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ID: 60105
Title: Assessing the effects of land use spatial structure on urban heat islands using HJ-IB remote sensing imagery in Wuhan, China.
Author: Hao Wu, Lu-Ping Ye, Wen-Zhong Shi, Keith C. Clarke.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 67-78 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Urban heat island, Land use spatial structure, Vegetation indexes, Landscape metrices, Fractal analysis, HJ-IB.
Abstract: Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, Vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and the remote sensing satellites were compared and analyzed to validate the performance of the HJ-IB. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three land-scape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decrease from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.
Location: TE 15 New Biology Building
Literature cited 1: Aguiar, R., Oliveira, M., Gonccedilaves, H., 2002. Climate change impacts on the thermal performance of Portuguese buildings. Results of the SIAM study. Build.Serv.Eng.Res.Technol. 23 (4), 223-231. Arnfield, A.J., 2003. Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island.Int.J.Climatol. 23 (1), 1-26.
Literature cited 2: Backes, A.R., Bruno, OM., 2013. Texture analysis using volume-radius fractal dimension. Appl.Math.Comput. 219 (11), 5870-5875. Batty, M., Longley, P.A., 1987. Fractal-based description of urban form. Environ.Plan. B: Plan.Des 14 (2), 123-134.

ID: 60104
Title: Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing.
Author: Shengguo Gao, Zhongli Zhu, Shaomin Liu, Rui Jin, Guangchao Yang, Lei Tan.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 54-66 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Soil moisture, Remote sensing, Wireless sensor network (WSN), Bayesian maximum entropy (BME), Soft data.
Abstract: Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the krigged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based the linear regression, then the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary information compared to Co-OK, and BME outperforms RK by integrating the auxiliary data in a probability form.
Location: TE 15 New Biology Building
Literature cited 1: Akylidiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E., 2002. Wireless sensor network: a survey.Comput.Netw.38, 393-422. Asli, M., Marcotte, D., 1995. Comparisoin of approaches to spatial estimation in a bivariate context.Math.Geol. 27, 641-658.
Literature cited 2: Bartlett, J.E., Kotrlik, J.W., Higgins, C.C., 2001. Organizational research: determining appropriate sample size in survey research appropriate sample size in survey research.Inf.Technol.Learn.Perform.J. 19 (1), 43-50. Bogaert, P., D ' Or, D., 2002. Estimating soil properties from thematic soil maps. Soil Sci.Soc.Am.J.66, 1492-1500.

ID: 60103
Title: Developing MODIS-based retrieval models of suspended particulate matter concentration in Dongting Lake, China.
Author: Guofeng Wu, Liangjie Liu, Fangyuan Chen, Teng Fei.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 46-53 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Lake management, Suspended particulate matter, Remote sensing, Empirical model.
Abstract: To case-II waters, suspended particulate matter (SPM) is one of the dominant water constituents, SPM concentration (CSPM) is a key parameter describing water quality, and developing remote sensing-based CSPM retrieval models is foundation for obtaining its spatiotemporal distributions. This study aimed to develop moderate resolution imaging spectroradiometer (MODIS)-based CSPM empirical retrieval models in Dongting Lake, China. The 95 CSPM measurements on 31 August 2012 and 14 June 2013and their corresponding MODIS Terra images were used to calibrate models, and the model calibration results showed that the 250 m MODIS red band obtained better fitting accuracies than the near infrared band; the quadratic and exponential models of single red band explained 75 % (estimated standard errors (SE) =6.19mg/l) and 71 % (SE=6.54 mg/l) of the variation of CSPM; and the quadratic and exponential models of red minus shortwave infrared (SWIR) band at 1240 and 1640 nm explained 72-73 % (SE=6.43-6.48 mg/l ) and 68-69 % (SE=6.83-6.96 mg/l) of the variations of CSPM, respectively. The quadratic and exponential models of red band and red minus SWIR band were applied to the MODIS Terra image on 16 September 2013 to estimate CSPM values. By comparing the estimated CSPM values on 16 September 2013 and the measured ones on 17 September 2013 at 40 sampling points for model validations, the results indicated that there existed significantly strong correlations between the measured and estimated CSPM values at a significance level of 0.05 for all models, and the exponential model of red minus SWIR band at 1240 nm achieved the best estimation result within all models. Such result provided foundation for obtaining the spatiotemporal distribution information of CSPM from MODIS images in Dongting Lake, which will be helpful for understanding, managing and protecting this ecosystem.
