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ID: 61050
Title: Temperature and emissivity separation and mineral mapping based on airborne TASI hyperspectral thermal infrared data.
Author: Jing Cui, Kokun Yan, Xinfeng Dong, Shimin Zhang, Jingfa Zhang, Feng Tian, Runsheng Wang.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 40 19-28 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperspectral, Thermal infrared remote sensing, Temperature and emissivity separation, Mineral mapping, TASI.
Abstract: Thermal infrared remote sensing (8-12 ?m) (TIR) has great potential for geologic remote sensing studies. TIR has been successfully used for terrestrial and planetary geologic studies to map surface materials. However, the complexity of the physics and the lack of hyperspectral data make the studies under-investigated. A new generation of commercial hyperspectral infrared sensors, known as Thermal Airborne Spectrographic Imager (TASI), was used for image analysis and mineral mapping in this study. In this paper, a combined method integrating normalized emissivity method (NEM), ratio algorithm (Ratio) and maximum-minimum apparent emissivity difference (MMD), being applied in multispectral data, has been modified and used to determine whether this method is suitable for retrieving emissivity from TASI hyperspectral data.MODTRAN 4 has been used for the atmospheric correction. The retrieved emissivity spectra matched well with the field measured spectra except for bands1, 2, and 32. Quartz, calcite, diopside/hedenbergite, hornblende and microline have been mapped by the emissivity image. Mineral mapping results agree with the dominant minerals identified by laboratory X-ray powder diffraction and spectroscopic analyses of field samples. Both of the results indicated that the atmospheric correction method and the combined temperature-emissivity method are suitable for TASI image. Carbonate skarnization was first found in the study area by the spatial extent of diopside. Chemical analyses of the skarn samples determined that the Au content was 0.32-1.74 g/t, with an average Au content of 0.73 g/t. This information provides an important resource for prospecting for skarn gold deposits. It is also suggested that TASI is suitable for prospect and deposit scale exploration.
Location: T E 15 New Biology Building.
Literature cited 1: Abrams, M, 2000.The advanced spaceborne thermal emission and reflection radiometer (ASTER): data products for the high spatial resolution imager on NASA ' s Terra platform.Int.J.Remote Sens.21, 847-859. Amin, B.P., Mazlan, H., 2012.The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits. Ore Geol.Rev.44, 1-9.
Literature cited 2: Barsi, J.A. Barker, J.L, Schott, J.R, 2003.An atmospheric Correction parameter Calculator for a Single Thermal Band Earth-sensing Instrument. Proceedings of IEEE IGARSS, Toulouse, France, pp. 3014-3016. Barsi, J.A., schott, J.R., Palluconi, F.D., Hook, S.J., 2005.Validation of a Web-based Atmospheric Correction Tool for Single Thermal Band Instruments. Proceedings of SPIE, 5882, 588 20E.1-588 20E.7.

ID: 61049
Title: Improved coastal wetland mapping using very-high 2-meter spatial resolution imagery.
Author: Matthew J.McCarthy, Elizabeth J.Merton, Frank E.Muller-Karger.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 40 11-18 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Wetlands, World-View-2, Landsat 8 OLI, Tampa Bay, Mangroves
Abstract: Accurate wetland maps are a fundamental requirement for land use management and for wetland restoration planning. Several wetland map products are available today; most of them based on remote sensing images, but their different data resources and mapping methods lead to substantially different estimations of wetland location and extent. We used two very high-resolution (2 m) WorldView-2 satellite images and one (30 m) Landsat 8 Operational Land Imager (OLI) image to assess wetland coverage in two coastal areas of Tampa Bay (Florida) : Fort De Soto State Park and Weedon Island Preserve. An initial unsupervised classification derived from WorldView-2 was more accurate at identifying wetlands based on ground truth data collected in the field than the classification derived from Landsat 8 OLI (82% vs.46 % accuracy).The worldview-2 data was then used to define parameters of a simple and efficient decision tree with four nodes for a more exacting classification. The criteria for the decision tree derived by extracting radiance spectra at 1500 separate pixels from the WorldView-2 data within field-validated regions. Results for both study areas showed high accuracy in both wetland (82 % at Fort De Soto State Park, and 94 % at Weedon Island Preserve) and non-wetland vegetation classes (90 % and 83 %, respectively).Historical, published land-use maps overestimate wetland surface cover by factors of 2-10 in the study areas. The proposed methods improve speed and efficiency of wetland map production, allow semi-annual monitoring through repeat satellite passes, and improve the accuracy and precision with which wetlands are identified.
