WorldWideScience

Sample records for cover maps produced

  1. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    1999-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...

  2. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    2002-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...

  3. Tree Cover Mapping Tool—Documentation and user manual

    Science.gov (United States)

    Cotillon, Suzanne E.; Mathis, Melissa L.

    2016-06-02

    The Tree Cover Mapping (TCM) tool was developed by scientists at the U.S. Geological Survey Earth Resources Observation and Science Center to allow a user to quickly map tree cover density over large areas using visual interpretation of high resolution imagery within a geographic information system interface. The TCM tool uses a systematic sample grid to produce maps of tree cover. The TCM tool allows the user to define sampling parameters to estimate tree cover within each sample unit. This mapping method generated the first on-farm tree cover maps of vast regions of Niger and Burkina Faso. The approach contributes to implementing integrated landscape management to scale up re-greening and restore degraded land in the drylands of Africa. The TCM tool is easy to operate, practical, and can be adapted to many other applications such as crop mapping, settlements mapping, or other features. This user manual provides step-by-step instructions for installing and using the tool, and creating tree cover maps. Familiarity with ArcMap tools and concepts is helpful for using the tool.

  4. Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

    Science.gov (United States)

    Cotillon, Suzanne E.; Mathis, Melissa L.

    2017-02-15

    The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).

  5. Effects of different scale land cover maps in watershed modelling

    Science.gov (United States)

    Nunes, Antonio; Araújo, Antonio; Alexandridis, Thomas; Chambel, Pedro

    2013-04-01

    Water management is a rather complex process that usually involves multiple stakeholder, multiple data and sources, and complex mathematical modelling. One of the key data sets to understand a particular water system is the characterization of the land cover. Land cover maps are essential for the estimation of environmental variables (e.g. LAI, ETa) related to water quantity. Also, land cover maps are used for modelling the water quality. For instance, watersheds that have intensive agriculture can have poor water quality due to increase of nutrients loading; forest fires have a significant negative impact over the water quality by increasing the sediment loads; forest fires can increase flood risks. The land cover dynamics can as well severely affect the water quantity and quality in watersheds. In the MyWater project we are conducting a study to supply water quantity and quality information services for five study areas in five different countries (Brazil, Greece, Mozambique, Netherlands, and Portugal). In this project several land cover maps were produced both at regional and local scales, based on the exploitation of medium and high resolution satellite images (MERIS and SPOT 4). These maps were produced through semi-automatic supervised classification procedures, using an LCCS based nomenclature of 15 classes. Validation results pointed to global accuracy values greater than 80% for all maps. In this paper we focus on studying the effect of using different scale land cover maps in the watershed modelling and its impact in results. The work presented is part of the FP7-EU project "Merging hydrological models and Earth observation data for reliable information on water - MyWater".

  6. User's guide for Bristol Bay land cover maps

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The purpose of this Users Guide is to explain how to use the land cover maps and field data generated by the Bristol Bay Land Cover Mapping Project. The complete...

  7. Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

    Science.gov (United States)

    Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

    2016-09-01

    Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

  8. FOREST COVER MAPPING IN ISKANDAR MALAYSIA USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    K. D. Kanniah

    2016-09-01

    Full Text Available Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV, non photosynthetic vegetation (NPV and soil surface (S. Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990 and 5% (2010 compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

  9. Towards an Integrated Global Land Cover Monitoring and Mapping System

    Directory of Open Access Journals (Sweden)

    Martin Herold

    2016-12-01

    Full Text Available Global land cover mapping has evolved in a number of ways over the past two decades including increased activity in the areas of map validation and inter-comparison, which is the main focus of this Special Issue in Remote Sensing. Here we describe the major trends in global land cover mapping that have occurred, followed by recent advances as exemplified by the papers in the Special Issue. Finally, we consider what the future holds for global land cover mapping.

  10. Enhancing the performance of regional land cover mapping

    Science.gov (United States)

    Wu, Weicheng; Zucca, Claudio; Karam, Fadi; Liu, Guangping

    2016-10-01

    Different pixel-based, object-based and subpixel-based methods such as time-series analysis, decision-tree, and different supervised approaches have been proposed to conduct land use/cover classification. However, despite their proven advantages in small dataset tests, their performance is variable and less satisfactory while dealing with large datasets, particularly, for regional-scale mapping with high resolution data due to the complexity and diversity in landscapes and land cover patterns, and the unacceptably long processing time. The objective of this paper is to demonstrate the comparatively highest performance of an operational approach based on integration of multisource information ensuring high mapping accuracy in large areas with acceptable processing time. The information used includes phenologically contrasted multiseasonal and multispectral bands, vegetation index, land surface temperature, and topographic features. The performance of different conventional and machine learning classifiers namely Malahanobis Distance (MD), Maximum Likelihood (ML), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs) and Random Forests (RFs) was compared using the same datasets in the same IDL (Interactive Data Language) environment. An Eastern Mediterranean area with complex landscape and steep climate gradients was selected to test and develop the operational approach. The results showed that SVMs and RFs classifiers produced most accurate mapping at local-scale (up to 96.85% in Overall Accuracy), but were very time-consuming in whole-scene classification (more than five days per scene) whereas ML fulfilled the task rapidly (about 10 min per scene) with satisfying accuracy (94.2-96.4%). Thus, the approach composed of integration of seasonally contrasted multisource data and sampling at subclass level followed by a ML classification is a suitable candidate to become an operational and effective regional land cover mapping method.

  11. Land Cover Mapping Using SENTINEL-1 SAR Data

    Science.gov (United States)

    Abdikan, S.; Sanli, F. B.; Ustuner, M.; Calò, F.

    2016-06-01

    In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR) imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH) Interferometric Wide swath mode (IW) data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM) method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.

  12. Generation and Assessment of Urban Land Cover Maps Using High-Resolution Multispectral Aerial Images

    DEFF Research Database (Denmark)

    Höhle, Joachim; Höhle, Michael

    2013-01-01

    to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures...... and their associated confidence intervals are used to adequately reflect uncertainty in the assessment based on the chosen sample size. Proof of concept for the method is given for an urban area in Switzerland. Here, the produced land cover map with six classes (building, wall and carport, road and parking lot, hedge...... tree learning based on recursive partitioning is investigated. We conclude that the open source software “R” provides all the tools needed for performing statistical prudent classification and accuracy evaluations of urban land cover maps....

  13. Improving automated disturbance maps using snow-covered landsat time series stacks

    Science.gov (United States)

    Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

    2012-01-01

    Snow-covered winter Landsat time series stacks are used to develop a nonforest mask to enhance automated disturbance maps produced by the Vegetation Change Tracker (VCT). This method exploits the enhanced spectral separability between forested and nonforested areas that occurs with sufficient snow cover. This method resulted in significant improvements in Vegetation...

  14. GENERATION OF 2D LAND COVER MAPS FOR URBAN AREAS USING DECISION TREE CLASSIFICATION

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2014-01-01

    A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objec...

  15. Mapping land cover from satellite images: A basic, low cost approach

    Science.gov (United States)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

    1978-01-01

    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  16. Land Use and Land Cover, Heard County, Georgia Land Cover Map, Published in 2005, 1:12000 (1in=1000ft) scale, Chattahoochee-Flint Regional Development.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Hardcopy Maps information as of 2005. It is described...

  17. On the Exel crossed product of topological covering maps

    CERN Document Server

    Carlsen, Toke Meier

    2008-01-01

    For dynamical systems defined by a covering map of a compact Hausdorff space and the corresponding transfer operator, the associated crossed product $C^*$-algebras $\\cros$ introduced by Exel and Vershik are considered. An important property for homeomorphism dynamical systems is topological freeness. It can be extended in a natural way to in general non-invertible dynamical systems generated by covering maps. In this article, it is shown that the following four properties are equivalent: the dynamical system generated by a covering map is topologically free; the canonical imbedding of $C(X)$ into $\\cros$ is a maximal abelian $C^*$-subalgebra of $\\cros$; any nontrivial two sided ideal of $\\cros$ has non-zero intersection with the imbedded copy of $C(X)$; a certain natural representation of $\\cros$ is faithful. This result is a generalization to non-invertible dynamics of the corresponding results for crossed product $C^*$-algebras of homeomorphism dynamical systems.

  18. Transmittance spectroscopy and transmitted multispectral imaging to map covered paints

    Directory of Open Access Journals (Sweden)

    Antonino Cosentino

    2016-01-01

    Full Text Available Transmitted spectroscopy and transmitted multispectral imaging in the 400-900 nm range have been applied for the mapping and tentative identification of paints covered by a white preparation as in the case of a ground laid for reusing a canvas for another painting. These methods can be applied to polychrome works of art, as long as their support and new preparation are sufficiently translucent. This work presents the transmittance spectra acquired from a test board consisting of a prepared canvas with swatches of 54 pigments covered with titanium white and the multispectral images realized with transmitted light to map covered paints on a mock-up painting. It was observed that 18 out of 54 historical pigments provide characteristic transmittance spectra even underneath a titanium white preparation layer and that transmitted light multispectral imaging can map hidden paint layers.

  19. A New Tree Cover Percentage Map in Eurasia at 500 m Resolution Using MODIS Data

    Directory of Open Access Journals (Sweden)

    Toshiyuki Kobayashi

    2013-12-01

    Full Text Available Global tree cover percentage is an important parameter used to understand the global environment. However, the available global percent tree cover products are few, and efforts to validate these maps have been limited. Therefore, producing a new broad-scale percent tree cover dataset is valuable. Our study was undertaken to map tree cover percentage, on a global scale, with better accuracy than previous studies. Using a modified supervised regression tree algorithm from Moderate Resolution Imaging Spectroradiometer (MODIS data of 2008, the tree cover percentage was estimated at 500 m resolution in Eurasia. Training data were created by simulation using reference data interpreted from Google Earth. We collected approximately 716 high-resolution images from Google Earth. The regression tree model was modified to fit those images for improved accuracy. Our estimation result was validated using 307 points. The root mean square error (RMSE between estimated and observed tree cover was 11.2%, and the weighted RMSE between them, in which five tree cover strata (0%–20%, 21%–40%, 41%–60%, 61%–80%, and 81%–100% were weighted equally, was 14.2%. The result was compared to existing global percent-scale tree cover datasets. We found that existing datasets had some pixels with estimation error of more than 50% and each map had different characteristics. Our map could be an alternative dataset and other existing datasets could be modified using our resultant map.

  20. A new MODIS daily cloud free snow cover mapping algorithm on the Tibetan Plateau

    Institute of Scientific and Technical Information of China (English)

    XiaoDong Huang; XiaoHua Hao; QiSheng Feng; Wei Wang; TianGang Liang

    2014-01-01

    Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa-ter equivalent products (SWE), several cloud elimination methods were integrated to produce a new daily cloud free snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area (TP) were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7%when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.

  1. Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

    Directory of Open Access Journals (Sweden)

    Sarah Malec

    2015-09-01

    Full Text Available Soil erosion can be linked to relative fractional cover of photosynthetic-active vegetation (PV, non-photosynthetic-active vegetation (NPV and bare soil (BS, which can be integrated into erosion models as the cover-management C-factor. This study investigates the capability of EnMAP imagery to map fractional cover in a region near San Jose, Costa Rica, characterized by spatially extensive coffee plantations and grazing in a mountainous terrain. Simulated EnMAP imagery is based on airborne hyperspectral HyMap data. Fractional cover estimates are derived in an automated fashion by extracting image endmembers to be used with a Multiple End-member Spectral Mixture Analysis approach. The C-factor is calculated based on the fractional cover estimates determined independently for EnMAP and HyMap. Results demonstrate that with EnMAP imagery it is possible to extract quality endmember classes with important spectral features related to PV, NPV and soil, and be able to estimate relative cover fractions. This spectral information is critical to separate BS and NPV which greatly can impact the C-factor derivation. From a regional perspective, we can use EnMAP to provide good fractional cover estimates that can be integrated into soil erosion modeling.

  2. Simon Fraser University Computer Produced Map Catalogue

    Directory of Open Access Journals (Sweden)

    Brian Phillips

    2013-05-01

    Full Text Available An IBM 360/50 computer and magnetic tape are used in a new univer- sity library to produce a map catalogue by area and up to six subiects for each map. Cataloguing is by non-professional staff using the Library of Congress "G, schedule. Author, title, and publisher are in variable length fields, and codes are seldom used for input or interpretation. Ma- chine searches by area, subjects, author, publisher, scale, pro-;ection, date and language can be carried out.

  3. Assessment of the thematic accuracy of land cover maps

    DEFF Research Database (Denmark)

    Høhle, Joachim

    2015-01-01

    Several land cover maps are generated from aerial imagery and assessed by different approaches. The test site is an urban area in Europe for which six classes (‘building’, ‘hedge and bush’, ‘grass’, ‘road and parking lot’, ‘tree’, ‘wall and car port’) had to be derived. Two classification methods...

  4. A globally complete map of supraglacial debris cover and a new toolkit for debris cover research

    Science.gov (United States)

    Herreid, Sam; Pellicciotti, Francesca

    2017-04-01

    A growing canon of literature is focused on resolving the processes and implications of debris cover on glaciers. However, this work is often confined to a handful of glaciers that were likely selected based on criteria optimizing their suitability to test a specific hypothesis or logistical ease. The role of debris cover in a glacier system is likely to not go overlooked in forthcoming research, yet the magnitude of this role at a global scale has not yet been fully described. Here, we present a map of debris cover for all glacierized regions on Earth including the Greenland Ice Sheet using 30 m Landsat data. This dataset will begin to open a wider context to the high quality, localized findings from the debris-covered glacier research community and help inform large-scale modeling efforts. A global map of debris cover also facilitates analysis attempting to isolate first order geomorphological and climate controls of supraglacial debris production. Furthering the objective of expanding the inclusion of debris cover in forthcoming research, we also present an under development suite of open-source, Python based tools. Requiring minimal and often freely available input data, we have automated the mapping of: i) debris cover, ii) ice cliffs, iii) debris cover evolution over the Landsat era and iv) glacier flow instabilities from altered debris structures. At the present time, debris extent is the only globally complete quantity but with the expanding repository of high quality global datasets and further tool development minimizing manual tasks and computational cost, we foresee all of these tools being applied globally in the near future.

  5. Spatial resolution requirements for urban land cover mapping from space

    Science.gov (United States)

    Todd, William J.; Wrigley, Robert C.

    1986-01-01

    Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.

  6. GENERATION OF 2D LAND COVER MAPS FOR URBAN AREAS USING DECISION TREE CLASSIFICATION

    OpenAIRE

    J. Höhle

    2014-01-01

    A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a ...

  7. Mapping Snow Cover Loss Patterns in the Western United States

    Science.gov (United States)

    Moore, C.; Kampf, S. K.; Richer, E.; Stone, B.

    2011-12-01

    Cara Moore, Stephanie Kampf, Eric Richer, Brandon Stone Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523-1499 The Western United States depends on snowmelt to provide water for industrial, municipal, and agricultural needs. Some areas in this region have observed an increase in the proportion of precipitation falling as rain rather than snow in response to climate warming, a trend that can alter the timing and magnitude of runoff. Transitional snow zones, which lie between lower elevation intermittent snowpack and higher elevation persistent snowpack, may be particularly sensitive to changing climate conditions. Snow covered area is an easily obtainable measurement that can help identify the locations and elevations of these transitional snow zones. The purpose of this study is to improve the understanding of snowpack characteristics in the Western U.S. by mapping snow cover loss patterns using the Moderate-Resolution Imaging Spectroradiometer (MODIS) snow covered area (SCA) product. Snow cover loss patterns can be difficult to compare objectively between regions because spring snow storms lead to abrupt increases and decreases in SCA. Therefore, we develop a curve-fitting snow cover depletion model (SCoDMod) used to derive standardized snow cover loss curves. We fit the model to snow cover patterns within 100m elevation zones from January 1st until July 19th for each USGS eight digit hydrologic unit in the Western US. We use the model to identify 11 year (2000-2010) average snow cover loss patterns and compare those patterns to snow cover loss behavior in wet and dry years. Model results give maps of average SCA in the Western United States on the first of the month from January to July, as well as maps of the date of SCA loss to 75% (Q75), 50% (Q50), and 25% (Q25) SCA. Results show that the Cascade, Sierra Nevada, and Rocky mountains from Colorado northward retain >90% SCA until March, whereas most parts of lower elevation

  8. Land cover mapping of Greater Mesoamerica using MODIS data

    Science.gov (United States)

    Giri, Chandra; Jenkins, Clinton N.

    2005-01-01

    A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

  9. Land-Cover Map for the Island of Maui, Hawaii, circa 2017

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This dataset describes land cover and vegetation for the island of Maui, Hawaii, circa 2017, hereinafter the 2017 land-cover map. The 2017 land-cover map is a...

  10. Automated Training Sample Extraction for Global Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Julien Radoux

    2014-05-01

    Full Text Available Land cover is one of the essential climate variables of the ESA Climate Change Initiative (CCI. In this context, the Land Cover CCI (LC CCI project aims at building global land cover maps suitable for climate modeling based on Earth observation by satellite sensors.  The  challenge  is  to  generate  a  set  of  successive  maps  that  are  both  accurate and consistent over time. To do so, operational methods for the automated classification of optical images are investigated. The proposed approach consists of a locally trained classification using an automated selection of training samples from existing, but outdated land cover information. Combinations of local extraction (based on spatial criteria and self-cleaning of training samples (based on spectral criteria are quantitatively assessed. Two large study areas, one in Eurasia and the other in South America, are considered. The proposed morphological cleaning of the training samples leads to higher accuracies than the statistical outlier removal in the spectral domain. An optimal neighborhood has been identified for the local sample extraction. The results are coherent for the two test areas, showing an improvement of the overall accuracy compared with the original reference datasets and a significant reduction of macroscopic errors. More importantly, the proposed method partly controls the reliability of existing land cover maps as sources of training samples for supervised classification.

  11. MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

    Science.gov (United States)

    This paper presents a fuzzy set-based method of mapping spatial accuracy of thematic map and computing several ecological indicators while taking into account spatial variation of accuracy associated with different land cover types and other factors (e.g., slope, soil type, etc.)...

  12. An Automated Approach for Mapping Persistent Ice and Snow Cover over High Latitude Regions

    Directory of Open Access Journals (Sweden)

    David J. Selkowitz

    2015-12-01

    Full Text Available We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N. Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI, and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI, with a mean accuracy (agreement with the RGI of 0.96, a mean precision (user’s accuracy of the snow/ice cover class of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class of 0.86, and a mean F-score (a measure that considers both precision and recall of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to

  13. An automated approach for mapping persistent ice and snow cover over high latitude regions

    Science.gov (United States)

    Selkowitz, David J.; Forster, Richard R.

    2016-01-01

    We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly

  14. Mapping of land cover in Northern California with simulated HyspIRI images

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2014-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (i.e., full range) of the spectrum have shown improved capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a full-range hyperspectral and thermal satellite being considered for development by NASA (hyspiri.jpl.nasa.gov). A hyperspectral satellite, such as HyspIRI, will provide detailed spectral and temporal information at global scales that could greatly improve our ability to map land cover with greater class detail and spatial and temporal accuracy than possible with conventional multispectral satellites. The broad goal of our research is to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping across a range of environmental and anthropogenic gradients in California. In this study, we mapped FAO Land Cover Classification System (LCCS) classes over 30,000 km2 in Northern California using multi-temporal HyspIRI imagery simulated from the AVIRIS airborne sensor. The Random Forests classification was applied to predictor variables derived from the multi-temporal hyperspectral data and accuracies were compared to that from Landsat 8 OLI. Results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different forest life-form types, such as mixed conifer and broadleaf forests and open- and closed-canopy forests.

  15. MAPPING OF THE LAND COVER SPATIOTEMPORAL CHARACTERISTICS IN NORTHERN RUSSIA CAUSED BY CLIMATE CHANGE

    Directory of Open Access Journals (Sweden)

    E. Panidi

    2016-06-01

    Full Text Available The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass. We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

  16. Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2017-01-01

    Full Text Available A detailed and accurate knowledge of land cover is crucial for many scientific and operational applications, and as such, it has been identified as an Essential Climate Variable. This accurate knowledge needs frequent updates. This paper presents a methodology for the fully automatic production of land cover maps at country scale using high resolution optical image time series which is based on supervised classification and uses existing databases as reference data for training and validation. The originality of the approach resides in the use of all available image data, a simple pre-processing step leading to a homogeneous set of acquisition dates over the whole area and the use of a supervised classifier which is robust to errors in the reference data. The produced maps have a kappa coefficient of 0.86 with 17 land cover classes. The processing is efficient, allowing a fast delivery of the maps after the acquisition of the image data, does not need expensive field surveys for model calibration and validation, nor human operators for decision making, and uses open and freely available imagery. The land cover maps are provided with a confidence map which gives information at the pixel level about the expected quality of the result.

  17. Integrating geographical data and phenological characteristics derived from MODIS data for improving land cover mapping

    Institute of Scientific and Technical Information of China (English)

    CAI Hongyan; ZHANG Shuwen; BU Kun; YANG Jiuchun; CHANG Liping

    2011-01-01

    The study developed a feasible method for large-area land cover mapping with combination of geographical data and phenological characteristics,taking Northeast China (NEC) as the study area.First,with the monthly average of precipitation and temperature datasets,the spatial clustering method was used to divide the NEC into four ecoclimate regions.For each ecoclimate region,geographical variables (annual mean precipitation and temperature,elevation,slope and aspect) were combined with phenological variables derived from the moderate resolution imaging spectroradiometer (MODIS) data (enhanced vegetation index (EVI) and land surface water index (LSWI)),which were taken as input variables of land cover classification.Decision Tree (DT) classifiers were then performed to produce land cover maps for each region.Finally,four resultant land cover maps were mosaicked for the entire NEC (NEC_MODIS),and the land use and land cover data of NEC (NEC_LULC) interpreted from Landsat-TM images was used to evaluate the NEC_MODIS and MODIS land cover product (MODIS_IGBP) in terms of areal and spatial agreement.The results showed that the phenological information derived from EVl and LSWl time series well discriminated land cover classes in NEC,and the overall accuracy was significantly improved by 5.29% with addition of geographical variables.Compared with NEC_LULC for seven aggregation classes,the area errors of NEC_MODIS were much smaller and more stable than that of MODIS_IGBP for most of classes,and the wall-to-wall spatial comparisons at pixel level indicated that NEC_MODIS agreed with NEC_LULC for 71.26% of the NEC,whereas only 62.16% for MODIS_IGBP.The good performance of NEC_MODIS demonstrates that the methodology developed in the study has great potential for timely and detailed land cover mapping in temperate and boreal regions.

  18. Aggregated Habitat Cover Maps Depicting the Shallow-water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Shallow-water, aggregated cover maps were produced by combining as many as four or more detailed habitat types into general cover categories. The original detailed...

  19. Aggregated Habitat Cover Maps Depicting the Shallow-water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Shallow-water, aggregated cover maps were produced by combining as many as four or more detailed habitat types into general cover categories. The original detailed...

  20. Shallow-water Benthic Habitats of the Northwestern Hawaiian Islands from Aggregated Habitat Cover Maps Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Shallow-water, aggregated cover maps were produced by combining as many as four or more detailed habitat types into general cover categories. The original detailed...

  1. Assessment of methods for mapping snow cover from MODIS

    Science.gov (United States)

    Rittger, Karl; Painter, Thomas H.; Dozier, Jeff

    2013-01-01

    Characterization of snow is critical for understanding Earth’s water and energy cycles. Maps of snow from MODIS have seen growing use in investigations of climate, hydrology, and glaciology, but the lack of rigorous validation of different snow mapping methods compromises these studies. We examine three widely used MODIS snow products: the “binary” (i.e., snow yes/no) global snow maps that were among the initial MODIS standard products; a more recent standard MODIS fractional snow product; and another fractional snow product, MODSCAG, based on spectral mixture analysis. We compare them to maps of snow obtained from Landsat ETM+ data, whose 30 m spatial resolution provides nearly 300 samples within a 500 m MODIS nadir pixel. The assessment uses 172 images spanning a range of snow and vegetation conditions, including the Colorado Rocky Mountains, the Upper Rio Grande, California’s Sierra Nevada, and the Nepal Himalaya. MOD10A1 binary and fractional fail to retrieve snow in the transitional periods during accumulation and melt while MODSCAG consistently maintains its retrieval ability during these periods. Averaged over all regions, the RMSE for MOD10A1 fractional is 0.23, whereas the MODSCAG RMSE is 0.10. MODSCAG performs the most consistently through accumulation, mid-winter and melt, with median differences ranging from -0.16 to 0.04 while differences for MOD10A1 fractional range from -0.34 to 0.35. MODSCAG maintains its performance over all land cover classes and throughout a larger range of land surface properties. Characterizing snow cover by spectral mixing is more accurate than empirical methods based on the normalized difference snow index, both for identifying where snow is and is not and for estimating the fractional snow cover within a sensor’s instantaneous field-of-view. Determining the fractional value is particularly important during spring and summer melt in mountainous terrain, where large variations in snow, vegetation and soil occur over

  2. Automated mapping of persistent ice and snow cover across the western U.S. with Landsat

    Science.gov (United States)

    Selkowitz, David J.; Forster, Richard R.

    2016-07-01

    We implemented an automated approach for mapping persistent ice and snow cover (PISC) across the conterminous western U.S. using all available Landsat TM and ETM+ scenes acquired during the late summer/early fall period between 2010 and 2014. Two separate validation approaches indicate this dataset provides a more accurate representation of glacial ice and perennial snow cover for the region than either the U.S. glacier database derived from US Geological Survey (USGS) Digital Raster Graphics (DRG) maps (based on aerial photography primarily from the 1960s-1980s) or the National Land Cover Database 2011 perennial ice and snow cover class. Our 2010-2014 Landsat-derived dataset indicates 28% less glacier and perennial snow cover than the USGS DRG dataset. There are larger differences between the datasets in some regions, such as the Rocky Mountains of Northwest Wyoming and Southwest Montana, where the Landsat dataset indicates 54% less PISC area. Analysis of Landsat scenes from 1987-1988 and 2008-2010 for three regions using a more conventional, semi-automated approach indicates substantial decreases in glaciers and perennial snow cover that correlate with differences between PISC mapped by the USGS DRG dataset and the automated Landsat-derived dataset. This suggests that most of the differences in PISC between the USGS DRG and the Landsat-derived dataset can be attributed to decreases in PISC, as opposed to differences between mapping techniques. While the dataset produced by the automated Landsat mapping approach is not designed to serve as a conventional glacier inventory that provides glacier outlines and attribute information, it allows for an updated estimate of PISC for the conterminous U.S. as well as for smaller regions. Additionally, the new dataset highlights areas where decreases in PISC have been most significant over the past 25-50 years.

  3. Integrating Recent Land Cover Mapping Efforts to Update the National Gap Analysis Program's Species Habitat Map

    Science.gov (United States)

    McKerrow, A. J.; Davidson, A.; Earnhardt, T. S.; Benson, A. L.

    2014-11-01

    Over the past decade, great progress has been made to develop national extent land cover mapping products to address natural resource issues. One of the core products of the GAP Program is range-wide species distribution models for nearly 2000 terrestrial vertebrate species in the U.S. We rely on deductive modeling of habitat affinities using these products to create models of habitat availability. That approach requires that we have a thematically rich and ecologically meaningful map legend to support the modeling effort. In this work, we tested the integration of the Multi-Resolution Landscape Characterization Consortium's National Land Cover Database 2011 and LANDFIRE's Disturbance Products to update the 2001 National GAP Vegetation Dataset to reflect 2011 conditions. The revised product can then be used to update the species models. We tested the update approach in three geographic areas (Northeast, Southeast, and Interior Northwest). We used the NLCD product to identify areas where the cover type mapped in 2011 was different from what was in the 2001 land cover map. We used Google Earth and ArcGIS base maps as reference imagery in order to label areas identified as "changed" to the appropriate class from our map legend. Areas mapped as urban or water in the 2011 NLCD map that were mapped differently in the 2001 GAP map were accepted without further validation and recoded to the corresponding GAP class. We used LANDFIRE's Disturbance products to identify changes that are the result of recent disturbance and to inform the reassignment of areas to their updated thematic label. We ran species habitat models for three species including Lewis's Woodpecker (Melanerpes lewis) and the White-tailed Jack Rabbit (Lepus townsendii) and Brown Headed nuthatch (Sitta pusilla). For each of three vertebrate species we found important differences in the amount and location of suitable habitat between the 2001 and 2011 habitat maps. Specifically, Brown headed nuthatch habitat in

  4. Mapping Forest Cover and Forest Cover Change with Airborne S-Band Radar

    Directory of Open Access Journals (Sweden)

    Ramesh K. Ningthoujam

    2016-07-01

    Full Text Available Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41 and 20 m (63% overall accuracy, κ = 0.27. The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its changes.

  5. Land cover mapping based on random forest classification of multitemporal spectral and thermal images.

    Science.gov (United States)

    Eisavi, Vahid; Homayouni, Saeid; Yazdi, Ahmad Maleknezhad; Alimohammadi, Abbas

    2015-05-01

    Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8's spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82%, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.

  6. Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

    Science.gov (United States)

    Stoner, E. R.

    1982-01-01

    The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

  7. Forest cover of North America in the 1970s mapped using Landsat MSS data

    Science.gov (United States)

    Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

    2015-12-01

    The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing

  8. Land Cover and Permafrost Change Mapping Using Dense Time Stacks of Landsat and Quickbird Imagery

    Science.gov (United States)

    Nyland, K. E.; Streletskiy, D. A.; Shiklomanov, N. I.

    2014-12-01

    Climate change is especially pronounced in the Arctic, and regions on permafrost are at the frontier of these changes. Increasing air temperatures affect the extent, type, and characteristics of permafrost which is critical to many natural phenomena and northern infrastructure. In areas of discontinuous permafrost certain land cover types are indicative of permafrost conditions making satellite imagery an important tool for assessing environmental change in these remote areas. In arctic environments remote sensing can be particularly challenging due to consistently high cloud cover, data gaps, and landscape heterogeneity. However, there has been success at dealing with such challenges in lower latitude regions using the emerging dense time stack methodology. In place of using an anniversary date for land cover comparisons from different years, this methodology includes scenes from all seasons in addition to imagery normally rejected due to data gaps and high amounts of cloud cover. The incorporation of all available data creates a "dense time stack" which provides both a more complete dataset and more nuanced spectral signatures for classification. This work applied the dense time stack method to mapping five drainage basins in the close vicinity of the city of Igarka, Russia using both Landsat and Quickbird satellite imagery. The resulting map series proved this method to be effective within the Arctic for multiscalar mapping both temporally (annual and seasonal) and spatially (at the resolutions of Landsat and Quickbird). The time series of observed land cover changes produced allowed areas of permafrost degradation to be identified. These maps will be applied in the future to ongoing hydrological research in the region investigating the sources of increased run off and its relation to permafrost degradation.

  9. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

    NARCIS (Netherlands)

    Ali, A.; de Bie, C.A.J.M.; Skidmore, A.K.; Scarrott, R.G.; Hamad, A.A.; Venus, V.; Lymberakis, P.

    2013-01-01

    The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typica

  10. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

    NARCIS (Netherlands)

    Ali, A.; Bie, de C.A.J.M.; Skidmore, A.K.; Scarrott, R.G.; Hamad, A.A.; Venus, V.; Lymberakis, P.