Location: TE 15 New Biology Building
Literature cited 1: Binding, C.E., Jerome, J.H., Bukata, R.P., Booty, W.G., 2010. Suspended particulate matter in Lake Erie derived from MODIS aquatic colour imagery.Int.J.Remote Sens, 31 (19), 5239-5255. Chen, S.S., Huang, W.R., Chen, X.Z., 2011a. An enhanced MODIS remote sensing model for detecting rainfall effects on sediment plume in the coastal waters of Apalachicola Bay.Mar.Environ.Res.72 (5), 265-272.
Literature cited 2: Chen, S.S., Huang, W.R., Chen, W.Q., Wang, H.Q., 2011b.Remote sensing analysis of rainstorm effects on sediment concentrations in Apalachicola Bay, USA. Ecol. Inform. 6 (2), 147-155. Chen, S.S., Huang, W.R., Wang, H.Q., Li, D., 2009.Remote sensing assessment of sediment re-suspension during Hurricane Frances in Apalachicola Bay, USA, E.col. Inform. 6 (2), 147-155.

ID: 60102
Title: Assessment of rice leaf chlorophyll content using visible bands at different growth stages at both the leaf and canopy scale.
Author: M.M. Saberioon, M.S.M. Amin, A.R. Anuar, A. Gholizadeh, A. Wayayok, S. Khairunniza-Bejo.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 35-45 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Conventional digital camera, Image analysis, Rice, Nitrogen, Principal component analysis, Low altitude remote sensing.
Abstract: Nitrogen is n important variable farming management. The objectives of this study were to develop and test a new method to determine the status of nitrogen and chlorophyll content in rice leaf by analysing and considering all visible bands derived from images captured using a conventional digital camera. The images from the 6-pannel leaf colour chart were acquired using Basler Scout scA640-70fc under light-emitting diode lighting, in which principal component analysis was used to retain the lower order principal component to develop a new index. Digital photographs of the upper most collared leaf of rice (Oriza sativa L), grown over a range of soils with different nitrogen treatments, were processed into 11 indices and IPCA through six growth stages. Also a conventional digital camera mounted to an unmanned aerial vehicle was used to acquire images over the rice canopy for the purpose of verification. The result indicated that the conventional digital camera at the both leaf (r=-0.81) and the canopy (r=0.78) scale could be used as a sensor to determine the status of chlorophyll content in rice plants through different growth stages. This indicates that conventional low-cost digital cameras can be used for determining chlorophyll content and consequently for monitoring nitrogen content of the growing rice plants, thus offering a potentially inexpensive, fast, accurate and suitable tool for rice growers. Additionally, results confirmed that a low cost LARS system would be well suited for high spatial and temporal resolution images and data analysis for proper assessment of key nutrients in rice farming in a fast, inexpensive and non-destructive way.
Location: TE 15 New Biology Building
Literature cited 1: Aber, J.S., Aaviksoo, K. Karofeld, E., Aber, S.W., 2002. Patterns in Estonian bogs as depicted in colour kite aerial photographs.Suo 53, 1-15. Adamsen, F.J., Pinter, P.J., Barnes, E.M., LaMorte, R.L., Wall, G.W., Leavitt, S.W., Kimbau, B.A., 1999. Measuring wheat senescence with a digital camera. Crop Sci.39, 719-724.
