bluuebunny/crossref_metadata_2025 huggingface dataset:
TEXTURE ANALYSIS BASED FUSION EXPERIMENTS USING HIGH-RESOLUTION SAR AND OPTICAL IMAGERY
Authors: Zhao S. , Luo Y. , Zhou H. , Xue Q. , Wang A.
Published: August 2012

Abstract. High resolution SAR images contain plenty of detailed textural features, and optical images have spectral features. For the different characteristics of the two images, Firstly, we extracted textural measures of TerraSAR-X image based on the Gray Level Co-occurrence Matrix (GLCM) method, and chose the appropriate window. Then data fusion between textural measures of TerraSAR-X image and QuickBird multi-spectral image was implemented based on PCA transform, and the fusion results were quantitatively evaluated, showing that the fusion image keep spectral information well and the spatial information be enhanced.
THE GLOBAL TANDEM-X DEM: PRODUCTION STATUS AND FIRST VALIDATION RESULTS
Authors: Huber M. , Gruber A. , Wendleder A. , Wessel B. , Roth A. , Schmitt A.
Published: August 2012

Abstract. The TanDEM-X mission will derive a global digital elevation model (DEM) with satellite SAR interferometry. Two radar satellites (TerraSAR-X and TanDEM-X) will map the Earth in a resolution and accuracy with an absolute height error of 10m and a relative height error of 2m for 90% of the data. In order to fulfill the height requirements in general two global coverages are acquired and processed. Besides the final TanDEM-X DEM, an intermediate DEM with reduced accuracy is produced after the first coverage is completed. The last step in the whole workflow for generating the TanDEM-X DEM is the calibration of remaining systematic height errors and the merge of single acquisitions to 1°x1° DEM tiles. In this paper the current status of generating the intermediate DEM and first validation results based on GPS tracks, laser scanning DEMs, SRTM data and ICESat points are shown for different test sites.
FULL WAVEFORM ACTIVE HYPERSPECTRAL LIDAR
Authors: Hakala T. , Suomalainen J. , Kaasalainen S.
Published: August 2012

Abstract. We have developed a prototype full waveform hyperspectral LiDAR and investigated its potential for remote sensing applications. Traditionally hyperspectral remote sensing is based on passive measurement of sunlit targets. These methods are sensitive to errors in illumination conditions and lack the range information. Our prototype can measure both the range and the spectral information from a single laser pulse. At this stage, the instrument is optimized for short range terrestrial applications. An active hyperspectral LiDAR opens up new possibilities for LiDAR data analysis. The lack of spectral information in traditional monochrome LiDARs rules out many of the classification techniques available for processing of hyperspectral data. Similarly, passive hyperspectral data does not allow extensive use of the classifications based on 3D shape parameters. With both hyperspectral and range data available in a single dataset, the best of the techniques can be applied to form more reliable classification results. The data also allows the mapping of spectral indices in 3D. As an example a Norway spruce is measured and spatial distribution of several spectral indices is illustrated.
AUTOMATIC CALCULATION OF OIL SLICK AREA FROM MULTIPLE SAR ACQUISITIONS FOR DEEPWATER HORIZON OIL SPILL
Authors: Osmanoğlu B. , Özkan C. , Sunar F. , Staples G.
Published: August 2012

Abstract. The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m3 of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries. For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellitebased oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR) satellites are a major contributer of monitoring marine environments for oil spill detection. We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band), Envisat ASAR (C-band) and Alos-PALSAR (L-band) sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days) allow us to eliminate artifacts and increase accuracy. Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.
TOWARDS AN URBAN DEM GENERATION WITH SATELLITE SAR INTERFEROMETRY
Authors: Rossi C. , Fritz T. , Eineder M. , Erten E. , Zhu X. X. , Gernhardt S.
Published: August 2012

Abstract. This paper analyzes the potentials offered by the TanDEM-X mission for the generation of urban DEMs. Operationally acquired urban Raw DEMs are validated using as reference a LiDAR DEM. The approach used for the validation is application-oriented as a subproduct is a derivation of a urban volume map. The mean buildings absolute height error is found to be below 5 meters. Neglecting the buildings geolocation errors, this value drops below 60 centimeters. Nevertheless, the operational municipal mapping is limited to the standard resolution of 12 meters. The limitation is attenuated with the use of high resolution spotlight data. High-resolution raw DEMs over Las Vegas and Berlin are first analyzed. Some modifications to the interferometric processing chain necessary to produce high quality DEMs are studied. The obtained results open a new perspective to the urban DEM generation with satellite SAR interferometry.
MATCHING PERSISTENT SCATTERERS TO BUILDINGS
Authors: Schunert A. , Schack L. , Soergel U.
Published: August 2012