    2013-01-01

    The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typica

  11. Mapping urban land cover from space: Some observations for future progress

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The multilevel classification system adopted by the USGS for operational mapping of land use and land cover at levels 1 and 2 is discussed and the successes and failures of mapping land cover from LANDSAT digital data are reviewed. Techniques used for image interpretation and their relationships to sensor parameters are examined. The requirements for mapping levels 2 and 3 classes are considered.

  12. Mapping of land cover in northern California with simulated hyperspectral satellite imagery

    Science.gov (United States)

    Clark, Matthew L.; Kilham, Nina E.

    2016-09-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands

  13. A bijection for covered maps, or a shortcut between Harer-Zagier's and Jackson's formulas

    CERN Document Server

    Bernardi, Olivier

    2010-01-01

    We consider maps on orientable surfaces. A map is unicellular if it has a single face. A covered map is a map with a marked unicellular spanning submap. For a map of genus g, the unicellular submap can have any genus g'=0,1,..,g. Our main result is a bijection between covered maps with n edges and genus g and pairs made of a plane tree with n edges and a unicellular bipartite map of genus g with n+1 edges. > > In the planar case, the covered maps are maps with a marked spanning tree (a.k.a. tree-rooted maps) and our bijection specializes into a construction previously described by the first author. A strong connection subsists between covered maps and tree-rooted maps in genus 1 (because a covered map is either a tree-rooted map or the dual of a tree-rooted map) and we thereby obtain a bijective explanation of a formula by Lehman and Walsh on the number of tree-rooted maps of genus 1. A more surprising byproduct of our bijection is an equivalence between an enumerative formula by Harer and Zagier concerning u...

  14. A methodology to generate a synergetic land-cover map by fusion of different land-cover products

    Science.gov (United States)

    Pérez-Hoyos, A.; García-Haro, F. J.; San-Miguel-Ayanz, J.

    2012-10-01

    The main goal of this study is to develop a general framework for building a hybrid land-cover map by the synergistic combination of a number of land-cover classifications with different legends and spatial resolutions. The proposed approach assesses class-specific accuracies of datasets and establishes affinity between thematic legends using a common land-cover language such as the UN Land-Cover Classification System (LCCS). The approach is illustrated over a large region in Europe using four land-cover datasets (CORINE, GLC2000, MODIS and GlobCover), but it can be applied to any set of existing products. The multi-classification map is expected to improve the performance of individual classifications by reconciling their best characteristics while avoiding their main weaknesses. The intermap comparison reveals improved agreement of the hybrid map with all other land-cover products and therefore indicates the successful exploration of synergies between the different products. The approach offers also estimates for the classification confidence associated with the pixel label and flexibility to shift the balance between commission and omission errors, which are critical in order to obtain a desired reliable map.

  15. Mapping of the Seagrass Cover Along the Mediterranean Coast of Turkey Using Landsat 8 Oli Images

    Science.gov (United States)

    Bakirman, T.; Gumusay, M. U.; Tuney, I.

    2016-06-01

    Benthic habitat is defined as ecological environment where marine animals, plants and other organisms live in. Benthic habitat mapping is defined as plotting the distribution and extent of habitats to create a map with complete coverage of the seabed showing distinct boundaries separating adjacent habitats or the use of spatially continuous environmental data sets to represent and predict biological patterns on the seafloor. Seagrass is an essential endemic marine species that prevents coast erosion and regulates carbon dioxide absorption in both undersea and atmosphere. Fishing, mining, pollution and other human activities cause serious damage to seabed ecosystems and reduce benthic biodiversity. According to the latest studies, only 5-10% of the seafloor is mapped, therefore it is not possible to manage resources effectively, protect ecologically important areas. In this study, it is aimed to map seagrass cover using Landsat 8 OLI images in the northern part of Mediterranean coast of Turkey. After pre-processing (e.g. radiometric, atmospheric, water depth correction) of Landsat images, coverage maps are produced with supervised classification using in-situ data which are underwater photos and videos. Result maps and accuracy assessment are presented and discussed.

  16. Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Foster, James L.

    2009-01-01

    Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed

  17. Land Use Cover Mapping of Water Melon and Cereals in Southern Italy

    Directory of Open Access Journals (Sweden)

    Costanza Fiorentino

    2010-06-01

    Full Text Available The new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT. More accurate and reliable maps of land cover can then be produced. However, classification procedure with these images is more complex than with the medium resolution remote sensing data for two main reasons: firstly, because of their exiguous number of spectral bands, secondly, owing to high spatial resolution, the assumption of pixel independence does not generally hold. It is then necessary to have a multi-temporal series of images or to use classifiers taking into account also proximal information. The data in this study were (i a remote sensing image taken by SPOT5 satellite in July 2007 and used to discriminate the water melon cover class and, (ii three multi-temporal remote sensing images taken by SPOT5 satellite in May, June and July 2008 used to discriminate water melon and cereal crop cover classes. For water melon recognition, providing a single image in 2007, an object-oriented technique was applied instead of a traditional, per pixel technique obtaining an increase of overall accuracy of 15%. In 2008, since it was available a multi-temporal data set, a traditional ‘Maximum Likelihood’ technique was applied for both water melon and cereal crop cover class. The overall accuracy is greater than 95%.

  18. Comparison results of forest cover mapping of Peninsular Malaysia using geospatial technology

    Science.gov (United States)

    Hamid, Wan Abdul; Abd Rahman, Shukri B. Wan

    2016-06-01

    Climate change and global warming transpire due to several factors. Among them is deforestation which occur mostly in developing countries including Malaysia where forested areas are converted to other land use for tangible economic returns and to a smaller extent, as subsistence for local communities. As a cause for concern, efforts have been taken by the World Resource Institute (WRI) and World Wildlife Fund (WWF) to monitor forest loss using geospatial technology - interpreting time-based remote sensing imageries and producing statistics of forested areas lost since 2001. In Peninsular Malaysia, the Forestry Department of Peninsular Malaysia(FDPM) has conducted forest cover mapping for the region using the same technology since 2011, producing GIS maps for 2009-2010,2011-2012,2013-2014 and 2015. This paper focuses on the comparative study of the results generated from WRI,WWF and FDPM interpretations between 2010 and 2015, the methodologies used, the similarities and differences, challenges and recommendations for future enhancement of forest cover mapping technique.

  19. The stepwise discriminant algorithm for snow cover mapping based on FY-3/MERSI data

    Science.gov (United States)

    Han, Tao; Wang, Dawei; Jiang, Youyan; Wang, Xiaowei

    2013-10-01

    Medium Resolution Spectral Imager (MERSI) on board China's new generation polar orbit meteorological satellite FY- 3A provides a new data source for snow monitoring in large area. As a case study, the typical snow cover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snow cover using FY- 3A/MERSI. By analyzing the spectral response characteristics of snow and other surface elements, as well as each channel image quality on FY-3A/MERSI, the widely used Normalized Difference Snow Index (NDSI) was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI, a tree-structure prototype version of snow identification model was proposed, including five newly-built multi-spectral indexes to remove those pixels such as forest, cloud shadow, water, lake ice, sand (salty land), or cloud that are usually confused with snow step by step, especially, a snow/cloud discrimination index was proposed to eliminate cloud, apart from use of cloud mask product in advance. Furthermore, land cover land use (LULC) image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snow final determination and optimization. This model is composed as the core of FY-3A/MERSI snow cover mapping flowchart, to produce daily snow map at 250m spatial resolution, and statistics can be generated on the extent and persistence of snow cover in each pixel for time series maps. Preliminary validation activities of our snow identification model have been undertaken. Comparisons of the 104 FY- 3A/MERSI snow cover maps in 2010-2011 snow season with snow depth records from 16 meteorological stations in Qilian Mountains region, the sunny snow cover had an absolute accuracy of 92.8%. Results of the comparison with the snow cover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snow cover maps compared with the 6

  20. Land cover mapping of the National Park Service northwest Alaska management area using Landsat multispectral and thematic mapper satellite data

    Science.gov (United States)

    Markon, C.J.; Wesser, Sara

    1998-01-01

    A land cover map of the National Park Service northwest Alaska management area was produced using digitally processed Landsat data. These and other environmental data were incorporated into a geographic information system to provide baseline information about the nature and extent of resources present in this northwest Alaskan environment.This report details the methodology, depicts vegetation profiles of the surrounding landscape, and describes the different vegetation types mapped. Portions of nine Landsat satellite (multispectral scanner and thematic mapper) scenes were used to produce a land cover map of the Cape Krusenstern National Monument and Noatak National Preserve and to update an existing land cover map of Kobuk Valley National Park Valley National Park. A Bayesian multivariate classifier was applied to the multispectral data sets, followed by the application of ancillary data (elevation, slope, aspect, soils, watersheds, and geology) to enhance the spectral separation of classes into more meaningful vegetation types. The resulting land cover map contains six major land cover categories (forest, shrub, herbaceous, sparse/barren, water, other) and 19 subclasses encompassing 7 million hectares. General narratives of the distribution of the subclasses throughout the project area are given along with vegetation profiles showing common relationships between topographic gradients and vegetation communities.

  1. Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map

    Directory of Open Access Journals (Sweden)

    Myroslava Lesiv

    2016-03-01

    Full Text Available Data fusion represents a powerful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own. This paper focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study, we compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-weighted logistic regression (GWR, as well as classification and regression trees (CART. We ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference between the methods. However, GWR was found to perform better than the other tested methods in areas with high disagreement between the inputs.

  2. ON THE SHARP GROWTH, COVERING THEOREMS FOR NORMALIZED BIHOLOMORPHIC MAPPINGS IN Cn

    Institute of Scientific and Technical Information of China (English)

    Liu Xiaosong; Liu Taishun

    2007-01-01

    In this article, a normalized biholomorphic mapping f defined on bounded starlike circular domain in Cn is considered, where z = 0 is a zero of order k + 1 of f(z) - z.The sharp growth, covering theorems for almost starlike mappings of order α and starlike mappings of order α are established. Meanwhile, the construction of the above mappings on bounded starlike circular domain in Cn is also discussed, it provides the extremal mappings for the growth, covering theorems of the above mappings.

  3. CRED Cumulative Map of Percent Scleractinian Coral Cover at Zealandia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  4. CRED Cumulative Map of Percent Scleractinian Coral Cover at Maug

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  5. CRED Cumulative Map of Percent Scleractinian Coral Cover at Tutuila

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  6. CRED Cumulative Map of Percent Scleractinian Coral Cover at Guguan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  7. CRED Cumulative Map of Percent Scleractinian Coral Cover at Arakane

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  8. CRED Cumulative Map of Percent Scleractinian Coral Cover at Saipan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  9. CRED Cumulative Map of Percent Scleractinian Coral Cover at Sarigan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  10. CRED Cumulative Map of Percent Scleractinian Coral Cover at Agrihan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  11. CRED Cumulative Map of Percent Scleractinian Coral Cover at Anatahan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  12. Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

    Science.gov (United States)

    Kadlec, Jiri

    to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7--1.2%. The output snow probability map data sets are published online using web applications and web services. Keywords: crowdsourcing, image analysis, interpolation, MODIS, R statistical software, snow cover, snowpack probability, Tethys platform, time series, WaterML, web services, winter sports.

  13. Land-Use and Land-Cover Mapping Using a Gradable Classification Method

    Directory of Open Access Journals (Sweden)

    Keigo Kitada

    2012-05-01

    Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.

  14. Integrating global land cover datasets for deriving user-specific maps

    NARCIS (Netherlands)

    Tsendbazar, Nandika; Bruin, de Sytze; Herold, Martin

    2016-01-01

    Global scale land cover (LC) mapping has interested many researchers over the last two decades as it is an input data source for various applications. Current global land cover (GLC) maps often do not meet the accuracy and thematic requirements of specific users. This study aimed to create an improv

  15. Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models

    Science.gov (United States)

    Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher

    2014-04-01

    This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.

  16. South African National Land-Cover Change Map

    African Journals Online (AJOL)

    Fritz Schoeman

    Various spatial modelling procedures were used to ensure compilation of comparable and .... 4.3 Temporal Land-Cover Change Modelling Issues ... The reasoning followed in developing these rules is based on logical principles associated ...

  17. HMI Synoptic Maps Produced by NSO/NISP

    CERN Document Server

    Hughes, Anna L H; Marble, Andrew R; Oien, Niles A; Petrie, Gordon; Pevtsov, Alexei A

    2016-01-01

    Recently, the National Solar Observatory (NSO) Solar-atmosphere Pipeline Working Group has undertaken the production of synoptic maps from Helioseismic and Magnetic Imager (HMI) magnetograms. A set of maps has been processed spanning the data available for 2010-2015 using twice daily images (taken at UT midnight and noon) and running them through the same algorithms used to produce SOLIS/VSM 6302l mean-magnetic and spatial-variance maps. The contents of this document provide an overview of what these maps look like, and the processing steps used to generate them from the original HMI input data.

  18. Land use and land cover map of a semiarid region of Brazil for meteorological and climatic models

    Directory of Open Access Journals (Sweden)

    Rita Marcia da Silva Pinto Vieira

    2013-06-01

    Full Text Available An updated vegetation cover and land use map over a semiarid region of Brazil has been produced at a 1 km spatial resolution, using satellite data and remote sensing techniques, for application in climate modeling. The map presents the location and distribution of major vegetation types and non-vegetated land surface formations for the Northeast Brazil Region, which includes the semiarid region. In this study, Radambrasil and IBGE vegetation maps, a digital mosaic of ETM+ Landsat 7, and TM Landsat 5 images from the period 1999-2000 were used. To update the map, the techniques of segmentation and unsupervised classification (ISOSEG were applied. A total of 7 land cover and land use categories were mapped according to the "Simplified Simple Biosphere"(SSiB model legend. This map shows that there has been a considerable increase in agricultural activities and pasture area. The vegetation in this region is an intricate combination of different life forms (e.g., trees and shrubs forming a closed cover in this region. The semiarid region of Brazil is susceptible to desertification due to climatic and environmental conditions. This updated map should provide important input for regional stratification in climate studies.

  19. Land cover change mapping using MODIS time series to improve emissions inventories

    Science.gov (United States)

    López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie

    2016-04-01

    MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.

  20. Application of Google Maps API service for creating web map of information retrieved from CORINE land cover databases

    Directory of Open Access Journals (Sweden)

    Kilibarda Milan

    2010-01-01

    Full Text Available Today, Google Maps API application based on Ajax technology as standard web service; facilitate users with publication interactive web maps, thus opening new possibilities in relation to the classical analogue maps. CORINE land cover databases are recognized as the fundamental reference data sets for numerious spatial analysis. The theoretical and applicable aspects of Google Maps API cartographic service are considered on the case of creating web map of change in urban areas in Belgrade and surround from 2000. to 2006. year, obtained from CORINE databases.

  1. Land cover mapping for development planning in Eastern and Southern Africa

    Science.gov (United States)

    Oduor, P.; Flores Cordova, A. I.; Wakhayanga, J. A.; Kiema, J.; Farah, H.; Mugo, R. M.; Wahome, A.; Limaye, A. S.; Irwin, D.

    2016-12-01

    Africa continues to experience intensification of land use, driven by competition for resources and a growing population. Land cover maps are some of the fundamental datasets required by numerous stakeholders to inform a number of development decisions. For instance, they can be integrated with other datasets to create value added products such as vulnerability impact assessment maps, and natural capital accounting products. In addition, land cover maps are used as inputs into Greenhouse Gas (GHG) inventories to inform the Agriculture, Forestry and other Land Use (AFOLU) sector. However, the processes and methodologies of creating land cover maps consistent with international and national land cover classification schemes can be challenging, especially in developing countries where skills, hardware and software resources can be limiting. To meet this need, SERVIR Eastern and Southern Africa developed methodologies and stakeholder engagement processes that led to a successful initiative in which land cover maps for 9 countries (Malawi, Rwanda, Namibia, Botswana, Lesotho, Ethiopia, Uganda, Zambia and Tanzania) were developed, using 2 major classification schemes. The first sets of maps were developed based on an internationally acceptable classification system, while the second sets of maps were based on a nationally defined classification system. The mapping process benefited from reviews from national experts and also from technical advisory groups. The maps have found diverse uses, among them the definition of the Forest Reference Levels in Zambia. In Ethiopia, the maps have been endorsed by the national mapping agency as part of national data. The data for Rwanda is being used to inform the Natural Capital Accounting process, through the WAVES program, a World Bank Initiative. This work illustrates the methodologies and stakeholder engagement processes that brought success to this land cover mapping initiative.

  2. Detailed forest formation mapping in the land cover map series for the Caribbean islands

    Science.gov (United States)

    Helmer, E. H.; Schill, S.; Pedreros, D. H.; Tieszen, L. L.; Kennaway, T.; Cushing, M.; Ruzycki, T.

    2006-12-01

    Forest formation and land cover maps for several Caribbean islands were developed from Landsat ETM+ imagery as part of a multi-organizational project. The spatially explicit data on forest formation types will permit more refined estimates of some forest attributes. The woody vegetation classification scheme relates closely to that of Areces-Malea et al. (1), who classify Caribbean vegetation according to standards of the US Federal Geographic Data Committee (FGDC, 1997), with modifications similar to those in Helmer et al. (2). For several of the islands, we developed image mosaics that filled cloudy parts of scenes with data from other scene dates after using regression tree normalization (3). The regression tree procedure permitted us to develop mosaics for wet and drought seasons for a few of the islands. The resulting multiseason imagery facilitated separation between classes such as seasonal evergreen forest, semi-deciduous forest (including semi-evergreen forest), and drought deciduous forest or woodland formations. We used decision tree classification methods to classify the Landsat image mosaics to detailed forest formations and land cover for Puerto Rico (4), St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines and Grenada. The decision trees classified a stack of raster layers for each mapping area that included the Landsat image bands and various ancillary raster data layers. For Puerto Rico, for example, the ancillary data included climate parameters (5). For some islands, the ancillary data included topographic derivatives such as aspect, slope and slope position, SRTM (6) or other topographic data. Mapping forest formations with decision tree classifiers, ancillary geospatial data, and cloud-free image mosaics, accurately distinguished spectrally similar forest formations, without the aid of ecological zone maps, on the islands where the approach was used. The approach resulted in maps of forest formations with comparable or better detail

  3. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2014-09-01

    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

  4. Diffusion-based method for producing density equalizing maps

    CERN Document Server

    Gastner, M T; Gastner, Michael T.

    2004-01-01

    Map makers have long searched for a way to construct cartograms -- maps in which the sizes of geographic regions such as countries or provinces appear in proportion to their population or some other analogous property. Such maps are invaluable for the representation of census results, election returns, disease incidence, and many other kinds of human data. Unfortunately, in order to scale regions and still have them fit together, one is normally forced to distort the regions' shapes, potentially resulting in maps that are difficult to read. Many methods for making cartograms have been proposed, some of them extremely complex, but all suffer either from this lack of readability or from other pathologies, like overlapping regions or strong dependence on the choice of coordinate axes. Here we present a new technique based on ideas borrowed from elementary physics that suffers none of these drawbacks. Our method is conceptually simple and produces useful, elegant, and easily readable maps. We illustrate the metho...

  5. GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia.

    Science.gov (United States)

    Nigatu Wondrade; Dick, Øystein B; Tveite, Havard

    2014-03-01

    Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very

  6. Watershed Land Cover/Land Use Mapping Using Remote Sensing and Data Mining in Gorganrood, Iran

    Directory of Open Access Journals (Sweden)

    Masoud Minaei

    2016-04-01

    Full Text Available The Gorganrood watershed (GW is experiencing considerable environmental change in the form of natural hazards and erosion, as well as deforestation, cultivation and development activities. As a result of this, different types of Land Cover/Land Use (LCLU change are taking place on an intensive level in the area. This research study investigates the LCLU conditions upstream of this watershed for the years 1972, 1986, 2000 and 2014, using Landsat MSS, TM, ETM+ and OLI/TIRS images. LCLU maps for 1972, 1986, and 2000 were produced using pixel-based classification methods. For the 2014 LCLU map, Geographic Object-Based Image Analysis (GEOBIA in combination with the data-mining capabilities of Gini and J48 machine-learning algorithms were used. The accuracy of the maps was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. The overall accuracy ranged from 89% to 95%, quantity disagreement from 2.1% to 6.6%, and allocation disagreement from 2.1% for 2014 to 2.7% for 2000. The results of this study indicate that a significant amount of change has occurred in the region, and that this has as a consequence affected ecosystem services and human activity. This knowledge of the LCLU status in the area will help managers and decision makers to develop plans and programs aimed at effectively managing the watershed into the future.

  7. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

    Directory of Open Access Journals (Sweden)

    Annett Bartsch

    2016-11-01

    Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

  8. Cover crops knowledge and implementation willingness by producers of several crops

    Directory of Open Access Journals (Sweden)

    Robin Gómez Gómez

    2017-04-01

    Full Text Available The objective of this study was to assess the knowledge on cover crops and native vegetation mulches and the willingness to implement them by papaya, oil palm, and banana producers in Costa Rica. An evaluation instrument with twenty eight questions to be answered as true or false was developed, and it was used to yield a knowledge indicator. Seven additional questions with responses on a scale from 0 to 5 were included to explore producers’ willingness to implement cover crops or native vegetation mulches on their farms. The evaluation was completed in 2014, and was filled out by 36 papaya producers, 30 oil palm producers, and 57 banana producers. Item analyses to determine reliability produced Cronbach’s alpha values above 90%. For this study a factors analysis was performed in order to determine the measurement of one single variable, knowledge on cover crops and native vegetation mulches. Global knowledge scores varied signi cantly between producer groups. Banana producers assessments yielded the highest mean with the lowest variability, whereas papaya producers had the lower mean and the highest variability. Likewise, answers to each of the questions differed importantly between producer groups. It was also determined that producers of these crops are willing to implement and get training on cover crops and native vegetation mulches.

  9. EnviroAtlas -Durham, NC- One Meter Resolution Urban Area Land Cover Map (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Durham, NC land cover map was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial...

  10. A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources

    OpenAIRE

    Wang, Jie; Ji, Luyan; Huang, Xiaomeng; Fu, Haohuan; Xu, Shiming; Li, Congcong

    2016-01-01

    There is a trend to acquire high accuracy land-cover maps using multi-source classification methods, most of which are based on data fusion, especially pixel- or feature-level fusions. A probabilistic graphical model (PGM) approach is proposed in this research for 30 m resolution land-cover mapping with multi-temporal Landsat and MODerate Resolution Imaging Spectroradiometer (MODIS) data. Independent classifiers were applied to two single-date Landsat 8 scenes and the MODIS time-series data, ...

  11. EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE

    Directory of Open Access Journals (Sweden)

    Symone Maria de Melo Figueiredo

    2006-03-01

    Full Text Available This study evaluated the accuracy of mapping land cover in Capixaba, state of Acre, Brazil, using decision trees. Elevenattributes were used to build the decision trees: TM Landsat datafrom bands 1, 2, 3, 4, 5, and 7; fraction images derived from linearspectral unmixing; and the normalized difference vegetation index (NDVI. The Kappa values were greater than 0,83, producingexcellent classification results and demonstrating that the technique is promising for mapping land cover in the study area.

  12. Elementary abelian regular coverings of Platonic maps, Case I: ordinary representations

    CERN Document Server

    Jones, Gareth A

    2012-01-01

    We classify the orientably regular maps which are elementary abelian regular branched coverings of Platonic maps M, in the case where the covering group and the rotation group G of M have coprime orders. The method involves studying the representations of G on certain homology groups of the sphere, punctured at the branch-points. We give a complete classification for branching over faces (or, dually, vertices) of M, and outline how the method extends to other branching patterns.

  13. Multitemporal Sentinel-1A Data for Urban Land Cover Mapping Using Deep Learning: Preliminary Results

    Science.gov (United States)

    McCutchan, Marvin; Ban, Yifang; Niu, Xin

    2016-08-01

    The objective of this research is to evaluate multitemporal Sentinel-1A SAR data for urban land cover mapping using a pixel-based Deep Belief Network (DBN) and an object-based post-processing. Multitemporal Sentinel-1A SAR in both ascending and descending orbits were acquired in Stockholm during the 2015 vegetation season. The images were first terrain corrected, co-registered, speckle filtered and scaled to 8 bit. Then the images were segmented using KTH-SEG, an edge- aware region growing and merging algorithm. For classification, a pixel-based deep belief network (DBN) was used. Then classification result was post-processed using object-based majority voting. For comparison, the same dataset was classified using an object-based support vector machine (SVM). The preliminary results show that the hybrid deep learning classification scheme produced comparable results as object-based SVM while yielded higher accuracies for builtup classes.

  14. Locally optimized separability enhancement indices for urban land cover mapping

    DEFF Research Database (Denmark)

    Feyisa, Gudina L.; Meilby, Henrik; Darrel Jenerette, G.

    2016-01-01

    Landsat data were used to assess urbanization-induced dynamics in Land use/cover (LULC), surface thermal intensity, and its relationships with urban biophysical composition. The study was undertaken in Addis Ababa city, Ethiopia. Ground-based data and high resolution images were used as reference...... data in LULC classification. To more accurately quantify landscape patterns and their changes, we applied new locally optimized separability enhancement indices and decision rules (SEI–DR approach) to address commonly observed classification accuracy problems in urban environments. We tested the SEI...... classification method, use of hotspot analysis, and the investigations of the UHI for an African city fill important research gaps for studies of urban thermal variation....

  15. An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

    Science.gov (United States)

    Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

    2015-12-01

    Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

  16. Global land cover map validation, comparison and integration for different user communities

    NARCIS (Netherlands)

    Tsendbazar, N.E.

    2016-01-01

    Global land cover map validation, comparison and integration for different user communities Abstract Observation of global-scale land cover is of importance to international initiatives, governments, and scientific communities that endeavour to understand and monito

  17. Sampling intensity and normalizations: Exploring cost-driving factors in nationwide mapping of tree canopy cover

    Science.gov (United States)

    John Tipton; Gretchen Moisen; Paul Patterson; Thomas A. Jackson; John Coulston

    2012-01-01

    There are many factors that will determine the final cost of modeling and mapping tree canopy cover nationwide. For example, applying a normalization process to Landsat data used in the models is important in standardizing reflectance values among scenes and eliminating visual seams in the final map product. However, normalization at the national scale is expensive and...

  18. Generation of Land Cover Maps Using High-Resolution Multispectral Aerial Cameras

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2013-01-01

    . The classification had an overall accuracy of 79%. Suggestions for the improvements in the applied methodology are made. The potential of land cover maps lies in updating of topographic databases, quality control of maps, studies of town development, and other geo-spatial domain applications. The automatic...

  19. Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

    Science.gov (United States)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

    2013-12-01

    US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

  20. Rapid Land Cover Map Updates Using Change Detection and Robust Random Forest Classifiers

    Directory of Open Access Journals (Sweden)

    Konrad J. Wessels

    2016-10-01

    Full Text Available The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and 2011 and Landsat ETM+ data for 2011. The entire system took 9.5 h to process. We expected that the use of the change mask would improve classification accuracy by reducing the number of mislabeled training data caused by land cover change between 2008 and 2011. However, this was not the case due to exceptional robustness of Random Forest classifier to mislabeled training samples. The system achieved an overall accuracy of 65%–67% using 22 detailed classes and 72%–74% using 12 aggregated national classes. “Water”, “Plantations”, “Plantations—clearfelled”, “Orchards—trees”, “Sugarcane”, “Built-up/dense settlement”, “Cultivation—Irrigated” and “Forest (indigenous” had user’s accuracies above 70%. Other detailed classes (e.g., “Low density settlements”, “Mines and Quarries”, and “Cultivation, subsistence, drylands” which are required for operational, provincial-scale land use planning and are usually mapped using manual image interpretation, could not be mapped using Landsat spectral data alone. However, the system was able to map the 12 national classes, at a sufficiently high level of accuracy for national scale land cover monitoring. This update approach and the highly automated, scalable LALCUM system can improve the efficiency and update rate of regional land

  1. A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

    Directory of Open Access Journals (Sweden)

    Jinwei Dong

    Full Text Available Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6 km(2 (GlobCover to 2.69×10(6 km(2 (MCD12Q1 in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR onboard the Advanced Land Observing Satellite (ALOS became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%. The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+ implementation, and

  2. A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

    Science.gov (United States)

    Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

    2014-01-01

    Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

  3. Land-cover mapping using multitemporal, dual-frequency polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Schou, Jesper; Dierking, Wolfgang

    2000-01-01

    The Danish Center for Remote Sensing (DCRS) is, in collaboration with the Danish mapping agency, conducting a study on topographic mapping using SAR data, and land cover mapping results are presented. The Danish EMISAR system (an L- and C-band, fully polarimetric, airborne SAR) have in 1994 to 19...... and coniferous forest types, wetlands, lakes, and urban areas. The data are used to study the classification potential of polarimetric SAR data using the Wishart distributed covariance matrix....

  4. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  5. MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

    Science.gov (United States)

    The accuracy of thematic map products is not spatially homogenous, but instead variable across most landscapes. Properly analyzing and representing the spatial distribution (pattern) of thematic map accuracy would provide valuable user information for assessing appropriate applic...

  6. On the reliability of manually produced bedrock lineament maps

    Science.gov (United States)

    Scheiber, Thomas; Viola, Giulio; Fredin, Ola; Jarna, Alexandra; Gasser, Deta; Łapinska-Viola, Renata

    2016-04-01

    Manual extraction of topographic features from digital elevation models (DEMs) is a commonly used technique to produce lineament maps of fractured basement areas. There are, however, several sources of bias which can influence the results. In this study we investigated the influence of the factors (a) scale, (b) illumination azimuth and (c) operator on remote sensing results by using a LiDAR (Light Detection and Ranging) DEM of a fractured bedrock terrain located in SW Norway. Six operators with different backgrounds in Earth sciences and remote sensing techniques mapped the same LiDAR DEM at three different scales and illuminated from three different directions. This resulted in a total of 54 lineament maps which were compared on the basis of number, length and orientation of the drawn lineaments. The maps show considerable output variability depending on the three investigated factors. In detail: (1) at larger scales, the number of lineaments drawn increases, the line lengths generally decrease, and the orientation variability increases; (2) Linear features oriented perpendicular to the source of illumination are preferentially enhanced; (3) The reproducibility among the different operators is generally poor. Each operator has a personal mapping style and his/her own perception of what is a lineament. Consequently, we question the reliability of manually produced bedrock lineament maps drawn by one person only and suggest the following approach: In every lineament mapping study it is important to define clear mapping goals and design the project accordingly. Care should be taken to find the appropriate mapping scale and to establish the ideal illumination azimuths so that important trends are not underrepresented. In a remote sensing project with several persons included, an agreement should be reached on a given common view on the data, which can be achieved by the mapping of a small test area. The operators should be aware of the human perception bias. Finally

  7. Object-Based Analysis of Aerial Photogrammetric Point Cloud and Spectral Data for Land Cover Mapping

    Science.gov (United States)

    Debella-Gilo, M.; Bjørkelo, K.; Breidenbach, J.; Rahlf, J.