Location: T E 15 New Biology Building.
Literature cited 1: C-CAP, 2013. Assessment report of wetland mapping improvement to NOAA ' s Coastal Change Analysis Program (C-CAP) land cover in western Washington State. State of Washington Department of Ecology. http://www.ecy.wa.gov/programs/sea/wetlands/pdf/C-CAP Wetlands Assessment Report.pdf/. (accessed 20.04.14). Cowardin, L., Carter, V., Golet, F., LaRoe, E., 1979.Classification of Wetlands and Deepwater Habitats of the United States, FWS/OBS79/31.U.S.Fish and Wildlife Service, Washington.
Literature cited 2: Dahl, T., Stedman, S., 2013.Status and trends of wetlands in the coastal watersheds of the Conterminous United States 2004 to 2009.U.S. Department of the Interior, Fish Wildlife Service and National Oceanic and Atmospheric Administration, National Marine Fisheries Service. (46 p.) Digital Globe, 2010.The Benefits of the Eight Spectral Bands od WorldView-2 Available in http: //www.digitalglobe.com/sites/default/files/DG-8SPECTRAL-WP.pdf/. (accessed 26.06.14).

ID: 61048
Title: Discriminating lava flows of different age within Nyamuragira ' s volcanic field using spectral mixture analysis.
Author: Long Li, Frank Canters, Carmen Solana, Weiwei Ma, Longqian Chen, Matthieu Kervyn.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 40 1-10 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Vegetation fraction, Lava flow, Spectral mixture analysis, Nyamuragira, Pleiades.
Abstract: In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ~15 years after eruption and occupies over 50 % of the lava surfaces ~40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization over time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons.
Location: T E 15 New Biology Building.
Literature cited 1: Abrams, M., Abbot, E., Kahle, A., 1991.Combined use of visible, reflected infrared, and thermal infrared images for mapping Hawaiian lava flows.J.Geophys.Res.96, 475-484. Abrams, M., Bianchi, R., Pieri, D., 1996.Revised mapping of lava flows on Mount Etna,Sicily.Photogramm.Eng.Remote Sens.62, 1353-1359.
Literature cited 2: ASTRIUM.2012.Pleiades Imagery User Guide. Toulouse. De Rose, R.C., Oguchi, T., Morishima, W., Collado, M., 2011.Land cover change on Mt.Pinatubo, the Philippines, monitored using ASTER VNIR.Int.J.Remote Sens.32, 9279-9305.

ID: 61047
Title: Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy.
Author: M.H.D.Franceschini, J.A.M.Dematte, F.da Silva Terra, L.E.Vicente, H.Bartholomeus, C.R. de Souza Filho.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 358-370 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Reflectance spectroscopy, Hyperspectral, Pedometrics, Soil properties, Unmixing analysis.
Abstract: Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other target occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS-Asia dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using air-borne sensor data (R2 of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R2 of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively).Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively).Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.
Location: T E 15 New Biology Building.
Literature cited 1: Alvares, C.A, Stape, J.L, Sentelhas, P.C., de Moraes Goncalves, J.L, Sparovek, G., 2013.Koppen ' s climate classification map for Brazil.Meteorol.Z.22 (6), 711-728. Bartholomeus, H., Epema, G., Schaepman, M.,2007.Determining iron content in Mediterranean soils in partly vegetated areas, using spectral reflectance and imaging spectroscopy.Int.J.Appl.Earth Observ.Geoinf.9, 194-203.
Literature cited 2: Bartholomeus, H.,Kooistra, L., Stevens,A., van Leeuwen, M., van Wesemael, B.,Ben-Dor, E., Tychon, B., 2011.Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy.Int.J.Appl.Earth Observ.Geoinf.13, 81-88. Baumgardner, M.F., Silva, L.F., Biehl, L.L, Stoner, R., 1985. Reflectance properties of soils.Adv.Agron.38.1-44.

ID: 61046
Title: Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study.
Author: Moses Azong Cho, Oupa Malahlela, Abel Ramoelo.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 349-357 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Subtropical forest, Tree species, Remote sensing, WorldView-2, Forest conservation.