Abstract. Persistent Scatterer Interferometry (PSI) is by now a mature technique for the estimation of surface deformation in urban areas. In contrast to the classical interferometry a stack of interferograms is used to minimize the influence of atmospheric disturbances and to select a set of temporarily stable radar targets, the so called Persistent Scatterers (PS). As a result the deformation time series and the height for all identified PS are obtained with high accuracy. The achievable PS density depends thereby on the characteristics of the scene at hand and on the spatial resolution of the used SAR data. This means especially that the location of PS cannot be chosen by the operator and consequently deformation processes of interest may be spatially undersampled and not retrievable from the data. In case of the newly available high resolution SAR data, offering a ground resolution around one metre, the sampling is potentially dense enough to enable a monitoring of single buildings. However, the number of PS to be found on a single building highly depends on its orientation to the viewing direction of the sensor, its facade and roof structure, and also the surrounding buildings. It is thus of major importance to assess the PS density for the buildings in a scene for real world monitoring scenarios. Besides that it is interesting from a scientific point of view to investigate the factors influencing the PS density. In this work, we fuse building outlines (i.e. 2D GIS data) with a geocoded PS point cloud, which consists mainly in estimating and removing a shift between both datasets. After alignment of both datasets, the PS are assigned to buildings, which is in turn used to determine the PS density per building. The resulting map is a helpful tool to investigate the factors influencing PS density at buildings.
STEREO DERIVED CLOUD TOP HEIGHT CLIMATOLOGY OVER GREENLAND FROM 20 YEARS OF THE ALONG TRACK SCANNING RADIOMETER (ATSR) INSTRUMENTS
Authors: Fisher D. , Muller J.-P.
Published: August 2012

Abstract. Current algorithms for the determination of cloud top height and cloud fraction in Polar Regions tend to provide unreliable results, particularly in the presence of isothermal conditions within the atmosphere. Alternative methods to determine cloud top heights in such regions effectively, from space borne sensors, are currently limited to stereo-photogrammetry and active sensing methods, such as LiDAR. Here we apply the modified census transform to one month of AATSR stereo data from June 2008. AATSR is unique in that it is the only space borne stereo capable instrument providing data continuously in both the visible, near infrared and thermal channels. This allows for year round imaging of the poles and therefore year round cloud top height and cloud fraction estimation. We attempt a preliminary validation of the stereo retrieved cloud top height measurements from AATSR against collocated cloud height measurements from the CALIOP LiDAR instrument. CALIOP provides an excellent validation tool due to its excellent height resolution of between 30-60 meters. In this validation, a pair of collocated swaths is assessed with a total of 154 inter-comparisons; the results show that AATSR correlates well with CALIOP cloud base layers with an R2 score of 0.71. However, in all cases AATSR appears to be underestimating the cloud top height compared to CALIOP, the causes for this are currently not fully understood and more extensive inter-comparisons are required. Once validation is completed a processing chain is in place to process the entire ATSR time-series data generating a 20 year cloud top height dataset for Greenland.
TOTAL COLUMN METHANE RETRIEVALS USING THE TROPOSPHERIC INFRARED MAPPING SPECTROMETER OVER SUNGLINT
Authors: Larsen N. , Kumer J. , Rairden R. , Jablonski K.
Published: August 2012

Abstract. Because it is a greenhouse gas, the detection of methane concentrations is a global issue. Additionally, the presence of methane is indicative of potential valuable petroleum and natural gas deposits. Therefore methane seep detection is useful for petroleum exploration around the world. The detection of methane, and other absorbing gases, over water is an issue for passive systems because one is seeking to detect an absorbing gas over an absorbing surface. The solution to this dilemma is to use the sun/sensor geometry for sun glint off of water to measure the absorbing gas over a reflecting surface, and therefore significantly increase the signal to noise of the measurement being taken. In September of 2010 Lockheed Martin performed a proof of concept by demonstrating from an airship over San Francisco Bay the capability of the Tropospheric Infrared Mapping Spectrometer's (TIMS) hyper spectral sensor to passively measure methane, CO, and water vapor over sunglint water. The Lockheed Martin prototype TIMS sensor system is a hyper spectral grating spectrometer instrument that operates in the 2.3 micron spectral region at 0.25 cm-1 resolution. The Lockheed Martin retrieval algorithm developed applies the kCARTA (kCompressed Atmospheric Radiative Transfer Algorithm) with Jacobians, with the HITRAN 2008 lineshape parameters, to retrieve the total column amount of atmospheric species along with the calibrated TIMS sensors radiometric input. A cell with known amount of methane was placed into the input to the TIMS to simulate atmospheric enhancements near the water surface. The amount in the cell was retrieved well within the uncertainty of 1% of the amount in the cell. Multi frame retrievals on data in which the cell was not placed into the input beam demonstrated 1% precision. In addition, in situ surface measurements were done over a landfill park, where measurements of methane were taken over known hotspots. This research allows for the future development of a system to measure methane, and other gases, for climate and petroleum exploration capabilities.
GLOBAL BURNED AREA MAPPING FROM EUROPEAN SATELLITES: THE ESA FIRE_CCI PROJECT
Authors: Chuvieco E. , Sandow C. , Guenther K. P. , González-Alonso F. , Pereira J. M. , Pérez O. , Bradley A. V. , Schultz M. , Mouillot F. , Ciais P.
Published: August 2012