    2013-04-01

    The acquisition of 3D point data with the use of both aerial laser scanning (ALS) and matching of aerial stereo images coupled with advances in image processing algorithms in the past years provide opportunities to map land cover types with better precision than before. The present study applies Object-Based Image Analysis (OBIA) to 3D point cloud data obtained from matching of stereo aerial images together with spectral data to map land cover types of the Nord-Trøndelag county of Norway. The multi-resolution segmentation algorithm of the Definiens eCognition™ software is used to segment the scenes into homogenous objects. The objects are then classified into different land cover types using rules created based on the definitions given for each land cover type by the Norwegian Forest and Landscape Institute. The quality of the land cover map was evaluated using data collected in the field as part of the Norwegian National Forest Inventory. The results show that the classification has an overall accuracy of about 80% and a kappa index of about 0.65. OBIA is found to be a suitable method for utilizing 3D remote sensing data for land cover mapping in an effort to replace manual delineation methods.

  8. Estimating Fractional Shrub Cover Using Simulated EnMAP Data: A Comparison of Three Machine Learning Regression Techniques

    Directory of Open Access Journals (Sweden)

    Marcel Schwieder

    2014-04-01

    Full Text Available Anthropogenic interventions in natural and semi-natural ecosystems often lead to substantial changes in their functioning and may ultimately threaten ecosystem service provision. It is, therefore, necessary to monitor these changes in order to understand their impacts and to support management decisions that help ensuring sustainability. Remote sensing has proven to be a valuable tool for these purposes, and especially hyperspectral sensors are expected to provide valuable data for quantitative characterization of land change processes. In this study, simulated EnMAP data were used for mapping shrub cover fractions along a gradient of shrub encroachment, in a study region in southern Portugal. We compared three machine learning regression techniques: Support Vector Regression (SVR; Random Forest Regression (RF; and Partial Least Squares Regression (PLSR. Additionally, we compared the influence of training sample size on the prediction performance. All techniques showed reasonably good results when trained with large samples, while SVR always outperformed the other algorithms. The best model was applied to produce a fractional shrub cover map for the whole study area. The predicted patterns revealed a gradient of shrub cover between regions affected by special agricultural management schemes for nature protection and areas without land use incentives. Our results highlight the value of EnMAP data in combination with machine learning regression techniques for monitoring gradual land change processes.

  9. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

    Science.gov (United States)

    Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.; Hamad, Amina; Venus, V.; Lymberakis, Petros

    2013-08-01

    The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R2 = 0.96), shrub cover (adj. R2 = 0.83), grass cover (adj. R2 = 0.71), bare soil (adj. R2 = 0.88), stone cover (adj. R2 = 0.83) and litter cover (adj. R2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land

  10. Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery

    Directory of Open Access Journals (Sweden)

    Yuanwei Qin

    2016-11-01

    Full Text Available Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS PALSAR Fine Beam Dual Polarization (FBD mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA, National Land Cover Database (NLCD, Oklahoma Ecological Systems Map (OKESM and Oklahoma Forest Resource Assessment (OKFRA, the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2, but much larger than those from JAXA (32,403 km2 and NLCD (37,628 km2. We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010 and gain (3630 km2, 9.0% in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be

  11. Land User and Land Cover Maps of Europe: a Webgis Platform

    Science.gov (United States)

    Brovelli, M. A.; Fahl, F. C.; Minghini, M.; Molinari, M. E.

    2016-06-01

    This paper presents the methods and implementation processes of a WebGIS platform designed to publish the available land use and land cover maps of Europe at continental scale. The system is built completely on open source infrastructure and open standards. The proposed architecture is based on a server-client model having GeoServer as the map server, Leaflet as the client-side mapping library and the Bootstrap framework at the core of the front-end user interface. The web user interface is designed to have typical features of a desktop GIS (e.g. activate/deactivate layers and order layers by drag and drop actions) and to show specific information on the activated layers (e.g. legend and simplified metadata). Users have the possibility to change the base map from a given list of map providers (e.g. OpenStreetMap and Microsoft Bing) and to control the opacity of each layer to facilitate the comparison with both other land cover layers and the underlying base map. In addition, users can add to the platform any custom layer available through a Web Map Service (WMS) and activate the visualization of photos from popular photo sharing services. This last functionality is provided in order to have a visual assessment of the available land coverages based on other user-generated contents available on the Internet. It is supposed to be a first step towards a calibration/validation service that will be made available in the future.

  12. Combining ENVISAT ASAR and MODIS data to enable improved snow cover maps

    OpenAIRE

    Mjøen, Håvard Uv

    2008-01-01

    Information about snow covered area is important for several purposes, and this information can be found by detecting reflection of optical waves using optical sensors or by using active radars such as SAR. This thesis is explaining how information from the measurements are used to make snow maps. Optival sensors cannot detect snow when the area is covered by clouds, and this is a problem in the melting season in Norway. Microwaves can penetrate clouds, and detect wet snow. I...

  13. Use of various remote sensing land cover products for PFT mapping over Siberia

    Directory of Open Access Journals (Sweden)

    C. Ottlé

    2013-06-01

    Full Text Available High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation. The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern

  14. Use of various remote sensing land cover products for PFT mapping over Siberia

    Science.gov (United States)

    Ottlé, C.; Lescure, J.; Maignan, F.; Poulter, B.; Wang, T.; Delbart, N.

    2013-06-01

    High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated

  15. Use of various remote sensing land cover products for plant functional type mapping over Siberia

    Science.gov (United States)

    Ottlé, C.; Lescure, J.; Maignan, F.; Poulter, B.; Wang, T.; Delbart, N.

    2013-11-01

    High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover

  16. Satellite Based Probabilistic Snow Cover Extent Mapping (SCE) at Hydro-Québec

    Science.gov (United States)

    Teasdale, Mylène; De Sève, Danielle; Angers, Jean-François; Perreault, Luc

    2016-04-01

    Over 40% of Canada's water resources are in Quebec and Hydro-Quebec has developed potential to become one of the largest producers of hydroelectricity in the world, with a total installed capacity of 36,643 MW. The Hydro-Québec fleet park includes 27 large reservoirs with a combined storage capacity of 176 TWh, and 668 dams and 98 controls. Thus, over 98% of all electricity used to supply the domestic market comes from water resources and the excess output is sold on the wholesale markets. In this perspective the efficient management of water resources is needed and it is based primarily on a good river flow estimation including appropriate hydrological data. Snow on ground is one of the significant variables representing 30% to 40% of its annual energy reserve. More specifically, information on snow cover extent (SCE) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in northern regions since the snowmelt provides the water that fills the reservoirs and is subsequently used for hydropower generation. For several years Hydro Quebec's research institute ( IREQ) developed several algorithms to map SCE and SWE. So far all the methods were deterministic. However, given the need to maximize the efficient use of all resources while ensuring reliability, the electrical systems must now be managed taking into account all risks. Since snow cover estimation is based on limited spatial information, it is important to quantify and handle its uncertainty in the hydrological forecasting system. This paper presents the first results of a probabilistic algorithm for mapping SCE by combining Bayesian mixture of probability distributions and multiple logistic regression models applied to passive microwave data. This approach allows assigning for each grid point, probabilities to the set of the mutually exclusive discrete outcomes: "snow" and "no snow". Its performance was evaluated using the Brier score since it is particularly appropriate to

  17. Sensitivity of land use change emission estimates to historical land use and land cover mapping

    Science.gov (United States)

    Peng, Shushi; Ciais, Philippe; Maignan, Fabienne; Li, Wei; Chang, Jinfeng; Wang, Tao; Yue, Chao

    2017-04-01

    The carbon emissions from land use and land cover change (ELUC) are an important anthropogenic component of the global carbon budget. Yet these emissions have a large uncertainty. Uncertainty in historical land use and land cover change (LULCC) maps and their implementation in global vegetation models is one of the key sources of the spread of ELUC calculated by global vegetation models. In this study, we used the Organizing Carbon and Hydrology in Dynamic Ecosystems terrestrial biosphere model to investigate how the different transition rules to define the priority of conversion from natural vegetation to agricultural land affect the historical reconstruction of plant functional types (PFTs) and ELUC. First, we reconstructed 10 sets of historical PFT maps using different transition rules and two methods. Then, we calculated ELUC from these 10 different historical PFT maps and an additional published PFT reconstruction, using the difference between two sets of simulations (with and without LULCC). The total area of forest loss is highly correlated with the total simulated ELUC (R2 = 0.83, P < 0.001) across the reconstructed PFT maps, which indicates that the choice of transition rules is a critical (and often overlooked) decision affecting the simulated ELUC. In addition to the choice of a transition rule, the initial land cover map and the reconstruction method for the reconstruction of historical PFT maps have an important impact on the resultant estimates of ELUC.

  18. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    Science.gov (United States)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  19. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  20. Vegetation Cover Mapping Based on Remote Sensing and Digital Elevation Model Data

    Science.gov (United States)

    Korets, M. A.; Ryzhkova, V. A.; Danilova, I. V.; Prokushkin, A. S.

    2016-06-01

    An algorithm of forest cover mapping based on combined GIS-based analysis of multi-band satellite imagery, digital elevation model, and ground truth data was developed. Using the classification principles and an approach of Russian forest scientist Kolesnikov, maps of forest types and forest growing conditions (FGC) were build. The first map is based on RS-composite classification, while the second map is constructed on the basis of DEM-composite classification. The spatial combination of this two layers were also used for extrapolation and mapping of ecosystem carbon stock values (kgC/m2). The proposed approach was applied for the test site area (~3600 km2), located in the Northern Siberia boreal forests of Evenkia near Tura settlement.

  1. Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

    Science.gov (United States)

    Ranson, K. J.; Montesano, P. M.; Nelson, R.

    2011-01-01

    The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

  2. NORMALIZED DIFFERENCE SNOW INDEX SIMULATION FOR SNOW-COVER MAPPING IN FOREST BY GEOSAIL MODEL

    Institute of Scientific and Technical Information of China (English)

    CAO Yun-gang; LIU Chuang

    2006-01-01

    The snow-cover mapping in forest area is always one of the difficult points for optical satellite remote sensing. To investigate reflectance variability and to improve the mapping of snow in forest area, GeoSail model was used to simulate the reflectance of a snow-covered forest. Using this model, the effects of varying canopy density, solar illumination and view geometry on the performance of the MODIS (Moderate-resolution Imaging Spectroradiometer)snow-cover mapping algorithm were investigated. The relationship between NDSI (Normalized Difference Snow Index), NDVI (Normalized Difference Vegetation Index) and snow fraction was discussed in detail. Results indicated that the weak performance would be achieved if fixed criteria were used for different regions especially in the complicated land cover components. Finally, some suggestions to MODIS SNOWMAP algorithm were put forward to improve snow mapping precision in forest area based on the simulation, for example, new criteria should be used in coniferous forest, that is, NDSI greater than 0.3 and NDVI greater than zero. Otherwise, a threshold on view zenith angle may be used in the criteria such as 45°.

  3. Using MERIS fused images for land-cover mapping vegetation status assessment in heterogeneous landscapes

    NARCIS (Netherlands)

    Zurita Milla, R.; Clevers, J.G.P.W.; Gijsel, J.A.E.; Schaepman, M.E.

    2011-01-01

    In this paper we evaluate the potential of ENVISAT–Medium Resolution Imaging Spectrometer (MERIS) fused images for land-cover mapping and vegetation status assessment in heterogeneous landscapes. A series of MERIS fused images (15 spectral bands; 25 m pixel size) is created using the linear mixing m

  4. Great Lakes Ice Cover Classification and Mapping Using Satellite Synthetic Aperture Radar (SAR) Data

    Science.gov (United States)

    Nghiem, S.; Leshkevich, G.; Kwok, R.

    1998-01-01

    Owing to the size and extent of the Great Lakes and the variety of ice types features found there, the timely and objective qualities inherent in computer processing of satellite data make it well suited for monitoring and mapping ice cover.

  5. Possibilities of MERIS for sub-pixel regional land cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Schaepman, M.E.; Clevers, J.G.P.W.

    2005-01-01

    The Medium Resolution Imaging Spectrometer, MERIS, on board of ENVISAT-1 fulfils the information gap between the current high and low spatial resolution sensors. In this respect, the use of MERIS full resolution data (300 m pixel size) has a great potential for regional and global land cover mapping

  6. LUSTERNIK-S CHNIRELMANN CATEGORY AND EMBEDDING FINITE COVERING MAPS, PRINCIPAL G-BUNDLES INTO BUNDLES

    Institute of Scientific and Technical Information of China (English)

    LIULUOFEI

    1996-01-01

    The author proves several embedding theorems for finite covering maps,principal G-bundies into bundles.The main results are 1. Let π:E→X be a finite covering map, and X a connected locally path-connected paracompact space. If cat X≤k, then the finite covering space π:E→X can be embedded into the trivial real k-plane bundle. 2. Let π:E→X be a principal G-bundle over a paracompact space. If there exists a linera action of Gon F(F=R or C)and cat X≤k ,then π:E→X can be embedded into ξ1 … ξn for any F-vector bundles ξi,i=1,…k.

  7. LAND-COVER DENSITY-BASED APPROACH TO URBAN LAND USE MAPPING USING HIGH-RESOLUTION IMAGERY

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiu-ying; FENG Xue-zhi; DENG Hui

    2005-01-01

    Nowadays, remote sensing imagery, especially with its high spatial resolution, has become an indispensable tool to provide timely up-gradation of urban land use and land cover information, which is a prerequisite for proper urban planning and management. The possible method described in the present paper to obtain urban land use types is based on the principle that land use can be derived from the land cover existing in a neighborhood. Here, moving window is used to represent the spatial pattern of land cover within a neighborhood and seven window sizes (61m×61 m,68m×68m, 75m×75m, 87m×87m, 99m×99m, 110m×110m and 121m×121m) are applied to determining the most proper window size. Then, the unsupervised method of ISODATA is employed to classify the layered land cover density maps obtained by the moving window. The results of accuracy evaluation show that the window size of 99m×99m is proper to infer urban land use categories and the proposed method has produced a land use map with a total accuracy of 85%.

  8. Mapping wind erosion hazard in Australia using MODIS-derived ground cover, soil moisture and climate data

    Science.gov (United States)

    Yang, X.; Leys, J.

    2014-03-01

    This paper describes spatial modeling methods to identify wind erosion hazard (WEH) areas across Australia using the recently available time-series products of satellite-derived ground cover, soil moisture and wind speed. We implemented the approach and data sets in a geographic information system to produce WEH maps for Australia at 500 m ground resolution on a monthly basis for the recent thirteen year period (2000-2012). These maps reveal the significant wind erosion hazard areas and their dynamic tendencies at paddock and regional scales. Dust measurements from the DustWatch network were used to validate the model and interpret the dust source areas. The modeled hazard areas and changes were compared with results from a rule-set approach and the Computational Environmental Management System (CEMSYS) model. The study demonstrates that the time series products of ground cover, soil moisture and wind speed can be jointly used to identify landscape erodibility and to map seasonal changes of wind erosion hazard across Australia. The time series wind erosion hazard maps provide detailed and useful information to assist in better targeting areas for investments and continuous monitoring, evaluation and reporting that will lead to reduced wind erosion and improved soil condition.

  9. Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

    Science.gov (United States)

    Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

    2016-06-01

    Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

  10. Land Cover of Northern Eurasia: Comparison and Assessment of Coarse Resolution Maps

    Science.gov (United States)

    Krankina, O. N.; Pflugmacher, D.; Cohen, W.; Kennedy, R.; Nelson, P.; Loboda, T.

    2007-12-01

    Consistent measurements of land cover are critical for addressing a range of important science questions, from quantifying the effects of vegetation on the carbon, energy, and water cycles, to understanding the social and economic causes and consequences of land-use and land-cover change. While multiple moderate and coarse- resolution land-cover products have been developed, they disagree significantly. Resolving discrepancies among maps is particularly challenging for boreal and temperate Northern Eurasia, where validation sites are sparse and processes of ecosystem disturbance and land-cover change are widespread. To identify specific needs and possibilities for improved mapping of land cover across boreal and temperate Northern Eurasia, we compared the performance of three recent land-cover products based on different sensors: MODIS (Global Land Cover Collection 4), AVHRR (DISCover v. 2.0), and SPOT VEGETATION (GLC2000 for Northern Eurasia v. 4.0). First, we examined the level of agreement among these data sets across the entire region. On a qualitative level, the assessment of general patterns indicates the highest degree of disagreement in transitional zones at the northern and southern fringes of boreal forest, in mountainous regions, and in areas of extensive wetlands, agricultural development, and urban land use. The quantitative analysis measured the level of disagreement between land-cover classes aggregated according to dominant type of vegetation (trees, shrubs, herbaceous, bare land, permanent snow/ice). Secondly, validation of these products was performed at two test sites where Landsat-based classifications were developed based on FAO Land Cover Classification System. Fractional land cover was calculated for each 1x1 km pixel and used to construct fractional error matrices. Most errors were associated with "mixed" coarse-resolution pixels (i.e. those having nearly equal percentage of multiple class types), while errors in "pure" (single class) pixels

  11. Evaluation of Bed Cover Properties Produced from Double Fabric Based on Honeycomb

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2015-01-01

    Full Text Available This research aims to innovate a new fabric structure, which could be used as a bed cover based on double honeycomb fabric with self-stitching. The honeycomb air pockets were aimed at facing each other to form closed small air chambers which work to sequester the air. The double fabric increases fabric thickness. Thus, the opportunity to improve thermal comfort could be achieved. A number of samples were produced with different densities and counts of weft yarn. Thermal insulation and water vapour permeability were measured and compared with bed covers produced from reversible weft backed structure. Geometrical properties, abrasion resistance, and air permeability were also measured. The results showed that the innovated structure had higher values of thermal insulation than reversible weft backed structure at certain weft counts and densities.

  12. Land cover change map comparisons using open source web mapping technologies

    Science.gov (United States)

    Erik Lindblom; Ian Housman; Tony Guay; Mark Finco; Kevin. Megown

    2015-01-01

    The USDA Forest Service is evaluating the status of current landscape change maps and assessing gaps in their information content. These activities have been occurring under the auspices of the Landscape Change Monitoring System (LCMS) project, which is a joint effort between USFS Research, USFS Remote Sensing Applications Center (RSAC), USGS Earth Resources...

  13. Land cover mapping in Latvia using hyperspectral airborne and simulated Sentinel-2 data

    Science.gov (United States)

    Jakovels, Dainis; Filipovs, Jevgenijs; Brauns, Agris; Taskovs, Juris; Erins, Gatis

    2016-08-01

    Land cover mapping in Latvia is performed as part of the Corine Land Cover (CLC) initiative every six years. The advantage of CLC is the creation of a standardized nomenclature and mapping protocol comparable across all European countries, thereby making it a valuable information source at the European level. However, low spatial resolution and accuracy, infrequent updates and expensive manual production has limited its use at the national level. As of now, there is no remote sensing based high resolution land cover and land use services designed specifically for Latvia which would account for the country's natural and land use specifics and end-user interests. The European Space Agency launched the Sentinel-2 satellite in 2015 aiming to provide continuity of free high resolution multispectral satellite data thereby presenting an opportunity to develop and adapted land cover and land use algorithm which accounts for national enduser needs. In this study, land cover mapping scheme according to national end-user needs was developed and tested in two pilot territories (Cesis and Burtnieki). Hyperspectral airborne data covering spectral range 400-2500 nm was acquired in summer 2015 using Airborne Surveillance and Environmental Monitoring System (ARSENAL). The gathered data was tested for land cover classification of seven general classes (urban/artificial, bare, forest, shrubland, agricultural/grassland, wetlands, water) and sub-classes specific for Latvia as well as simulation of Sentinel-2 satellite data. Hyperspectral data sets consist of 122 spectral bands in visible to near infrared spectral range (356-950 nm) and 100 bands in short wave infrared (950-2500 nm). Classification of land cover was tested separately for each sensor data and fused cross-sensor data. The best overall classification accuracy 84.2% and satisfactory classification accuracy (more than 80%) for 9 of 13 classes was obtained using Support Vector Machine (SVM) classifier with 109 band

  14. A Large-Area, Spatially Continuous Assessment of Land Cover Map Error and Its Impact on Downstream Analyses.

    Science.gov (United States)

    Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly

    2017-09-16

    Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess 1) the magnitude of error in several current generation land cover maps, and 2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g. at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g. with forest as adjacent cover, carbon map error was 200-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users

  15. Fractional Snow Cover Mapping from FY-2 VISSR Imagery of China

    Directory of Open Access Journals (Sweden)

    Gongxue Wang

    2017-09-01

    Full Text Available Daily fractional snow cover (FSC products derived from optical sensors onboard low Earth orbit (LEO satellites are often discontinuous, primarily due to prevalent cloud cover. To map the daily cloud-reduced FSC over China, we utilized clear-sky multichannel observations from the first-generation Chinese geostationary orbit (GEO satellites (namely, the FY-2 series by taking advantage of their high temporal resolution. The method proposed in this study combines a newly developed binary snow cover detection algorithm designed for the Visible and Infrared Spin Scan Radiometer (VISSR onboard FY-2F with a simple linear spectral mixture technique applied to the visible (VIS band. This method relies upon full snow cover and snow-free end-members to estimate the daily FSC. The FY-2E/F VISSR FSC maps of China were compared with the Moderate Resolution Imaging Spectroradiometer (MODIS FSC data based on the multiple end-member spectral mixture analysis (MESMA, and with Landsat-8 Operational Land Imager (OLI FSC maps based on the SNOWMAP approach. The FY-2E/F VISSR FSC maps, which demonstrate a lower cloud coverage, exhibit the root mean squared errors (RMSEs of 0.20/0.19 compared with the MODIS FSC data. When validated against the Landsat-8 OLI FSC data, the FY-2E/F VISSR FSC maps, which display overall accuracies that can reach 0.92, have an RMSE of 0.18~0.29 with R2 values ranging from 0.46 to 0.80.

  16. Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

    Science.gov (United States)

    Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

    2016-06-01

    This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

  17. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    Science.gov (United States)

    Ban, Yifang; Gong, Peng; Giri, Chandra

    2015-05-01

    Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

  18. a Study on Producing Highly Reliabile Reference Data Sets for Global Land Cover Validation

    Science.gov (United States)

    Soyama, N.; Muramatsu, K.; Daigo, M.; Ochiai, F.; Fujiwara, N.

    2016-06-01

    Validating the accuracy of land cover products using a reliable reference dataset is an important task. A reliable reference dataset is produced with information derived from ground truth data. Recently, the amount of ground truth data derived from information collected by volunteers has been increasing globally. The acquisition of volunteer-based reference data demonstrates great potential. However information given by volunteers is limited useful vegetation information to produce a complete reference dataset based on the plant functional type (PFT) with five specialized forest classes. In this study, we examined the availability and applicability of FLUXNET information to produce reference data with higher levels of reliability. FLUXNET information was useful especially for forest classes for interpretation in comparison with the reference dataset using information given by volunteers.

  19. Accuracy assessment for the U.S. Geological Survey Regional Land-Cover Mapping Program: New York and New Jersey Region

    Science.gov (United States)

    Zhiliang Zhu; Limin Yang; Stephen V. Stehman; Raymond L. Czaplewski

    2000-01-01

    The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific...

  20. Evaluating the Quality of Predictive Geological Maps Produced using Self-Organizing Maps

    Science.gov (United States)

    Carter-McAuslan, Angela; Farquharson, Colin

    2016-04-01

    With increased data collection, extraction of useful information from large, often multi-dimensional (where each dimension is a unique data-type), datasets becomes a challenge. Associated with the problem of extracting usable information is the need to evaluate the information extracted to determine its validity. Traditionally, geophysical data has been interpreted in map or profile form one data-type at a time using primarily visual inspection by the interpreter. This approach become increasingly difficult as the dimensionality (e.g. number of data-types) of the dataset is increased. As such, new methods for discovering patterns in multi-dimensional geophysical datasets need to be investigated. Self-organizing maps (SOMs) are a class of unsupervised artificial neural network algorithm which are used to cluster multi-dimensional data while preserving the overall topology of the original dataset. As geophysical responses measured in the field are closely linked to the local geology it is postulated that SOMs can be employed to cluster multi-dimensional geophysical data in order to produce predictive geological maps. In the development of an effective work flow for creating predictive geological maps using SOMs, synthetic and real world test cases are used so that the predictive maps can be compared to a known geology. This comparison can be done through visual inspection. However, quantitative measures of clustering quality are also desired. In this project three different types of cluster quality measures are investigated: cluster morphology measures (e.g. the Quantization Error and the Dunn Index); class/cluster concatenation measures (e.g. Cluster Purity and Normalized Mutual Information); and decision-based measures (e.g. the Rand Index and F-Measure). SOM predictive mapping was applied to mapping the Baie Verte Peninsula on the north coast of the island of Newfoundland, Canada. The Baie Verte Peninsula is a region of complex geology with good regional

  1. Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

    Science.gov (United States)

    Akyurek, Z.; Kuter, S.; Weber, G. W.

    2016-12-01

    Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model

  2. A fractional snow cover mapping method for optical remote sensing data, applicable to continental scale

    OpenAIRE

    2013-01-01

    This thesis focuses on the determination of fractional snow cover (FSC) from optical data provided by satellite instruments. It describes the method development, starting from a simple regionally applicable linear interpolation method and ending at a globally applicable, semi-empirical modeling approach. The development work was motivated by the need for an easily implementable and feasible snow mapping method that could provide reliable information particularly for forested areas. The con...

  3. A fractional snow cover mapping method for optical remote sensing data, applicable to continental scale

    OpenAIRE

    2013-01-01

    This thesis focuses on the determination of fractional snow cover (FSC) from optical data provided by satellite instruments. It describes the method development, starting from a simple regionally applicable linear interpolation method and ending at a globally applicable, semi-empirical modeling approach. The development work was motivated by the need for an easily implementable and feasible snow mapping method that could provide reliable information particularly for forested areas. The co...

  4. A spatial-temporal Hopfield neural network approach for super-resolution land cover mapping with multi-temporal different resolution remotely sensed images

    Science.gov (United States)

    Li, Xiaodong; Ling, Feng; Du, Yun; Feng, Qi; Zhang, Yihang

    2014-07-01

    The mixed pixel problem affects the extraction of land cover information from remotely sensed images. Super-resolution mapping (SRM) can produce land cover maps with a finer spatial resolution than the remotely sensed images, and reduce the mixed pixel problem to some extent. Traditional SRMs solely adopt a single coarse-resolution image as input. Uncertainty always exists in resultant fine-resolution land cover maps, due to the lack of information about detailed land cover spatial patterns. The development of remote sensing technology has enabled the storage of a great amount of fine spatial resolution remotely sensed images. These data can provide fine-resolution land cover spatial information and are promising in reducing the SRM uncertainty. This paper presents a spatial-temporal Hopfield neural network (STHNN) based SRM, by employing both a current coarse-resolution image and a previous fine-resolution land cover map as input. STHNN considers the spatial information, as well as the temporal information of sub-pixel pairs by distinguishing the unchanged, decreased and increased land cover fractions in each coarse-resolution pixel, and uses different rules in labeling these sub-pixels. The proposed STHNN method was tested using synthetic images with different class fraction errors and real Landsat images, by comparing with pixel-based classification method and several popular SRM methods including pixel-swapping algorithm, Hopfield neural network based method and sub-pixel land cover change mapping method. Results show that STHNN outperforms pixel-based classification method, pixel-swapping algorithm and Hopfield neural network based model in most cases. The weight parameters of different STHNN spatial constraints, temporal constraints and fraction constraint have important functions in the STHNN performance. The heterogeneity degree of the previous map and the fraction images errors affect the STHNN accuracy, and can be served as guidances of selecting the

  5. Very High Resolution Mapping of Tree Cover Using Scalable Deep Learning Architectures

    Science.gov (United States)

    ganguly, sangram; basu, saikat; nemani, ramakrishna; mukhopadhyay, supratik; michaelis, andrew; votava, petr; saatchi, sassan

    2016-04-01

    Several studies to date have provided an extensive knowledge base for estimating forest aboveground biomass (AGB) and recent advances in space-based modeling of the 3-D canopy structure, combined with canopy reflectance measured by passive optical sensors and radar backscatter, are providing improved satellite-derived AGB density mapping for large scale carbon monitoring applications. A key limitation in forest AGB estimation from remote sensing, however, is the large uncertainty in forest cover estimates from the coarse-to-medium resolution satellite-derived land cover maps (present resolution is limited to 30-m of the USGS NLCD Program). As part of our NASA Carbon Monitoring System Phase II activities, we have demonstrated that uncertainties in forest cover estimates at the Landsat scale result in high uncertainties in AGB estimation, predominantly in heterogeneous forest and urban landscapes. We have successfully tested an approach using scalable deep learning architectures (Feature-enhanced Deep Belief Networks and Semantic Segmentation using Convolutional Neural Networks) and High-Performance Computing with NAIP air-borne imagery data for mapping tree cover at 1-m over California and Maryland. Our first high resolution satellite training label dataset from the NAIP data can be found here at http://csc.lsu.edu/~saikat/deepsat/ . In a comparison with high resolution LiDAR data available over selected regions in the two states, we found our results to be promising both in terms of accuracy as well as our ability to scale nationally. In this project, we propose to estimate very high resolution forest cover for the continental US at spatial resolution of 1-m in support of reducing uncertainties in the AGB estimation. The proposed work will substantially contribute to filling the gaps in ongoing carbon monitoring research and help quantifying the errors and uncertainties in related carbon products.

  6. Snow Cover Maps from MODIS Images at 250 m Resolution, Part 2: Validation

    Directory of Open Access Journals (Sweden)

    Marc Zebisch

    2013-03-01

    Full Text Available The performance of a new algorithm for binary snow cover monitoring based on Moderate Resolution Imaging Spectroradiometer (MODIS satellite images at 250 m resolution is validated using snow cover maps (SCA based on Landsat 7 ETM+ images and in situ snow depth measurements from ground stations in selected test sites in Central Europe. The advantages of the proposed algorithm are the improved ground resolution of 250 m and the near real-time availability with respect to the 500 m standard National Aeronautics and Space Administration (NASA MODIS snow products (MOD10 and MYD10. It allows a more accurate snow cover monitoring at a local scale, especially in mountainous areas characterized by large landscape heterogeneity. The near real-time delivery makes the product valuable as input for hydrological models, e.g., for flood forecast. A comparison to sixteen snow cover maps derived from Landsat ETM/ETM+ showed an overall accuracy of 88.1%, which increases to 93.6% in areas outside of forests. A comparison of the SCA derived from the proposed algorithm with standard MODIS products, MYD10 and MOD10, indicates an agreement of around 85.4% with major discrepancies in forested areas. The validation of MODIS snow cover maps with 148 in situ snow depth measurements shows an accuracy ranging from 94% to around 82%, where the lowest accuracies is found in very rugged terrain restricted to in situ stations along north facing slopes, which lie in shadow in winter during the early morning acquisition.