Literature cited 2: Bayer, B.E., 1976. Color imaging array. US Patent 3,971,065.Eastman Kodak Company, Rochester, N.Y. Blackmer, T.M., Schepers, J.S., 1995. Use of a chlorophyll meter to monitor nitrogen status and schedule fertigation for corn.J. Prod. Agric. 8, 56-60.

ID: 60101
Title: Impact of the construction of a large dam on riparian vegetation cover at different elevation zones as observed from remotely sensed data.
Author: Christopher H.Kellogg, Xiaobing Zhou.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 19-34 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Vegetation cover, Three Gorges Dam, MODIS vegetation index, Time series, Elevation zone, Environmental impact.
Abstract: The impact of the construction of a large dam on riparian vegetation cover can be multifold. How the riparian vegetation cover changes at different elevation zones in response to the construction of a large dam and the subsequent impound of reservoir water is still an open question. In this study, we used satellite remote sensing data integrated with geographic information system (GIS) to monitor vegetation cover change at different riparian elevation zones on large spatial scale, taking the Three Gorges Dam in China as an example. Due to the large scale of this newly formed reservoir, it is expected to impact the riparian vegetation canopy both directly and indirectly. We chose to monitor vegetation cover changes along the 100 km riparian stretch of river directly upstream of the Three Gorges Dam site, over the construction period of eleven years (2000-2010), using MODIS vegetation indices products, digital elevation model (DEM) data from ASTER, and the time series water level data of the Three Gorges reservoir as the data sources. Results show that non-vegetated area increased within the elevation zone of 175-177 m and no change in vegetation cover was observed above 775 m in elevation. Regression analysis between the vegetation index data and the reservoir water level shows that increasing water levels have had a negative impact on vegetation cover below 175 m, a positive impact on vegetation cover is limited to the region between 175 and 775 m, and no significant impact was observed above 775 m. MODIS EVI product is less sensitive in mapping non-vegetated land cover change, but more sensitive in mapping vegetated land cover change, caused by the reservoir water level variation; both products are similar in effectively tracking a trend land cover change, caused by the reservoir water level variation, both products are similar in effectively tracking a trend between land cover change in each elevation zone with time or with reservoir water level.
Location: TE 15 New Biology Building
Literature cited 1: Baxter, R.M., 1977. Environmental effects of dams and impoundments. Annu.Rev.Ecol.Syst, 8, 255-283. Beck, P., Atzberger, C., Hogda, K., Johansen, B., Skidmore, A., 2006. Improved monitoring of vegetation dynamics of very high altitudes: a new method using MODIS NDVI, Remote Sens.Environ.100, 321-334.
Literature cited 2: Bellone, T., Boccardo, P., Perez, F., 2009. Investigation of vegetation dynamics using long-term normalized difference vegetation index time series.Am.J. Environ. Sci 5 (4), 460-466. Chen, G., 1993. Studies on Influences of Three Gorges Project on Ecological Environment. Science Press, Beijing, China.

ID: 60100
Title: Image-based correlation of Laser Scanning point cloud time series for landslide monitoring.
Author: Julien Travelleti, Jean-Philippe Malet, Christophe Delacourt.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 32. 1-18 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Terrestrial Laser Scanning, Point clouds, Image correlation, Landslide, Kinematics, Strain analysis.
Abstract: Very high resolution monitoring of landslide kinematics is an important aspect for a physical understanding of the failure mechanisms and for quantifying the associated hazard. In the last decade, the potential of Terrestrial Laser Scanning (TLS) to monitor slow-moving landslides has been largely demonstrated but accurate processing methods are still needed to extract useful information available in point cloud time series. This work presents an approach to measure the 3D deformation and displacement patterns from repeated TLS surveys. The method is based on the simplification of a 3D matching problem in 2D matching problem by using a 2D problem by using a 2D statistical normalized cross-correlation function. The computed displacement amplitudes are compared to displacements (1) calculated with the classical approach of iterative closest point and (2) measured from repeated dGPS observations. The performance of the method is tested on a 3 years dataset acquired at the Super-Sauze landslide (South French Alps) The observed landslide displacements are heterogeneous in time and space. Within the landslide, sub-areas presenting different deformation patterns (extension, compression) are detected by a strain analysis. It is demonstrated that pore water pressure changes within the landslide is the main controlling factor of the kinetics.