Abstract. The European Space Agency (ESA) Climate Change Initiative (CCI) is part of the European contribution to the Global Climate Observing System (GCOS) program. Fire disturbance is one of the Essential Climate Variables (ECV) included in the ESA CCI program. It focus on mapping burned area (BA) using European sensors (ATSR, VEGETATION and MERIS data), and in comparing the performance of the results with other existing datasets. The project aims at developing and validating algorithms to produce consistent, stable, error-characterized global BA information. The project includes as well developing algorithms to generate georeferenced and calibrated reflectances of (A)ATSR, VEGETATION and MERIS data, identifying potential sources of confusion with burned areas (clouds, smoke, cloud shadows, water, snow, topographic shadows). The final product will be a merging of BA information derived from three different sensors . The outputs will be adapted to the needs of the atmospheric and vegetation modelling communities.
GROUND-BASED CLOUD OBSERVATION FOR SATELLITE-BASED CLOUD DISCRIMINATION AND ITS VALIDATION
Authors: Yamashita M. , Yoshimura M.
Published: August 2012

Abstract. Solar radiation is a source of energy for ground surfaces. Clouds control energy budget on both local and global scales. We propose the simple ground-based observation method for various sky conditions instead of the existing visual observation. In the paper, we mainly describe how to discriminate clouds area on whole sky images, how to overlay the cloud areas to the satellite-based images and the test experiment. As for the discrimination of sky conditions, we use Sky Index (SI) and Brightness Index (BI) calculated from whole sky imageries. SI shows the extent of the blueness and grayscale and BI indicates the extent of the brightness. Sun, cloud and blue sky areas are divided by SI and BI threshold. As an extension of ground-based observation to satellite-based observation, clouds area discriminated by ground-based observation overlay to satellite images. Through this experiment, the utilities of ground-based cloud observation are discussed. The proposed ground-based cloud observation method and its satellite-based extension should be connected to satellite products with high quality by implementation of sky and clouds observation covering a wide area.
REMOTE SENSING OF WATER QUALITY IN OPTICALLY COMPLEX LAKES
Authors: Kutser T. , Paavel B. , Verpoorter C. , Kauer T. , Vahtmäe E.
Published: August 2012

Abstract. Solving of several global and regional problems requires adequate data about lake water quality parameters like the amount and type of phytoplankton dominating in the lakes, the amount of dissolved and coloured dissolved organic matter and/or concentration of suspended sediment. Remote sensing is the only practical way to study many lakes provided it can produce sufficiently accurate estimates of the water characteristics. We studied optically very variable lakes in order to test both physics based methods and conventional band-ratio type algorithms in retrieval of water parameters. The modelled spectral library used in the physics based approach provided very good results for chlorophyll-a retrieval. The number of different concentrations of CDOM and suspended matter used in the simulations was too low to provide good estimates of these parameters. Extending the spectral library is currently in progress. Band-ratio type algorithms worked well in chlorophyll-a and CDOM retrieval. None of the algorithms tested for total suspended matter, organic suspended matter and inorganic suspended matter retrieval performed well enough and there is need in further testing.
KAL-HAITI: A RESEARCH DATABASE FOR RISKS MANAGEMENT AND SUSTAINABLE RECONSTRUCTION IN HAITI
Authors: Giros A. , Fontannaz D. , Allenbach B. , Treinsoutrot D. , De Michele M.
Published: August 2012

Abstract. Following the 12th January 2010 earthquake in Haiti, the French Agence Nationale de la Recherche has funded a project named KAL-Haiti which aims at gathering remote sensing imagery as well as in-situ and exogenous data into a knowledge base. This database, seen as a shareable resource, can serve as a basis for helping the reconstruction of the country, but also as a reference for scientific studies devoted to all phases of risk management. The project main outcome will be a geo-referenced database containing a selection of remotely sensed imagery acquired before and after the disastrous event supplemented with all relevant ancillary data, and enriched with in-situ measurements and exogenous data. The resulting reference database is freely available for research and for reconstruction tasks. It is strongly expected that users will also become contributors by sharing their own data production, thus participating to the growth of the initial kernel. The database will also be enriched with new satellite images, monitoring the evolution of the Haitian situation over the next 10 years.
Using MODIS Normalized Difference Vegetation Index to monitor seasonal and inter-annual dynamics of wetland vegetation in the Great Artesian Basin: a baseline for assessment of future changes in a unique ecosystem
Authors: Petus C. , Lewis M. , White D.
Published: August 2012