  7. Land Cover Mapping in Southwestern China Using the HC-MMK Approach

    Directory of Open Access Journals (Sweden)

    Guangbin Lei

    2016-04-01

    Full Text Available Land cover mapping in mountainous areas is a notoriously challenging task due to the rugged terrain and high spatial heterogeneity of land surfaces as well as the frequent cloud contamination of satellite imagery. Taking Southwestern China (a typical mountainous region as an example, this paper established a new HC-MMK approach (Hierarchical Classification based on Multi-source and Multi-temporal data and geo-Knowledge, which was especially designed for land cover mapping in mountainous areas. This approach was taken in order to generate a 30 m-resolution land cover product in Southwestern China in 2010 (hereinafter referred to as CLC-SW2010. The multi-temporal native HJ (HuanJing, small satellite constellation for disaster and environmental monitoring CCD (Charge-Coupled Device images, Landsat TM (Thematic Mapper images and topographical data (including elevation, aspect, slope, etc. were taken as the main input data sources. Hierarchical classification tree construction and a five-step knowledge-based interactive quality control were the major components of this proposed approach. The CLC-SW2010 product contained six primary categories and 38 secondary categories, which covered about 2.33 million km2 (accounting for about a quarter of the land area of China. The accuracies of primary and secondary categories for CLC-SW2010 reached 95.09% and 87.14%, respectively, which were assessed independently by a third-party group. This product has so far been used to estimate the terrestrial carbon stocks and assess the quality of the ecological environments. The proposed HC-MMK approach could be used not only in mountainous areas, but also for plains, hills and other regions. Meanwhile, this study could also be used as a reference for other land cover mapping projects over large areas or even the entire globe.

  8. Mapping Rural Areas with Widespread Plastic Covered Vineyards Using True Color Aerial Data

    Directory of Open Access Journals (Sweden)

    Eufemia Tarantino

    2012-06-01

    Full Text Available Plastic covering is used worldwide to protect crops against damaging growing conditions. This agricultural practice raises some controversial issues. While it significantly impacts on local economic vitality, plasticulture also shows several environmental affects. In the Apulia Region (Italy the wide-spreading of artificial plastic coverings for vineyard protection has showed negative consequences on the hydrogeological balance of soils as well as on the visual quality of rural landscape. In order to monitor and manage this phenomenon, a detailed site mapping has become essential. In this study an efficient object-based classification procedure from Very High Spatial Resolution (VHSR true color aerial data was developed on eight test areas located in the Ionian area of the Apulia Region in order to support the updating of the existing land use database aimed at plastic covered vineyard monitoring.

  9. The potential of more accurate InSAR covariance matrix estimation for land cover mapping

    Science.gov (United States)

    Jiang, Mi; Yong, Bin; Tian, Xin; Malhotra, Rakesh; Hu, Rui; Li, Zhiwei; Yu, Zhongbo; Zhang, Xinxin

    2017-04-01

    Synthetic aperture radar (SAR) and Interferometric SAR (InSAR) provide both structural and electromagnetic information for the ground surface and therefore have been widely used for land cover classification. However, relatively few studies have developed analyses that investigate SAR datasets over richly textured areas where heterogeneous land covers exist and intermingle over short distances. One of main difficulties is that the shapes of the structures in a SAR image cannot be represented in detail as mixed pixels are likely to occur when conventional InSAR parameter estimation methods are used. To solve this problem and further extend previous research into remote monitoring of urban environments, we address the use of accurate InSAR covariance matrix estimation to improve the accuracy of land cover mapping. The standard and updated methods were tested using the HH-polarization TerraSAR-X dataset and compared with each other using the random forest classifier. A detailed accuracy assessment complied for six types of surfaces shows that the updated method outperforms the standard approach by around 9%, with an overall accuracy of 82.46% over areas with rich texture in Zhuhai, China. This paper demonstrates that the accuracy of land cover mapping can benefit from the 3 enhancement of the quality of the observations in addition to classifiers selection and multi-source data ingratiation reported in previous studies.

  10. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  11. High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

    Science.gov (United States)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.

    2012-12-01

    The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

  12. Land cover/use mapping using multi-band imageries captured by Cropcam Unmanned Aerial Vehicle Autopilot (UAV) over Penang Island, Malaysia

    Science.gov (United States)

    Fuyi, Tan; Boon Chun, Beh; Mat Jafri, Mohd Zubir; Hwee San, Lim; Abdullah, Khiruddin; Mohammad Tahrin, Norhaslinda

    2012-11-01

    The problem of difficulty in obtaining cloud-free scene at the Equatorial region from satellite platforms can be overcome by using airborne imagery. Airborne digital imagery has proved to be an effective tool for land cover studies. Airborne digital camera imageries were selected in this present study because of the airborne digital image provides higher spatial resolution data for mapping a small study area. The main objective of this study is to classify the RGB bands imageries taken from a low-altitude Cropcam UAV for land cover/use mapping over USM campus, penang Island, Malaysia. A conventional digital camera was used to capture images from an elevation of 320 meter on board on an UAV autopilot. This technique was cheaper and economical compared with other airborne studies. The artificial neural network (NN) and maximum likelihood classifier (MLC) were used to classify the digital imageries captured by using Cropcam UAV over USM campus, Penang Islands, Malaysia. The supervised classifier was chosen based on the highest overall accuracy (statistic (<0.8). The classified land cover map was geometrically corrected to provide a geocoded map. The results produced by this study indicated that land cover features could be clearly identified and classified into a land cover map. This study indicates the use of a conventional digital camera as a sensor on board on an UAV autopilot can provide useful information for planning and development of a small area of coverage.

  13. Tree Canopy Cover Mapping Using LiDAR in Urban Barangays of Cebu City, Central Philippines

    Science.gov (United States)

    Ejares, J. A.; Violanda, R. R.; Diola, A. G.; Dy, D. T.; Otadoy, J. B.; Otadoy, R. E. S.

    2016-06-01

    This paper investigates tree canopy cover mapping of urban barangays (smallest administrative division in the Philippines) in Cebu City using LiDAR (Light Detection and Ranging). Object-Based Image Analysis (OBIA) was used to extract tree canopy cover. Multi-resolution segmentation and a series of assign-class algorithm in eCognition software was also performed to extract different land features. Contextual features of tree canopies such as height, area, roundness, slope, length-width and elliptic fit were also evaluated. The results showed that at the time the LiDAR data was collected (June 24, 2014), the tree cover was around 25.11 % (or 15,674,341.8 m2) of the city's urban barangays (or 62,426,064.6 m2). Among all urban barangays in Cebu City, Barangay Busay had the highest cover (55.79 %) while barangay Suba had the lowest (0.8 %). The 16 barangays with less than 10 % tree cover were generally located in the coastal area, presumably due to accelerated urbanization. Thirty-one barangays have tree cover ranging from 10.59--27.3 %. Only 3 barangays (i.e., Lahug, Talamban, and Busay) have tree cover greater than 30 %. The overall accuracy of the analysis was 96.6 % with the Kappa Index of Agreement or KIA of 0.9. From the study, a grouping can be made of the city's urban barangays with regards to tree cover. The grouping will be useful to urban planners not only in allocating budget to the tree planting program of the city but also in planning and creation of urban parks and playgrounds.

  14. Accuracy assessment of global land cover maps: lessons learnt from the GlobCover and GlobCorine experiences

    NARCIS (Netherlands)

    Defourny, P.; Bontemps, S.; Obsomer, V.; Schouten, L.; Bartalev, S.; Herold, M.; Bicheron, P.; Bogaert, van E.; Leroy, M.; Arino, O.

    2010-01-01

    The validation of global land cover products becomes a critical and challenging issue as more global products are made available more regularly to the international community. The GlobCover 2005 product delivered in 2008 was the first global land cover product at 300 m resolution. Later on, the

  15. Crop Ground Cover Fraction and Canopy Chlorophyll Content Mapping using RapidEye imagery

    Science.gov (United States)

    Zillmann, E.; Schonert, M.; Lilienthal, H.; Siegmann, B.; Jarmer, T.; Rosso, P.; Weichelt, T.

    2015-04-01

    Remote sensing is a suitable tool for estimating the spatial variability of crop canopy characteristics, such as canopy chlorophyll content (CCC) and green ground cover (GGC%), which are often used for crop productivity analysis and site-specific crop management. Empirical relationships exist between different vegetation indices (VI) and CCC and GGC% that allow spatial estimation of canopy characteristics from remote sensing imagery. However, the use of VIs is not suitable for an operational production of CCC and GGC% maps due to the limited transferability of derived empirical relationships to other regions. Thus, the operational value of crop status maps derived from remotely sensed data would be much higher if there was no need for reparametrization of the approach for different situations. This paper reports on the suitability of high-resolution RapidEye data for estimating crop development status of winter wheat over the growing season, and demonstrates two different approaches for mapping CCC and GGC%, which do not rely on empirical relationships. The final CCC map represents relative differences in CCC, which can be quickly calibrated to field specific conditions using SPAD chlorophyll meter readings at a few points. The prediction model is capable of predicting SPAD readings with an average accuracy of 77%. The GGC% map provides absolute values at any point in the field. A high R2 value of 80% was obtained for the relationship between estimated and observed GGC%. The mean absolute error for each of the two acquisition dates was 5.3% and 8.7%, respectively.

  16. Chemical composition of overland flow produced on soils covered with vegetative ash

    Directory of Open Access Journals (Sweden)

    M.B. Bodí

    2013-05-01

    Full Text Available The objective of this study was to ascertain the differences between the soluble elements of ash obtained under laboratory conditions and the dissolved in overland flow from soils covered with a layer of ash. The overland flow was obtained during series of rainfall simulations over soils covered with two different types of ash. This study indicates that the soluble elements released from ash can modify water quality increasing its pH, electrical conductivity and especially cation content. The nutrients solubilised are not necessarily the same as the elemental composition of ash itself. Runoff composition depends on the volume of water produced, on the solubility of the ash components and on the chemical interactions with water from rainfall and soil. After the first intense rain event, most of the elements are solubilised and lixiviated or washed out, however, some of them may increase in the runoff or soil water some weeks later due to chemical interactions with water from rainfall and soil nutrients.

  17. Global land cover mapping at 30 m resolution: A POK-based operational approach

    Science.gov (United States)

    Chen, Jun; Chen, Jin; Liao, Anping; Cao, Xin; Chen, Lijun; Chen, Xuehong; He, Chaoying; Han, Gang; Peng, Shu; Lu, Miao; Zhang, Weiwei; Tong, Xiaohua; Mills, Jon

    2015-05-01

    Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products. Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. To handle the classification process of 10 land cover types, a split-and-merge strategy was employed, i.e. firstly each class identified in a prioritized sequence and then results are merged together. For the identification of each class, a robust integration of pixel-and object-based classification was developed. To improve the quality of the classification results, a knowledge-based interactive verification procedure was developed with the support of web service technology. The performance of the POK-based approach was tested using eight selected areas with differing landscapes from five different continents. An overall classification accuracy of over 80% was achieved. This indicates that the developed POK-based approach is effective and feasible

  18. Multiple support vector machines for land cover change detection: An application for mapping urban extensions

    Science.gov (United States)

    Nemmour, Hassiba; Chibani, Youcef

    The reliability of support vector machines for classifying hyper-spectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for land cover change detection. First, SVM-based change detection is presented and performed for mapping urban growth in the Algerian capital. Different performance indicators, as well as a comparison with artificial neural networks, are used to support our experimental analysis. In a second step, a combination framework is proposed to improve change detection accuracy. Two combination rules, namely, Fuzzy Integral and Attractor Dynamics, are implemented and evaluated with respect to individual SVMs. Recognition rates achieved by individual SVMs, compared to neural networks, confirm their efficiency for land cover change detection. Furthermore, the relevance of SVM combination is highlighted.

  19. The effect of Thematic Mapper spectral properties on land cover mapping for hydrologic modeling

    Science.gov (United States)

    Gervin, J. C.; Lu, Y. C.; Gauthier, R. L.; Miller, J. R.; Irish, R. R.

    1986-01-01

    The accuracy of unsupervised land-cover classification from all seven Landsat TM bands and from six combinations of three or four bands is evaluated using images of the Clinton River Basin, a suburban watershed near Detroit. Data from aerial TMS photography, USGS topographic maps, and ground surveys are employed to determine the classification accuracy. The mapping accuracy of all seven bands is found to be significantly better (6 percent overall, 12 percent for residential areas, and 13 percent for commercial districts) than that with bands 2, 3, and 4; but almost the same accuracy is obtained by including at least one band from each major spectral region (visible, NIR, and mid-IR).

  20. Assessment of dynamic probabilistic methods for mapping snow cover in Québec Canada

    Science.gov (United States)

    De Seve, D.; Perreault, L.; Vachon, F.; Guay, F.; choquette, Y.

    2012-04-01

    Hydro-Quebec is the leader in electricity production in North America and uses hydraulic resources to generate 97% of its overall production where snow represents 30% of its annual energy reserve. Information on snow cover extent (SC) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in Nordic regions where a majority of total precipitations falls as snow. Accurate estimation of the spatial distribution of snow cover variables is required to measure the extent of this resource but snow surveys are expensive due to inaccessibility factors and to the large extent nature of the Quebec geography. Consequently, the follow-up of snowmelt is particularly challenging for operational forecasting resulting in the need to develop a new approach to assist forecasters. For improved understanding of the dynamics of snow melting over watersheds and to generate optimized power production, Hydro-Québec's Research Institute (IREQ) has developed expertise in in-situ, remote sensing monitoring and statistical treatment of such data. The main goal of this Hydro-Quebec project is to develop an automatic and dynamic snow mapping system providing a daily snow map by merging remote sensing (AVHRR and SSMI) and in situ data. This paper focuses on the work accomplished on passive microwave SSM/I data to follow up snow cover. In our problematic, it is highly useful to classify snow, more specifically during the snowmelt period. The challenge is to be able to discriminate ground from wet snow as it will react as a black body, therefore, adding noise to global brightness temperature. Two dynamic snow classifiers were developed and tested. For this purpose, channels at 19 and 37 GHz in vertical polarization have been used to feed each model. SWE values from gamma ray in situ stations (GMON) and data snow depth from ultrasonic sensor (SR50) were used to validate the output models. The first algorithm is based on a standard K-mean clustering approach, combined

  1. GAP Land Cover - Image

    Data.gov (United States)

    Minnesota Department of Natural Resources — This raster dataset is a simple image of the original detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of...

  2. GAP Land Cover - Vector

    Data.gov (United States)

    Minnesota Department of Natural Resources — This vector dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of...

  3. Estimation of agricultural pesticide use in drainage basins using land cover maps and county pesticide data

    Science.gov (United States)

    Nakagaki, Naomi; Wolock, David M.

    2005-01-01

    A geographic information system (GIS) was used to estimate agricultural pesticide use in the drainage basins of streams that are studied as part of the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program. Drainage basin pesticide use estimates were computed by intersecting digital maps of drainage basin boundaries with an enhanced version of the National Land Cover Data 1992 combined with estimates of 1992 agricultural pesticide use in each United States county. This report presents the methods used to quantify agricultural pesticide use in drainage basins using a GIS and includes the estimates of atrazine use applied to row crops, small-grain crops, and fallow lands in 150 watersheds in the conterminous United States. Basin atrazine use estimates are presented to compare and analyze the results that were derived from 30-meter and 1-kilometer resolution land cover and county pesticide use data, and drainage basin boundaries at various grid cell resolutions. Comparisons of the basin atrazine use estimates derived from watershed boundaries, county pesticide use, and land cover data sets at different resolutions, indicated that overall differences were minor. The largest potential for differences in basin pesticide use estimates between those derived from the 30-meter and 1-kilometer resolution enhanced National Land Cover Data 1992 exists wherever there are abrupt agricultural land cover changes along the basin divide. Despite the limitations of the drainage basin pesticide use data described in this report, the basin estimates provide consistent and comparable indicators of agricultural pesticide application in surface-water drainage basins studied in the NAWQA Program.

  4. A GIS Software Toolkit for Monitoring Areal Snow Cover and Producing Daily Hydrologic Forecasts using NASA Satellite Imagery Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Aniuk Consulting, LLC, proposes to create a GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts. This toolkit will be...

  5. Mapping dominant annual land cover from 2009 to 2013 across Victoria, Australia using satellite imagery

    Science.gov (United States)

    Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden

    2015-01-01

    There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications. PMID:26602009

  6. Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data.

    Science.gov (United States)

    Fallati, Luca; Savini, Alessandra; Sterlacchini, Simone; Galli, Paolo

    2017-08-01

    The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe's WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product's overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.

  7. Multitemporal RADARSAT-2 polarimetric SAR data for urban land-cover mapping

    Science.gov (United States)

    Gao, Liang; Ban, Yifang

    2010-11-01

    The objective of this research is to evaluate the performance of multitemporal RADARSAT-2 polarimetric SAR data for urban land use/land-cover classification. Three dates of RADARSAT-2 polarimetric SAR data were acquired during the summer of 2008 over the rural-urban fringe of the Greater Toronto Area. The major land-cover types are residential areas, industry areas, bare land, golf courses, forest, and agricultural crops. The methodology used in this study follow the manner that first extracting the features and then carrying out the supervised classification taking the different feature combinations as an input. Support vectors machine is selected to be the classifier. SAR features including amplitude, intensity, long-term coherence, Freeman-Durden decomposition are extracted and compared by evaluating the classification abilities. Long-term coherence plays an important role in building discrimination in this study. The best classification results achieved by using the three dates HH, VH, HV amplitude layers and the coherence map. The overall accuracy is 82.3%. The results indicate that RADARSAT-2 polarimetric data has a potential to urban land-cover classification with the proper feature combinations.

  8. Multitemporal unmixing of medium-spatial-resolution satellite images: A case study using MERIS images for land-cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Gómez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Champs-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this

  9. Multitemporal unmixing of medium-spatial-resolution satellite images: a case study using MERIS images for land - cover mapping

    NARCIS (Netherlands)

    Zurita-Milla, R.; Gomez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Camps-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this

  10. Multitemporal unmixing of medium-spatial-resolution satellite images: A case study using MERIS images for land-cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Gómez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Champs-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this stud

  11. The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

    Science.gov (United States)

    Hogan, Christine A.

    1996-01-01

    A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

  12. Analysis for Producing a Facsimile of the Cadastral Map of Varaždin

    Directory of Open Access Journals (Sweden)

    Mirko Husak

    2012-12-01

    Full Text Available This paper investigates and suggests methods for producing a facsimile of the 1 860 cadastral map of Varaždin. The methods used to produce the map, the coordinate systems, map contents, usage, maintenance and damage are described. Three samples from the map that display the elements of damage noted were researched, and the possibility of replacing damaged sections with undamaged sections using digital methods investigated. The sources available were the original cadastral colour map of Varaždin, along with the line art cadastral map and field cadastral sketches. The original colour and line art maps were scanned using the DeSkan Express scanning system for large formats. A flatbed UMAX Mirage II A3 scanner was used for scanning the field cadastral map. For the research image-processing, Adobe Photoshop CE 7.0 software was used, although it was primarily designed for processing photographs. The colour separation method was rejected from the start, since the map was made by hand. The paper discusses the possibility of copying and inserting missing parts from additional map sources, changing the colour of the paper to white or another colour, removing the map content added in red ink and lead pencil, and so on. The discussion is based on actual examples from the digital image. The conclusion suggests image-processing methods for achieving optimal results in producing a facsimile of the Varaždin cadastral map.Keywords: facsimile; cadastral map; map content; scanning; digital image processing

  13. Mapping tsunami impacts on land cover and related ecosystem service supply in Phang Nga, Thailand

    Science.gov (United States)

    Kaiser, G.; Burkhard, B.; Römer, H.; Sangkaew, S.; Graterol, R.; Haitook, T.; Sterr, H.; Sakuna-Schwartz, D.

    2013-12-01

    The 2004 Indian Ocean tsunami caused damages to coastal ecosystems and thus affected the livelihoods of the coastal communities who depend on services provided by these ecosystems. The paper presents a case study on evaluating and mapping the spatial and temporal impacts of the tsunami on land use and land cover (LULC) and related ecosystem service supply in the Phang Nga province, Thailand. The method includes local stakeholder interviews, field investigations, remote-sensing techniques, and GIS. Results provide an ecosystem services matrix with capacity scores for 18 LULC classes and 17 ecosystem functions and services as well as pre-/post-tsunami and recovery maps indicating changes in the ecosystem service supply capacities in the study area. Local stakeholder interviews revealed that mangroves, casuarina forest, mixed beach forest, coral reefs, tidal inlets, as well as wetlands (peat swamp forest) have the highest capacity to supply ecosystem services, while e.g. plantations have a lower capacity. The remote-sensing based damage and recovery analysis showed a loss of the ecosystem service supply capacities in almost all LULC classes for most of the services due to the tsunami. A fast recovery of LULC and related ecosystem service supply capacities within one year could be observed for e.g. beaches, while mangroves or casuarina forest needed several years to recover. Applying multi-temporal mapping the spatial variations of recovery could be visualised. While some patches of coastal forest were fully recovered after 3 yr, other patches were still affected and thus had a reduced capacity to supply ecosystem services. The ecosystem services maps can be used to quantify ecological values and their spatial distribution in the framework of a tsunami risk assessment. Beyond that they are considered to be a useful tool for spatial analysis in coastal risk management in Phang Nga.

  14. Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

    Directory of Open Access Journals (Sweden)

    Dongyang Hou

    2016-06-01

    Full Text Available Automatic discovery of isolated land cover web map services (LCWMSs can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler

  15. Energy potential mapping for energy-producing neighborhoods

    NARCIS (Netherlands)

    Dobbelsteen, van den A.; Broersma, S.; Stremke, S.

    2011-01-01

    Over the past five years, the method of energy potential mapping (EPM) has evolved from a cartoonish charting of climatic features with energy consequences to a detailed methodology for the development of spatial plans based on energy-effective foundations. By means of EPM the rudimentary features

  16. Fish on avian lampbrush chromosomes produces higher resolution gene mapping

    NARCIS (Netherlands)

    Galkina, S.A.; Deryusheva, S.; Fillon, V.; Vignal, A.; Crooijmans, R.P.M.A.; Groenen, M.A.M.; Rodionov, A.V.; Gaginskaya, E.

    2006-01-01

    Giant lampbrush chromosomes, which are characteristic of the diplotene stage of prophase I during avian oogenesis, represent a very promising system for precise physical gene mapping. We applied 35 chicken BAC and 4 PAC clones to both mitotic metaphase chromosomes and meiotic lampbrush chromosomes

  17. A method for producing digital probabilistic seismic landslide hazard maps

    Science.gov (United States)

    Jibson, R.W.; Harp, E.L.; Michael, J.A.

    2000-01-01

    The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include: (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24 000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10 m grid spacing using ARC/INFO GIS software on a UNIX computer. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure. ?? 2000 Elsevier Science B.V. All rights reserved.

  18. Fish on avian lampbrush chromosomes produces higher resolution gene mapping

    NARCIS (Netherlands)

    Galkina, S.A.; Deryusheva, S.; Fillon, V.; Vignal, A.; Crooijmans, R.P.M.A.; Groenen, M.A.M.; Rodionov, A.V.; Gaginskaya, E.

    2006-01-01

    Giant lampbrush chromosomes, which are characteristic of the diplotene stage of prophase I during avian oogenesis, represent a very promising system for precise physical gene mapping. We applied 35 chicken BAC and 4 PAC clones to both mitotic metaphase chromosomes and meiotic lampbrush chromosomes o

  19. Investigating the rank-size relationship of urban areas using land cover maps

    Science.gov (United States)

    Kinoshita, Tsuguki; Kato, Etsushi; Iwao, Koki; Yamagata, Yoshiki

    2008-09-01

    We investigated the possibility that the rank-size rule can be applied to the relationship between urban size and rank order. Accordingly, using a global land cover data set, we clustered contiguous urban grid cells, calculated the area in each cluster, and ranked urban areas in each of the countries studied. This research revealed that Zipf's law can be applied to the relationship between urban area and rank order as well as to city populations. Comparisons were made in some countries, and it was shown that the urban area rank-size rule was free from administrative boundaries. Finally, in Japan, using land-use maps for several times in recent history, changes in rank-size were investigated. As a result, it was found that the slopes for urban areas did not change vis-à-vis their rank in a double logarithmic graph and that only the x and y interception changed.

  20. Extrasolar Storms: Mapping Cloud Cover Evolution with Joint HST-Spitzer Observations

    Science.gov (United States)

    Apai, Daniel; Extrasolar Storms Team

    2017-01-01

    Observations of directly imaged and transiting exoplanets and brown dwarfs reveal the wide-spread presence of condensate clouds. These clouds profoundly influence the energy transport through ultracool atmospheres and impact their pressure-temperature profiles. Yet, the structure and properties of these cloud layers remain mostly unexplored and pose one of the great challenges to our understanding ultracool atmospheres. I will show how using HST and Spitzer jointly -- by exploiting their photometric stability and sensitivity and combining their wavelength ranges -- allows us to address this challenge. With time-resolved spectroscopy and photometry of rotating brown dwarfs - rotational phase mapping — we are exploring the longitudinal structure of condensate clouds and with multiple epoch observations we are following the evolution of the cloud cover. These new observations are opening a new window on the dynamics of ultracool atmospheres.

  1. Mapping CORINE Land Cover from Sentinel-1A SAR and SRTM Digital Elevation Model Data using Random Forests

    Directory of Open Access Journals (Sweden)

    Heiko Balzter

    2015-11-01

    Full Text Available The European CORINE land cover mapping scheme is a standardized classification system with 44 land cover and land use classes. It is used by the European Environment Agency to report large-scale land cover change with a minimum mapping unit of 5 ha every six years and operationally mapped by its member states. The most commonly applied method to map CORINE land cover change is by visual interpretation of optical/near-infrared satellite imagery. The Sentinel-1A satellite carries a C-band Synthetic Aperture Radar (SAR and was launched in 2014 by the European Space Agency as the first operational Copernicus mission. This study is the first investigation of Sentinel-1A for CORINE land cover mapping. Two of the first Sentinel-1A images acquired during its ramp-up phase in May and December 2014 over Thuringia in Germany are analysed. 27 hybrid level 2/3 CORINE classes are defined. 17 of these were present at the study site and classified based on a stratified random sample of training pixels from the polygon-eroded CORINE 2006 map. Sentinel-1A logarithmic radar backscatter at HH and HV polarisation (May acquisition, VV and VH polarisation (December acquisition, and the HH image texture are used as input bands to the classification. In addition, a Digital Terrain Model (DTM, a Canopy Height Model (CHM and slope and aspect maps from the Shuttle Radar Topography Mission (SRTM are used as input bands to account for geomorphological features of the landscape. In future, elevation data will be delivered for areas with sufficiently high coherence from the Sentinel-1A Interferometric Wide-Swath Mode itself. When augmented by elevation data from radar interferometry, Sentinel-1A is able to discriminate several CORINE land cover classes, making it useful for monitoring of cloud-covered regions. A bistatic Sentinel-1 Convoy mission would enable single-pass interferometric acquisitions without temporal decorrelation.

  2. Object-Based Land-Cover Mapping with High Resolution Aerial Photography at a County Scale in Midwestern USA

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Li

    2014-11-01

    Full Text Available There are growing demands for detailed and accurate land cover maps in land system research and planning. Macro-scale land cover maps normally cannot satisfy the studies that require detailed land cover maps at micro scales. In the meantime, applying conventional pixel-based classification methods in classifying high-resolution aerial imagery is ineffective to develop high accuracy land-cover maps, especially in spectrally heterogeneous and complicated urban areas. Here we present an object-based approach that identifies land-cover types from 1-meter resolution aerial orthophotography and a 5-foot DEM. Our study area is Tippecanoe County in the State of Indiana, USA, which covers about a 1300 km2 land area. We used a countywide aerial photo mosaic and normalized digital elevation model as input datasets in this study. We utilized simple algorithms to minimize computation time while maintaining relatively high accuracy in land cover mapping at a county scale. The aerial photograph was pre-processed using principal component transformation to reduce its spectral dimensionality. Vegetation and non-vegetation were separated via masks determined by the Normalized Difference Vegetation Index. A combination of segmentation algorithms with lower calculation intensity was used to generate image objects that fulfill the characteristics selection requirements. A hierarchical image object network was formed based on the segmentation results and used to assist the image object delineation at different spatial scales. Finally, expert knowledge regarding spectral, contextual, and geometrical aspects was employed in image object identification. The resultant land cover map developed with this object-based image analysis has more information classes and higher accuracy than that derived with pixel-based classification methods.

  3. Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa

    Science.gov (United States)

    Vaglio Laurin, Gaia; Liesenberg, Veraldo; Chen, Qi; Guerriero, Leila; Del Frate, Fabio; Bartolini, Antonio; Coomes, David; Wilebore, Beccy; Lindsell, Jeremy; Valentini, Riccardo

    2013-04-01

    The classification of tropical fragmented landscapes and moist forested areas is a challenge due to the presence of a continuum of vegetation successional stages, persistent cloud cover and the presence of small patches of different land cover types. To classify one such study area in West Africa we integrated the optical sensors Landsat Thematic Mapper (TM) and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) with the Phased Arrayed L-band SAR (PALSAR) sensor, the latter two on-board the Advanced Land Observation Satellite (ALOS), using traditional Maximum Likelihood (MLC) and Neural Networks (NN) classifiers. The impact of texture variables and the use of SAR to cope with optical data unavailability were also investigated. SAR and optical integrated data produced the best classification overall accuracies using both MLC and NN, respectively equal to 91.1% and 92.7% for TM and 95.6% and 97.5% for AVNIR-2. Texture information derived from optical images was critical, improving results between 10.1% and 13.2%. In our study area, PALSAR alone was able to provide valuable information over the entire area: when the three forest classes were aggregated, it achieved 75.7% (with MCL) and 78.1% (with NN) overall classification accuracies. The selected classification and processing methods resulted in fine and accurate vegetation mapping in a previously untested region, exploiting all available sensors synergies and highlighting the advantages of each dataset.

  4. USGS Land Cover (NLCD) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) National Land Cover Database (NLCD)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 1992, NLCD 2001, NLCD 2006, and NLCD 2011 are National Land Cover Database classification schemes based primarily on Landsat data along with ancillary data...

  5. Regional adaptation of a dynamic global vegetation model using a remote sensing data derived land cover map of Russia

    Science.gov (United States)

    Khvostikov, S.; Venevsky, S.; Bartalev, S.

    2015-12-01

    The dynamic global vegetation model (DGVM) SEVER has been regionally adapted using a remote sensing data-derived land cover map in order to improve the reconstruction conformity of the distribution of vegetation functional types over Russia. The SEVER model was modified to address noticeable divergences between modelling results and the land cover map. The model modification included a light competition method elaboration and the introduction of a tundra class into the model. The rigorous optimisation of key model parameters was performed using a two-step procedure. First, an approximate global optimum was found using the efficient global optimisation (EGO) algorithm, and afterwards a local search in the vicinity of the approximate optimum was performed using the quasi-Newton algorithm BFGS. The regionally adapted model shows a significant improvement of the vegetation distribution reconstruction over Russia with better matching with the satellite-derived land cover map, which was confirmed by both a visual comparison and a formal conformity criterion.

