by 4-50C. The findings suggest that turbulent and diapycnal mixing are responsible for cooler SSTs. Turbulent air-sea fluxes are analyzed using Objectively Analyzed air-sea Fluxes (OAFlux) daily products. During the mature stage of MALA higher latent heat flux (LHF), sensible heat flux (SHF), and enthalpy (LHF + SHF) are observed in the right side of this extreme event.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55789
Title: A hierarchial naive Bayesian network classifier embedded GMM for textural image
Author: Jianbin Tao, Qingquan Li, Changqing Zhu, Jili Li
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Bayesian network, High-dimensional remote sensing data, Textural image, classification
Abstract: To address several problems in high-dimensional textures feature space and the deficiencies of the single Gaussian distribution for remote sensing data, this paper proposes a hierarchical naive Bayesian network classifier embedded in a Gaussian mixture model for high-dimensional textural image classification. High-dimensional features are grouped by the model on the basis of the correlations between them. In this way, the high-dimensional problem is decomposed into multiple problems of lower dimension. At the same time, for each group of features, a Gaussian mixture model is applied to simulate the data distribution in feature space for land covers, which fits the "original" data distribution better than a single Gaussian model. The Gaussian mixture model is embedded as a child node into a naive Bayesian network, and then the final classification result is obtained within the naive Bayesian network classifier framework. Experimental results for the classification of Landsat ETM+ and QuickBird image textures demonstrated that the classification accuracy of this method is better than that of a traditional Bayesian network classifier and some other classival classifiers. Comparing with the method dealing with original high-dimensional features, it is also more efficiency and effectiveness with fewer demand of sample size and lower time complexity.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55788
Title: Image-based predictive ecosystem mapping in Canadian arctic parks
Author: Robert Fraser, Donald McLennan, Serguei Ponomarenko, Ian Olthof
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Remote sensing, decision trees, predictive modeling, ecosystem mapping, digital elevation model
Abstract: Ecological monitoring of Arctic national parks is challenging owing to their size and remote locations. Baselien ecosystem maps are a basic requriement for monitoring and are often derived from classification of remote sensing data. In many cases, however, the vegetation communities of interest overlap spectrally and cannot be separated using imagery alone. One solution is to use ancillay spatial data that are able to predict the distribution of Arctic ecosystems, which are often structured along environmental gradients. This paper presents a new image-based predictive ecosystem mapping (I-PEM) method that integrates remote sensing-based vegetation mapping with predictive terrain attributes from a digital elevation model. The approach is unique in its use of a conventional, air photo-based ecosystem map to train a decision tree classifier for mapping over a larger area of satellite coverage. I-PEM is demonstrated using SPOT HRVIR imagery over Ivvavik National Park in Yukon and Torngat Mountains National Park in Newfoundland. Results indicate that a 28-class ecosystem map derived from air-photo interpretation can be reproduced using the method with 85% or greater accuracy.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55787
Title: Multi-and hyperspectral geologic remote sensing: A review
Author: Freek D van der Meer, Harald M A van der Werff, Frank J A van Ruitenbeek, Chris A Hecker, Wim H Bakker, Marleen F Noomen, Mark van der Meijde, E John M Carranza, J Boudewijn de Smeth, Tsehaie Woldai
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Geologic remote sensing, Landsat, ASTER, Hyperspectral
Abstract: Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region alloweed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc). The step toward quantitative and validated (subpixel) surface mineralogic mappign was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectral and to unravel mixed pixel spectra to pure endmember spectra to derive sub-pixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) dat continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly workflows should be multidisciplinary and remote sensing data should be integrated with field observations and subsurface geophysical data to monitor and understand geologic processes.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55786
Title: Identifying a suitable combination of classification technique and bandwidth (s) for burned area mapping in tallgrass prairie with MODIS imagery
Author: Rhett L Mohler, Douglas G Goodin
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Burned area mapping, MODIS, object-based classification, Tallgrass prairie, grasslands