Abstract. The Great Artesian Basin mound springs (Australia) are unique wetland ecosystems of great significance. However, these unique ecosystems are endangered by anthropogenic water extraction. Relationships have been established between the vegetated wetland area and the discharge associated with individual springs, providing a potential means of monitoring groundwater flow using measurements of wetland area. Previous studies using this relationship to monitor Great Artesian Basin springs have used aerial photography or high resolution satellite images, giving sporadic temporal information. These "snapshot " studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study, the potential of medium resolution MODIS Normalized Difference Vegetation Index data for studying the long-term and high frequency temporal dynamics of wetland vegetation at the Dalhousie Spring Complex of the GAB is tested. Photosynthetic activity within Dalhousie wetlands could be differentiated from surrounding land responses. The study showed good correlation between wetland vegetated area and groundwater flow, but also the important influence of natural species phenologies, rainfall, and human activity on the observed seasonal and inter-annual vegetation dynamic. Declining trends in the extent of wetland areas were observed over the 2000– 2009 period followed by a return of wetland vegetation since 2010. This study underlined the need to continue long-term medium resolution satellite studies of the Great Artesian Basin as these data provide a good understanding of variability within the wetlands, give temporal context for less frequent studies and a strong baseline for assessment of future changes.
PARTICIPATORY GIS FOR SOIL CONSERVATION IN PHEWA WATERSHED OF NEPAL
Authors: Bhandari K. P.
Published: August 2012

Abstract. Participatory Geographic Information Systems (PGIS) can integrate participatory methodologies with geo-spatial technologies for the representation of characteristic of particular place. Over the last decade, researchers use this method to integrate the local knowledge of community within a GIS and Society conceptual framework. Participatory GIS are tailored to answer specific geographic questions at the local level and their modes of implementation vary considerably across space, ranging from field-based, qualitative approaches to more complex web-based applications. These broad ranges of techniques, PGIS are becoming an effective methodology for incorporating community local knowledge into complex spatial decision-making processes. The objective of this study is to reduce the soil erosion by formulating the general rule for the soil conservation by participation of the stakeholders. The poster was prepared by satellite image, topographic map and Arc GIS software including the local knowledge. The data were collected from the focus group discussion and the individual questionnaire for incorporate the local knowledge and use it to find the risk map on the basis of economic, social and manageable physical factors for the sensitivity analysis. The soil erosion risk map is prepared by the physical factors Rainfall-runoff erosivity, Soil erodibility, Slope length, Slope steepness, Cover-management, Conservation practice using RUSLE model. After the comparison and discussion among stakeholders, researcher and export group, and the soil erosion risk map showed that socioeconomic, social and manageable physical factors management can reduce the soil erosion. The study showed that the preparation of the poster GIS map and implement this in the watershed area could reduce the soil erosion in the study area compared to the existing national policy.
GEOGRAPHICAL INFORMATION ANALYSIS OF TSUNAMI FLOODED AREA BY THE GREAT EAST JAPAN EARTHQUAKE USING MOBILE MAPPING SYSTEM
Authors: Koarai M. , Okatani T. , Nakano T. , Nakamura T. , Hasegawa M.
Published: August 2012

Abstract. The great earthquake occurred in Tohoku District, Japan on 11th March, 2011. This earthquake is named "the 2011 off the Pacific coast of Tohoku Earthquake", and the damage by this earthquake is named "the Great East Japan Earthquake". About twenty thousand people were killed or lost by the tsunami of this earthquake, and large area was flooded and a large number of buildings were destroyed by the tsunami. The Geospatial Information Authority of Japan (GSI) has provided the data of tsunami flooded area interpreted from aerial photos taken just after the great earthquake. This is fundamental data of tsunami damage and very useful for consideration of reconstruction planning of tsunami damaged area. The authors analyzed the relationship among land use, landform classification, DEMs data flooded depth of the tsunami flooded area by the Great East Japan Earthquake in the Sendai Plain using GIS. Land use data is 100 meter grid data of National Land Information Data by the Ministry of Land, Infrastructure, Transportation and Tourism (MLIT). Landform classification data is vector data of Land Condition Map produced by GSI. DEMs data are 5 meters grid data measured with LiDAR by GSI after earthquake. Especially, the authors noticed the relationship between tsunami hazard damage and flooded depth. The authors divided tsunami damage into three categories by interpreting aerial photos; first is the completely destroyed area where almost wooden buildings were lost, second is the heavily damaged area where a large number of houses were destroyed by the tsunami, and third is the flooded only area where houses were less destroyed. The flooded depth was measured by photogrammetric method using digital image taken by Mobile Mapping System (MMS). The result of these geographic analyses show the distribution of tsunami damage level is as follows: 1) The completely destroyed area was located within 1km area from the coastline, flooded depth of this area is over 4m, and no relationship between damaged area and landform classification. 2) The heavily damaged area was observed up to 3 or 4km from the coastline. Flooded depth of this area is over 1.5m, and there is a good relationship between damaged area and height of DEMs. 3) The flood only area was observed up to 4 or 5km from the coastline. Flooded depth of this area was less than 1.5m, and there is a good relationship between damaged area and landform. For instance, a certain area in valley plain or flooded plain was not affected by the tsunami, even though an area with almost the same height in coastal plain or delta was flooded. These results mean that it is important for tsunami disaster management to consider not only DEMs but also landform classification.
ESTIMATION OF VEGETATION HEIGHT THROUGH SATELLITE IMAGE TEXTURE ANALYSIS
Authors: Petrou Z. I. , Tarantino C. , Adamo M. , Blonda P. , Petrou M.
Published: August 2012