  6. Per pixel uncertainty modelling and its spatial representation on land cover maps obtained by hybrid classification.

    Science.gov (United States)

    Pons, Xavier; Sevillano, Eva; Moré, Gerard; Serra, Pere; Cornford, Dan; Ninyerola, Miquel

    2013-04-01

    The usage of remote sensing imagery combined with statistical classifiers to obtain categorical cartography is now common practice. As in many other areas of geographic information quality assessment, knowing the accuracy of these maps is crucial, and the spatialization of quality information is becoming ever more important for a large range of applications. Whereas some classifiers (e.g., maximum likelihood, linear discriminant analysis, naive Bayes, etc) permit the estimation and spatial representation of the uncertainty through a pixel level probabilistic estimator (and, from that, to compute a global accuracy estimator for the whole map), for other methods such a direct estimator does not exist. Regardless of the classification method applied, ground truth data is almost always available (to train the classifier and/or to compute the global accuracy and, usually, a confusion matrix). Our research is devoted to the development of a protocol to spatialize the error on a general framework based on the classifier parameters, and some ground truth reference data. In the methodological experiment presented here we provide an insight into uncertainty modelling for a hybrid classifier that combines unsupervised and supervised stages (implemented in the MiraMon GIS). In this work we describe what we believe is the first attempt to characterise pixel level uncertainty in a two stage classification process. We describe the model setup, show the preliminary results and identify future work that will be undertaken. The study area is a Landsat full frame located at the North-eastern region of the Iberian Peninsula. The six non-thermal bands + NDVI of a multi-temporal set of six geometrically and radiometrically corrected Landsat-5 images (between 2005 and 2007) were submitted to a hybrid classification process, together with some ancillary data (climate, slopes, etc). Training areas were extracted from the Land Cover Map of Catalonia (MCSC), a 0.5 m resolution map created by

  7. Cover design for radioactive and AMD-producing mine waste in the Ronneburg area, eastern Thuringia.

    Science.gov (United States)

    Gatzweiler, R; Jahn, S; Neubert, G; Paul, M

    2001-01-01

    At the former uranium mining site of Ronneburg, large scale underground and open pit mining for nearly 40 years resulted in a production of about 113,000 tonnes of uranium and about 200 million cubic metres of mine waste. In their present state, these materials cause risks to human health and strong environmental impacts and therefore demand remedial action. The remediation options available are relocation of mine spoil into the open pit and on site remediation by landscaping/contouring, placement of a cover and revegetation. A suitable vegetated cover system combined with a surface water drainage system provides long-term stability against erosion and reduces acid generation thereby meeting the main remediation objectives which are long-term reduction of radiological exposure and contaminant emissions and recultivation. The design of the cover system includes the evaluation of geotechnical, radiological, hydrological, geochemical and ecological criteria and models. The optimized overall model for the cover system has to comply with general conditions as, e.g. economic efficiency, public acceptance and sustainability. Most critical elements for the long-term performance of the cover system designed for the Beerwalde dump are the barrier system and its long-term integrity and a largely self-sustainable vegetation.

  8. The XH-map algorithm: A method to process stereo video to produce a real-time obstacle map

    Science.gov (United States)

    Rosselot, Donald; Hall, Ernest L.

    2005-10-01

    This paper presents a novel, simple and fast algorithm to produce a "floor plan" obstacle map in real time using video. The XH-map algorithm is a transformation of stereo vision data in disparity map space into a two dimensional obstacle map space using a method that can be likened to a histogram reduction of image information. The classic floor-ground background noise problem is addressed with a simple one-time semi-automatic calibration method incorporated into the algorithm. This implementation of this algorithm utilizes the Intel Performance Primitives library and OpenCV libraries for extremely fast and efficient execution, creating a scaled obstacle map from a 480x640x256 stereo pair in 1.4 milliseconds. This algorithm has many applications in robotics and computer vision including enabling an "Intelligent Robot" robot to "see" for path planning and obstacle avoidance.

  9. AN ASSESSMENT OF CITIZEN CONTRIBUTED GROUND REFERENCE DATA FOR LAND COVER MAP ACCURACY ASSESSMENT

    Directory of Open Access Journals (Sweden)

    G. M. Foody

    2015-08-01

    Full Text Available It is now widely accepted that an accuracy assessment should be part of a thematic mapping programme. Authoritative good or best practices for accuracy assessment have been defined but are often impractical to implement. Key reasons for this situation are linked to the ground reference data used in the accuracy assessment. Typically, it is a challenge to acquire a large sample of high quality reference cases in accordance to desired sampling designs specified as conforming to good practice and the data collected are normally to some degree imperfect limiting their value to an accuracy assessment which implicitly assumes the use of a gold standard reference. Citizen sensors have great potential to aid aspects of accuracy assessment. In particular, they may be able to act as a source of ground reference data that may, for example, reduce sample size problems but concerns with data quality remain. The relative strengths and limitations of citizen contributed data for accuracy assessment are reviewed in the context of the authoritative good practices defined for studies of land cover by remote sensing. The article will highlight some of the ways that citizen contributed data have been used in accuracy assessment as well as some of the problems that require further attention, and indicate some of the potential ways forward in the future.

  10. A Temporal Map in Geostationary Orbit: The Cover Etching on the EchoStar XVI Artifact

    CERN Document Server

    Weisberg, J M

    2012-01-01

    Geostationary satellites are unique among orbital spacecraft in that they experience no appreciable atmospheric drag. After concluding their respective missions, geostationary spacecraft remain in orbit virtually in perpetuity. As such, they represent some of human civilization's longest lasting artifacts. With this in mind, the EchoStar XVI satellite, to be launched in fall 2012, will play host to a time capsule intended as a message for the deep future. Inspired in part by the Pioneer Plaque and Voyager Golden Records, the EchoStar XVI Artifact is a pair of gold-plated aluminum jackets housing a small silicon disc containing one hundred photographs. The Cover Etching, the subject of this paper, is etched onto one of the two jackets. It is a temporal map consisting of a star chart, pulsar timings, and other information describing the epoch from which EchoStar XVI came. The pulsar sample consists of 13 rapidly rotating objects, 5 of which are especially stable, having spin periods < 10 ms and extremely sma...

  11. VT National Land Cover Dataset - 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The NLCD2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 land cover layer for mapping zone 65 was produced...

  12. User's Guide for the Land-Cover map of the Coastal Plain of the Arctic National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — A landcover map of the coastal plain of the Arctic National Wildlife Refuge in northeastern Alaska was produced using LANOSA T Thematic Mapper satellite imagery,...

  13. Evaluating maps produced by urban search and rescue robots: Lessons learned from RoboCup

    NARCIS (Netherlands)

    Balaguer, B.; Balakirsky, S.; Carpin, S.; Visser, A.

    2009-01-01

    This paper presents the map evaluation methodology developed for the Virtual Robots Rescue competition held as part of RoboCup. The procedure aims to evaluate the quality of maps produced by multi-robot systems with respect to a number of factors, including usability, exploration, annotation and oth

  14. Generating Up-to-Date and Detailed Land Use and Land Cover Maps Using OpenStreetMap and GlobeLand30

    Directory of Open Access Journals (Sweden)

    Cidália Costa Fonte

    2017-04-01

    Full Text Available With the opening up of the Landsat archive, global high resolution land cover maps have begun to appear. However, they often have only a small number of high level land cover classes and they are static products, corresponding to a particular period of time, e.g., the GlobeLand30 (GL30 map for 2010. The OpenStreetMap (OSM, in contrast, consists of a very detailed, dynamically updated, spatial database of mapped features from around the world, but it suffers from incomplete coverage, and layers of overlapping features that are tagged in a variety of ways. However, it clearly has potential for land use and land cover (LULC mapping. Thus the aim of this paper is to demonstrate how the OSM can be converted into a LULC map and how this OSM-derived LULC map can then be used to first update the GL30 with more recent information and secondly, enhance the information content of the classes. The technique is demonstrated on two study areas where there is availability of OSM data but in locations where authoritative data are lacking, i.e., Kathmandu, Nepal and Dar es Salaam, Tanzania. The GL30 and its updated and enhanced versions are independently validated using a stratified random sample so that the three maps can be compared. The results show that the updated version of GL30 improves in terms of overall accuracy since certain classes were not captured well in the original GL30 (e.g., water in Kathmandu and water/wetlands in Dar es Salaam. In contrast, the enhanced GL30, which contains more detailed urban classes, results in a drop in the overall accuracy, possibly due to the increased number of classes, but the advantages include the appearance of more detailed features, such as the road network, that becomes clearly visible.

  15. On retracting properties and covering homotopy theorem for S-maps into Sχ-cofibrations and Sχ-fibrations

    Directory of Open Access Journals (Sweden)

    Amin Saif

    2016-10-01

    Full Text Available In this paper we generalize the retracting property in homotopy theory for topological semigroups by introducing the notions of deformation S-retraction with its weaker forms and ES-homotopy extension property. Furthermore, the covering homotopy theorems for S-maps into Sχ-fibrations and Sχ-cofibrations are introduced and pullbacks for Sχ-fibrations behave properly.

  16. Mapping Land Surface Temperature and Land Cover to Detect Urban Heat Island Effect: A Case Study of Tarkwa, South West Ghana

    Directory of Open Access Journals (Sweden)

    Michael Soakodan Aduah

    2012-01-01

    Full Text Available Urban Heat Island (UHI effect controls internal climates of buildings and affects energy use and comfort of urban dwellers. The objective of this study was to detect UHI from Land Surface Temperature (LST and to investigate whether land cover has any influence on UHI in Tarkwa, South West Ghana using satellite remote sensing techniques. A Landsat 7 ETM+ image, DEM and meteorological data were used to generate a land cover map with the maximum likelihood classification algorithm whiles LST was modeled with the Landsat Plank’s curve. Validation of the LST map was achieved by comparing it with air temperature measured at the UMaT meteorological station. The mean modeled LST of 298.60 Kelvin compared well with the mean observed air temperature of 298.30 Kelvin. Furthermore, LST ranged between 289 and 305 Kelvin while urban areas and bare soils had higher LSTs than vegetated areas implying that higher NDVI areas are associated with lower temperatures. Hence, LST maps produced indicated the existence of UHI effect in the Tarkwa area. From the study it is evident that impervious and non-evaporative surfaces have high LSTs due to absence of vegetation. Therefore, uncontrolled land cover changes may intensify the UHI effect. The study has proven that remote sensing can be used in operational mapping of LST for climate studies, vegetation monitoring and detecting UHIs in the humid regions of Ghana. This confirms the important role Earth observation and geoinformation technology can play in environmental monitoring and management as global climate and land cover changes.

  17. Mapping the land cover in coastal Gabes oases using the EO-1 HYPERION hyperspectral sensor

    Science.gov (United States)

    Ben-Arfa, Jouda; Bergès, Jean Claude; Beltrando, Gérard; Rim, Katlane; Zargouni, Fouad

    2015-04-01

    Gabes region is characterized by unique maritime oases in Mediterranean basin. Unfortunately these oases are sensitive areas due to a harsh competition for land and water between different user groups (urban, industry, agriculture). An industrial complex is now located in center of this region, cultivation practices have shifted from a traditional multi-layer plant association system and moreover the Gabes city itself is expanding in the very core of oases. The oases of Gabes are transformed into city oases; they undergo multiform interactions whose amplify their environmental dynamic. A proper management of this environment should be based on a fine cartography of land use and remote sensing plays a major role in this issue. However the use of legacy natural resource remote sensing data is disappointing. The crop production strategies rely on a fine scale ground split among various uses and the ground resolution of these satellites is not adequate. Our study relies on hyperspectral images in order to cartography oases boundaries and land use. We tested the potential of Hyperion hyperspectral satellite imagery for mapping dynamics oases covered. We have the opportunity to access EO1/Hyperion data on seven different dates on 2009 and 2010. This dataset allows us to compare various hyperspectral based processing both on the basis on information pertinence and time stability. In this frame some index appear as significantly efficient: cellulose index, vegetation mask, water presence index. On another side spectral unmixing looks as more sensitive to slight ground changes. These results raise the issue of compared interest of enhancing spatial resolution versus spectral resolution. Whereas high resolution ground observation satellites are obviously more appropriate for visual recognition process, reliable information could be extracted from hyperspectral information through a fully automatic process.

  18. GAP Land Cover - Tiled Raster

    Data.gov (United States)

    Minnesota Department of Natural Resources — This raster dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of...

  19. Land cover mapping with emphasis to burnt area delineation using co-orbital ALI and Landsat TM imagery

    Science.gov (United States)

    Petropoulos, George P.; Kontoes, Charalambos C.; Keramitsoglou, Iphigenia

    2012-08-01

    In this study, the potential of EO-1 Advanced Land Imager (ALI) radiometer for land cover and especially burnt area mapping from a single image analysis is investigated. Co-orbital imagery from the Landsat Thematic Mapper (TM) was also utilised for comparison purposes. Both images were acquired shortly after the suppression of a fire occurred during the summer of 2009 North-East of Athens, the capital of Greece. The Maximum Likelihood (ML), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) classifiers were parameterised and subsequently applied to the acquired satellite datasets. Evaluation of the land use/cover mapping accuracy was based on the error matrix statistics. Also, the McNemar test was used to evaluate the statistical significance of the differences between the approaches tested. Derived burnt area estimates were validated against the operationally deployed Services and Applications For Emergency Response (SAFER) Burnt Scar Mapping service. All classifiers applied to either ALI or TM imagery proved flexible enough to map land cover and also to extract the burnt area from other land surface types. The highest total classification accuracy and burnt area detection capability was returned from the application of SVMs to ALI data. This was due to the SVMs ability to identify an optimal separating hyperplane for best classes' separation that was able to better utilise ALI's advanced technological characteristics in comparison to those of TM sensor. This study is to our knowledge the first of its kind, effectively demonstrating the benefits of the combined application of SVMs to ALI data further implying that ALI technology may prove highly valuable in mapping burnt areas and land use/cover if it is incorporated into the development of Landsat 8 mission, planned to be launched in the coming years.

  20. CRED Cumulative Map of Percent Scleractinian Coral Cover at Lisianski Island, 2001-2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  1. CRED Cumulative Map of Percent Scleractinian Coral Cover at Midway Atoll, 2002-04

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  2. CRED Cumulative Map of Percent Scleractinian Coral Cover at St. Rogatien West, 2001

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  3. CRED Cumulative Map of Percent Scleractinian Coral Cover at Niihau, 2005

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  4. CRED Cumulative Map of Percent Scleractinian Coral Cover at Guam, 2003

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  5. CRED Cumulative Map of Percent Scleractinian Coral Cover at French Frigate Shoals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  6. CRED Cumulative Map of Percent Scleractinian Coral Cover at Supply Reef

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  7. CRED Cumulative Map of Percent Scleractinian Coral Cover at Stingray Shoals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  8. CRED Cumulative Map of Percent Scleractinian Coral Cover at Esmerelda Bank

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  9. CRED Cumulative Map of Percent Scleractinian Coral Cover at Santa Rosa Reef

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  10. CRED Cumulative Map of Percent Scleractinian Coral Cover at Necker Island, 2002-2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  11. CRED Cumulative Map of Percent Scleractinian Coral Cover at Palmyra Atoll, 2002-2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  12. CRED Cumulative Map of Percent Scleractinian Coral Cover at Maro Reef, 2001-2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  13. CRED Cumulative Map of Percent Scleractinian Coral Cover at Ta'u

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  14. CRED Cumulative Map of Percent Scleractinian Coral Cover at Ofu & Olosega

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  15. CRED Cumulative Map of Percent Scleractinian Coral Cover at Molokai, 2005

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  16. CRED Cumulative Map of Percent Scleractinian Coral Cover at Pearl and Hermes Atoll, 2002-2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  17. CRED Cumulative Map of Percent Scleractinian Coral Cover at Raita Bank, 2001

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  18. CRED Cumulative Map of Percent Scleractinian Coral Cover at Johnston Atoll, 2004

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  19. CRED Cumulative Map of Percent Scleractinian Coral Cover at Farallon de Pajaros (Uracas)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  20. CRED Cumulative Map of Percent Scleractinian Coral Cover at Kauai, 2005

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry.

  1. Mapping Land Cover in the Taita Hills, se Kenya, Using Airborne Laser Scanning and Imaging Spectroscopy Data Fusion

    Science.gov (United States)

    Piiroinen, R.; Heiskanen, J.; Maeda, E.; Hurskainen, P.; Hietanen, J.; Pellikka, P.

    2015-04-01

    The Taita Hills, located in south-eastern Kenya, is one of the world's biodiversity hotspots. Despite the recognized ecological importance of this region, the landscape has been heavily fragmented due to hundreds of years of human activity. Most of the natural vegetation has been converted for agroforestry, croplands and exotic forest plantations, resulting in a very heterogeneous landscape. Given this complex agro-ecological context, characterizing land cover using traditional remote sensing methods is extremely challenging. The objective of this study was to map land cover in a selected area of the Taita Hills using data fusion of airborne laser scanning (ALS) and imaging spectroscopy (IS) data. Land Cover Classification System (LCCS) was used to derive land cover nomenclature, while the height and percentage cover classifiers were used to create objective definitions for the classes. Simultaneous ALS and IS data were acquired over a 10 km x 10 km area in February 2013 of which 1 km x 8 km test site was selected. The ALS data had mean pulse density of 9.6 pulses/m2, while the IS data had spatial resolution of 1 m and spectral resolution of 4.5-5 nm in the 400-1000 nm spectral range. Both IS and ALS data were geometrically co-registered and IS data processed to at-surface reflectance. While IS data is suitable for determining land cover types based on their spectral properties, the advantage of ALS data is the derivation of vegetation structural parameters, such as tree height and crown cover, which are crucial in the LCCS nomenclature. Geographic object-based image analysis (GEOBIA) was used for segmentation and classification at two scales. The benefits of GEOBIA and ALS/IS data fusion for characterizing heterogeneous landscape were assessed, and ALS and IS data were considered complementary. GEOBIA was found useful in implementing the LCCS based classification, which would be difficult to map using pixel-based methods.

  2. Repeatability in photo-interpretation of tree canopy cover and its effect on predictive mapping

    Science.gov (United States)

    Thomas A. Jackson; Gretchen G. Moisen; Paul L. Patterson; John Tipton

    2012-01-01

    In this study, we explore repeatability in photo-interpreted imagery from the National Agriculture Imagery Program that was sampled as part of the National Land Cover Database 2011 Tree Canopy Cover pilot project. Data were collected in 5 diverse pilot areas in the US, including one each in Oregon, Utah, Kansas, Michigan and Georgia. Repeatability metrics. The intra-...

  3. Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

    Science.gov (United States)

    A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

  4. An integrated physical map covering 25 cM of human chromosome 8

    Energy Technology Data Exchange (ETDEWEB)

    Chen, W.; Hou, J.; Wagner, M.J.; Wells, D.E. [Univ. of Houston, TX (United States)

    1996-02-15

    This article reports on an integrated physical map of human chromosome 8 using STS content analysis of somatic cell hybrids and YAC contigs. Such mapping efforts will help to localize genes linked to hereditary diseases. 17 refs., 1 fig., 1 tab.

  5. Preliminary results of mapping urban land cover with Seasat SAR imagery

    Science.gov (United States)

    Henderson, F. M.; Wharton, S. W.; Toll, D. L.

    1980-01-01

    The detectability of urban land cover types is explored using digitally processed Seasat SAR imagery of the Denver, Colorado area. Test sites within the metropolitan area were selected to include a cross section of Anderson, et. al. Level II land cover classes and cover types representative of the urban area growth stages. Using the Image 100 interactive processing system each test site was level sliced in an attempt to define specific reflectance boundaries for each cover type and to determine the spectral and spatial characteristics of homogeneous response regions. The rural-urban fringe boundary was readily definable, but a precise Level I and Level II land cover classification was not possible. High density housing could be separated from low density housing and from parks, but reflectance values were often look angle dependent. Confusion between some water and vegetation responses also posed problems.

  6. Application of satellite and GIS technologies for land-cover and land-use mapping at the rural-urban fringe - A case study

    Energy Technology Data Exchange (ETDEWEB)

    Treitz, P.M.; Howarth, P.J.; Gong, Peng (Waterloo, University (Canada))

    1992-04-01

    SPOT HRV multispectral and panchromatic data were recorded and coregistered for a portion of the rural-urban fringe of Toronto, Canada. A two-stage digital analysis algorithm incorporating a spectral-class frequency-based contextual classification of eight land-cover and land-use classes resulted in an overall Kappa coefficient of 82.2 percent for training-area data and a Kappa coefficient of 70.3 percent for test-area data. A matrix-overlay analysis was then performed within the geographic information system (GIS) to combine the land-cover and land-use classes generated from the SPOT digital classification with zoning information for the area. The map that was produced has an estimated interpretation accuracy of 78 percent. Global Positioning System (GPS) data provided a positional reference for new road networks. These networks, in addition to the new land-cover and land-use map derived from the SPOT HRV data, provide an up-to-date synthesis of change conditions in the area. 51 refs.

  7. Comparison of manually produced and automated cross country movement maps using digital image processing techniques

    Science.gov (United States)

    Wynn, L. K.

    1985-01-01

    The Image-Based Information System (IBIS) was used to automate the cross country movement (CCM) mapping model developed by the Defense Mapping Agency (DMA). Existing terrain factor overlays and a CCM map, produced by DMA for the Fort Lewis, Washington area, were digitized and reformatted into geometrically registered images. Terrain factor data from Slope, Soils, and Vegetation overlays were entered into IBIS, and were then combined utilizing IBIS-programmed equations to implement the DMA CCM model. The resulting IBIS-generated CCM map was then compared with the digitized manually produced map to test similarity. The numbers of pixels comprising each CCM region were compared between the two map images, and percent agreement between each two regional counts was computed. The mean percent agreement equalled 86.21%, with an areally weighted standard deviation of 11.11%. Calculation of Pearson's correlation coefficient yielded +9.997. In some cases, the IBIS-calculated map code differed from the DMA codes: analysis revealed that IBIS had calculated the codes correctly. These highly positive results demonstrate the power and accuracy of IBIS in automating models which synthesize a variety of thematic geographic data.

  8. Decision Tree and Texture Analysis for Mapping Debris-Covered Glaciers in the Kangchenjunga Area, Eastern Himalaya

    Directory of Open Access Journals (Sweden)

    Adina Racoviteanu

    2012-10-01

    Full Text Available In this study we use visible, short-wave infrared and thermal Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER data validated with high-resolution Quickbird (QB and Worldview2 (WV2 for mapping debris cover in the eastern Himalaya using two independent approaches: (a a decision tree algorithm, and (b texture analysis. The decision tree algorithm was based on multi-spectral and topographic variables, such as band ratios, surface reflectance, kinetic temperature from ASTER bands 10 and 12, slope angle, and elevation. The decision tree algorithm resulted in 64 km2 classified as debris-covered ice, which represents 11% of the glacierized area. Overall, for ten glacier tongues in the Kangchenjunga area, there was an area difference of 16.2 km2 (25% between the ASTER and the QB areas, with mapping errors mainly due to clouds and shadows. Texture analysis techniques included co-occurrence measures, geostatistics and filtering in spatial/frequency domain. Debris cover had the highest variance of all terrain classes, highest entropy and lowest homogeneity compared to the other classes, for example a mean variance of 15.27 compared to 0 for clouds and 0.06 for clean ice. Results of the texture image for debris-covered areas were comparable with those from the decision tree algorithm, with 8% area difference between the two techniques.

  9. Soft supervised self-organizing mapping (3SOM) for improving land cover classification with MODIS time-series

    Science.gov (United States)

    Lawawirojwong, Siam

    Classification of remote sensing data has long been a fundamental technique for studying vegetation and land cover. Furthermore, land use and land cover maps are a basic need for environmental science. These maps are important for crop system monitoring and are also valuable resources for decision makers. Therefore, an up-to-date and highly accurate land cover map with detailed and timely information is required for the global environmental change research community to support natural resource management, environmental protection, and policy making. However, there appears to be a number of limitations associated with data utilization such as weather conditions, data availability, cost, and the time needed for acquiring and processing large numbers of images. Additionally, improving the classification accuracy and reducing the classification time have long been the goals of remote sensing research and they still require the further study. To manage these challenges, the primary goal of this research is to improve classification algorithms that utilize MODIS-EVI time-series images. A supervised self-organizing map (SSOM) and a soft supervised self-organizing map (3SOM) are modified and improved to increase classification efficiency and accuracy. To accomplish the main goal, the performance of the proposed methods is investigated using synthetic and real landscape data derived from MODIS-EVI time-series images. Two study areas are selected based on a difference of land cover characteristics: one in Thailand and one in the Midwestern U.S. The results indicate that time-series imagery is a potentially useful input dataset for land cover classification. Moreover, the SSOM with time-series data significantly outperforms the conventional classification techniques of the Gaussian maximum likelihood classifier (GMLC) and backpropagation neural network (BPNN). In addition, the 3SOM employed as a soft classifier delivers a more accurate classification than the SSOM applied as

  10. EnviroAtlas - Durham, NC - One Meter Resolution Urban Area Land Cover Map (2010) Web Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The EnviroAtlas Durham, NC...

  11. Map of percent scleractinian coral cover and sand along camera tow tracks in west Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral and sand overlaid on bathymetry and landsat imagery northwest...

  12. Map of percent scleractinian coral cover along camera tow tracks in west Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry and landsat imagery northwest of...

  13. Implementation of forest cover and carbon mapping in the Greater Mekong subregion and Malaysia project - A case study of Thailand

    Science.gov (United States)

    Pungkul, S.; Suraswasdi, C.; Phonekeo, V.

    2014-02-01

    The Great Mekong Subregion (GMS) contains one of the world's largest tropical forests and plays a vital role in sustainable development and provides a range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. However, the forest in this Subregion is experiencing deforestation rates at high level due to human activities. The reduction of the forest area has negative influence to the environmental and natural resources issues, particularly, more severe disasters have occurred due to global warming and the release of the greenhouse gases. Therefore, in order to conduct forest management in the Subregion efficiently, the Forest Cover and Carbon Mapping in Greater Mekong Subregion and Malaysia project was initialized by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation (APFNet) with the collaboration of various research institutions including Institute of Forest Resource Information Technique (IFRIT), Chinese Academy of Forestry (CAF) and the countries in Sub region and Malaysia comprises of Cambodia, the People's Republic of China (Yunnan province and Guangxi province), Lao People's Democratic Republic, Malaysia, Myanmar, Thailand, and Viet Nam. The main target of the project is to apply the intensive use of recent satellite remote sensing technology, establishing regional forest cover maps, documenting forest change processes and estimating carbon storage in the GMS and Malaysia. In this paper, the authors present the implementation of the project in Thailand and demonstrate the result of forest cover mapping in the whole country in 2005 and 2010. The result of the project will contribute towards developing efficient tools to support decision makers to clearly understand the dynamic change of the forest cover which could benefit sustainable forest resource management in Thailand and the whole Subregion.

  14. Deriving a per-field land use and land cover map in an agricultural mosaic catchment

    Directory of Open Access Journals (Sweden)

    B. Seo

    2014-04-01

    Full Text Available Detailed data on land use and land cover constitutes important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly, however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in an agricultural mosaic catchment Haean, South Korea. We recorded the land cover types with additional information on agricultural practice and make this data available at the public repository Pangaea (doi:10.1594/PANGAEA.823677. In this paper we introduce the data, its collection and the post-processing protocol. During the studied period, a large portion of dry fields was converted to perennial crops. A comparison between our dataset and MODIS Land Cover Type (MCD12Q1 suggested that the MODIS product was restricted in this area since it does not distinguish irrigated fields from general croplands. In addition, linear landscape elements such as water bodies were not detected in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research.

  15. Mapping woody plant cover in desert grasslands using canopy reflectance modeling and MISR data

    Science.gov (United States)

    Chopping, Mark J.; Su, Lihong; Laliberte, Andrea; Rango, Albert; Peters, Debra P. C.; Martonchik, John V.

    2006-09-01

    A simplified geometric-optical model (SGM) was inverted using red band reflectance data acquired at 275 m in nine viewing angles from the Multiangle Imaging SpectroRadiometer (MISR) flown on NASA's Terra satellite, to provide estimates of fractional woody plant cover for large areas (over 3519 km2) in parts of the Chihuahuan Desert in New Mexico, USA. The use of the model in these semi-arid environments was enabled by the derivation of a priori estimates of the soil/understory background reflectance response. This was made possible by determining relationships between the kernel weights from a LiSparse-RossThin model adjusted against the same MISR data - together with spectral reflectance data derived from MISR's nadir-viewing camera - and the parameters of the Walthall model used to represent the background. Spatial distributions of retrieved fractional woody plant cover match those of % tree cover in the global MODIS Vegetation Continuous Fields product but also include shrubs. Good relationships were obtained with fractional shrub cover measured in pastures in the USDA, ARS Jornada Experimental Range but tree cover in higher elevation and riparian zones was dramatically over-estimated as a result of the fixing of crown height and shape parameters.

  16. Disruption of Transient Serotonin Accumulation by Non-Serotonin-Producing Neurons Impairs Cortical Map Development

    Directory of Open Access Journals (Sweden)

    Xiaoning Chen

    2015-01-01

    Full Text Available Polymorphisms that alter serotonin transporter SERT expression and functionality increase the risks for autism and psychiatric traits. Here, we investigate how SERT controls serotonin signaling in developing CNS in mice. SERT is transiently expressed in specific sets of glutamatergic neurons and uptakes extrasynaptic serotonin during perinatal CNS development. We show that SERT expression in glutamatergic thalamocortical axons (TCAs dictates sensory map architecture. Knockout of SERT in TCAs causes lasting alterations in TCA patterning, spatial organizations of cortical neurons, and dendritic arborization in sensory cortex. Pharmacological reduction of serotonin synthesis during the first postnatal week rescues sensory maps in SERTGluΔ mice. Furthermore, knockdown of SERT expression in serotonin-producing neurons does not impair barrel maps. We propose that spatiotemporal SERT expression in non-serotonin-producing neurons represents a determinant in early life genetic programming of cortical circuits. Perturbing this SERT function could be involved in the origin of sensory and cognitive deficits associated with neurodevelopmental disorders.

  17. Developing Methods for Fraction Cover Estimation Toward Global Mapping of Ecosystem Composition

    Science.gov (United States)

    Roberts, D. A.; Thompson, D. R.; Dennison, P. E.; Green, R. O.; Kokaly, R. F.; Pavlick, R.; Schimel, D.; Stavros, E. N.

    2016-12-01

    Terrestrial vegetation seldom covers an entire pixel due to spatial mixing at many scales. Estimating the fractional contributions of photosynthetic green vegetation (GV), non-photosynthetic vegetation (NPV), and substrate (soil, rock, etc.) to mixed spectra can significantly improve quantitative remote measurement of terrestrial ecosystems. Traditional methods for estimating fractional vegetation cover rely on vegetation indices that are sensitive to variable substrate brightness, NPV and sun-sensor geometry. Spectral mixture analysis (SMA) is an alternate framework that provides estimates of fractional cover. However, simple SMA, in which the same set of endmembers is used for an entire image, fails to account for natural spectral variability within a cover class. Multiple Endmember Spectral Mixture Analysis (MESMA) is a variant of SMA that allows the number and types of pure spectra to vary on a per-pixel basis, thereby accounting for endmember variability and generating more accurate cover estimates, but at a higher computational cost. Routine generation and delivery of GV, NPV, and substrate (S) fractions using MESMA is currently in development for large, diverse datasets acquired by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We present initial results, including our methodology for ensuring consistency and generalizability of fractional cover estimates across a wide range of regions, seasons, and biomes. We also assess uncertainty and provide a strategy for validation. GV, NPV, and S fractions are an important precursor for deriving consistent measurements of ecosystem parameters such as plant stress and mortality, functional trait assessment, disturbance susceptibility and recovery, and biomass and carbon stock assessment. Copyright 2016 California Institute of Technology. All Rights Reserved. We acknowledge support of the US Government, NASA, the Earth Science Division and Terrestrial Ecology program.