Abstract: Indigenous forest biome in South Africa is highly fragmented in to patches of various sizes (most patches <1km2). The utilization of timber and non-timber resources by poor rural communities living around protected forest patches produce subtle changes in the forest canopy which can be hardly detected on a timely manner using traditional field surveys. The aims of this study were to assess: (i) the utility of very high resolution (VHR) remote sensing imagery (WorldView-2, 0.5-2 m spatial resolution) for mapping trees species and canopy gaps in one of the protected subtropical coastal forests in South Africa (the Dukuduku forest patch (ca.3200 ha) located in the province of KwaZulu-Natal) and (ii) the implications of the map products to forest conservation. Three dominant canopy tree species namely, Albizia adianthifolia, Strychnos spp. and Acacia spp., and canopy gap types including bushes (grass/shrubby), bare soil and burnt patches were accurately mapped (overall accuracy +89.3 ? 2.1%) using WorldView-2 image and support vector machine classifier. The maps revealed subtle forest disturbances such as bush encroachment and edge effects resulting from forest fragmentation by roads and a power-line. In two stokeholders ' workshops organized to assess the implications of the map products to conservation, participants generally agreed amongst others implications that the VHR maps provide valuable information that could be used for implementing and monitoring the effects of rehabilitation measures. The use of VHR imagery is recommended for timely inventorying and monitoring of the small and fragile patches of subtropical forests in Southern Africa.
Location: T E 15 New Biology Building.
Literature cited 1: Aizzi, B., Baronti, S., Lotti, F., Selva, M., 2009. A comparison between global and context-adaptive pansharpening of multispectral images geoscience and remote sensing letters.IEEE 6 (2), 302-306. Asner, G.P., Knapp, D.E., Kennedy-Bowdoin, T., Jones, M.O., Martin, R.E., Boardman, J., Hughes, R.F., 2008.Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR. Remote Sens.Environ. 112 (5), 1942-1955
Literature cited 2: Asner, G.P., Martin, R.E., 2009. Airborne spectronomics: mapping canopy chemical and taxonomic diversity in tropical forests.Front.Ecol.Environ. 7 (5), 269-276. Bender, D., Tischendorf, L., Fahrig, L., 2003. Using patch isolation metrics to predict animal movement in binary landscapes. Landscape Ecol.18 (1), 17-39.

ID: 61045
Title: Monitoring levels of cyanobacterial blooms using the visual cyanobacteria index (VCI) and floating algae index (FAI).
Author: Yoichi Oyama, Takehiko Fukushima, Bunkei Matsushita, Hana Matsuzaki, Koichi Kamiya, Hisao Kobinata.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 335-348 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Cyanobacterial blooms, Landsat, Lake, Chlorophyll-a, Phycocyanin, Water amenity.
Abstract: Cyanobacterial bloom is a growing environmental problem in inland waters. In this study, we propose a method for monitoring levels of cyanobacterial blooms from Landsat/ETM + images. The visual cyanobacteria index (VCI) is a simple index for in-situ visual interpretation of cyanobacterial blooms levels, by classifying them into six categories based on aggregation (e.g., subsurface blooms, surface scum). The floating algae index (FAI) and remote sensing reflectance in the red wavelength domain, which can be obtained from Landsat/ETM+images, were related to the VCI for estimating cyanobacteria bloom levels from the Landsat/ETM+images, were related to the VCI for estimating cyanobacteria bloom levels from the Landsat/ETM+images.Nine field campaigns were carried out at lakes Nishiura and Kitaura (Lake Kasumigaura group), Japan, from June to August 2012. We also collected reflectance spectra at 20 stations for different VCI levels on August 3, 2012. The reflectance spectra were recalculated in correspondence to each ETM+band, and used to calculate the FAI. The FAI values were then used to determine thresholds for classifying cyanobacterial blooms into different VCI levels. These FAI thresholds were validated using three Landsat/ETM+images.Results showed that FAI values differed significantly at the respective VCI levels except between levels 1 and 2 (subsurface blooms) and levels 5 and 6 (surface scum and hyperscum). This indicated that the FAI was able to detect the high level of cyanobacteria that forms surface scum. In contrast, the Landsat/ETM + band 3 reflectance could be used as an alternative index for distinguishing surface scum and hyperscum. Application of the thresholds for VCI classifications to three Landsat/ETM +images showed that the volume of cyanobacteria blooms can be effectively classified into the six VCI levels.
Location: T E 15 New Biology Building.