Abstract. Vegetation height plays a crucial role in various ecological and environmental applications, such as biodiversity assessment and monitoring, landscape characterization, conservation planning and disaster management. Its estimation is traditionally based on in situ measurements or airborne Light Detection And Ranging (LiDAR) sensors. However, such methods are often proven insufficient in covering large area landscapes due to high demands in cost, labor and time. Considering a multispectral image from a passive satellite sensor as the only available source of information, we propose and evaluate new ways of discriminating vegetated habitat species according to their height, through calculation of texture analysis measures, based on local variance, entropy and local binary patterns. The methodology is applied in a Quickbird image of Le Cesine protected site, Italy. The proposed methods are proven particularly effective in discriminating low and mid phanerophytes from tall phanerophytes, having a height of less and more than 2 meters, respectively. The results indicate a promising alternative in vegetation height estimation when in situ or LiDAR data are not available or affordable, thus facilitating and reducing the cost of ecological monitoring and environmental sustainability planning tasks.
ANALYSING AND QUANTIFYING VEGETATION RESPONSES TO RAINFALL WITH HIGH RESOLUTION SPATIO-TEMPORAL TIME SERIES DATA FOR DIFFERENT ECOSYSTEMS AND ECOTONES IN QUEENSLAND
Authors: Schmidt M. , Udelhoven T.
Published: August 2012

Abstract. Vegetation responses and ecosystem function are spatially variable and influenced by climate variability. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to combine MODIS (Moderate Resolution Imaging Spectrometer) and Landsat TM/ETM+ (Thematic Mapper/ Enhanced Thematic Mapper plus) imagery for an 8 year dataset (2000–2007) at 30m spatial resolution with 8 day intervals. This dataset allows for a functional analysis of ecosystem responses, suitable for heterogeneous landscapes. Derived vegetation index information in form of the NDVI (Normalised Difference Vegetation Index) was used to investigate the relationship between vegetation responses and gridded rainfall data for regional ecosystems. A hierarchical decomposition of the time series has been carried out in which relationships among the time-series were individually assessed for deterministic time-series components (trend component and seasonality) as well as for the stochastic seasonal anomalies. While no common long-term trends in NDVI and rainfall data in the time period considered exist, there is however, a strong concurrence in the seasonally of NDVI and rainfall data. This component accounts for the majority of variability in the time-series. On the level of seasonal anomalies, these relationships are more subtle. The statistical analysis required, among others, the removal of temporal autocorrelation for an unbiased assessment of significance. Significant lagged correlations between rainfall and NDVI were found in complex Queensland savannah vegetation communities. For grasslands and open woodlands, significant relationships with lag times between 8 and 16 days were found. For denser, evergreen vegetation communities greater lag times of up to 2.5 months were found. The derived distributed lag models may be used for short-term NDVI and biomass predictions on the spatial resolution scale of Landsat (30m).
RIPARIAN VEGETATION STATUS AND RATES OF WATER USE FROM SATELLITE DATA
Authors: Sheffield K. , Abuzar M. , Whitfield D. , McAllister A. , O'Connell M.
Published: August 2012

Abstract. Hydrology and water availability are key determinants of the health of riparian vegetation systems, and an understanding of the interactions between vegetation and hydrology is a prerequisite for the maintenance and improvement of these systems under managed water regimes. Changes to natural flooding cycles, caused by the regulation of river flows and irrigation activities, have changed the composition and amount of vegetation, and the distribution of species within riparian areas (Chong and Ladson, 2003; Lawrence and Colloff, 2008). The extent and frequency of flooding cycles are key issues for the health of riparian ecosystems under controlled water management regimes. This paper demonstrates the potential contribution of satellite-based measurements to an improved understanding of the changes in vegetation status of riparian systems, and, also, of their water requirement. Evapotranspiration (ET) and Normalised Difference Vegetation Index (NDVI) of the Barmah Forest were derived from satellite imagery over a number of years. NDVI provided a general measure of vegetation status and cover. ET measures provided an indication of the availability of water to the existing vegetation, and an assessment of areas under water-stress (Anderson et al., 2012). Previous work has demonstrated that these indicators provide a comprehensive measure of riparian vegetation status (Sheffield et al., 2011), and estimates of vegetation water requirement (Whitfield et al., 2010a; Sheffield et al., 2011). This paper addresses changes in NDVI and ET rate of major vegetation classes in the Barmah Forest over the period, 1993 – 2008. Measures of ET and NDVI, analysed in conjunction with rainfall and river flow data, provided insights into the response of vegetation to changes in water availability, which may be used to evaluate impacts of management practices and water regime within riparian zones.
REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN
Authors: Wittamperuma I. , Hafeez M. , Pakparvar M. , Louis J.
Published: August 2012