Abstract: Prescribed fire is crucial to the ecology and maintenance of tallgrass prairie, and its application affects a variety of human and natural systems. Consequently, maps showing the location and extent of these fires are critical to managing tallgrass prairies in a manner that balances the need of all stakeholders. Satellite-based optical remote sensing can provide the necessary input for this mapping, but it requires the development mapping methods that are specific to tallgrass prairie. In this research, we devise and test a suitable mapping method by comparing the efficacy of seven combinations of bands and indices from the MODIS sensor using both pixel and object -based classification methods. Due to the relatively small size of many prescribed fires in tallgrass prairie, scenarios based on the 250 m spatial resolution red and NIR bands outperformed those based on the coarser 500m spatial resolution bands, and a combination of both red and NIR performed better than each 250 m band individually. Object-based classfication offered no improvement over pixel-based classification, and performed poorer insome cases. Our results suggest that mapping burned areas in tallgrass prairie should be doen at a minimum of 250m spatial resolution, should used as a pixel-based classification technique, and should use a combination of red and NIR.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55785
Title: Assessing ground cover at patch and hillslope scale in semi-arid woody vegetation and pasture using fused Quickbird data
Author: Carlos Munoz-Robles, Paul Frazier, Matthew Tighe, Nick Reid, sue V Briggs, Brian Wilson
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Ecohydrology, Image fusion, Inter-patches, Modified intensity-hue-saturation, transform, patches, Australia
Abstract: The amount and distribution of vegetation and ground cover are important factors that influence resource transfer (e.g. runoff, sediment) in patterned semi-arid landscapes. Identifying and describing these features in detail is an essential part of measuring and understanding ecohydrological processes at hillslope scales that can then be applied at broader scales. The aim of this study was to develop a comprehensive methodology to map ground cover using high resolution Quickbird imagery in woody and non-woody (pasture) vegetation. The specific goals were to: (1) investigate the use of several techniques of image fusion, namely principal components analysis (PCA), Brovey transform, modified intensity-hue-saturation (MIHS) and wavelet transform to increase the spatial detail of multispectral Quickbird data ; (2) evaluate the performance of the red and near-infra-red bands (NIR), the difference vegetation index (DVI), and the normalised difference vegetation index (NDVI) in estimating ground cover, and (3) map and assess spatial and temporal changes in ground cover at hillslope scale using the most appropriate method or combination of methods. Estimates of ground cover from the imagery were compared with a subset of observed ground cover estimates to determine map accuracy. The MIHS alogrithm produced images that best preserved spectral and spatial integrity, while the red band fused with the panchromatic band produced the most accurate ground cover maps. The patch size of the ground cover beneath canopies was similar to canopy size, and percent ground cover (mainly litter) increased with canopy size. Ground cover was mapped with relative accuracies of 84% in the woody vegetation and 86% in the pasture. From 2008 to 2009, ground cover increased from 55% to 65% in the woody vegetation and from 40% to 45% in the pasture. These ground cover maps can be used to explore the spatial ecohydrological interactions between areas of different ground cover at hillslope scale with application to management at broader scales.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55784
Title: Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products
Author: Elodie Vintrou, Annie Desbrosse, Agnes Begue, Sibiry Traore, Christian Baron, Danny Lo Seen
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Cultivated area, MODIS time series, stratification, Global land products, Mali
Abstract: In Africa, food security early warning systems use satellite-derived data concerning crop conditions and agricultural production. Such systems can be improved if they are provided with a more reliable estimation of the cultivated area at national scale. This paper evaluates the potential of using time series from the MODerate resolution Imaging Spectroradiometer MOD13Q1 (16-day composite of normalized difference vegetation index at 250m resolution) to extract cultivated areas in the fragmented rural landscapes of Mali. To this end, we first stratified Southern Mali inot 13 rural landscapes based on the spatio-temporal variability of NDVI and textural indices, using an object-oriented classfication scheme. The accuracy of the resulting map (MODIScrop) and how it compares with existing