Literature cited 1: Aizaki, M., Fukushima, T., Takagi, H., Kitamura, H., 1995a.Ebvaluation of Lake Kasumigaura, Japan, using a landscape index for cyanobacterial bloom. In: Aizaki, M., Fukushima, T. (Eds), Aoko (Water-blooms of Blue-green Algae); Measurement, Occurrence, and Factors on Its Growth. National Institute for Environmental Studies, Tsukuba, Japan, pp.33-39 (in Japanese). Aizaki, M., Fukushima, T., Kitamura, H., Ohashi, H., 1995b. What are criteria for cyanobacterial bloom? An analysis of questionnaire investigation using the visual cyanobacterial index. In: Aizaki, M., Fukushima, T.(Eds), Aoko (Water-blooms of Blu-green Algae); Measurement, Occurrence, and Factors on Its Growth. National Institute for Environmental Studies, Tsukuba, Japan, pp. 40-48 (In Japanese).
Literature cited 2: Bartram, J., Carmichael, W.W., Chorus, I., Jones, G., Skulberg, O.M., 1999.Introduction.In: Chorus, I., Bartram, J.(Eds)., Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management.E & FN Spon, London and New York, pp.1-14. Bartram, J., Rees, G. (Eds), 2000. London, E&FN Spon Press, London and New York.

ID: 61044
Title: Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data.
Author: J.Meghan Salmon, Mark A. Friedl. Steve Frolking, Dominik Wisser, Ellen M. Douglas.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 321-334 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Irrigation, MODIS, Remote sensing Paddy, Cropland, Water management.
Abstract: Irrigation accounts for 70 % of global water use by humans and 33-40 % of global food production comes from irrigated croplands. Accurate and timely information related to global irrigation is therefore needed to manage increasingly scarce water resources and to improve food security in the face of yield gaps, climate change and extreme events such as droughts, floods, and heat waves. Unfortunately, this information is not available for many regions of the world. This study aims to improve characterization of global rain-fed, irrigated and paddy croplands by integrating information from national and sub-national surveys, remote sensing, and gridded climate data sets. To achieve this goal, we used supervised classification of remote sensing, climate, and agricultural inventory data to generate a global map of irrigated, rain-fed, and paddy croplands. We estimate that 314 million hectares (Mha) worldwide were irrigated circa 2005. This includes 66 Mha of irrigated paddy cropland and 249 Mha of irrigated non-paddy cropland. Additionally, we estimate that 1047 Mha of cropland and 985 Mha of rain-fed non-paddy cropland. More generally, our results show that global mapping of irrigated, rain-fed, and paddy cropland is possible by combining information from multiple data sources. However, regions with rapidly changing irrigation or complex mixtures of irrigated and non-irrigated crops present significant challenges and require more and better data to support high quality mapping of irrigation.
Location: T E 15 New Biology Building.
Literature cited 1: AgRISTER: Agriculture and Resources Inventory Surveys thought Aerospace Remote Sensing, 1981.NASA, Lyndon B Johnson Space Center, Houston, Texas59, 110-123. Arino, O., Gross, D., Ranera, F., Bourg, L., Leroy, M., Bicheron, P., Weber, J.L., 2007.GlobCover: ESA service for global land cover from MERIS.In: Geoscience and Remote Sensing Symposium, 2007.IGARSS 2007.IEEE International. IEEE, Barcelona, Spain, pp.2412-2415.
Literature cited 2: Bartholome, Belward, A.S., 2005. GLC2000: a new approach to global land cover mapping from Earth observation data.Int.J.Remote Sens. 26 (9), 1959-1977. Biggs, T.W., Thenkabail, P.S., Gumma, M.K., Scott, C.A., Parthsaradhi, G.R, Turral, H.N., 2006. Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India.Int.J.Remote Sens. 27 (19), 4245-4266.

ID: 61043
Title: Fusion of hyperspectral and LIDAR data using decision template-based fuzzy classifier system.
Author: Behnaz Bigdeli, Farhad Samdzadegan, Peter Reinartz.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 309-320 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: LIDAR, Hyperspectral, Fuzzy classification, Multiple classifier system, Sensor fusion.