Abstract. Remote sensing is a rapid and reliable method for estimating crop growth data from individual plant to crops in irrigated agriculture ecosystem. The LAI is one of the important biophysical parameter for determining vegetation health, biomass, photosynthesis and evapotranspiration (ET) for the modelling of crop yield and water productivity. Ground measurement of this parameter is tedious and time-consuming due to heterogeneity across the landscape over time and space. This study deals with the development of remote-sensing based empirical relationships for the estimation of ground-based LAI (LAIG) using NDVI, modelled with and without atmospheric correction models for three irrigated crops (corn, wheat and rice) grown in irrigated farms within Coleambally Irrigation Area (CIA) which is located in southern Murray Darling basin, NSW in Australia. Extensive ground truthing campaigns were carried out to measure crop growth and to collect field samples of LAI using LAI- 2000 Plant Canopy Analyser and reflectance using CROPSCAN Multi Spectral Radiometer at several farms within the CIA. A Set of 12 cloud free Landsat 5 TM satellite images for the period of 2010-11 were downloaded and regression analysis was carried out to analyse the co-relationships between satellite and ground measured reflectance and to check the reliability of data sets for the crops. Among all the developed regression relationships between LAI and NDVI, the atmospheric correction process has significantly improved the relationship between LAI and NDVI for Landsat 5 TM images. The regression analysis also shows strong correlations for corn and wheat but weak correlations for rice which is currently being investigated.
A PROPOSED NEW VEGETATION INDEX, THE TOTAL RATIO VEGETATION INDEX (TRVI), FOR ARID AND SEMI-ARID REGIONS
Authors: Fadaei H. , Suzuki R. , Sakai T. , Torii K.
Published: August 2012

Abstract. Vegetation indices that provide important key to predict amount vegetation in forest such as percentage vegetation cover, aboveground biomass, and leaf-area index. Arid and semi-arid areas are not exempt of this rule. Arid and semi-arid areas of northeast Iran cover about 3.4 million ha and are populated by two main tree species, the broadleaf Pistacia vera (pistachio) and the conifer Juniperus excelsa ssp. polycarpos (Persian juniper). Natural stands of pistachio in Iran are not only environmentally important but also genetically essential as seed sources for pistachio production in orchards. We investigated the relationships between tree density and vegetation indices in the arid and semi-arid regions in the northeast of Iran by analysing Advanced Land Observing Satellite (ALOS) data PRISM is a panchromatic radiometer with a 2.5 m spatial resolution at nadir, and has one band with a wavelength of 0.52–0.77 μm (JAXA EORC). AVNIR-2 is a visible and near infrared radiometer for observing land and coastal zones with a 10 m spatial resolution at nadir, and has four multispectral bands: blue (0.42–0.50 μm), green (0.52–0.60 μm), red (0.61–0.69 μm), and near infrared (0.76–0.89 μm) (JAXA EORC). In this study, we estimated various vegetation indices using maximum filtering algorithm (5×5) and examined. This study carried out of juniper forests and natural pistachio stand using Advanced Land Observing Satellite (ALOS) and field inventories. Have been compared linear regression model of vegetation indices and proposed new vegetation index for arid and semi-arid regions. Also, we estimated the densities of juniper forests and natural pistachio stands using remote sensing to help in the sustainable management and production of pistachio in Iran. We present a new vegetation index for arid and semi-arid regions with sparse forest cover, the Total Ratio Vegetation Index (TRVI), and we investigate the relationship of the new index to tree density by analysing data from the Advanced Land Observing Satellite (ALOS) using 5×5 maximum filtering algorithms. The results for pistachio forest showed the coefficient regression of NDVI, SAVI, MSAVI, OSAVI, and TRVI were (R2= 0.68, 0.67, 0.68, 0.68, and 0.71) respectively. The results for juniper forest showed the coefficient regression of NDVI, SAVI, MSAVI, OSAVI, and TRVI were (R2= 0.51, 0.52, 0.51, 0.52, and 0.56) respectively. I hope this research can provide decision of managers to helping sustainable management for arid and semi-arid regions in Iran.
ESTIMATING MIXED BROADLEAVES FOREST STAND VOLUME USING DSM EXTRACTED FROM DIGITAL AERIAL IMAGES
Authors: Sohrabi H.
Published: August 2012