Location: TE 15 New Biology Building
Literature cited 1: Abellan, A., Jaboyedoff, M., Oppikoffer, T., Vilaplana, J.M., 2009. Detection of milli-metric deformation using terrestrial laser scanner. : Experiment and application to a rockfall event.Nat.Hazards Earth Syst.Sci 9, 365-372. Aryal, A., Brooks, A.B., Reid, M.E., Bawden, G.W., Pawlak, G., 2012. Displacement fields form point cloud data: application of particle imaging velocimetry to landslide geodesy.J.Geophys.Res.117 (F1), 1-15.
Literature cited 2: Avian,, M., Kellerre-Pirklbauer, A., Bauer, A., 2009. LiDAR for monitoring mass movements in permafrost environments at the cirque Hinteres Langtal, Austria, between 2000 and 2008.Nat.Hazards Earth Syst.Sci,9, 1087-1094. Bauer, A., Paar, G., Kaufmann, V., 2003. Terrestrial laser scanning for rock glacier monitoring. In: Phillips, M., Springman, S.M., Arenson, L.U. 9Eds). Proceedings of the eighth International Permafrost Conference, vol.1. Zurich, Balkema, pp. 55-60.

ID: 60099
Title: Differences between cropland and rangeland MODIS phenology (start-of-season) in Mali.
Author: Agnes Begue, Elodie Vintrou, Alexandre Saad, Pierre Hiernaux.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 167-170 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Phenology, Cropland, Rangeland, MODIS, MCD 12Q2, Start of season.
Abstract: Start-of-season data are more and more used to qualify the land surface phenology trends in relation with climate variability and, more rarely, with human land management. In this paper, we compared the phenology product (MODIS MCD 12 Q2-Land Cover Dynamics Yearly), and an enhanced crop mask of Mali. The differences in terms of start-of -season (SOS) are spatially (north south gradient) and temporally (10 years, 2001-2009) analyzed in bioclimatic terms. Our results show that globally the MODIS MCD12Q2 SOS dates of croplands and rangeland differ, and that these differences depend on the bioclimatic zone. In Sahelian and Guinean regions, cropland vegetation begins to grow earlier than rangeland vegetation (8-day and 4-day advance, respectively). Between, in the Sudanian and Sudano-Sahelian parts of Mali, rangeland vegetation greens about one week earlier than croplands. These results are discussed in the context of the land surface heterogeneity at MODIS scale, and in the context of the natural vegetation ecology. These results could help interpreting phenological trends in climate change analysis.
Location: TE 15 New Biology Building
Literature cited 1: Archibald, S., Scholes, R.J., 2007. Leaf green-up in a semi-arid African savanna-separating tree and grass responses to environmental cues. J. Vegetat. Sci. 18 (4), 583-594. De Beurs, K.M., Henebry, G.M., 2004. Land surface phenology, climatic variation, and institutional change: analyzing agricultural land cover change in Kazakhstan. Remote Sens. Environ. 89 (4), 497-509.
Literature cited 2: Do, F.C., Goudiaby, V.A., Gimenez, O., Diagne, A.L., Diouf, M., Rocheteau, A., Akpo, I.E., 2005. Environmental influence on canopy phenology in the dry tropics. Forest Ecol.Manage.215 (1-3), 319-328. Ganguly, S., Friedl, M.A., Tan, B., Zhang, X., Verma, M., 2010. Land surface phenology from MODIS: characterization of the collection 5 global land cover dynamics product. Remote Sens.Environ.114 (8), 1805-1816.

ID: 60098
Title: Quantifying uncertainty in remote sensing-based urban land-use mapping.