Abstract: Regarding to the limitations and benefits of remote sensing sensors, fusion of remote sensing data from multiple sensors such as hyperspectral and LIDAR (light detection and ranging) is effective at land cover classification. Hyperspectral images (HSI) provide detailed information. However, because of the more complexities and mixed information in LIDAR and HIS, traditional crisp classification methods could not be more efficient. In this situation, fuzzy classifiers could deliver more satisfactory results than crisp classification approaches. Also, referring to the limitation of single classifiers, multiple classifier system (MCS) may exhibit better performance in the field of multi-sensor fusion. This paper presents a fuzzy multiple classifier system for fusions of HSI and LIDAR data based on decision template (DT) After feature extraction and feature selection on each data; all selected features of both data are applied on a cube. Then classifications were performed by fuzzy k-nearest neighbor (FKNN) and fuzzy maximum likelihood (FML) on cube of features. Finally, a fuzzy decision fusion method is utilized to fuse the results of fuzzy classifiers. In order to assess fuzzy MCS proposed method, a crisp MCS based on support vector machine (SVM), KNN and maximum likelihood (ML) as crisp classifiers and na?ve Bayes (NB) as crisp classifier fusion method is applied on selected cube feature. A co-registered HSI and LIDAR data set from Houston of USA was available to examine the effect of proposed MCS. Fuzzy MCS and HSI and LIDAR data provide interesting conclusions on the effectiveness and potentialities of the joint use of these two data.
Location: T E 15 New Biology Building.
Literature cited 1: Axelsson, P., 1999. Processing of laser scanner data-algorithms and applications. ISPRS J. Photogramm. 54, 138-147. Bartels, M., Wei, H., 2006. Rule-based improvement of maximum likelihood classified LIDAR data fused with co-registered bands. In: Annual Conference of the Remote Sensing and Photogrammetry Society.CD Proceedings, pp.1-9.
Literature cited 2: Brenan, R., Webster, T.L., 2006. Object -oriented land cover classification of LIDAR-derived surfaces.Can.J.Remote Sens. 32, 162-172. Breve, F., Ponti, M., Mascarenhas, N., 2007. Multilayer perceptron classifier combination for identification of materials on noisy soil science multispectral images. In: XX Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI, pp. 24-239.

ID: 61042
Title: The impact of size variations in the ground instantaneous field of view of pixels on MODIS BRDF modeling.
Author: Geoffrey McCamley, Ian Grant, Simon Jones, Chris Bellman.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 302-308 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: MODIS, BRDF, GIFOV, MCD43, NDVI.
Abstract: Bidirectional reflectance distribution functions (BRDF) seek to represent surface reflectance anisotropy resulting from surface physical structure and changes in a satellite sensor ' s view and solar illumination angles. NASA ' s MODerate resolution imaging spectroradiometer (MODIS) is a wide field of view sensor that generates observations over a large range of view angles. Based on MODIS observations, a BRDF product and several sub-products have been developed by MODIS science teams, i.e. the MCD43 product suite. Variations in pixel ' s ground instantaneous field of view sensors such as MODIS science teams, i.e. the size of a pixel ' s footprint on the ground, is a well known effect associated with wide field of view sensors such as MODIS, but is not specifically considered in the MODIS BRDF algorithm nor has research been undertaken into its effects on MODIS BRDF modeling. This paper introduces two metrics to examine the relationship between reflectance variations associated with changes in MODIS pixel ' s GIFOV and the MODIS BRDF (MCD43) product. These metrics are applied to four different study areas and epochs across the Australian continent. The two metrics are shown to be well correlated (mean correlation coefficient of 0.81 for the four study areas); suggesting the variations in pixels ' GIFOW are consistent, non-random source of variance in MODIS BRDF modeling. The results contained in this paper suggest that all downstream products which include MODIS BRDF processing in their derivation and results directly based on MODIS BRDF processing may need to be reassessed.
Location: T E 15 New Biology Building.
Literature cited 1: Armston, J.D., Scarth, P.F., Phinn, S.R., Danaher, T.J., 2006. Analysis of multi-data MISR measurements for forest and woodland communities, Queensland Australia. Remote Sens.Environ. 107, 287-298. Bannari, A., Morin, D., Bonn, F., Huete, A., 1995. A review of vegetation indices. Remote Sens.Rev.13, 95-120.
Literature cited 2: Diner, D.J., Asner, G.P., Davies, R., Knyazikhin, Y., Muller, J.-P., Nolin, A.W., Pinty, B., Schaaf, C.B., Stoeve, J., 1999. New Directions in earth observing: scientific applications of multiangle remote sensing.Bull.Am.Meteorol.Soc.80, 2209-2228.

ID: 61041
Title: The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) after fifteen years: Review of global products.