Abstract. In mixed old growth broadleaves of Hyrcanian forests, it is difficult to estimate stand volume at plot level by remotely sensed data while LiDar data is absent. In this paper, a new approach has been proposed and tested for estimating stand forest volume. The approach is based on this idea that forest volume can be estimated by variation of trees height at plots. In the other word, the more the height variation in plot, the more the stand volume would be expected. For testing this idea, 120 circular 0.1 ha sample plots with systematic random design has been collected in Tonekaon forest located in Hyrcanian zone. Digital surface model (DSM) measure the height values of the first surface on the ground including terrain features, trees, building etc, which provides a topographic model of the earth's surface. The DSMs have been extracted automatically from aerial UltraCamD images so that ground pixel size for extracted DSM varied from 1 to 10 m size by 1m span. DSMs were checked manually for probable errors. Corresponded to ground samples, standard deviation and range of DSM pixels have been calculated. For modeling, non-linear regression method was used. The results showed that standard deviation of plot pixels with 5 m resolution was the most appropriate data for modeling. Relative bias and RMSE of estimation was 5.8 and 49.8 percent, respectively. Comparing to other approaches for estimating stand volume based on passive remote sensing data in mixed broadleaves forests, these results are more encouraging. One big problem in this method occurs when trees canopy cover is totally closed. In this situation, the standard deviation of height is low while stand volume is high. In future studies, applying forest stratification could be studied.
CROWN DELINEATION INFLUENCE ON STANDING VOLUME CALCULATIONS IN PROTECTED AREA
Authors: Stereńczak K. , Miścicki S.
Published: August 2012

Abstract. The aim of this study was to evaluate the automatically determined parameters of tree crowns, which are then used in two-phase inventory method of growing stock. Research was performed in forest stands of different age, located in the Stolowe Mountains National Park (south-western Poland) where the dominant species was Norway spruce (Picea abies L.). On the test area of approximately 500 hectares, 35 sample plots were measured. On LIDAR-based Crow Height Model (CHM), in the places corresponding to the position of 500 m2 circular ground samples, automatic segmentation was carried out. The extent of the crown was associated with the height of the tree. Two variants of the assigning separate crowns in the sample were used: (1) according to the centroid position, (2) according to the location of any fragment of the crown inside the sample plot boundary. In each of the variants five series of measurements with different relative height of the range 0.65–0.8 (with a gap of 0.05) were carried out. Relationship between the volume of living trees measured on the ground and LIDAR parameters (average height of trees and tree canopy projection area) automatically measured based on CHM was determined. Multiple correlation coefficient differed depending on the location to extract coverage crowns and ranged from 0.687 to 0.788. The variant of counting of all trees with crowns or pieces inside the sample appeared to perform better. The relationship between the above-indicated characteristics was stronger after elimination of dead trees (about 0.1 for each of cases). This means that for measurements of the growing stock in forests under protection, it is necessary to improve the process of automatic segmentation of the crown, by identification and elimination of dead trees – usually present at sample plot.
TRAJECTORY ANALYSIS OF FOREST CHANGES IN NORTHERN AREA OF CHANGBAI MOUNTAINS, CHINA FROM LANDSAT TM IMAGE
Authors: Huang F. , Zhang H. J. , Wang P.
Published: August 2012

Abstract. Based on the information from integrated Landsat TM/ETM images and geographic information systems (GIS), using dynamic model, landscape indices and temporal trajectory analysis, spatio-temporal changes in forest in the northern area of Changbai Mountains were investigated in the past 20 years. The results showed that the forests decreased by 141461 ha at the annual decrease rate of 0.19% from 1986 to 2006. The numbers of forest patch increased, while the patch size of forest land declined. Forestland experienced the process of substantial fragmentation. Close forest showed a net reduction of 13.3×104ha. The typical trajectories of forest changes included forestland-forestland-cropland, forestland-cropland-cropland, forestland-forestland-grassland and forestland-cropland-built-up land. The total area of human-induced change is 1.7 times than that of natural change in the study area. Population, cropland area and gross domestic product increased significantly as forests decreased.
DEVELOPMENTS IN MONITORING RANGELANDS USING REMOTELY-SENSED CROSS-FENCE COMPARISONS
Authors: Kilpatrick A. D. , Warren-Smith S. C. , Read J. L. , Lewis M. M. , Ostendorf B.
Published: August 2012

Abstract. This paper presents a new method for the use of earth-observation images to assess relative land condition over broad regions, using a cross-fence comparison methodology. It controls for natural spatial and temporal variables (e.g. rainfall, temperature soils, ecosystem) so that we can objectively monitor rangelands and other areas for the effects of management. The method has been tested with small and large scale theoretical models, as well as a case study in South Australian rangelands. This method can also be applied in other systems and experiments such as field trials of crop varieties as a robust spatial statistic.
OPERATIONAL OBSERVATION OF AUSTRALIAN BIOREGIONS WITH BANDS 8–19 OF MODIS
Authors: McAtee B. K. , Gray M. , Broomhall M. , Lynch M. , Fearns P.
Published: August 2012