  18. Comment on "Retrieval practice produces more learning than elaborative studying with concept mapping".

    Science.gov (United States)

    Mintzes, Joel J; Canas, Alberto; Coffey, John; Gorman, James; Gurley, Laine; Hoffman, Robert; McGuire, Saundra Y; Miller, Norma; Moon, Brian; Trifone, James; Wandersee, James H

    2011-10-28

    Karpicke and Blunt (Reports, 11 February 2011, p. 772) reported that retrieval practice produces greater gains in learning than elaborative studying with concept mapping and concluded that this strategy is a powerful way to promote meaningful learning of complex concepts commonly found in science education. We question their findings on methodological and epistemological grounds.

  19. Using Commercial Digital Cameras and Structure-for-Motion Software to Map Snow Cover Depth from Small Aircraft

    Science.gov (United States)

    Sturm, M.; Nolan, M.; Larsen, C. F.

    2014-12-01

    A long-standing goal in snow hydrology has been to map snow cover in detail, either mapping snow depth or snow water equivalent (SWE) with sub-meter resolution. Airborne LiDAR and air photogrammetry have been used successfully for this purpose, but both require significant investments in equipment and substantial processing effort. Here we detail a relatively inexpensive and simple airborne photogrammetric technique that can be used to measure snow depth. The main airborne hardware consists of a consumer-grade digital camera attached to a survey-quality, dual-frequency GPS. Photogrammetric processing is done using commercially available Structure from Motion (SfM) software that does not require ground control points. Digital elevation models (DEMs) are made from snow-free acquisitions in the summer and snow-covered acquisitions in winter, and the maps are then differenced to arrive at snow thickness. We tested the accuracy and precision of snow depths measured using this system through 1) a comparison with airborne scanning LiDAR, 2) a comparison of results from two independent and slightly different photogrameteric systems, and 3) comparison to extensive on-the-ground measured snow depths. Vertical accuracy and precision are on the order of +/-30 cm and +/- 8 cm, respectively. The accuracy can be made to approach that of the precision if suitable snow-free ground control points exists and are used to co-register summer to winter DEM maps. Final snow depth accuracy from our series of tests was on the order of ±15 cm. This photogrammetric method substantially lowers the economic and expertise barriers to entry for mapping snow.

  20. Boreal Forest Land Cover Mapping in Iceland and Finland Using Sentinel-1A

    Science.gov (United States)

    Haarpaintner, J.; Davids, C.; Storvold, R.; Johansen, K. S.; Arnason, K.; Rauste, Y.; Mutanen, T.

    2016-08-01

    The complete Sentinel-1A (S1A) data set since autumn 2014 until September 2015 over two test sites of the EU FP7 project NorthState has been collected: Hallormsstaður in the north-east of Iceland of 50x50 km2 and Hyytiälä in southern Finland of 200x200 km2. The dense 20m-resolution dual-polarization S1A time series allow for a new level of forest land cover monitoring capabilities compared to ESA's former Envisat A(dvanced)SAR sensor. Temporal filtered dual- polarized mosaics clearly show different land covers that can be classified into forest land cover (FLC) products. Even single agricultural fields can be distinguished from these mosaics. The S1A data set also allowed the construction of a precise water mask for these sites. Results of S1A-based FLC based on two different approaches are compared to 2010 ALOS PALSAR derived FLC results and very high resolution (VHR) NDVI aerial photos. The forest land cover classes extracted are forest, disturbed forest, peatland, grassland, bare land, and settlements.

  1. Mapping of landslides under dense vegetation cover using object - oriented analysis and LiDAR derivatives

    NARCIS (Netherlands)

    Van Den Eeckhout, Miet; Kerle, Norman; Hervas, Javier; Supper, Robert; Margottini, C.; Canuti, P.; Sassa, K.

    2013-01-01

    Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify

  2. Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes

    Science.gov (United States)

    Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy B. Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

    2011-01-01

    Accurate landscape-scale maps of forests and associated disturbances are critical to augment studies on biodiversity, ecosystem services, and the carbon cycle, especially in terms of understanding how the spatial and temporal complexities of damage sustained from disturbances influence forest structure and function. Vegetation change tracker (VCT) is a highly automated...

  3. Mapping of landslides under dense vegetation cover using object - oriented analysis and LiDAR derivatives

    NARCIS (Netherlands)

    Van Den Eeckhout, Miet; Kerle, N.; Hervas, Javier; Supper, Robert; Margottini, C.; Canuti, P.; Sassa, K.

    2013-01-01

    Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify

  4. Cytogenetic characterization and AFLP-based genetic linkage mapping for the butterfly Bicyclus anynana, covering all 28 karyotyped chromosomes.

    Directory of Open Access Journals (Sweden)

    Arjen E Van't Hof

    Full Text Available BACKGROUND: The chromosome characteristics of the butterfly Bicyclus anynana, have received little attention, despite the scientific importance of this species. This study presents the characterization of chromosomes in this species by means of cytogenetic analysis and linkage mapping. METHODOLOGY/PRINCIPAL FINDINGS: Physical genomic features in the butterfly B. anynana were examined by karyotype analysis and construction of a linkage map. Lepidoptera possess a female heterogametic W-Z sex chromosome system. The WZ-bivalent in pachytene oocytes of B. anynana consists of an abnormally small, heterochromatic W-chromosome with the Z-chromosome wrapped around it. Accordingly, the W-body in interphase nuclei is much smaller than usual in Lepidoptera. This suggests an intermediate stage in the process of secondary loss of the W-chromosome to a ZZ/Z sex determination system. Two nucleoli are present in the pachytene stage associated with an autosome and the WZ-bivalent respectively. Chromosome counts confirmed a haploid number of n = 28. Linkage mapping had to take account of absence of crossing-over in females, and of our use of a full-sib crossing design. We developed a new method to determine and exclude the non-recombinant uninformative female inherited component in offspring. The linkage map was constructed using a novel approach that uses exclusively JOINMAP-software for Lepidoptera linkage mapping. This approach simplifies the mapping procedure, avoids over-estimation of mapping distance and increases the reliability of relative marker positions. A total of 347 AFLP markers, 9 microsatellites and one single-copy nuclear gene covered all 28 chromosomes, with a mapping distance of 1354 cM. Conserved synteny of Tpi on the Z-chromosome in Lepidoptera was confirmed for B. anynana. The results are discussed in relation to other mapping studies in Lepidoptera. CONCLUSIONS/SIGNIFICANCE: This study adds to the knowledge of chromosome structure and

  5. Time-Series analysis of MODIS NDVI data along with ancillary data for Land use/Land cover mapping of Uttarakhand

    Science.gov (United States)

    Patakamuri, S. K.; Agrawal, S.; Krishnaveni, M.

    2014-12-01

    Land use and land cover plays an important role in biogeochemical cycles, global climate and seasonal changes. Mapping land use and land cover at various spatial and temporal scales is thus required. Reliable and up to date land use/land cover data is of prime importance for Uttarakhand, which houses twelve national parks and wildlife sanctuaries and also has a vast potential in tourism sector. The research is aimed at mapping the land use/land cover for Uttarakhand state of India using Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The study also incorporated smoothening of time-series plots using filtering techniques, which helped in identifying phenological characteristics of various land cover types. Multi temporal Normalized Difference Vegetation Index (NDVI) data for the year 2010 was used for mapping the Land use/land cover at 250m coarse resolution. A total of 23 images covering a single year were layer stacked and 150 clusters were generated using unsupervised classification (ISODATA) on the yearly composite. To identify different types of land cover classes, the temporal pattern (or) phenological information observed from the MODIS (MOD13Q1) NDVI, elevation data from Shuttle Radar Topography Mission (SRTM), MODIS water mask (MOD44W), Nighttime Lights Time Series data from Defense Meteorological Satellite Program (DMSP) and Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) data were used. Final map product is generated by adopting hybrid classification approach, which resulted in detailed and accurate land use and land cover map.

  6. Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations

    Science.gov (United States)

    Kutser, Tiit; Vahtmäe, Ele; Martin, Georg

    2006-04-01

    One of the objectives of monitoring benthic algal cover is to observe short- and long-term changes in species distribution and structure of coastal benthic habitats as indicators of ecological state. Mapping benthic algal cover with conventional methods (diving) provides great accuracy and high resolution, yet is very expensive and is limited by the time and manpower necessary. We measured reflectance spectra of three indicator species for the Baltic Sea: Cladophora glomerata (green macroalgae), Furcellaria lumbricalis (red macroalgae), and Fucus vesiculosus (brown macroalgae) and used a bio-optical model in an attempt to estimate whether these algae are separable from each other and sandy bottom or deep water by means of satellite remote sensing. Our modelling results indicate that to some extent it is possible to map the studied species with multispectral satellite sensors in turbid waters. However, the depths where the macroalgae can be detected are often shallower than the maximum depths where the studied species usually grow. In waters deeper than just a few meters, the differences between the studied bottom types are seen only in band 2 (green) of the multispectral sensors under investigation. It means that multispectral sensors are capable of detecting difference in brightness only in one band which is insufficient for recognition of different bottom types in waters where no or few in situ data are available. Configuration of MERIS spectral bands allows the recognition of red, green and brown macroalgae based on their spectral signatures provided the algal belts are wider than MERIS spatial resolution. Commercial stock of F. lumbricalis in West-Estonian Archipelago covers area where MERIS 300 m spatial resolution is adequate. However, strong attenuation of light in the water column and signal to noise ratio of the sensor do not allow mapping of Furcellaria down to maximum depths where it occurs.

  7. Effect of Training Class Label Noise on Classification Performances for Land Cover Mapping with Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Charlotte Pelletier

    2017-02-01

    Full Text Available Supervised classification systems used for land cover mapping require accurate reference databases. These reference data come generally from different sources such as field measurements, thematic maps, or aerial photographs. Due to misregistration, update delay, or land cover complexity, they may contain class label noise, i.e., a wrong label assignment. This study aims at evaluating the impact of mislabeled training data on classification performances for land cover mapping. Particularly, it addresses the random and systematic label noise problem for the classification of high resolution satellite image time series. Experiments are carried out on synthetic and real datasets with two traditional classifiers: Support Vector Machines (SVM and Random Forests (RF. A synthetic dataset has been designed for this study, simulating vegetation profiles over one year. The real dataset is composed of Landsat-8 and SPOT-4 images acquired during one year in the south of France. The results show that both classifiers are little influenced for low random noise levels up to 25%–30%, but their performances drop down for higher noise levels. Different classification configurations are tested by increasing the number of classes, using different input feature vectors, and changing the number of training instances. Algorithm complexities are also analyzed. The RF classifier achieves high robustness to random and systematic label noise for all the tested configurations; whereas the SVM classifier is more sensitive to the kernel choice and to the input feature vectors. Finally, this work reveals that the cross-validation procedure is impacted by the presence of class label noise.

  8. Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan

    Directory of Open Access Journals (Sweden)

    Chih-Yih Hsieh

    2014-01-01

    Full Text Available Two major earthquakes of ML greater than 6.0 occurred in Taiwan in the first half of 2013. The vibrant shaking brought landslides, falling rocks and casualties. This paper presents a seismic network developed by National Taiwan University (NTU with 401 Micro-Electro Mechanical System (MEMS accelerators. The network recorded high quality strong motion signals from the two events and produced delicate shaking maps within one minute after the earthquake occurrence. The high shaking regions of the intensity map produced by the NTU system suggest damage and casualty locations. Equipped with a dense array of MEMS accelerometers, the NTU system is able to accommodate 10% signals loss from part of the seismic stations and maintain its normal functions for producing shaking maps. The system also has the potential to identify the rupture direction which is one of the key indices used to estimate possible damage. The low cost MEMS accelerator array shows its potential in real-time earthquake shaking map generation and damage avoidance.

  9. Practical Applications of Low Cost Seismic Network for Producing Quick Shaking Map in Taiwan

    Science.gov (United States)

    Wu, Yih-Min

    2014-05-01

    Two major earthquakes of ML greater than 6.0 occurred in Taiwan in the first half of 2013. The vibrantly shakings brought landslides, falling rocks and casualties. This paper presents a seismic network developed by National Taiwan University (NTU) with 401 Micro-ElectroMechanical Systems (MEMS) accelerators. The network recorded high quality strong motion signals of the two events and produced delicate shaking maps within one minute after the earthquake occurrence. The high shaking regions of the intensity map produced by the NTU system precisely indicate the locations of damages and casualties. Equipping with the dense array of MEMS accelerometers, the NTU system is able to accommodate 10% signals loss from part of the seismic stations and maintains its normal functions for producing shaking maps. The system also has the potential to identify the direction of rupture which is one of the key indices to estimate possible damages. The low cost MEMS accelerator array shows its potential in real-time earthquake shaking map generation and damage avoidance.

  10. Historical land-use induced evapotranspiration changes estimated from present-day observations and reconstructed land-cover maps

    Directory of Open Access Journals (Sweden)

    J. P. Boisier

    2014-02-01

    Full Text Available Recent model intercomparison studies, within the framework of the LUCID project, have revealed large discrepancies in the evapotranspiration (ET changes simulated between the preindustrial period and the present in response to the historical change in land use. Distinct land-surface parameterizations are behind those discrepancies, but understanding those differences and attributing them to specific causes rely on evaluations using still very limited measurements. Model benchmarking studies with observed global-scale ET are required in order to reduce the current uncertainties in the impacts of land use in terrestrial water flows. Here we present a new estimate of historical land-use induced changes in ET based on three different state-of-the-art observation-based ET products. These products are used to derive regression models of ET as a function of land-cover partitioning, leaf area index and environmental variables. We then reconstruct past ET changes based on the set of land-cover maps of 1870 and 1992 used in LUCID. Our results show an average decrease in global terrestrial ET of 1260 ± 850 km3 yr−1 between the preindustrial period and the present-day. This estimate is of the same order but larger in magnitude than the model-mean change in ET simulated within LUCID, and substantially weaker in magnitude than other estimates based on observations. Although decreases in ET dominate in deforested regions, large summertime increases in ET are diagnosed over areas of large cropland expansion. The multiple ET reconstructions carried out here show a large spread that we attribute principally to the different land-cover maps adopted and to the crops' ET rates that are derived from the various products assessed. We therefore conclude that the current uncertainties of past ET changes could be reduced efficiently with improved historical land-cover reconstructions and better estimates of cropland ET.

  11. Utilizing a Multi-Source Forest Inventory Technique, MODIS Data and Landsat TM Images in the Production of Forest Cover and Volume Maps for the Terai Physiographic Zone in Nepal

    Directory of Open Access Journals (Sweden)

    Kalle Eerikäinen

    2012-12-01

    Full Text Available An approach based on the nearest neighbors techniques is presented for producing thematic maps of forest cover (forest/non-forest and total stand volume for the Terai region in southern Nepal. To create the forest cover map, we used a combination of Landsat TM satellite data and visual interpretation data, i.e., a sample grid of visual interpretation plots for which we obtained the land use classification according to the FAO standard. These visual interpretation plots together with the field plots for volume mapping originate from an operative forest inventory project, i.e., the Forest Resource Assessment of Nepal (FRA Nepal project. The field plots were also used in checking the classification accuracy. MODIS satellite data were used as a reference in a local correction approach conducted for the relative calibration of Landsat TM images. This study applied a non-parametric k-nearest neighbor technique (k-NN to the forest cover and volume mapping. A tree height prediction approach based on a nonlinear, mixed-effects (NLME modeling procedure is presented in the Appendix. The MODIS image data performed well as reference data for the calibration approach applied to make the Landsat image mosaic. The agreement between the forest cover map and the field observed values of forest cover was substantial in Western Terai (KHAT 0.745 and strong in Eastern Terai (KHAT 0.825. The forest cover and volume maps that were estimated using the k-NN method and the inventory data from the FRA Nepal project are already appropriate and valuable data for research purposes and for the planning of forthcoming forest inventories. Adaptation of the methods and techniques was carried out using Open Source software tools.

  12. Accuracy Assessment for the U.S. Geological Survey Regional Land-Cover Mapping Program: New York and New Jersey Region

    Science.gov (United States)

    Zhu, Zhi-Liang; Yang, Limin; Stehman, Stephen V.; Czaplewski, Raymond L.

    2000-01-01

    The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific accuracies. In Region 2, consisting of New York and New Jersey, the accuracy assessment was completed for 15 land-cover and land-use classes, using interpreted 1:40,000-scale aerial photographs as reference data. The methodology used for Region 2 features a two-stage, geographically stratified approach, with a general sample of all classes (1,033 sample sites), and a separate sample for rare classes (294 sample sites). A confidence index was recorded for each land-cover interpretation on the 1:40,000-scale aerial photography The estimated overall accuracy for Region 2 was 63 percent (standard error 1.4 percent) using all sample sites, and 75.2 percent (standard error 1.5 percent) using only reference sites with a high-confidence index. User's and producer's accuracies for the general sample and user's accuracy for the sample of rare classes, as well as variance for the estimated accuracy parameters, were also reported. Narrowly defined land-use classes and heterogeneous conditions of land cover are the major causes of misclassification errors. Recommendations for modifying the accuracy assessment methodology for use in the other nine Federal regions are provided.

  13. ANWR progress report FY87: Accuracy assessment of Landsat land cover maps of the coastal plain of the Arctic National Wildlife Refuge, Alaska, 1987

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Accuracy assessments of two versions of Landsat-assisted land cover maps were conducted on the coastal plain of the Arctic National Wildlife Refuge. Ground...

  14. Mapping socio-economic scenarios of land cover change: a GIS method to enable ecosystem service modelling.

    Science.gov (United States)

    Swetnam, R D; Fisher, B; Mbilinyi, B P; Munishi, P K T; Willcock, S; Ricketts, T; Mwakalila, S; Balmford, A; Burgess, N D; Marshall, A R; Lewis, S L

    2011-03-01

    We present a GIS method to interpret qualitatively expressed socio-economic scenarios in quantitative map-based terms. (i) We built scenarios using local stakeholders and experts to define how major land cover classes may change under different sets of drivers; (ii) we formalized these as spatially explicit rules, for example agriculture can only occur on certain soil types; (iii) we created a future land cover map which can then be used to model ecosystem services. We illustrate this for carbon storage in the Eastern Arc Mountains of Tanzania using two scenarios: the first based on sustainable development, the second based on 'business as usual' with continued forest-woodland degradation and poor protection of existing forest reserves. Between 2000 and 2025 4% of carbon stocks were lost under the first scenario compared to a loss of 41% of carbon stocks under the second scenario. Quantifying the impacts of differing future scenarios using the method we document here will be important if payments for ecosystem services are to be used to change policy in order to maintain critical ecosystem services.

  15. Land Use and Land Cover, Rhode Island 1962 Land-Cover Maps; Set of 37 scanned maps of land cover for the State of Rhode Island originally prepared by John J. Kupa and William R. Whitman based on 1962 aerial photographs., Published in 2011, 1:2400 (1in=200ft) scale, State of Rhode Island and Providence Plantations.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of 2011. It is described as...

  16. Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

    Science.gov (United States)

    Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

    2016-04-01

    Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map

  17. Climate change effect on the phytosanitary problems: methodology of map producing

    Directory of Open Access Journals (Sweden)

    Renata Ribeiro do Valle Gonçalves

    2006-12-01

    Full Text Available The climate change caused by anthropic action can alter the current scenario of phytosanitary problems in Brazilian agriculture. The aim of this study was to evaluate the methodology of producing maps of spatial distribution of phytosanitary problems of plants associated with climate change effects in Brazil. A case study was applied to coffee leaf miner (Leucoptera coffeella, considered the most important pest of this culture, comparing its distribution in current and in future climate conditions. As current climate, the average of 1960 to 1990 period was considered. For the future climate conditions, the first method used increments in the temperature fixed to the country and, the second one, adopted increases, varying spatially, both aiming 2080 decade (simulating the period between 2017 to 2100, to A2 scenario. A Geographical Information System (GIS was used to produce the maps. The pest model, proposed by Parra (1985, estimates the probable number of coffee leaf miner cycles. In both methods of producing maps, increases of probable number of coffee leaf miner cycles were observed in the future. Although, using fixed increases in the average temperature caused a substimation of the number of cycles in the future, comparing to adopting increases of temperatures varying spatially. Besides the sazonal differences, regional differents were observed to the number of cycles of the leaf miner coffee.

  18. High-resolution global maps of 21st-century forest cover change.

    Science.gov (United States)

    Hansen, M C; Potapov, P V; Moore, R; Hancher, M; Turubanova, S A; Tyukavina, A; Thau, D; Stehman, S V; Goetz, S J; Loveland, T R; Kommareddy, A; Egorov, A; Chini, L; Justice, C O; Townshend, J R G

    2013-11-15

    Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

  19. High-resolution global maps of 21st-century forest cover change

    Science.gov (United States)

    Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; Kommareddy, A.; Egorov, A.; Chini, L.; Justice, C.O.; Townshend, J.R.G.

    2013-01-01

    Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil’s well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

  20. Mapping folds and fractures in basement and cover rocks using UAV photogrammetry, Cape Liptrap and Cape Paterson, Victoria, Australia

    Science.gov (United States)

    Vollgger, Stefan A.; Cruden, Alexander R.

    2016-04-01

    Brittle and ductile deformation of alternating layers of Devonian sandstone and mudstone at Cape Liptrap, Victoria, Australia, resulted in upright folds with associated fold accommodation faults and multiple fracture sets. Structures were mapped at the Fold Stack locality at Cape Liptrap using high-resolution aerial photographs acquired by a digital camera mounted on an unmanned aerial vehicle (UAV). Subsequent photogrammetric modelling resulted in georeferenced spatial datasets (point cloud, digital elevation model and orthophotograph) with sub-cm resolution and cm accuracy, which were used to extract brittle and ductile structure orientation data. An extensive dataset of bedding measurements derived from the dense point cloud was used to compute a 3D implicit structural trend model to visualise along-strike changes of Devonian (Tabberabberan) folds at the Fold Stack locality and to estimate bulk shortening strain. This model and newly collected data indicate that first generation shallowly south-southwest plunging upright folds were gently refolded about a steeply plunging/subvertical fold axis during a Devonian low-strain north-south shortening event. This also led to the local tightening of first generation folds and possibly strike-slip movement along regional scale faults. In order to distinguish fractures associated with Devonian compression from those that formed during Cretaceous extension and later inversion, we compared the five fracture sets defined at Cape Liptrap to previously mapped joints and faults within the overlying sedimentary cover rocks of the Cretaceous Strzelecki Group (Gippsland Basin), which crop out nearby. An east-southeast trending fracture set that is not evident in the Strzelecki Group can be linked to the formation of Devonian folds. Additionally, hinge line traces extracted from the Fold Stack dataset are aligned parallel to a dominant fracture set within the overlying cover sediments. This suggests that basement structures (folds

  1. Mapping the spatio-temporal distribution of key vegetation cover properties in lowland river reaches, using digital photography.

    Science.gov (United States)

    Verschoren, Veerle; Schoelynck, Jonas; Buis, Kerst; Visser, Fleur; Meire, Patrick; Temmerman, Stijn

    2017-06-01

    The presence of vegetation in stream ecosystems is highly dynamic in both space and time. A digital photography technique is developed to map aquatic vegetation cover at species level, which has a very high spatial and a flexible temporal resolution. A digital single-lens reflex (DSLR) camera mounted on a handheld telescopic pole is used. The low-altitude (5 m) orthogonal aerial images have a low spectral resolution (red-green-blue), high spatial resolution (∼1.9 pixels cm(-2), ∼1.3 cm length) and flexible temporal resolution (monthly). The method is successfully applied in two lowland rivers to quantify four key properties of vegetated rivers: vegetation cover, patch size distribution, biomass and hydraulic resistance. The main advantages are that the method is (i) suitable for continuous and discontinuous vegetation covers, (ii) of very high spatial and flexible temporal resolution, (iii) relatively fast compared to conventional ground survey methods, (iv) non-destructive and (v) relatively cheap and easy to use, and (vi) the software is widely available and similar open source alternatives exist. The study area should be less than 10 m wide, and the prevailing light conditions and water turbidity levels should be sufficient to look into the water. Further improvements of the image processing are expected in the automatic delineation and classification of the vegetation patches.

  2. Benthic Cover

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic cover (habitat) maps are derived from aerial imagery, underwater photos, acoustic surveys, and data gathered from sediment samples. Shallow to moderate-depth...

  3. SRTM-DEM AND LANDSAT ETM+ DATA FOR MAPPING TROPICAL DRY FOREST COVER AND BIODIVERSITY ASSESSMENT IN NICARAGUA

    Directory of Open Access Journals (Sweden)

    Brett G. Dickson

    2008-08-01

    Full Text Available Tropical dry and deciduous forest comprises as much as 42% of the world’s tropical forests, but hasreceived far less attention than forest in wet tropical areas. Land use change threatens to greatly reducethe extent of dry forest that is known to contain high levels of plant and animal diversity. Forest fragmentationmay further endanger arboreal mammals that play principal role in the dispersal of large seeded fruits, plantcommunity assembly and diversity in these systems. Data on the spatial arrangement and extent of dryforest and other land cover types is greatly needed to enhance studies of forest fragmentation effects onanimal populations. To address this issue, we compared two Random Forest decision tree models forland cover classification in a Nicaraguan tropical dry forest landscape with and without the use of terrainvariables derived from Space Shuttle Radar and Topography Mission digital elevation data (SRTM-DEM.Landsat Enhanced Thematic Mapper (ETM+ bands and vegetation indices were the principle source ofspectral variables used. Overall classification accuracy for nine land cover types improved from 82.4% to87.4% once terrain and spectral predictor variables were combined. Error matrix comparisons showedthat class accuracy was significantly greater (z = 2.57, p-value < 0.05 with the inclusion of terrain variables(e.g., slope, elevation and topographic wetness index in decision tree models. Variable importance metricsindicated that a corrected Normalized Difference Vegetation Index (NDVIc and terrain variables improveddiscrimination of forest successional types and wetlands in the study area. Results from this study demonstratethe capability of terrain variables to enhance land cover classification and habitat mapping useful tobiodiversity assessment in tropical dry forest.

  4. Land Cover Mapping for the Development of Green House Gas (GHG) Inventories in the Eastern and Southern Africa Region

    Science.gov (United States)

    Wakhayanga, J. A.; Oduor, P.; Korme, T.; Farah, H.; Limaye, A. S.; Irwin, D.; Artis, G.

    2014-12-01

    Anthropogenic activities are responsible for the largest share of green house gas (GHG) emissions. Research has shown that greenhouse gases cause radioactive forcing in the stratosphere, leading to ozone depletion. Different land cover types act as sources or sinks of carbon dioxide (CO2), the most dominant GHG.Under the oversight of the United Nations Framework Convention on Climate Change (UNFCCC) the Eastern and Southern Africa (ESA) region countries are developing Sustainable National GHG Inventory Management Systems. While the countries in the ESA region are making substantial progress in setting up GHG inventories, there remains significant constraints in the development of quality and sustainable National GHG Inventory Systems. For instance, there are fundamental challenges in capacity building and technology transfer, which can affect timely and consistent reporting on the land use, land-use change and forestry (LULUCF) component of the GHG inventory development. SERVIR Eastern and Southern Africa is a partnership project between the National Aeronautics and Space Administration (NASA) and the Regional Center for Mapping of Resources for Development (RCMRD), an intergovernmental organization in Africa, with 21 member states in the ESA region. With support from the United States Agency for International Development (USAID), SERVIR ESA is implementing the GHG Project in 9 countries. The main deliverables of the project are land cover maps for the years 2000 and 2010 (also 1990 for Malawi and Rwanda), and related technical reports, as well as technical training in land cover mapping using replicable methodologies. Landsat imagery which is freely available forms the main component of earth observation input data, in addition to ancillary data collected from each country. Supervised classification using maximum likelihood algorithm is applied to the Landsat images. The work is completed for the initial 6 countries (Malawi, Zambia, Rwanda, Tanzania, Botswana, and

  5. GlobeLand30 as an alternative fine-scale global land cover map: Challenges, possibilities, and implications for developing countries

    DEFF Research Database (Denmark)

    Jokar Arsanjani, Jamal; Tayyebi, A.; Vaz, E.

    2016-01-01

    these regions, their coarse spatial resolution e.g., 500 m as well as their accuracy are very challenging. Recently, GlobeLand30 a global land cover with a relatively fine resolution at 30 m extracted from Landsat images has been released, which seems to be a potential dataset for mapping areas with limited......Global land cover maps are a vital source for mapping our globe into a set of thematic types. They have been extensively used as a basis layer for a large number of applications including ecosystem services, environmental planning, climate change, hydrological processes and policy making. While...

  6. Exploring diversity in ensemble classification: Applications in large area land cover mapping

    Science.gov (United States)

    Mellor, Andrew; Boukir, Samia

    2017-07-01

    Ensemble classifiers, such as random forests, are now commonly applied in the field of remote sensing, and have been shown to perform better than single classifier systems, resulting in reduced generalisation error. Diversity across the members of ensemble classifiers is known to have a strong influence on classification performance - whereby classifier errors are uncorrelated and more uniformly distributed across ensemble members. The relationship between ensemble diversity and classification performance has not yet been fully explored in the fields of information science and machine learning and has never been examined in the field of remote sensing. This study is a novel exploration of ensemble diversity and its link to classification performance, applied to a multi-class canopy cover classification problem using random forests and multisource remote sensing and ancillary GIS data, across seven million hectares of diverse dry-sclerophyll dominated public forests in Victoria Australia. A particular emphasis is placed on analysing the relationship between ensemble diversity and ensemble margin - two key concepts in ensemble learning. The main novelty of our work is on boosting diversity by emphasizing the contribution of lower margin instances used in the learning process. Exploring the influence of tree pruning on diversity is also a new empirical analysis that contributes to a better understanding of ensemble performance. Results reveal insights into the trade-off between ensemble classification accuracy and diversity, and through the ensemble margin, demonstrate how inducing diversity by targeting lower margin training samples is a means of achieving better classifier performance for more difficult or rarer classes and reducing information redundancy in classification problems. Our findings inform strategies for collecting training data and designing and parameterising ensemble classifiers, such as random forests. This is particularly important in large area

  7. Effective roughness calculated from satellite-derived land cover maps and hedge-information used in a weather forecasting model

    DEFF Research Database (Denmark)

    Hasager, C.B.; Nielsen, N.,W.; Jensen, N.O.

    2003-01-01

    In numerical weather prediction, climate and hydrological modelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamic roughness, surface temperature and surface humidity. These local land cover variations give rise to sub-grid scale surface flux...... to be well-described in any large-scale model. A method of aggregating the roughness step changes in arbitrary real terrain has been applied in flat terrain (Denmark) where sub-grid scale vegetation-driven roughness variations are a dominant characteristic of the landscape. The aggregation model...... is a physical two-dimensional atmospheric flow model in the horizontal domain based on a linearized version of the Navier Stoke equation. The equations are solved by the Fast Fourier Transformation technique, hence the code is very fast. The new effective roughness maps have been used in the HIgh Resolution...

  8. Retrieval practice produces more learning than elaborative studying with concept mapping.

    Science.gov (United States)

    Karpicke, Jeffrey D; Blunt, Janell R

    2011-02-11

    Educators rely heavily on learning activities that encourage elaborative studying, whereas activities that require students to practice retrieving and reconstructing knowledge are used less frequently. Here, we show that practicing retrieval produces greater gains in meaningful learning than elaborative studying with concept mapping. The advantage of retrieval practice generalized across texts identical to those commonly found in science education. The advantage of retrieval practice was observed with test questions that assessed comprehension and required students to make inferences. The advantage of retrieval practice occurred even when the criterial test involved creating concept maps. Our findings support the theory that retrieval practice enhances learning by retrieval-specific mechanisms rather than by elaborative study processes. Retrieval practice is an effective tool to promote conceptual learning about science.