Author: Michael Abrams, Hiroji Tsu, Glynn Hulley, Koki Iwao, David Pieri, Tom Cudahy, Jeffrey Kargel.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 292-301 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: ASTER, Terra, Earth Observing System, Global data.
Abstract: The advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 15-channel imaging instrument operating on NASA ' s Terra satellite. A joint project between the U.S National Aeronautics and Space Administration and Japan ' s Ministry of Economy, Trade, and Industry, Aster has been acquiring data for 15 years, since March 2000. The archive now contains over 2.8 million scenes; for the majority of them, a stereo pair was collected using nadir and backward telescopes imaging in the NIR wavelength. The majority of users require only a few to a few dozen scenes for their work. Studies have ranged over numerous scientific disciplines, and many practical applications have benefited from ASTER ' s unique data. A few researchers have been able to mine the entire ASTER archive that is now global in extent due to the long duration of the mission. Six samples of global products are described in this contribution: the ASTER Global Digital Elevation Model (GDEM), the most complete, highest resolution DEM available to all users; the ASTER Emissivity Database (ASTER GED), a global 5-band emissivity map of the land surface; the ASTER Volcano Archive (AVA), an archive of over 1500 active volcanoes; ASTER Geoscience products of the continent of Australia; and the Global Ice Monitoring from Space (GLIMS) project.
Location: T E 15 New Biology Building.
Literature cited 1: Abrams, M., Bailey, B., Tsu, H., Hato, M., 2010. The ASTER Global DEM.J.Am.Soc.Photogramm.Remote Sens.20, 344-348. Agapiou, A., Alexakis, D.D., Hadjimitsis, D.G., 2014. Spectral sensitivity of ALOS, ASTER, IKONOS, LANDSAT and SPOT satellite imagery intended for the detection of archaeological crop marks.Int.J.Digital Earth 7 (5), 351-372, http://dx.doi.org/10.1080/17538947.2012.674159.
Literature cited 2: Amici, S., Piscini, A., Buongiorno, M.F., Pieri, D., 2013. Gewological classification of volcano Teide by hyperspectral and multispectral satellite data. Int.J.Remote Sens.34 (9-10), 3356-3375. ASTER Global Validation Summary Reoprt.2009.https://Ipdaac.usgs.gov/Ipdaac/content/download/4009/20069/version/1/file/ASTER+GDEM+Validation+Summary+Report+-Final+for+posting+06-28-09.pdf (viewed 15.09.14).

ID: 61040
Title: Integration of WorldView-2 and airborne LiDAR data for tree species level carbon stock mapping in Kayar Khola watershed, Nepal.
Author: Yogendra K.Karna, Yousif Ali Hussain, Hammad Gilani, M.C.Bronsveld, M.S.R.Murthy, Faisal Mueen Qamer, Bhaskar Singh Karky, Thakur Bhattarai, Xu Aigong, Chitra Bahadur Baniya.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 280-291 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Airborne LiDAR, CHM, CPA, Image classification, Multiresolution segmentation, WorldView-2.
Abstract: Integration of WorldView-2 satellite image with small footprint airborne LiDAR data for estimation of tree carbon at species level has been investigated in tropical forests of Nepal. This research aims to quantify and map carbon stock for dominant tree species in Chitwan district of central Nepal. Object based image analysis and supervised nearest neighbor classification methods were deployed for tree canopy retrieval and species level classification respectively. Initially, six dominant tree species (Shorea robusta, Schima wallichii, Lagerstroemia parviflora, Terminalia tomentosa, Mallotus phillippinensis and Semecarpus anacardium) were able to identified and mapped through image classification. The result showed a 76% accuracy of segmentation and 1970.99 as best average separability. Tree canopy height model (CHM) was extracted based on LiDAR ' s first and last return from an entire study area. On average, a significant correlation coefficient (r) between canopy projection area (CPA) and carbon; height and carbon; and CPA and height were obtained as 0.73, 0.76 and 0.63, respectively for correctly detected trees. Carbon stock model validation results showed regression models being able to explain up to 94 %, 78 %, 76 %, 84 % and 78 % of variations in carbon estimation for the following tree species: S.robusa, L.parviflora, T.tomentosa,S.walichii and others (combination of rest tree species).
Location: T E 15 New Biology Building.