Author: Kasper Cockx, Tim Van de Voorde, Frank Canters.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 154-166 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Uncertainty, Land-use mapping, Urban remote sensing, Image classification, Spectral unmixing, Monte Carlo simulation.
Abstract: Land-use/and -cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land -use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface over at sub-pixel level through level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages Of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map-indicating absence of bias in the mapping process-it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map ' s uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modeling of urban growth.
Location: TE 15 New Biology Building
Literature cited 1: Agresti, A., Categorical Data Analysis, second ed. John Wiley & Sons, Hoboken, NJ. Baraldi, A., Parmiggiani, F., 1994. A Nagao-Matsuyama approach to high-resolution satellite image classification. IEEE Trans. Geosci.Remote Sens. 32 (4), 749-758.
Literature cited 2: Barnsley, M.J., Barr, S.L., 1996. Inferring urban land use from satellite sensor images using kernel-based spatial reclassification. Photogramm. Eng. Remote Sens. 62 (8), 949-958. Burnicki, A.C., Brown, D.G., Goovaerts, P., 2007. Simulating error propagation in land-cover change analysis: the implications of temporal dependence. Comput. Environ. Urban Syst. 31, 282-302.

ID: 60097
Title: Regional-scale estimation of evapotranspiration for the North China plain using MODIS data and the triangle -approach.
Author: Mads Olander Rasmussen, Mikael Kamp Sorensen, Bingfang Wu, Nana Yan, Huanhuan Qin, Inge Sandholt.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 143-153 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Evapotranspiration, MODIS, Triangle method, Fengyun, Latent heat.
Abstract: A method for the estimation of daily evapotranspiration is tested for the North China Plain. The method is designed to be simple to implement and with very limited requirements for ground data (air temperature and humidity). The method uses MODIS NDVI and Land Surface Temperature (LST) data to derive evaporative fraction, using an adaption of the ?triangle method?. The energy available for evapotranspiration is estimated using a combination of satellite data from MODIS and the (geostationary) Fengyun 2-series of sensors and station-based air temperature data. A gapfilling routine is applied to the time series of evaporative fraction to create complete daily maps for the region, allowing for the use of the ET-estimates for applications requiring complete daily coverage (e.g. hydrological models). Results show that ET estimation on a daily scale is feasible with the proposed method, and that seasonal patterns are in accordance with other independent ET-estimates. There are some indications that our ET-estimates are somewhat overestimated when comparing to other RS-methods and model simulations. It is demonstrated that the proposed method provides a relatively simple way of obtaining spatially distributed daily estimates of ET, making the method suitable for applications in studies where ground data availability is limited.
Location: TE 15 New Biology Building
Literature cited 1: Anderson, M., Norman, J., Diak, G., Kustas, W., Mecikalski, J., 1997. A two- source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ. 60(2), 195-216. Bristow, K., Campbell, G., Papendick, R., Elliott, L., 1986. Simulation of heat and moisture transfer through a surface residue soil system. Agric. Forest Meteorol. 36 (3), 193-214.
Literature cited 2: Campbell, G., 1985. Soil Physics with BASIC: Transport Models for Soil-plant Systems, Elsevier, Amsterdam. Cao, G., Zheng, C., Scanlon, B.R., Liu, J., Li, W., 2013. Use of flow modeling to assess sustainability of groundwater resources in the North China Plain. Water Resour. Res. 49 (1), 159-175.

ID: 60096
Title: A monitoring protocol for vegetation changes on Irish peatland and heath.
Author: J.O Connell, J. Connolly, N.M.Holden
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 130-142 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Change detection, Cross calibration, Peatlands, EV12, Heaths.