  9. OBJECT BASED AGRICULTURAL LAND COVER CLASSIFICATION MAP OF SHADOWED AREAS FROM AERIAL IMAGE AND LIDAR DATA USING SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    R. T. Alberto

    2016-06-01

    Full Text Available Aerial image and LiDAR data offers a great possibility for agricultural land cover mapping. Unfortunately, these images leads to shadowy pixels. Management of shadowed areas for classification without image enhancement were investigated. Image segmentation approach using three different segmentation scales were used and tested to segment the image for ground features since only the ground features are affected by shadow caused by tall features. The RGB band and intensity were the layers used for the segmentation having an equal weights. A segmentation scale of 25 was found to be the optimal scale that will best fit for the shadowed and non-shadowed area classification. The SVM using Radial Basis Function kernel was then applied to extract classes based on properties extracted from the Lidar data and orthophoto. Training points for different classes including shadowed areas were selected homogeneously from the orthophoto. Separate training points for shadowed areas were made to create additional classes to reduced misclassification. Texture classification and object-oriented classifiers have been examined to reduced heterogeneity problem. The accuracy of the land cover classification using 25 scale segmentation after accounting for the shadow detection and classification was significantly higher compared to higher scale of segmentation.

  10. Development of an object-based classification model for mapping mountainous forest cover at high elevation using aerial photography

    Science.gov (United States)

    Lateb, Mustapha; Kalaitzidis, Chariton; Tompoulidou, Maria; Gitas, Ioannis

    2016-08-01

    Climate change and overall temperature increase results in changes in forest cover in high elevations. Due to the long life cycle of trees, these changes are very gradual and can be observed over long periods of time. In order to use remote sensing imagery for this purpose it needs to have very high spatial resolution and to have been acquired at least 50 years ago. At the moment, the only type of remote sensing imagery with these characteristics is historical black and white aerial photographs. This study used an aerial photograph from 1945 in order to map the forest cover at the Olympus National Park, at that date. An object-based classification (OBC) model was developed in order to classify forest and discriminate it from other types of vegetation. Due to the lack of near-infrared information, the model had to rely solely on the tone of the objects, as well as their geometric characteristics. The model functioned on three segmentation levels, using sub-/super-objects relationships and utilising vegetation density to discriminate forest and non-forest vegetation. The accuracy of the classification was assessed using 503 visually interpreted and randomly distributed points, resulting in a 92% overall accuracy. The model is using unbiased parameters that are important for differentiating between forest and non-forest vegetation and should be transferrable to other study areas of mountainous forests at high elevations.

  11. Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

    Directory of Open Access Journals (Sweden)

    Frank Canters

    2008-06-01

    Full Text Available Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city’s inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing.

  12. Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels.

    Science.gov (United States)

    Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

    2008-06-10

    Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing.

  13. Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

    Science.gov (United States)

    Broich, Mark

    Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single

  14. Land Use and Land Cover - MO 2015 Meramec Land Cover (GDB)

    Data.gov (United States)

    NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Meramec River bottomland in Missouri. LiDAR elevation and vegetation height information and...

  15. Land Use and Land Cover - MO 2015 Silver Land Cover (GDB)

    Data.gov (United States)

    NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Upper Silver Creek Watershed in Illinois. LiDAR elevation and vegetation height information...

  16. Land cover mapping of the upper Kuskokwim Resource Managment Area using LANDSAT and a digital data base approach

    Science.gov (United States)

    Markon, Carl J.

    1988-01-01

    Digital land cover and terrain data for the Upper Kuskokwim Resource Hanagement Area (UKRMA) were produced by the U.S. Geological Survey, Earth Resources Observation Systems Field Office, Anchorage, Alaska for the Bureau of Land Management. These and other environmental data, were incorporated into a digital data base to assist in the management and planning of the UKRMA. The digital data base includes land cover classifications, elevation, slope, and aspect data centering on the UKRMA boundaries. The data are stored on computer compatible tapes at a 50-m pixel size. Additional digital data in the data base include: (a) summer and winter Landsat multispectral scanner (MSS) data registered to a 50-m Universal Transverse Mercator grid; (b) elevation, slope, aspect, and solar illumination data; (c) soils and surficial geology; and (e) study area boundary. The classification of Landsat MSS data resulted in seven major classes and 24 subclasses. Major classes include: forest, shrubland, dwarf scrub, herbaceous, barren, water, and other. The final data base will be used by resource personnel for management and planning within the UKRMA.

  17. Indiana forest cover mapping based on multi-stage integrated classification using satellite and in situ forest inventory data

    Science.gov (United States)

    Shao, Gang

    Forest species classification through remote sensing data is a complex process, which usually is done either at a coarse level or with low accuracy. This study examines a multi-stage classification algorithm combining supervised and unsupervised classifications to classify forest areas in Indiana. Integrated classification makes the procedures automatic and reduces human errors. Splitting the classification into two steps increases the accuracy with limited ground data. In the first step, in which the Indiana state forest area is classified, the point plug-in classification algorithm is employed, because plenty of ground data are available. In the second step the classifying of the state forest including a surrounding 8km buffer, the ground data are insufficient to process the point plug-in classification approach. In this case, the polygon plug-in classification algorithm is used to realize the extended area classification at the second stage. The resultant land cover map has six tree species (conifer, mixed forest, oak and hickory, mixed oak and hickory/ hardwood, maple and other hardwood). The overall accuracy is 81.93%.

  18. On growth and covering theorems of quasi-convex mappings in the unit ball of a complex Banach space

    Institute of Scientific and Technical Information of China (English)

    张文俊; 刘太顺

    2002-01-01

    A class of biholomorphic mappings named "quasi-convex mapping" is introduced in the unitball of a complex Banach space. It is proved that this class of mappings is a proper subset of the class ofstarlike mappings and contains the class of convex mappings properly, and it has the same growth and coveringtheorems as the convex mappings. Furthermore, when the Banach space is confined to Cn, the "quasi-convexmapping" is exactly the "quasi-convex mapping of type A" introduced by K. A. Roper and T. J. Suffridge.

  19. Land Use and Land Cover, Comprehensive Planning Maps, Published in 2007, 1:24000 (1in=2000ft) scale, Lafayette County Land Records.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Published Reports/Deeds information as of 2007. It is...

  20. Forests and Forest Cover, Parcel Map/Taxroll Data, Published in 1997, 1:24000 (1in=2000ft) scale, Lafayette County Land Records.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Forests and Forest Cover dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Published Reports/Deeds information as of 1997. It...

  1. Mapping the potential beverage quality of coffee produced in the Zona da Mata, Minas Gerais, Brazil.

    Science.gov (United States)

    Silva, Samuel de Assis; de Queiroz, Daniel Marçal; Ferreira, Williams Pinto Marques; Corrêa, Paulo Cesar; Rufino, José Luis Dos Santos

    2016-07-01

    Detailed knowledge of coffee production systems enables optimization of crop management, harvesting and post-harvest techniques. In this study, coffee quality is mapped as a function of coffee variety, altitude and terrain aspect attributes. The work was performed in the Zona da Mata, Minas Gerais, Brazil. A large range of coffee quality grades was observed for the Red Catuai variety. For the Yellow Catuai variety, no quality grades lower than 70 were observed. Regarding the terrain aspect, samples from the southeast-facing slope (SEFS) and the northwest-facing slope (NWFS) exhibited distinct behaviors. The SEFS samples had a greater range of quality grades than did the NWFS samples. The highest grade was obtained from an NWFS point. The lowest quality values and the largest range of grades were observed at lower altitudes. The extracts from the highest-altitude samples did not produce any low-quality coffee. The production site's position and altitude are the primary variables that influenced the coffee quality. The study area has micro-regions with grades ranging from 80 to 94. These areas have the potential for producing specialty coffees. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  2. A matrix clustering method to explore patterns of land-cover transitions in satellite-derived maps of the Brazilian Amazon

    Science.gov (United States)

    Müller-Hansen, Finn; Cardoso, Manoel F.; Dalla-Nora, Eloi L.; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen; Thonicke, Kirsten

    2017-02-01

    Changes in land-use systems in tropical regions, including deforestation, are a key challenge for global sustainability because of their huge impacts on green-house gas emissions, local climate and biodiversity. However, the dynamics of land-use and land-cover change in regions of frontier expansion such as the Brazilian Amazon are not yet well understood because of the complex interplay of ecological and socioeconomic drivers. In this paper, we combine Markov chain analysis and complex network methods to identify regimes of land-cover dynamics from land-cover maps (TerraClass) derived from high-resolution (30 m) satellite imagery. We estimate regional transition probabilities between different land-cover types and use clustering analysis and community detection algorithms on similarity networks to explore patterns of dominant land-cover transitions. We find that land-cover transition probabilities in the Brazilian Amazon are heterogeneous in space, and adjacent subregions tend to be assigned to the same clusters. When focusing on transitions from single land-cover types, we uncover patterns that reflect major regional differences in land-cover dynamics. Our method is able to summarize regional patterns and thus complements studies performed at the local scale.

  3. A multicriteria framework for producing local, regional, and national insect and disease risk maps

    Science.gov (United States)

    Frank J. Jr. Krist; Frank J. Sapio; Borys M. Tkacz

    2010-01-01

    The construction of the 2006 National Insect and Disease Risk Map, compiled by the USDA Forest Service, State and Private Forestry Area, Forest Health Protection Unit, resulted in the development of a GIS-based, multicriteria approach for insect and disease risk mapping that can account for regional variations in forest health concerns and threats. This risk mapping...

  4. Use of Land Use Land Cover Change Mapping Products in Aiding Coastal Habitat Conservation and Restoration Efforts of the Mobile Bay NEP

    Science.gov (United States)

    Spruce, Joseph P.; Swann, Roberta; Smooth, James

    2010-01-01

    The Mobile Bay region has undergone significant land use land cover change (LULC) over the last 35 years, much of which is associated with urbanization. These changes have impacted the region s water quality and wildlife habitat availability. In addition, much of the region is low-lying and close to the Gulf, which makes the region vulnerable to hurricanes, climate change (e.g., sea level rise), and sometimes man-made disasters such as the Deepwater Horizon (DWH) oil spill. Land use land cover change information is needed to help coastal zone managers and planners to understand and mitigate the impacts of environmental change on the region. This presentation discusses selective results of a current NASA-funded project in which Landsat data over a 34-year period (1974-2008) is used to produce, validate, refine, and apply land use land cover change products to aid coastal habitat conservation and restoration needs of the Mobile Bay National Estuary Program (MB NEP). The project employed a user defined classification scheme to compute LULC change mapping products for the entire region, which includes the majority of Mobile and Baldwin counties. Additional LULC change products have been computed for select coastal HUC-12 sub-watersheds adjacent to either Mobile Bay or the Gulf of Mexico, as part of the MB NEP watershed profile assessments. This presentation will include results of additional analyses of LULC change for sub-watersheds that are currently high priority areas, as defined by MB NEP. Such priority sub-watersheds include those that are vulnerable to impacts from the DWH oil spill, as well as sub-watersheds undergoing urbanization. Results demonstrating the nature and permanence of LULC change trends for these higher priority sub-watersheds and results characterizing change for the entire 34-year period and at approximate 10-year intervals across this period will also be presented. Future work will include development of value-added coastal habitat quality

  5. The global rainforest mapping project JERS-1: a paradigm of international collaboration for monitoring land cover change

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The Global Rainforest Mapping (GRFM) project was initiated in 1995 and, through a dedicated data acquisition policy by the National Space Development Agency of Japan (NASDA), data acquisitions could be completed within a 1.5-year period, resulting in a spatially and temporally homogeneous coverage to contain the entire Amazon Basin from the Atlantic to the Pacific; Central America up to the Yucatan Peninsular in Mexico; equatorial Africa from Madagascar and Kenya in the east to Sierra Leone in the west; and Southeast Asia, including Papua New Guinea. To some extent, GRFM project is an international endeavor led by NASDA, with the goal of producing spatially and temporally contiguous Synthetic Aperture Radar (SAR) data sets over the tropical belt on the Earth by use of the JERS-1 L-band SAR, through the generation of semi-continental, 100m resolution, image mosaics. The GRFM project relies on extensive collaboration with the National Aeronautics and Space Administration (NASA), the Joint Research Center of the European Commission (JRC) and the Japanese Ministry of International Trade and Industry (MITI) for data acquisition, processing, validation and product generation. A science program is underway in parallel with product generation. This involves the agencies mentioned above, as well as a large number of international organizations, universities and individuals to perform field activities and data analysis at different levels.

  6. Comparison of multi-temporal NOAA-AVHRR and SPOT-XS satellite data for mapping land-cover dynamics in the West African Sahel

    Science.gov (United States)

    Marsh, S. E.; Walsh, J. L.; Lee, C. T.; Beck, L. R.; Hutchinson, C. F.

    1992-01-01

    Multi-resolution and multi-temporal remote sensing data (SPOT-XS and AVHRR) were evaluated for mapping local land-cover dynamics in the Sahel of West Africa. The aim of this research was to evaluate the agricultural information that could be derived from both high and low spatial resolution data in areas where there is very often limited ground information. A combination of raster-based image processing and vector-based geographical information system mapping was found to be effective for understanding both spatial and spectral land-cover dynamics. The SPOT data proved useful for mapping local land-cover classes in a dominantly recessive agricultural region. The AVHRR-LAC data could be used to map the dynamics of riparian vegetation, but not the changes associated with recession agriculture. In areas where there was a complex mixture of recession and irrigated agriculture, as well as riparian vegetation, the AVHRR data did not provide an accurate temporal assessment of vegetation dynamics.

  7. Mapping of debris-covered glaciers in parts of the Greater Himalaya Range, Ladakh, western Himalaya, using remote sensing and GIS

    Science.gov (United States)

    Ghosh, Swagata; Pandey, Arvind C.; Nathawat, Mahendra S.

    2014-01-01

    Glacier inventories based on visual interpretation and manual delineation of glacier boundaries are time consuming. Supraglacial debris (debris accumulated on glacier terrain) of Himalayan glaciers creates difficulty with automated glacier mapping when using satellite images. In the present study, a combination of band ratio using the TM image and slope parameter was proven to be useful for delineating glaciers' debris-covered areas. Compared to original TM bands, supervised classification using a combination of principal components two, three, and six of debris and nonglacierized areas facilitated identification of various types of supraglacial debris. Use of principal components four, three, and two of snow- and ice-covered areas as input bands for supervised classification was helpful in classifying different types of snow and ice. Results corresponded well with manually delineated glacier outlines and field observations. Error matrix revealed that the accuracy of classification of the snow- and ice-covered parts of glaciers was 86.29%. Although manual editing was required to differentiate supraglacial debris from periglacial debris (debris outside the glacier boundary), the approach using the ability of morphometric parameter combined with band ratio for delineation of debris-covered parts of glaciers and supervised classification with principal component analysis for mapping of supraglacial covers is observed to be faster than manual delineation.

  8. Connecting geomorphology to dust emission through high-resolution mapping of global land cover and sediment supply

    Science.gov (United States)

    Parajuli, Sagar Prasad; Zender, Charles S.

    2017-08-01

    A key challenge in modeling dust emissions is to represent the location and strength of dust sources. One critical aspect of dust sources that is not well understood and thus not represented in dust models is their geomorphology. In this work, we investigate the geomorphology of global dust sources by developing two high-resolution (∼500 m), seamless, global maps. First is a land surface map in which landforms are classified into different categories based on geomorphology using an image classification technique. The land surface map shows the distribution of landforms in dust source regions and is useful in defining the boundaries of different dust sources in dust models. Second is the sediment supply map developed by combining the upstream drainage area with the visible reflectance retrieved by the Moderate-resolution Imaging Spectroradiometer (MODIS). This map, due to the inclusion of surface reflectance, highlights dust sources such as playa/sabkha and sand dunes and anthropogenic dust sources such as agricultural areas, that may not be captured by the commonly used elevation-based erodibility maps. We establish the connection between geomorphology and dust emission by comparing the sediment supply map with the land surface map and dust frequency map, qualitatively and quantitatively. We show that the sediment supply is linked to the land surface type and that playa/sabkha corresponds to the greatest inferred sediment supply. The sediment supply map is largely consistent with the land surface map and correlates well with the frequency of occurrence map derived from high-resolution MODIS level-2 aerosol optical depth (AOD) data.

  9. The value of snow cover maps for hydrological model calibration in snow dominated catchments in Central Asia

    Science.gov (United States)

    Duethmann, Doris; Güntner, Andreas; Peters, Juliane; Vorogushyn, Sergiy

    2013-04-01

    This study aims at investigating the value of snow cover data in addition to discharge data for the calibration of a hydrological model in six headwater catchments of the Karadarya basin, Central Asia. If a hydrological model is to be used for the investigation of potential impacts of climate change, it is important that also internal variables are simulated correctly. Snow melt is of particular relevance, as it is probably the most important runoff generation process in these catchments. The study investigates whether there is a trade-off between good simulations with respect to discharge and with respect to snow cover area. Furthermore, we are interested in the information content of snow cover data, i.e. how many snow cover images would be sufficient for effective calibration of a hydrological model. As suitable precipitation data for the study area are only available up to 1990, MODIS snow cover data could not be used and we instead resorted to AVHRR data. Processing of the AVHRR snow cover data is time consuming, because georeferencing has to be performed manually. If only few images could already exclude parameter sets resulting in low model performance with respect to snow cover area, this would be a very valuable piece of information. In order to investigate this, a varying number of snow cover images is used for model calibration within a Monte-Carlo framework, and the effect on model performance with respect to snow cover area in the validation period is evaluated. The selected study period is 1986-1989, in which both AVHRR data and other input data are available. It is split into two parts with up to around 20 snow cover scenes for model calibration and about the same number for model validation. In most of the catchments we found only a small trade-off between good simulations with respect to discharge and with respect to snow cover area, but if the parameters were selected based on the discharge objective function only, this could also include

  10. Synergy of airborne LiDAR and Worldview-2 satellite imagery for land cover and habitat mapping: A BIO_SOS-EODHaM case study for the Netherlands

    Science.gov (United States)

    Mücher, C. A.; Roupioz, L.; Kramer, H.; Bogers, M. M. B.; Jongman, R. H. G.; Lucas, R. M.; Kosmidou, V. E.; Petrou, Z.; Manakos, I.; Padoa-Schioppa, E.; Adamo, M.; Blonda, P.

    2015-05-01

    A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of

  11. Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

    Science.gov (United States)

    Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

    2011-12-01

    The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan

  12. Matching methods to produce maps for pest risk analysis to resources

    Directory of Open Access Journals (Sweden)

    Richard Baker

    2013-09-01

    Full Text Available Decision support systems (DSSs for pest risk mapping are invaluable for guiding pest risk analysts seeking to add maps to pest risk analyses (PRAs. Maps can help identify the area of potential establishment, the area at highest risk and the endangered area for alien plant pests. However, the production of detailed pest risk maps may require considerable time and resources and it is important to match the methods employed to the priority, time and detail required. In this paper, we apply PRATIQUE DSSs to Phytophthora austrocedrae, a pathogen of the Cupressaceae, Thaumetopoea pityocampa, the pine processionary moth, Drosophila suzukii, spotted wing Drosophila, and Thaumatotibia leucotreta, the false codling moth. We demonstrate that complex pest risk maps are not always a high priority and suggest that simple methods may be used to determine the geographic variation in relative risks posed by invasive alien species within an area of concern.

  13. Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

    Science.gov (United States)

    Steyaert, L.T.; Hall, F.G.; Loveland, T.R.

    1997-01-01

    A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

  14. Land Cover Mapping using GEOBIA to Estimate Loss of Salacca zalacca Trees in Landslide Area of Clapar, Madukara District of Banjarnegara

    Science.gov (United States)

    Permata, Anggi; Juniansah, Anwar; Nurcahyati, Eka; Dimas Afrizal, Mousafi; Adnan Shafry Untoro, Muhammad; Arifatha, Na'ima; Ramadhani Yudha Adiwijaya, Raden; Farda, Nur Mohammad

    2016-11-01

    Landslide is an unpredictable natural disaster which commonly happens in highslope area. Aerial photography in small format is one of acquisition method that can reach and obtain high resolution spatial data faster than other methods, and provide data such as orthomosaic and Digital Surface Model (DSM). The study area contained landslide area in Clapar, Madukara District of Banjarnegara. Aerial photographs of landslide area provided advantage in objects visibility. Object's characters such as shape, size, and texture were clearly seen, therefore GEOBIA (Geography Object Based Image Analysis) was compatible as method for classifying land cover in study area. Dissimilar with PPA (PerPixel Analyst) method that used spectral information as base object detection, GEOBIA could use spatial elements as classification basis to establish a land cover map with better accuracy. GEOBIA method used classification hierarchy to divide post disaster land cover into three main objects: vegetation, landslide/soil, and building. Those three were required to obtain more detailed information that can be used in estimating loss caused by landslide and establishing land cover map in landslide area. Estimating loss in landslide area related to damage in Salak (Salacca zalacca) plantations. This estimation towards quantity of Salak tree that were drifted away by landslide was calculated in assumption that every tree damaged by landslide had same age and production class with other tree that weren't damaged. Loss calculation was done by approximating quantity of damaged trees in landslide area with data of trees around area that were acquired from GEOBIA classification method.

  15. Analysis and Mapping of the Spectral Characteristics of Fractional Green Cover in Saline Wetlands (NE Spain Using Field and Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Manuela Domínguez-Beisiegel

    2016-07-01

    Full Text Available Inland saline wetlands are complex systems undergoing continuous changes in moisture and salinity and are especially vulnerable to human pressures. Remote sensing is helpful to identify vegetation change in semi-arid wetlands and to assess wetland degradation. Remote sensing-based monitoring requires identification of the spectral characteristics of soils and vegetation and their correspondence with the vegetation cover and soil conditions. We studied the spectral characteristics of soils and vegetation of saline wetlands in Monegros, NE Spain, through field and satellite images. Radiometric and complementary field measurements in two field surveys in 2007 and 2008 were collected in selected sites deemed as representative of different soil moisture, soil color, type of vegetation, and density. Despite the high local variability, we identified good relationships between field spectral data and Quickbird images. A methodology was established for mapping the fraction of vegetation cover in Monegros and other semi-arid areas. Estimating vegetation cover in arid wetlands is conditioned by the soil background and by the occurrence of dry and senescent vegetation accompanying the green component of perennial salt-tolerant plants. Normalized Difference Vegetation Index (NDVI was appropriate to map the distribution of the vegetation cover if the green and yellow-green parts of the plants are considered.

  16. EnviroAtlas - Minneapolis/St. Paul, MN - One Meter Resolution Urban Area Land Cover Map (MULC) (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Minneapolis-St. Paul, MN EnviroAtlas Meter-scale Urban Land Cover (MULC) data were generated from four-band (red, green, blue, and near infrared) aerial...

  17. Tetlin NWR /Scottie Creek Earth Cover Classification User's Guide

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — In 2005, the U.S. Fish and Wildlife Service and Ducks Unlimited, Inc. began a mapping effort to produce earth cover data for three National Wildlife Refuges (NWRs)...

  18. VT National Land Cover Dataset - Impervious Only - 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The LandLandcov_IMPERV2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 for mapping zone 65 was produced...

  19. Map of percent scleractinian coral cover along camera tows and ROV tracks in the Auau Channel, Island of Maui, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral overlaid on bathymetry and landsat imagery. Optical data were...

  20. Map of percent scleractinian coral cover and sand along camera tows and ROV tracks of West Maui, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This map displays optical validation observation locations and percent coverage of scleractinian coral and sand overlaid on bathymetry and landsat imagery. Optical...

  1. Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

    Science.gov (United States)

    Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

    2017-04-01

    The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the

  2. Detailed geomorphological mapping of debris-covered and rock glaciers in the Hólar area, Tröllaskagi Peninsula (northern Iceland).

    Science.gov (United States)

    Tanarro, Luis M.; Palacios, David; Zamorano, Jose J.; Andres, Nuria

    2017-04-01

    Most studies conducted on rock and debris-covered glaciers only include simplified geomorphological maps representing main units (ridges, furrows, front, and thermokarst depressions). The aim of this study is to develop a detailed geomorphological mapping of the Hóladalsjökull debris-covered glacier (65°42' N; 18°57' W) and the Fremri-Grjótárdalur rock glacier (65°43' N 19° W), located near Hólar, a village in the central area of the Trolläskagi peninsula (northern Iceland). The mapping process has been conducted using standard stereo-photointerpretation of aerial photographs and stereo-plotting of a topographic map at 1:2000 scale. Also, landforms have been represented in different transects. Lastly, the geomorphological map has been designed using the elevation digital model, and a 3D pdf file has been generated, allowing for better viewing and understanding the different units and their modelling. The geomorphological mapping of the Hóladalsjökull debris-covered glacier and the Fremri-Grjótárdalur rock glacier represents the prominent walls of their valley heads and their summits, which form a flat highland at 1,200-1,330 metres above sea level, covered by blockfield and patterned ground features. Rockfall and slide landforms are common processes at the foot of these 100-170 metre-high cirque-walls. Debris-covered glaciers and rock glaciers are born right under these walls, building up a spoon-shaped hollow around glacial ice, surrounded by young moraine ridges at their fronts. The dominant features in the Hóladalsjökull debris-covered glacier are large longitudinal ridges and furrows, stretching over 1.5 km in length in the central and western areas. Medium-sized thermokarst depressions (between 15-40 metres in diameter), often running parallel to the furrows, dot the surface of the debris-covered glacier. Parallel alternate ridges and furrows can be seen near the snout. Ridges are rugged and fall around 30-40 metres, with over 30 degree slopes

  3. Mapping Decadal Land Cover Changes in the Woodlands of North Eastern Namibia from 1975 to 2014 Using the Landsat Satellite Archived Data

    Directory of Open Access Journals (Sweden)

    Vladimir R. Wingate

    2016-08-01

    Full Text Available Woodlands and savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to subsistence and intensive agriculture or urbanized. This study investigates changes in land cover over four administrative regions of North Eastern Namibia within the Kalahari woodland savannah biome, covering a total of 107,994 km2. Land cover is mapped using multi-sensor Landsat imagery at decadal intervals from 1975 to 2014, with a post-classification change detection method. The dominant change observed was a reduction in the area of woodland savannah due to the expansion of agriculture, primarily in the form of small-scale cereal and pastoral production. More specifically, woodland savannah area decreased from 90% of the study area in 1975 to 83% in 2004, and then increased to 86% in 2014, while agricultural land increased from 6% to 12% between 1975 and 2014. We assess land cover changes in relation to towns, villages, rivers and roads and find most changes occurred in proximity to these. In addition, we find that most land cover changes occur within land designated as communally held, followed by state protected land. With widespread changes occurring across the African continent, this study provides important data for understanding drivers of change in the region and their impacts on the distribution of woodland savannahs.

  4. Land Use and Land Cover - Montana Land Cover Framework 2013

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This statewide land cover theme is a baseline digital map of Montana's natural and human land cover. The baseline map is adapted from the Northwest ReGAP project...

  5. Methodology to produce a water and energy stream map (WESM in the South African manufacturing industry

    Directory of Open Access Journals (Sweden)

    Davies, Edward

    2016-11-01

    Full Text Available The increasing demand for water and energy in South Africa, and the capacity constraints and restrictions of both resources, have led to a rapid increase in their cost. The manufacturing industry remains South Africa’s third-largest consumer of water and second- largest consumer of national energy. The improvement of water and energy efficiency is becoming an increasingly important theme for both organisational success and national economic sustainability. This paper presents the ‘lean based water and energy stream mapping framework’ developed for the manufacturing industry, with the specific objective of decreasing its water and energy intensity. As with the traditional value stream mapping tool, the water and energy stream mapping focuses on eliminating water- and energy-specific wastes within a process. Water and energy waste categories that will be used in conjunction with the framework will also be discussed. The key objective of this paper is to detail the process of creating the water and energy stream mapping, and the statistical forecasting methodology used to develop the baseline water and energy demand data. The outcome of the implementation of the framework is the future state water and energy stream mapping, which is effectively a blueprint for increased water and energy efficiency within a studied process.

  6. Mapping of

    Directory of Open Access Journals (Sweden)

    Sayed M. Arafat

    2014-06-01

    Full Text Available Land cover map of North Sinai was produced based on the FAO-Land Cover Classification System (LCCS of 2004. The standard FAO classification scheme provides a standardized system of classification that can be used to analyze spatial and temporal land cover variability in the study area. This approach also has the advantage of facilitating the integration of Sinai land cover mapping products to be included with the regional and global land cover datasets. The total study area is covering a total area of 20,310.4 km2 (203,104 hectare. The landscape classification was based on SPOT4 data acquired in 2011 using combined multispectral bands of 20 m spatial resolution. Geographic Information System (GIS was used to manipulate the attributed layers of classification in order to reach the maximum possible accuracy. GIS was also used to include all necessary information. The identified vegetative land cover classes of the study area are irrigated herbaceous crops, irrigated tree crops and rain fed tree crops. The non-vegetated land covers in the study area include bare rock, bare soils (stony, very stony and salt crusts, loose and shifting sands and sand dunes. The water bodies were classified as artificial perennial water bodies (fish ponds and irrigated canals and natural perennial water bodies as lakes (standing. The artificial surfaces include linear and non-linear features.

  7. Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set

    Directory of Open Access Journals (Sweden)

    Jinshui Zhang

    2017-04-01

    Full Text Available This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD, to determine optimal parameters for support vector data description (SVDD model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient (C and kernel width (s, in mapping homogeneous specific land cover.

  8. Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

    Science.gov (United States)

    Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

    2017-04-26

    This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient (C) and kernel width (s), in mapping homogeneous specific land cover.

  9. Mapping decadal land cover changes in the woodlands of north eastern Namibia using the Landsat satellite archive (1975-2014)

    Science.gov (United States)

    Wingate, Vladimir; Phinn, Stuart; Kuhn, Nikolaus

    2016-04-01

    Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes over 108,038 km2 in NE Namibia using multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.

  10. On the spatial and temporal resolution of land cover products for applied use in wind resource mapping

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Dellwik, Ebba

    The suitability of Copernicus Global Land Service products for wind assessment is investigated using two approaches. In the first approach the CORINE land cover database and the pan-European highresolution products were considered as input to atmospheric flow models. The CORINE data were used...

  11. WWC Quick Review of "Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping"

    Science.gov (United States)

    What Works Clearinghouse, 2011

    2011-01-01

    The study examined whether using the retrieval-practice studying technique--in which students alternate between reading a passage and writing memorable information from that passage--improved student learning of a science passage more than the study-once, repeated-study, or concept-mapping techniques. The study found that students using the…

  12. New CSIR tool produces detailed maps of SA’s economic geography

    CSIR Research Space (South Africa)

    Mass media

    2007-10-01

    Full Text Available A new digital mapping and geographic analysis platform (GAP) is enabling researchers and decision-makers to estimate the spatial distribution of economic activity in South Africa in greater detail than ever before. The result of an 18 month...

  13. Accuracy of migrant landbird habitat maps produced from LANDSAT TM data: Two case studies in southern Belize

    Science.gov (United States)

    Spruce, J.P.; Sader, S.; Robbins, C.S.; Dowell, B.A.; Wilson, Marcia H.; Sader, Steven A.