Literature cited 1: Ahmed, R., Siqueira, P., Hensley, S., 2003. A study of forest biomass estimates from LiDAR in the northern temperate forests of New England. Remote Sens.Environ.130, 121-135. Asner, G., Mascaro, J., Muller-Landau, H., Vieilledent, G., Vaudry, R., Rasamoelina, M., Hall, J., Breugel, M., 2012.A universal airborne LiDAR approach for tropical forest carbon mapping.Oecologia 168, 1147-1160.
Literature cited 2: Bartelink, H.H., 1996.Allometric relationships on biomass and needle area of Douglas-fir.for.Ecol.Manage.86, 193-203. Belgiu, M., Dragut, L., 2014.Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery.ISPRS J.Photogramm.Remote Sens. 96, 67-75.

ID: 61039
Title: Detecting understory plant invasion in urban forests using LiDAR.
Author: Kunwar K.Singh, Amy J. Davis, Ross K.Meentemeyer.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 267-279 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Biological invasion, Chinese privet, Data integration, IKONOS, LiDAR, Lingustrum sinense, Random forest.
Abstract: Light detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Lingustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L.sinense, occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized in to the following groups: overstory, topography, and overall vegetation characteristics, and IKONOS spectral features-optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L.sinense We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L.sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming model from the RF classifier produced the highest kappa of 64.8 %, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2 % over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L.sinense.
Location: T E 15 New Biology Building.
Literature cited 1: Andrew, M.E., Ustin, S.L., 2009.Habitat suitability modeling of an invasive plant with advanced remote sensing data.Divers.Distrib.15, 627-640. Asner, G.P., Vitousek, P.M., 2005.Remote analysis of biological invasion and biogeochemical change.Proc.Natl.Acad.Sci.U.S.A.102, 4383-4386.
Literature cited 2: Asner, G.P., Knapp, D.E., Kennedy-Bowdoin, T., Jones, M.O., Martin, R.E., Boardman, J., Hughes, R.F., 2008.Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR.Remote Sens.Environ.112, 1942-1955. BCAL LiDAR Tools (2013).Idaho State University, Department of Geosciences.In.Boise, Idaho: Boise Center Aerospace Laboratory (BCAL).

ID: 61038
Title: Spectra and vegetation index variations in moss soil crust in different seasons, and in wet and dry conditions.
Author: Shibo Fang, Weiguo Yu, Yue Qi.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 261-266 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Biological soil crusts (BSCs) Normalized difference vegetation index (NDVI), Biological soil crust index (BSCI), CI (Crust index).
Abstract: Similar to vascular plants, non-vascular plant mosses have different periods of seasonal growth. There has been little research on the spectral variations of moss soil crust (MSC) over different growth periods. Few studies have paid attention to the difference in spectral characteristics between wet MSC that is photosynthesizing and dry MSC in suspended metabolism. The dissimilarity of MSC spectra in wet and dry conditions during different seasons needs further investigation. In this study, the spectral reflectance of wet MSC and the dominant vascular plant (Artemisia) were characterized in situ during the summer (July) and autumn (September).The variations in the normalized difference vegetation index (NDVI), biological soil crust index (BSCI) and CI (crust index) in different seasons and under different soil moisture conditions were also analyzed. It was found that (1) the spectral characteristics of both wet and dry MSCs varied seasonally; (2) the spectral features of wet MSC appear similar to those of the vascular plant, Artemisia, whether in summer or autumn; (3) both in summer and in autumn, much higher NDVI values were acquired for wet than for dry MSC (0.6 ~0.7vs 0.3~0.4 units), which may lead to misinterpretation of vegetation dynamics in the presence of MSC and with the variations in rainfall occurring in arid and semi-arid zones; and (4)the BSCI and CI values of wet MSC were close to that of Artemisia in both summer and autumn, indicating that BSCI and CI could barely differentiate between the wet MSC and Artemisia.
Location: T E 15 New Biology Building.
Literature cited 1: Belnap, J., 2001.Biological Soil crusts: Structure, Function, and Management.Springer-Verlag, Berlin. Belnap, J.2002.Nitrogen fixation in biological soil crusts from southern Utah, USA, Biol.Fert.Soils 35, 128-135.
Literature cited 2: Beringer,J.,Lynch,A.H.,Chapin,F.S.,Mack,M.,Bonan,G.B., 2001.The representation of arctic soils in the land surface model: the importance of mosses.J.Climate 14, 3324-3335. Chen, J., Zhang, M.Y., Wang, L., Shimazaki, H., Tamura, M., 2005.A new index for mapping lichen-dominated biological crusts in desert areas. Remote Sens.Environ.96, 165-175.