Abstract: Amendments to Article 3.3 and 3.4 of the Kyoto Protocol have meant that detection of vegetation change may now from an interracial part of national soil carbon stocks. In this study multispectral multi-platform satellite data was processed to detect change to the surface vegetation of four peatland sites and one heath in Ireland. Spectral and spatial thresholds were used on difference images between master and slave data in the extraction of temporally invariant targets for multi-platform cross calibration. The Kolmogorov -Smirnov test was used to evaluate any difference in the cumulative probability distributions of the master, slave and calibrated slave data as expressed by the D statistic, with values reduced by an average of 89.7% due to the cross calibration procedure. A change detection model was created which incorporated a spatial threshold of 9 pixels and a standard deviation (SD) spectral threshold. Kappa accuracy values for the five sites ranged from 80 to 97%, showing that 1.5 SD was optimum spectral threshold for detecting vegetation change. Change detection results showed mean percentage change ranging from 2.11 to 3.28% of total area and cumulative change over the observed tome period of between 15.24 and 49.27% of total area.
Location: TE 15 New Biology Building
Literature cited 1: Achard, F., G., Herold, M., Mollicone, D., 2008. Use of satellite remote sensing in LULUCF sector. In: GOFLCD. (Ed) IPCC Guidance on Estimating Emissions and Removals of Greenhouse Gases from Land Uses such as Agriculture and Forestry. Land Cover Project Office, pp. 1-25. Bragg, O.M., Tallis, J.H., 2001. The sensitivity of peat-covered upland landscapes. Catena 423, 345-360.
Literature cited 2: Connolly, J., Holden, N.M., 2009. Mapping peat soils in Ireland; updating the derived Irish peat map. Irish Geogr. 3, 343-352. Connolly, J., Holden, N.M., 2011a. Classification of peatland disturbance. Land Degrad. Dev. 24, 548-555.

ID: 60095
Title: Sparse dimensionality reduction of hyperspectral image based on semi-supervised local Fisher discriminant analysis.
Author: Zhenfeng Shao, Lei Zhang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 122-129 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Sparsity preserving projections (SPP) Dimensionality reduction , Semi-supervised local Fisher discriminant.
Abstract: This paper presents a novel sparse dimensionality reduction method of hyperspectral image based on semi-supervised local Fisher discriminant analysis (SELF). The proposed method is designed to be especially effective for dealing with the out-of -sample extrapolation to realize advantageous complementarities between SELF and Sparsity preserving projections (SPP). Compared to SELF and SPP, the method proposed herein offers highly discriminative ability and produces an explicit nonlinear feature mapping for the out-of sample extrapolation. This is due to the fact that the proposed method can get an explicit feature mapping for dimensionality reduction. Experimental analysis on the sparsity and efficacy of low dimensional outputs shows that, sparse dimensionality reduction based on SELF can yield good classification results and interpretability in the field of hyperspectral remote sensing.
Location: TE 15 New Biology Building
Literature cited 1: Belhumeur, P.N., Hespanha, J.P., Kreigman, D.J., 1997. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans.Pattern Anal.19 (7), 711-720. Belkin, M., Niyogi, P., 2003. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 15 (6), 1373-1396.
Literature cited 2: Bellman, R., 1961. Adaptive Control Processes: A guided Tour. Princeton University Press, Princeton. Chakrabarti, A., Zickler, T., 2011. Statistics of Real-World Hyperspectral Images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

ID: 60094
Title: Object based change detection of Central Asian Tugai vegetation with very high spatial resolution satellite imagery.
Author: Philipp Gartner, Michael Forster, Alishir Kurban, Birgit Kleinschmit.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 110-121 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Tree detection, Tree crown delineation, QuickBird, WorldView 2, Riparian forest, Populus euphratica.
Abstract: Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to combat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on QuickBird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P.Euphrantica trees, delineate tree crown areas and quantify crown diameter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in WorldView2 images. The results of the automated tree crown delineation show a moderate relation to field reference data with R22005: 0.36 and R22011: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem.