coarse - resolution global land products (GLC2000 Africa, GLOBCOVER, MODIS V05 and ECOCLIMAP-II), was then assessed against six crop/non-crop maps derived from SPOT 2.5 m resolution images used as references. For crop areal coverage, the MODIScrop cultivated map was successful in assessing the overall cultivated area at five out of the six validation sites (less than 6% of the absolute difference), while in terms of crop spatial distribution, the producer accuracy was between 33.1% and 80.8%. This accuracy was linearly correlated with the mean patch size index calculated on the SPOT crop maps (r2 = 0.8). Using the Pareto boundary as an accuracy assessment method at the study sites, we showed that (i) 20-40% of the classification crop error was due to the spatial resolution of the MODIS sensor (250 m), and that (ii) compared to MODIS V05, which otherwise performed better than the other existing products, MODIScrop generally minimized omission-commission errors. A spatial validation of the different products was carried out using SPOT image classifications as reference. In the corresponding error matrices, the fraction of correctly classified pixels for our product was 70%, compared to 58% for MODIS V05, while it ranged between 40% and 51% for the GLC2000, the ECOCLIMAP-II and the GLOBCOVER.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55783
Title: Understanding the 2007-2008 eruption of Anak Krakatau Volcano by combining remote sensing technique and seismic data
Author: Agustan, Fumiaki Kimata, Yoga Era Pamitro, Hasanuddin Z Abidin
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Krakatau, PALSAR, InSAR, ground deformation, volcano eruption
Abstract: One of the most violent volcanic eruption in recorded history is the Krakatau eruption on August 27, 1883. This caldera-forming eruption destroyed two thirds of the Krakatau volcanic island in the Sunda Strait resulting in the remaining three small islands later known as the Krakatau complex. From 1927 to 1929, eruptions in the center of Krakatau complex have produced a new volcano named Anak Krakatau, which continuously builds its body through eruptions until now. One eruption event took place between 2007 and 2008 with several eruptions that lasted in total from the end of October 2007 to August 2008. Eruptions were characterized by Strombolian activity with ash columns 1 km high, as well as pyroclastic and lava flows. We monitored the ground deformation of Anak Krakatau Volcano by interfering PALSAR data from June 2007 to February 2009. The result of InSAR technique shows a complex pattern of ground deformation. Inflation up to 4 cm, together with subsidence around the crater, was measured for almost three months before the eruption with a volume increase of approximately 1 x 106 m3. After the eruption, the southwest side of the volcanic cone subsided by 18 cm, whereas the northeast side of the cone uplifted 12 cm in almost two years. The observed ground deformation after the eruption can be explained by 4 m of tensile opening along a dipping rectangular tensile dislocation buried in an elastic half-space, approximately 400m below sea level.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55782
Title: Identifying transit corridors for elephant using a long time-series
Author: Claudia Pittiglio, Andrew K Skidmore, Hein A M J van Gils, Herbert H T Prins
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Species distribution, transit corridor, Kernel density, path analysis, l9ogistic regression, long-term aerial survey
Abstract: The role of corridors in mitigating the effects of landscape fragmentation on biodiversity is controversial. Recent studies have highlighted the need for new approaches in corridor design usign long-term datasets. We present a method to identify transit corridors for elephant at a population scale over a large area and an extended period of time using long-term aerial surveys. We investigated environmental and anthropogenic factors directly and indirectly related to the wet versus dry season distribution of elephant and its transit corridors. Four environmental variables predicted the presence of elephant at the landscape scale in both seasons: distance from permanent water, protected areas and settlements and vegetation structure. Path analysis revealed that altitude and monthly average NDVI, and distance from temporary water had a significant indirect effect on elephant distribution at local scale in dry and wet seasons respectively. Five transit corridors connectign Tarangire National Park and the northern as well as south-eastern wet season dispersal areas were identified and matched the wildlife migration routes described in the 1960s. The corridors are stable over the decades, providing landscape connectivity for elephant. Our approach yielded insights how advanced spatial analysis can be integrated with biological data available from long-term datasets to identify actual transit corridors and predictors of species distribution.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55781