Abstract. Data from bands 1–7 are the most common bands of the MODIS instrument used for near-real time terrestrial earth observation operations in Australia. However, many of Australia's bioregions present unique scenarios which constitute a challenge for quantitative environmental remote sensing. We believe that data from MODIS bands 8–19 may provide significant benefit to Earth observation over particular bioregions of the Australian continent. Examples here include the use of band 8 in characterising aerosol optical depth over typically bright land surfaces and accounting for anomalous retrievals of atmospheric water vapour obtained using MOD05 based on the abundance of Australia's 'red dirt', which exhibits absorption features in the near infrared bands 17–19 of MODIS. Bioregion-focused applications such as those mentioned above have driven the development of automated processing, infrastructure for the atmospheric and BRDF correction of the first 19 bands of MODIS rather than only the first 7, which is more often the case. This work has been facilitated by the AusCover project which is the remote sensing component of the Terrestrial Ecosystem Research Network (TERN), itself a program designed to create a new generation of infrastructure for ecological study of the Australian landscape.
AUTOMATED CONSTRUCTION OF COVERAGE CATALOGUES OF ASTER SATELLITE IMAGE FOR URBAN AREAS OF THE WORLD
Authors: Miyazaki H. , Iwao K. , Shibasaki R.
Published: August 2012

Abstract. We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST), Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.
HIGH TEMPORAL FREQUENCY BIOPHYSICAL AND STRUCTURAL VEGETATION INFORMATION FROM MULTIPLE REMOTE SENSING SENSORS CAN SUPPORT MODELLING OF EVENT BASED HILLSLOPE EROSION IN QUEENSLAND
Authors: Schoettker B. , Searle R. , Schmidt M. , Phinn S.
Published: August 2012

Abstract. This study demonstrates the potential applicability of high temporal frequency information on the biophysical condition of the vegetation from a time series of the global Moderate Resolution Imaging Spectroradiometer (MODIS) Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from 2000 to 2006 (collection 4; 8-day composites in 1 km spatial resolution) to improve modelling of soil loss in a tropical, semi-arid catchment in Queensland. Combining the biophysical information from the MODIS FPAR with structural vegetation information from the Geoscience Laser Altimeter System on the Ice, Cloud, and land Elevation Satellite (ICESat) for six vegetation structural categories identified from a Landsat Thematic Mapper 5 (TM) and Enhanced Thematic Mapper 7 (ETM+) woody foliage projective cover product representing floristically and structurally homogeneous areas, dynamic vegetative cover factor (vCf) estimates were calculated. The dynamic vCf were determined in accordance with standard calculation methods used in erosion models worldwide. Time series of dynamic vCf were integrated into a regionally improved version of the Universal Soil Loss Equation (USLE) to predict daily soil losses for the study area. Resulting time series of daily soil loss predictions averaged over the study area coincided well with measures of total suspended solids (TSS) (mg/l) at a gauge at the outlet of the catchment for three wet seasons (R2 of 0.96 for a TSS-event). By integrating the dynamic vCf into modified USLE, the strength of the dependence of daily soil loss predictions to the only other dynamic factor in the equation – daily rainfall erosivity – was reduced.
THE USE OF MODIS DATA TO DEFINE NATURAL BOUNDARIES AND REGIONS IN THE MARINE WATER COLOUMN
Authors: Leach J. H. J. , Kitchingman A.
Published: August 2012

Abstract. This study looks at the elements that define a natural boundary and its marine variant. It then aims to quantify and delimit natural marine boundaries from satellite sea surface temperature and ocean colour imagery. Natural boundaries often have a fuzzy or zonal nature, can be dependent on and independent from the character of the region which they bound, and have temporal characteristics that occur over a variety of temporal scales. Natural marine boundaries have the added complexity of occurring in three dimensions and of being temporally dynamic throughout the water column. A monthly time-series of MODIS satellite imagery from July 2002 to June 2006 was used in this study. The standardised principle component analysis (sPCA) was used to identify the mean state of identifiable natural process and to quantifying a degree of spatio-temporal (seasonal) dichotomy in detected marine processes. Component images from the sPCA provided a spatial representation of marine phenomena, while sPCA loadings indicated the temporal fluxes exhibited in a given component. Classification of significant sPCA components was conducted to derive regional boundaries. Initially, this was performed in an unsupervised manner using an ISO process. Subsequent classified images were then simplified using a combination of dendrograms and knowledge-based examination. A comparison of these results with similarly derived regionalisation showed that the spatio-temporal representations have the potential to further inform marine spatial management regimes. It was also shown that the delimitation of natural phenomena is feasible and can have seasonal dynamics represented.