Location: TE 15 New Biology Building
Literature cited 1: Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., 2012a. Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images. Int.J.Appl.Earth Observ.Geoinform.15, 57-69, http://dx.doi.org/10.1016/j.jag.2011.06.005. Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., Nov 2012b.Quantification of crown changes and change uncertainty of trees in an urban environment.ISPRS J. Photogramm.Remote Sens.74, 41-55, http://dx.doi.org/10.1016/j.isprsjprs.2012.08.007.
Literature cited 2: Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS J.Photogram.Remote Sens. 65, 2-16, htpp://d.doi.org/10.1016/j.isprsjprs.2009.06.004. Blaschke,T., Johansen,K., Tiede, D., 2011. Object-based image analysis for vegetation mapping and monitoring. In: Weng,Q.(Ed), Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications.CRC Press Taylor & Francis Group, Boca Raton, FL, United States, pp.241-271.

ID: 60093
Title: Lithological mapping from hyperspectral data by improved use of spectral angle mapper.
Author: Xiya Zhang, Peijun Li.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 95-109 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Lithological mapping, Hyperspectral data, Spectral variability, Spectral angle mapper, Matched filtering.
Abstract: The spectral angle mapper (SAM), as a spectral matching method, has been widely used in lithological type identification and mapping using hyperspectral data. The SAM quantifies the spectral similarity between an image pixel spectrum and a reference spectrum with known components. In most existing studies a mean reflectance spectrum has been used as the reference spectrum for a specific lithological class. However, this conventional use of SAM does not take into account the spectral variability, which is an inherent property of many rocks and is further magnified in remote sensing data acquisition process. In this study, two methods of determining reference spectra used in SAM are proposed for the improved lithological mapping. In first method the mean of spectral derivative was combined with the mean of original spectra, i.e., the mean spectrum and the mean spectral derivative were jointly used in SAM classification, to improve the class separability. The second method is the use of multiple reference spectra in SAM to accommodate the spectral variability. The proposed methods were evaluated in lithological mapping using EO-1 Hyperion hyperspectral data of two arid areas. The spectral variability and separability of the rock types under investigation were also examined and compared using spectral data alone and using both spectral data and first derivatives. The experimental results indicated that spectral variability significantly affected the identification of lithological classes with the conventional SAM method using a mean reference spectrum. The proposed methods achieved significant improvement in the accuracy of lithological mapping, outperforming the conventional use of SAM with a mean spectrum as the reference spectrum, and the matching filtering, a widely used spectral mapping method.
Location: TE 15 New Biology Building
Literature cited 1: Angelopoulou, E., Lee, S.W., Bajcsy, R., 1999. Spectral gradient: a material descriptor invariant to geometry and incident illumination. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision, pp. 861-867. Barry, P., 2001, EO-1/Hyperion science data user ' s guide, Level 1_B. TRW Space, Defense & Information Systems, Redondo Beach, CA, Rep.HYP.TO 1.
Literature cited 2: Bateson, C.A., Asner, G.P., Wessman, C.A., 2000. Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis. IEEE Trans.Geosci.Remote Sens.38, 1083-1094. Bowers, T.L., Rowan, L.C., 1996. Remote minerologic and lithologic mapping of the ice river alkaline complex, British Columbia, Canada, using AVIRIS data. Photogramm.Eng.Remote Sens.62, 1379-1386.

ID: 60092
Title: Estimating ecological indicators of karst rocky desertification by linear spectral unmixing method.
Author: Xia Zhang, Kun Shang, Yi Cen, Tong Shuai, Yanli Sun.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 86-94 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperspectral remote sensing, Linear spectral unmixing, Spectral index, Karst rocky desertification.