ID: 61037
Title: Non-destructive estimation of foliar chlorophyll and carotenoid contents: Focus on informative spectral bands.
Author: Oz Kira, Raphael Linker, Antoly Gitelson.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 251-260 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Carotenoids, Chlorophyll, Neural network, Non-destructive technique, Reflectance.
Abstract: Leaf pigment content provides valuable insight into the productivity, physiological and phonological status of vegetation. Measurement of spectral reflectance offers a fast, nondestructive method for pigment estimation. A number of methods were used previously for estimation of leaf pigment content, however, spectral bands employed varied widely among the models and data used. Our objective was to find informative spectral bands in three types of models, vegetation indices (VI), neural network (NN) and partial least squares (PLS) regression, for estimating leaf chlorophyll (Chl) and carotenoids (Car) contents of three unrelated tree species and to assess the accuracy of the models using a minimal number of bands. The bands selected by PLS, NN and VIs were in close agreement and did not depend on the data used. The results of the uninformative variable elimination PLS approach, where the reliability parameter was used as indicator of the information contained in the spectral bands, confirmed the bands selected by the VIs, NN and PLS models. All three types of models were able to accurately estimate Chl content with coefficient of variation below 12 % for all three species with VI showing the best performance. NN and PLS using reflectance in four spectral bands were able to estimate accurately Car content with coefficient of variation below 14 %.The quantitative framework presented here offers a new way of estimating foliar pigment content not requiring model-re-parameterization for different species. The approach was tested using the spectral bands of the future Sentinel-2 satellite and the results of these simulations showed that accurate pigment estimation from satellite would be possible.
Location: T E 15 New Biology Building.
Literature cited 1: Baret, F., Houles, V., Guerif, M., 2007.Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management.J.Exp.Bot.58, 869-880. Blackburn, G.A., 2007a.Hyperspectral remote sensing of plant pigments.J.Exp.Bot.58, 855-867.
Literature cited 2: Blackburn, G.A., 2007b.Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation.Int.J.Remote Sens.28, 2831-2855. Blackburn, G.A., 1998. Quantifying chlorophylls and carotenoids at leaf and canopy scales: an evaluation of some hyperspectral approaches. Remote Sens.Environ.66, 273-285.

ID: 61036
Title: Integrating optical satellite data and airborne laser scanning in habitat classification for wildlife management.
Author: W.Nijland, N.C.Coops, S.E.Nielsen, G.Stenhouse.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 242-250 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Lidar, Grizzly, Habitat, Landcover, Classification, Landsat.
Abstract: Wildlife habitat selection is determined by a wide range of factors including food availability, shelter, security and landscape heterogeneity all of which are closely related to the more readily mapped land-cover types and disturbance regimes. Regional wildlife habitat studies often used moderate resolution multispectral satellite imagery for wall to wall mapping, because it offers favourable mix of availability, cost and resolution. However, certain habitat characteristics such as canopy structure and topographic factors are not well discriminated with these passive, optical datasets. Airborne laser scanning (ALS) provides highly accurate three dimensional data on canopy structure and the underlying terrain, thereby offers significant enhancements to wildlife habitat mapping. In this paper, we introduce an approach to integrate ALS data and multispectral images to develop a new heuristic wildlife habitat, and cover with optical estimates of species (conifer vs. deciduous) composition in to a decision tree classifier for habitat-or landcover types. We believe this new approach is highly versatile and transferable, because class rules can be easily adapted for other species or functional groups. We discuss the implications of increased ALS availability for habitat mapping and wildlife management and provide recommendations for integrating multispectral and ALS data into wildlife management.
Location: T E 15 New Biology Building.
Literature cited 1: Allen,A.W.,Jordan,P.A.,Terrell,J.W., 1987.Habitat suitability index models:Moose,Lake Superior region.U.S.Dep.Inter.FishWildl.Serv.Biol.Rep.82,60. Baker,C.,Lawrence,R.,Montage,C.,Patten,D.,2006.Mapping Wetlands and riparian areas using Landsat ETM+imagery and decision-tree-based models. Wetlands 26, 465-474.
Literature cited 2: Barret, F., Guyot, G., 1991.Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens.Environ.35, 161-173. Bardshaw, C., Hebert, D., 1996.Woodland caribou population decline in Alberta: fact or fiction? Rangifer 9 (Special issue), 223-224.