Title: An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping
Author: H A Nefeslioglu, B T San, C Gokceoglu, T Y Duman
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Terra ASTER L3A data, DEM, topographic attributes, Landslide susceptibility, kelemen catchment area (Western Black Sea region Turkey)
Abstract: The main purpose of the present study is to evaluate the potential use of Terra ASTER data-the L3A DEM and its derivatives in landslide susceptibility mapping. For the purpose, an appropriate application site from the Western Black Sea region of Turkey - the Kelemen catchment area was selected. During the analyses, a two-stage comparative evaluation was carried out. In the first stage, the differences between the DEMs obtained from Terra ASTER L3A data and the conventional topographic data; and their first and second derivatives were investigated. Subsequently, different susceptibility maps were produced by using the DEMs and the topographic attributes obtained from both source of data in addition to the spectral information acquired from satellite sensor. According to the results of the comparative evaluations, a strong correlation between Terra ASTER L3A DEM and the conventional topographic data was obtained. However, depending on the increment of the degree of the derivative, an evident decrease in the spatial correlations was observed. On the contrary, the final model performance, prediction capacity, and the spatial performance statistics for the landslide susceptibility maps produced by using both source of data were found as very high and close to each other.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55780
Title: Water-poverty relationships in the coastal town of Mbour (Senegal): Relevance of GIS for decision support
Author: Nene Makoya Toure, Alioune Kane, Jean Francois Noel, Vincent Turmine, Valentine Nedeff, Gabriel Lazar
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Fresh water, sustainable development, coastline, poverty, GIS
Abstract: Coastal area is always a zone with complex problems. Due to the attraction they exert, are facing many social problems. Therefore, a coastal city is usually a city with problems. Its extension, caused by the influx of people from different backgrounds, creates an increased demand for services. One of the problems frequently encountered, especially in Senegal, is access to water. The problem of access to water is poorly treated, without beig correlated with the urban evolution, i.e. with increasing population and demand growth. The water resource is facing numerous complications such as the lack of integrated management, integration issues at the governance level, where the local factor is often forgotten. The town of Mbour, object of our study, does not come out of that lot, being an attractive coastal city, from an African country. This indicates the need for an integrated management oriented from local to a global basis and not vice versa. The study presented in this paper indicates that a large proportion of the population has not access to a verified drinking water system and uses water from wells or standpipes. Half of the surveyed population (50%) has no access to a water supply system. The water poverty map of the town overlaps with that of the general poverty excepting few neighborhoods. This means that even areas that are not affected by poverty have a very low or poor access to water, which so far remains the perverse effect of the reform of teh Senegalese water sector in 1995.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55779
Title: Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya
Author: Gayantha R L Kodikara, Tsehaie Woldai, Frank J A van Ruitenbeek, Zack Kuria, Freek van der Meer, Keith D Shepherd, G J van Hummel
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Hyperion, Lake Magadi, MTMF, surface mineral mapping, Magadiite, kenyaite
Abstract: Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed. Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach Iimage analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and vocanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows that usefulness of the hyperspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55778
Title: Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed
Author: Dongchuan Wang, Jianhua Gong, Liding Chen, Lihui Zhang, Yiquan Song, Yujuan Yue
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Change trajectories, Land use/cover change, Landscape metrics, RCI, Slope, Aspect, River line