Abstract: Coverage rates of vegetation and exposed bedrock are two key indicators of karst rocky desertification. In this study, the abundance of vegetation and exposed rock were retrieved from a hyperspectral Hyperion image using linear spectral unmixing method. The results were verified using the spectral indices of karst rocky desertification (KRDSI) and an integrated LAI spectral index: modified chlorophyll absorption ratio index (MCAR12). The abundances showed significant linear correlations with KRDSI and MCAR12. The coefficients of determination (R2) were 0.93, 0.66, and 0.84 for vegetation, soil, and rock, respectively, indicating that the abundances of vegetation and bedrock can characterize their coverage rates to a certain extent. Finally, the abundances of vegetation and bedrock were graded and integrated to evaluate rocky desertification in a typical karst region. This study suggests that spectral unmixing algorithm and hyperspectral remote sensing imagery can be used to monitor and evaluate karst rocky desertification.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J.B., Sabol, D.E., Kapos, V., et al., 1995. Classification of multispectral images based on fractions of endmembers: application to land -cover change in the Brazilian Amazon. Remote Sens. Environ. 52, 137-154. Baret, F., Jacquemoud, S., Guyot, G., Leprieur, C., 1992. Modelled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands. Remote Sens. Environ. 41, 133-142.
Literature cited 2: Boardman, J.W., Kruse, F.A., 1994. Automated spectral analysis: a geological example using AVIRIS data, north Grapevine Mountains. In: Proceedings of ERIM Tenth Thematic Conference on Geologic Remote Sensing, pp. 1-407-1-418. Broge, N.H., Leblanc, E., 2000. Comparing prediction power and stability of broad-band and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sens. Environ. 76, 156-172.

ID: 60091
Title: Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion.
Author: Feng Zhao, Yiqing Guo, Yanbo Huang, Krishna N. Reddy, Matthew A. Lee, Reginald S. Fletcher, Steven J.Thomson.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 78-85 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Crop injury, Glyphosate, Foliar biochemistry, Sensitive analysis, Model inversion, Hyperspectrtal.
Abstract: Early detection of crop injury from herbicide glyphosate is of significant importance in crop management. In this paper, we attempt to detect glyphosate-induced crop injury by PROSPECT (leaf optical PROperty SPECTra model) inversion through leaf hyperspectral reflectance measurements for non-Glyphosate-Resistant (non-GR) soybean and non-GR cotton leaves. The PROSPECT model was inverted to retrieve chlorophyll content (Ca+b), equivalent water thickness (Cw), and leaf mass per area (Cm) from leaf hyper-spectral reflectance spectra. The leaf stress conditions were then evaluated by examining the temporal variations of these biochemical constituents after glyphosate treatment. The approach was validated with green-house-measured datasets. Results indicated that the leaf injury caused by glyphosate treatments could be detected shortly after the spraying for both soybean and cotton by PROSPECT inversion, with Ca+b of the leaves treated with high dose solution decreasing more rapidly compared with leaves left untreated, whereas the Cw and Cm showed no obvious difference between treated and untreated leaves. For both non-GR soybean and non-GR cotton, the retrieved Ca+b values of the glyphosate treated plants from leaf hyperspectral data could be distinguished from that of the untreated plants within 48 h after the treatment, which could be employed as a useful indicator for glyphosate injury detection. These findings demonstrate the feasibility of applying the PROSPECT inversion technique for the early detection of leaf injury from glyphosate and its potential for agricultural plant status monitoring.
Location: TE 15 New Biology Building
Literature cited 1: ASD Inc, 2008. ASD Document 60060 Rev. B., Integrating Sphere User Manual. Barnes, J.D., Balaguer, L., Manrique, E., Elvira, S., Davison, A.W., 1992. A reappraisal of the use of DMSO for the extraction and determination of chlorophylls a and b in lichens and higher plants. Environ.Exp.Bot. 32, 85-100.
Literature cited 2: Carter, G.A., 1994. Ratios of leaf reflectances in narrow wavebands as indicators of plant stress. Int. J. Remote Sens. 15, 697-703. Ding, W., Reddy, K.N., Krutz, L.J., Thomson, S.J., Huang, Y., Zablotowicz, R.M., 2011. Biological response of soybean and cotton to aerial glyphosate drift. J. Crop Improv. 25, 291-302.