Abstract: Human-induced land use/cover change has been considered to be one of the most important parts of global environmental changes. In loess hilly and gully regions, to prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades. The main objective of this study is to quantify the spatio-temporal variability of land use/cover change spatial patterns and make preliminary estimation of the role of human activity in the environmental change in Xihe watershed, Gansu Province, China. To achieve this objective, the methodology was developed in two different aspects, that is. (1) analysis of change patterns by binary image of change trajectories overlaid with different natural geographic factors, in which Relative Change Intensity (RCI) metric was established and used to make comparisons, and (2) analysis based on pattern metrics of main trajectories in the study area. Multi-source and multi-temporal Remote Sensing (RS) images (including Landsat ETM+ (30 June 2001), SPOT imagery (21 November 2003 and 5 May 2008) and CBERS02 CCD (5 June 2006) were used due to the constraints of the availability of remotely sensed data. First, they were used to extract land use/cover types of each time node by object-oriented classification method. Classification results were then utilized in the trajectory of land use/cover changes through the given four time nodes. Trajectories at every pixel were acquired to trace the history of land use/cover change for every location in the study area. Landscape metrics of trajectories were then analyzed to detect the change characteristics in time and space through the given time series. Analysis showed that most land use/cover changes were caused by human activities, most of which, under the direction of local government, had mainly led to virtuous change on the ecological environments. While, on the contrary, about one quarter of human- induced changes were vicious ones. Analyis through overlaying binary image of change trajectories with natural factors can efficiently show the spatio-temporal distribution characteristics of land use/cover change patterns. It is found that in the study area RCi of land use/cover changes is related to the distance to the river line. And there is a certain correlation between RCI and slope grades. However, no obvious correlation exists between RCI and aspect grades.
Location: 241
Literature cited 1: None
Literature cited 2: None


ID: 55777
Title: Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: Accounting for soil brightness variation
Author: S Veraverbeke, B Somers, I Gitas, T Katagis, A Polychronaki, R Goossens
Editor: Alfred Stein
Year: 2012
Publisher: Elsevier, Vol 14, Issue 1, February 2012
Source: Centre for Ecological Sciences
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Fire, vegetation recovery, Landsat Thematic Mapper, Spectral mixture analysis, MESMA, segmentation
Abstract: Post-fire vegetation cover is a crucial parameter in rangeland management. This study aims to assess the post-fire vegetation recovery 3 years after the large 2007 Pelophonnese (Greece) wildfires. Post-fire recovery landscapes typically are mixed vegetation-substrate environments which makes spectral mixture analysis (SMA) a very effective tool to derive fractional vegetation cover maps. Using a combination of field and simulation techniques this study aimed to account for the impact of background brightness variability on SMA model performance. The field data consisted out of a spectral library of in situ measured reflectance signals of vegetation and substrate and 78 line transect plots. In addition, a Landsat Thematic Mapper (TM) scene was employed in the study. A simple SMA, in which each constituting terrain feature is represented by its mean spectral signature, a multiple endmember SMA (MESMA) and a segmented SMA, which accounts for soil brightness variations by forcing the substrate endmember choice based on ancillary data (lithological map), were applied. In the study area two main spectrally different lithological units were present: relatively bright limestone and relatively dark flysch (sand-siltstone). Although the simple SMA model resulted in reasonable regression fits for the flysch and limestones subsets separately (coefficient of determination R2 of respectively 0.67 and 0.72 between field and TM data), the performance of the regression model on the pooled dataset was considerably weaker (R2 = 0.65). More over, the regression lines significantly diverged among the different subsets leading to systematic over-or underestimations of the vegetative fraction depending on the substrate type. MESMA did not solve the endmember variability issue. The MESMA model did not manage to select the proper substrate spectrum on a reliable basis due to the lack fo shape differences between the flysch and limestone spectra. The segmented SMA model which accounts for soil brightness variations minimized the variability problems. Compared to the simple SMA and MESMA models, the segmented SMA resulted in a higher overall correlation (R2 = 0.70), its regression slope and intercept were more similar among the different substrate types and its resulting regression lines more closely resembled the expected one-one line. This paper demonstrates the improvement of a segment approach in accounting for soil brightness variations in estimating vegetative cover using SMA. However, further research is required to evaluate the model ' s performance for other soil types, with other image data and at different post-frve timings.
Location: 241
Literature cited 1: None
Literature cited 2: None