    1995-01-01

    The study investigated the utility of Landsat TM data applied to produce geo-referenced habitat maps for two study areas (Toledo and Stann Creek). Locational and non-site-specific map accuracy was evaluated by stratified random sampling and statistical analysis of satellite classification (SCR) versus air photo interpretation results (PIR) for the overall classification and individual classes. The effect of classification scheme specificity on map accuracy was also assessed. A decision criteria was developed for the minimum acceptable level of map performance (i.e., classification accuracy and scheme specificity). A satellite map was deemed acceptable if it has a useful degree of classification specificity, plus either an adequate overall locational agreement (SCR and PIR are equal). For the most detailed revised classification, overall locational accuracy ranges from 52% (5 classes) for the Toledo to 63% (9 classes) for the Stann Creek. For the least detailed revised classification, overall locational accuracy ranges from 91% (2 classes) for Toledo to 86% (5 classes) for Stann Creek. Considering both location and non-site-specific accuracy results, the most detailed yet insufficient accurate classification for both sites includes low/medium/tall broadleaf forest, broadleaf forest scrub and herb-dominated openings. For these classifications, the overall locational accuracy is 72% for Toledo (4 classes) and 75% for Stann Creek (7 classes). This level of classification detail is suitable for aiding many analyses of migrant landbird habitat use.

  14. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  15. Mapping forest plantations in Mainland China: combining remotely sensed land cover and census land use data in a land transition model

    Science.gov (United States)

    Ying, Q.; Hurtt, G. C.; Chini, L. P.; Fisk, J.; Liang, S.; Hansen, M.; Dolan, K. A.

    2013-12-01

    Forest plantations have played an important role in shaping the coverage and compositions of China's forests. Maps characterizing the spatial and temporal patterns of forest plantations in china are essential to both identifying and quantifying how forest plantations are driving changes to the countries ecosystem structure and terrestrial carbon cycle. At this time there are no detailed spatial maps of plantations in China accessible to public. Land transition model that employs Metropolis simulated annealing optimization has been demonstrated effective in land use mapping when land cover observations and land use census data are available. This study aims to map forest plantations in Mainland China by linking remote sensing observations of land cover and census statistics on land use in land transition model. Two models, a national model and a regional model were developed in the study. National model depicted a universal relationship between land cover and land use across the whole country. One of the land use data sources came from the 7th National Forest Inventory (NFI) that depicted forest plantation area in the period of 2004-2008 in each provincial jurisdictions of China (Data from Taiwan, Hongkong and Macau is not available). In accordance with land use data, MODIS yearly IGBP land cover product that contains sixteen-land cover types has been averaged upon the same time period and summarized for each province. The pairwise correlation coefficient between modeled value and reported value is 0.9996. In addition, the 95% confidence interval of true population correlation of these two variables is [0.9994, 0.9998]. Because the targeted forest plantations cover much less area compared to the other land use type of non-plantation, model precision on forest plantations was isolated to eliminate the dominance in area of non-plantation and the correlation coefficient is 0.8058. National model tends to underestimate plantation area. Due to distinct geographic and

  16. Louisiana Land Cover Data Set, UTM Zone 15 NAD83, USGS [landcover_la_nlcd_usgs_2001.tif

    Data.gov (United States)

    Louisiana Geographic Information Center — The National Land Cover Database 2001 land cover layer for mapping zone 37A was produced through a cooperative project conducted by the Multi-Resolution Land...

  17. A Discussion on Land Cover Mapping%关于土地覆被遥感监测的几点思考

    Institute of Scientific and Technical Information of China (English)

    张磊; 吴炳方

    2011-01-01

    针对国内外土地覆被遥感监测中存在的突出问题展开讨论,分析土地覆被分类系统的目标适应性; 总结现有分类算法的特点及存在问题,分析小尺度和大尺度监测技术的差异性和效果; 研究不同尺度土地覆被监测所解决的应用问题及尺度空间变化下的分类效果; 分析现有监测体系的分类精度及产生误差的原因和解决方法.%This paper has dealt with some key problems existent in land cover mapping and analyzed objective adaptability of the classification system, which include the impacts of land cover definition uncertainty on classification effects, the features and adaptability of the classification algorithms, the gap and effects of fine and coarse scale monitoring techniques, the capability of land cover scaling for application, the scaling effects on classification, the procedures, problems and solutions of the classification system of land cover, the classification algorithm and its accuracy assessment, and the factors and solutions of accuracy and errors of the current monitoring systems.

  18. From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?

    Science.gov (United States)

    Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

    2017-03-01

    Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the applicability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation proxies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegetation records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predictors. Separate models were calculated using NBI from hyperspectral data as well as from the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used (cross validated R2 = 0.89). In contrast, errors in AGB estimations were considerably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the models based on hyperspectral compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite

  19. Development of a Decision Support Tree Approach for Mapping Urban Vegetation Cover From Hyperspectral Imagery and GIS: the case of Athens, Greece

    Science.gov (United States)

    Georgopoulou, Iro; Petropoulos, George P.; Kalivas, Dionissios P.

    2013-04-01

    Urban vegetation represents one of the main factors directly influencing human life. Consequently, extracting information on its spatial distribution is of crucial importance to ensure, between other, sustainable urban planning and successful environmental management. To this end, remote sensing & Geographical Information Systems (GIS) technology has demonstrated a very promising, viable solution. In comparison to multispectral systems, use of hyperspectral imagery in particular, enhances dramatically our ability to accurately identify different targets on the Earth's surface. In our study, a decision tree-based classification method is presented for mapping urban vegetation cover from hyperspectral imagery. The ability of the proposed method is demonstrated using as a case study the city of Athens, Greece, for which satellite hyperspectral imagery from Hyperion sensor has been acquired. Hyperion collects spectral data in 242 spectral bands from visible to middle-infrared regions of electromagnetic spectrum and at a spatial resolution of 30 meters. Validation of our proposed method is carried out on a GIS environment based on the error matrix statistics, using as reference very high resolution imagery acquired nearly concurrently to Hyperion at our study region, supported by field visits conducted in the studied area. Additionally, the urban vegetation cover maps derived from our proposed here technique are compared versus analogous results obtained against other classification methods traditionally used in mapping urban vegetation cover. Our results confirmed the ability of our approach combined with Hyperion imagery to extract urban vegetation cover for the case of a densely-populated city with complex urban features, such as Athens. Our findings can potentially offer significant information at local scale as regards the presence of open green spaces in urban environment, since such information is vital for the successful infrastructure development, urban

  20. Spatial Accuracy Assessment and Integration of Global Land Cover Datasets

    Directory of Open Access Journals (Sweden)

    Nandin-Erdene Tsendbazar

    2015-11-01

    Full Text Available Along with the creation of new maps, current efforts for improving global land cover (GLC maps focus on integrating maps by accounting for their relative merits, e.g., agreement amongst maps or map accuracy. Such integration efforts may benefit from the use of multiple GLC reference datasets. Using available reference datasets, this study assesses spatial accuracy of recent GLC maps and compares methods for creating an improved land cover (LC map. Spatial correspondence with reference dataset was modeled for Globcover-2009, Land Cover-CCI-2010, MODIS-2010 and Globeland30 maps for Africa. Using different scenarios concerning the used input data, five integration methods for an improved LC map were tested and cross-validated. Comparison of the spatial correspondences showed that the preferences for GLC maps varied spatially. Integration methods using both the GLC maps and reference data at their locations resulted in 4.5%–13% higher correspondence with the reference LC than any of the input GLC maps. An integrated LC map and LC class probability maps were computed using regression kriging, which produced the highest correspondence (76%. Our results demonstrate the added value of using reference datasets and geostatistics for improving GLC maps. This approach is useful as more GLC reference datasets are becoming publicly available and their reuse is being encouraged.

  1. GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using Weights of Evidence Approach in Gengma Region, Sanjiang District, China

    Institute of Scientific and Technical Information of China (English)

    Bassam F Al Bassam

    2003-01-01

    Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydrothermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydrothermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydrothermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology,geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps defme almost similar favorable zones.Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.

  2. Optical mapping of single-molecule human DNA in disposable, mass-produced all-polymer

    DEFF Research Database (Denmark)

    Østergaard, Peter Friis; Lopacinska-Jørgensen, Joanna; Pedersen, Jonas Nyvold

    2015-01-01

    We demonstrate all-polymer injection molded devices for optical mapping of denaturation–renaturation (DR) patterns on long, single DNA-molecules from the human genome. The devices have channels with ultra-low aspect ratio, only 110 nm deep while 20 μm wide, and are superior to the silica devices...... used previously in the field. With these polymer devices, we demonstrate on-chip recording of DR images of DNA-molecules stretched to more than 95% of their contour length. The stretching is done by opposing flows Marie et al (2013 Proc. Natl Acad. Sci. USA 110 4893–8). The performance is validated...... by mapping 20 out of 24 Mbp-long DNA fragments to the human reference genome. We optimized fabrication of the devices to a yield exceeding 95%. This permits a substantial economies-of-scale driven cost-reduction, leading to device costs as low as 3 USD per device, about a factor 70 lower than the cost...

  3. Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

    Science.gov (United States)

    Olokeogun, O. S.; Iyiola, K.; Iyiola, O. F.

    2014-11-01

    Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

  4. An Object-Based Approach for Mapping Shrub and Tree Cover on Grassland Habitats by Use of LiDAR and CIR Orthoimages

    Directory of Open Access Journals (Sweden)

    Thomas Hellesen

    2013-01-01

    Full Text Available Due to the abandonment of former agricultural management practices such as mowing and grazing, an increasing amount of grassland is no longer being managed. This has resulted in increasing shrub encroachment, which poses a threat to a number of species. Monitoring is an important means of acquiring information about the condition of the grasslands. Though the use of traditional remote sensing is an effective means of mapping and monitoring land cover, the mapping of small shrubs and trees based only on spectral information is challenged by the fact that shrubs and trees often spectrally resemble grassland and thus cannot be safely distinguished and classified. With the aid of LiDAR-derived information, such as elevation, the classification of spectrally similar objects can be improved. In this study, we applied high point density LiDAR data and colour-infrared orthoimages for the classification of shrubs and trees in a study area in Denmark. The classification result was compared to a classification based only on colour-infrared orthoimages. The overall accuracy increased significantly with the use of LiDAR and, for shrubs and trees specifically, producer’s accuracy increased from 81.2% to 93.7%, and user’s accuracy from 52.9% to 89.7%. Object-based image analysis was applied in combination with a CART classifier. The potential of using the applied approach for mapping and monitoring of large areas is discussed.

  5. Utilizing NASA Earth Observations to Assess Estuary Health and Enhance Management of Water Resources in Coastal Texas through Land Cover and Precipitation Mapping

    Science.gov (United States)

    Crepps, G.; Gonsoroski, E.; Lynn, T.; Schick, R.; Pereira da Silva, R.

    2015-12-01

    This project partnered with the National Park Service (NPS) to help analyze the correlation between mesquite trees and the salinity of the Laguna Madre of Padre Island National Seashore. The lagoon is a hypersaline estuary; however, there is historical evidence that this was not always the case. It is hypothesized that the increase in the number of honey mesquite trees (Prosopis grandulosa var. glandulosa) in the area has contributed to the Laguna Madre's increased salinity by decreasing the groundwater inflow to the lagoon. These mesquite trees have long taproots capable of extracting significant amounts of groundwater. This project utilized Earth observation data in ERDAS IMAGINE and ArcGIS software to create map time series and analyze the data. Landsat 5, 7, and 8 data were used to create land use/land cover (LULC) maps in order to analyze the change in the occurrence of mesquite trees over time. Thermal maps of the lagoon were generated using Landsat 5, 7, and 8 data to understand changes in groundwater inflow. In addition, TRMM and GRACE derived changes in root zone soil moisture content data were compared over the study period. By investigating the suspected positive correlation between the mesquite trees and the salinity of the Laguna Madre, the NPS can improve future land management practices.

  6. New maps, new questions: Global cities beyond the advanced producer and financial services sector

    NARCIS (Netherlands)

    Toly, N.J.; Bouteligier, S.; Gibson, B.; Smith, G.

    2012-01-01

    This article broadens the discussion of cities as strategic sites in which global activities are organized. It deploys methodology commonly used to study the distribution and disproportionate concentration of advanced producer and financial services firms in order to study the office distribution of

  7. Using official map data on topography, wetlands and vegetation cover for prediction of stream water chemistry in boreal headwater catchments

    Directory of Open Access Journals (Sweden)

    J.-O. Andersson

    2009-04-01

    Full Text Available A large part of the spatial variation of stream water chemistry can be related to inputs from headwater streams. In order to understand and analyse the dominant processes taking place in small and heterogeneous catchments, accurate data with high spatial and temporal resolution is necessary. In most cases, the quality and resolution of available map data are considered too poor to be used in environmental assessments and modelling of headwater stream chemistry. In this study 18 forested catchments (1–4 km2 were selected within a 120×50 km region in the county of Värmland in western Sweden. The aim was to test if topographic and vegetation variables derived from official datasets were correlated to stream water chemistry, primarily the concentration of dissolved organic carbon (DOC, but also Al, Fe and Si content. GIS was used to analyse the elevation characteristics, generate topographic indices, and calculate the percentage of wetlands and a number of vegetation classes. The results clearly show that topography has a major influence on stream water chemistry. There were strong correlations between mean slope and percentage wetland, percentage wetland and DOC, mean slope and DOC, and a very strong correlation between mean topographic wetness index (TWI and DOC. The conclusion was that official topographic data, despite uncertain or of low quality and resolution, could be useful in the prediction of headwater DOC-concentration in boreal forested catchments.

  8. Raman mapping of mannitol/lysozyme particles produced via spray drying and single droplet drying

    DEFF Research Database (Denmark)

    Pekka Pajander, Jari; Matero, Sanni Elina; Sloth, Jakob

    2015-01-01

    PURPOSE: This study aimed to investigate the effect of a model protein on the solid state of a commonly used bulk agent in spray-dried formulations. METHODS: A series of lysozyme/mannitol formulations were spray-dried using a lab-scale spray dryer. Further, the surface temperature of drying droplet......-ray powder diffractometry (XRPD) and Raman microscopy. Partial Least Squares Discriminant Analysis was used for analyzing the Raman microscopy data. RESULTS: XRPD results indicated that a mixture of β-mannitol and α-mannitol was produced in the spray-drying process which was supported by the Raman analysis...

  9. Shape indexes for semi-automated detection of windbreaks in thematic tree cover maps from the central United States

    Science.gov (United States)

    Liknes, Greg C.; Meneguzzo, Dacia M.; Kellerman, Todd A.

    2017-07-01

    Windbreaks are an important ecological resource across the large expanse of agricultural land in the central United States and are often planted in straight-line or L-shaped configurations to serve specific functions. As high-resolution (i.e., morphology-based index that we have named the Straight and Narrow Feature Index (SNFI), a windbreak sinuosity index, and an area index indicating the occupied fractional area of a bounding box. The indexes were tested in two study areas: (1) a riparian area dominated by sinuous bands of trees but mixed with row crop agriculture and (2) an agricultural area with a mix of straight-line and L-shaped windbreaks. In the riparian area, a Kruskall-Wallis rank sum test indicated class differences for all three indexes, and pairwise comparisons indicate windbreaks and riparian trees are separable using any of the three indexes. SNFI also produced significant differences between windbreaks oriented in different directions (east-west vs. north-south). In the agricultural area, the Kruskall-Wallis rank sum test indicated differences between classes for all three indexes, and pairwise comparisons show that all class pairs have significant differences for at least one index, with the exception of L-shaped windbreaks vs. non-windbreak tree patches. We also used classification trees to objectively assign representative samples of tree patches to classes using both single indexes and multiple indexes. Classes were correctly assigned for more than 90% of the samples in both the riparian and agricultural study areas. In the riparian area, combining indexes did not improve accuracy compared to using SNFI alone, whereas in the agricultural area, combining the three indexes produced the best result. Thematic datasets derived from high-resolution imagery are becoming more available, and extracting useful information can be a challenge, partly due to the large amount of data to assess. Calculating the three shape indexes presented can assist with

  10. MR evaluation ex vivo and in vivo of a covered stent-graft for abdominal aortic aneurysms: ferromagnetism, heating, artifacts, and velocity mapping.

    Science.gov (United States)

    Engellau, L; Olsrud, J; Brockstedt, S; Albrechtsson, U; Norgren, L; Ståhlberg, F; Larsson, E M

    2000-07-01

    Magnetic resonance imaging (MRI) safety was evaluated at 1.5 T in a covered nickel titanium stent-graft (Vanguard) used for endovascular treatment of abdominal aortic aneurysms (AAAs). Imaging artifacts were assessed on MRI with contrast-enhanced (CE) three-dimensional (3D) MR angiography (MRA) and spiral computed tomography (CT) in 10 patients as well as ex vivo. Velocity mapping was performed in the suprarenal aorta and femoral arteries in 14 patients before and after stent-graft placement. For comparison it was also performed in six healthy volunteers. No ferromagnetism or heating was detected. Metal artifacts caused minimal image distortion on MRI/MRA. The artifacts disturbed image evaluation on CT at the graft bifurcation and graft limb junction. No significant differences in mean flow were found in patients before and after stent-graft placement. Our study indicates that MRI at 1.5 T may be performed safely in patients with the (Vanguard) stent-graft. MRI/MRA provides diagnostic image information. Velocity mapping is not included in our routine protocol.

  11. A co-training, mutual learning approach towards mapping snow cover from multi-temporal high-spatial resolution satellite imagery

    Science.gov (United States)

    Zhu, Liujun; Xiao, Pengfeng; Feng, Xuezhi; Zhang, Xueliang; Huang, Yinyou; Li, Chengxi

    2016-12-01

    High-spatial and -temporal resolution snow cover maps for mountain areas are needed for hydrological applications and snow hazard monitoring. The Chinese GF-1 satellite is potential to provide such information with a spatial resolution of 8 m and a revisit of 4 days. The main challenge for the extraction of multi-temporal snow cover from high-spatial resolution images is that the observed spectral signature of snow and snow-free areas is non-stationary in both spatial and temporal domains. As a result, successful extraction requires adequate labelled samples for each image, which is difficult to be achieved. To solve this problem, a semi-supervised multi-temporal classification method for snow cover extraction (MSCE) is proposed. This method extends the co-training based algorithms from single image classification to multi-temporal ones. Multi-temporal images in MSCE are treated as different descriptions of the same land surface, and consequently, each pixel has multiple sets of features. Independent classifiers are trained on each feature set using a few labelled samples, and then, they are iteratively re-trained in a mutual learning way using a great number of unlabelled samples. The main principle behind MSCE is that the multi-temporal difference of land surface in spectral space can be the source of mutual learning inspired by the co-training paradigm, providing a new strategy to deal with multi-temporal image classification. The experimental findings of multi-temporal GF-1 images confirm the effectiveness of the proposed method.

  12. TIPS bilateral noise reduction in 4D CT perfusion scans produces high-quality cerebral blood flow maps

    Energy Technology Data Exchange (ETDEWEB)

    Mendrik, Adrienne M; Van Ginneken, Bram; Viergever, Max A [Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands); Vonken, Evert-jan; De Jong, Hugo W; Riordan, Alan; Van Seeters, Tom; Smit, Ewoud J; Prokop, Mathias, E-mail: a.m.mendrik@gmail.com [Radiology Department, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands)

    2011-07-07

    patient data showed that the TIPS bilateral filter resulted in realistic mean values with a smaller standard deviation than the other evaluated filters and higher contrast-to-noise ratios. Therefore, applying the proposed TIPS bilateral filtering method to 4D CTP data produces higher quality CBF maps than applying the standard Gaussian, 3D bilateral or 4D bilateral filter. Furthermore, the TIPS bilateral filter is computationally faster than both the 3D and 4D bilateral filters.

  13. TIPS bilateral noise reduction in 4D CT perfusion scans produces high-quality cerebral blood flow maps

    Science.gov (United States)

    Mendrik, Adriënne M.; Vonken, Evert-jan; van Ginneken, Bram; de Jong, Hugo W.; Riordan, Alan; van Seeters, Tom; Smit, Ewoud J.; Viergever, Max A.; Prokop, Mathias

    2011-07-01

    patient data showed that the TIPS bilateral filter resulted in realistic mean values with a smaller standard deviation than the other evaluated filters and higher contrast-to-noise ratios. Therefore, applying the proposed TIPS bilateral filtering method to 4D CTP data produces higher quality CBF maps than applying the standard Gaussian, 3D bilateral or 4D bilateral filter. Furthermore, the TIPS bilateral filter is computationally faster than both the 3D and 4D bilateral filters.

  14. Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China

    Directory of Open Access Journals (Sweden)

    Chaobin Yang

    2017-02-01

    Full Text Available The spatio-temporal patterns of land use/land cover changes (LUCC can significantly affect the distribution and intensity of the urban heat island (UHI effect. However, few studies have mapped a clear picture of the influence of LUCC on UHI. In this study, both qualitative and quantitative models are employed to explore the effect of LUCC on UHI. UHI and LUCC maps were retrieved from Landsat data acquired from 1984, 1992, 2000, 2007, and 2014 to show their spatiotemporal patterns. The results showed that: (1 both the patterns of LUCC and UHI have had dramatic changes in the past 30 years. The urban area of Changchun increased more than four times, from 143.15 km2 in 1984 to 577.45 km2 in 2014, and the proportion of UHI regions has increased from 15.27% in 1984 to 29.62% in 2014; (2 the spatiotemporal changes in thermal environment were consistent with the process of urbanization. The average LST of the study area has been continuously increasing as many other land use types have been transformed to urban regions. The mean temperatures were higher in urban regions than rural areas over all of the periods, but the UHI intensity varied based on different measurements; and (3 the thermal environment inside the city varied widely even within a small area. The LST possesses a very strong positive relationship with impervious surface area (ISA, and the relationship has become stronger in recent years. The UHI we employ, specifically in this study, is SUHI (surface urban heat island.

  15. Mekong Land Cover Dasboard: Regional Land Cover Mointoring Systems

    Science.gov (United States)

    Saah, D. S.; Towashiraporn, P.; Aekakkararungroj, A.; Phongsapan, K.; Triepke, J.; Maus, P.; Tenneson, K.; Cutter, P. G.; Ganz, D.; Anderson, E.

    2016-12-01

    SERVIR-Mekong, a USAID-NASA partnership, helps decision makers in the Lower Mekong Region utilize GIS and Remote Sensing information to inform climate related activities. In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The team found that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services, including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible making the data unusable across country boundaries and with resource management partners. Many of these countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. Based on these facts, key regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. SERVIR-Mekong is currently developing a solution that leverages recent developments in remote sensing science and technology, such as Google Earth Engine (GEE), and working together with production partners to develop a system that will use a common set of input data sources to generate high

  16. Snow Cover Mapping Algorithm Based on HJ-1B Satellite Data%基于HJ-1B卫星数据的积雪面积制图算法研究

    Institute of Scientific and Technical Information of China (English)

    何咏琪; 黄晓东; 方金; 王玮; 郝晓华; 梁天刚

    2013-01-01

    Snow cover is an important factor affecting climate. Using the HJ satellite with higher spatial and temporal resolution for snow cover mapping has a great significance to promoting China's own remote sensing satellites in the field of snow monitoring. In this paper, the normalized difference snow index (NDSI) method based on HJ-1B satellite data is used to study the snow cover mapping algorithm in Darlag County, Qinghai Province. The accuracies of MODIS daily snow cover map and the HJ-1B snow cover map are compared. It is found that: 1) the suitable NDSI threshold of HJ-1B snow cover mapping algorithm is 0.37 and the total classification accuracy is 97.97%. 2) Compared with the MODIS daily snow cover map, the HJ-1B snow cover map has higher coherence with "true value" snow cover image with Khat coefficient of 0. 911, more than that of MODIS daily snow cover map, 0. 817. The accuracy of snow cover mapping algorithm based on HJ-1B is established in this study, which is reliable for snow cover dynamic monitoring in the study area. The HJ-1B with higher spatial and temporal resolution can improve the accuracy of snow cover area monitoring. However, the terrain is an important factor for snow cover monitoring accuracy when using HJ-1B data. The snow classification error increases with slope, especially the commission error.%积雪是影响气候变化的重要因子,采用更高时空分辨率的环境减灾卫星遥感数据进行积雪制图算法的研究,对推进我国自主遥感卫星在积雪监测领域的应用具有重要意义.采用环境减灾HJ-1B卫星数据,以青海省果洛藏族自治州达日县为研究区,应用归一化差值积雪指数(NDSI)法建立了基于HJ-1B卫星数据的积雪面积制图算法,并比较MODIS与HJ-1B积雪图精度.结果表明:研究区HJ-1B积雪制图合理的NDSI阈值为0.37,总分类精度达到97.97%;与“真值”影像比较,HJ-1B积雪图Khat系数为0.911,高于MODIS的0.817.说

  17. The effect of topographic normalization on fractional tree cover mapping in tropical mountains: An assessment based on seasonal Landsat time series

    Science.gov (United States)

    Adhikari, Hari; Heiskanen, Janne; Maeda, Eduardo Eiji; Pellikka, Petri K. E.

    2016-10-01

    Free archive of georectified and atmospherically corrected Landsat satellite images create a large range of opportunities for environmental research. However, the topographic effects in images are typically normalized regionally by end-users, and it remains uncertain if this procedure is always necessary. Our objective was to assess the effect of topographic normalization on the fractional tree cover (Fcover) modelling in a tropical mountain landscape, in Southeastern Kenya. We carried out topographic normalization by C-correction for all available Landsat images between June 2012 and October 2013, and examined if normalization improves Fcover regressions. The reference Fcover was based on airborne LiDAR data. Furthermore, we tested several vegetation indices and seasonal features (annual percentiles and means), and compared three digital elevation models (DEM). Our results showed that the fit of Fcover models did not improve after topographic normalization in the case of ratio-based vegetation indices (Normalized Difference Vegetation Index, NDVI; Reduced Simple Ratio, RSR) or Tasseled Cap Greenness but improved in the case of Brightness and Wetness, particularly in the period of the lowest sun elevation. RSR was the best vegetation index to predict Fcover. Furthermore, SRTM DEM provided stronger relationship with cosine of the solar incidence angle than ASTER DEM and regional DEM based on topographic maps. We conclude that NDVI and RSR are robust against topographic effects in the tropical mountain landscapes throughout the year. However, if Tasseled Cap indices are preferred, we recommend topographic normalization using SRTM DEM.

  18. Urban land use/land cover mapping with high-resolution SAR imagery by integrating support vector machines into object-based analysis

    Science.gov (United States)

    Hu, Hongtao; Ban, Yifang

    2008-10-01

    This paper investigates the capability of high-resolution SAR data for urban landuse/land-cover mapping by integrating support vector machines (SVMs) into object-based analysis. Five-date RADARSAT fine-beam C-HH SAR images with a pixel spacing of 6.25 meter were acquired over the rural-urban fringe of the Great Toronto Area (GTA) during May to August in 2002. First, the SAR images were segmented using multi-resolution segmentation algorithm and two segmentation levels were created. Next, a range of spectral, shape and texture features were selected and calculated for all image objects on both levels. The objects on the lower level then inherited features of their super objects. In this way, the objects on the lower level received detailed descriptions about their neighbours and contexts. Finally, SVM classifiers were used to classify the image objects on the lower level based on the selected features. For training the SVM, sample image objects on the lower level were used. One-against-one approach was chosen to apply SVM to multiclass classification of SAR images in this research. The results show that the proposed method can achieve a high accuracy for the classification of high-resolution SAR images over urban areas.

  19. Land Cover Characterization Program

    Science.gov (United States)

    ,

    1997-01-01

    The U.S. Geological Survey (USGS) has a long heritage of leadership and innovation in land use and land cover mapping. The USGS Anderson system defined the principles for land use and land cover mapping that have been the model both nationally and internationally for more than 20 years. The Land Cover Characterization Program (LCCP) is founded on the premise that the Nation's needs for land cover and land use data are diverse and increasingly sophisticated. The range of projects, programs, and organizations that use land cover data to meet their planning, management, development, and assessment objectives has expanded significantly. The reasons for this are numerous, and include the improved capabilities provided by geographic information systems, better and more data-intensive analytic models, and increasing requirements for improved information for decision making. The overall goals of the LCCP are to:

  20. Using Satellite Remote Sensing to Map Changes in Aquatic Invasive Plant Cover in the Sacramento-San Joaquin River Delta of California

    Science.gov (United States)

    Potter, Christopher

    2017-01-01

    Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed a 80% overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

  1. Land Cover

    Data.gov (United States)

    Kansas Data Access and Support Center — The Land Cover database depicts 10 general land cover classes for the State of Kansas. The database was compiled from a digital classification of Landsat Thematic...

  2. Water Bodies’ Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band

    Directory of Open Access Journals (Sweden)

    Yun Du

    2016-04-01

    Full Text Available Monitoring open water bodies accurately is an important and basic application in remote sensing. Various water body mapping approaches have been developed to extract water bodies from multispectral images. The method based on the spectral water index, especially the Modified Normalized Difference Water Index (MDNWI calculated from the green and Shortwave-Infrared (SWIR bands, is one of the most popular methods. The recently launched Sentinel-2 satellite can provide fine spatial resolution multispectral images. This new dataset is potentially of important significance for regional water bodies’ mapping, due to its free access and frequent revisit capabilities. It is noted that the green and SWIR bands of Sentinel-2 have different spatial resolutions of 10 m and 20 m, respectively. Straightforwardly, MNDWI can be produced from Sentinel-2 at the spatial resolution of 20 m, by upscaling the 10-m green band to 20 m correspondingly. This scheme, however, wastes the detailed information available at the 10-m resolution. In this paper, to take full advantage of the 10-m information provided by Sentinel-2 images, a novel 10-m spatial resolution MNDWI is produced from Sentinel-2 images by downscaling the 20-m resolution SWIR band to 10 m based on pan-sharpening. Four popular pan-sharpening algorithms, including Principle Component Analysis (PCA, Intensity Hue Saturation (IHS, High Pass Filter (HPF and À Trous Wavelet Transform (ATWT, were applied in this study. The performance of the proposed method was assessed experimentally using a Sentinel-2 image located at the Venice coastland. In the experiment, six water indexes, including 10-m NDWI, 20-m MNDWI and 10-m MNDWI, produced by four pan-sharpening algorithms, were compared. Three levels of results, including the sharpened images, the produced MNDWI images and the finally mapped water bodies, were analysed quantitatively. The results showed that MNDWI can enhance water bodies and suppressbuilt

  3. Using a stochastic gradient boosting algorithm to analyse the effectiveness of Landsat 8 data for montado land cover mapping: Application in southern Portugal

    Science.gov (United States)

    Godinho, Sérgio; Guiomar, Nuno; Gil, Artur

    2016-07-01

    This study aims to develop and propose a methodological approach for montado ecosystem mapping using Landsat 8 multi-spectral data, vegetation indices, and the Stochastic Gradient Boosting (SGB) algorithm. Two Landsat 8 scenes (images from spring and summer 2014) of the same area in southern Portugal were acquired. Six vegetation indices were calculated for each scene: the Enhanced Vegetation Index (EVI), the Short-Wave Infrared Ratio (SWIR32), the Carotenoid Reflectance Index 1 (CRI1), the Green Chlorophyll Index (CIgreen), the Normalised Multi-band Drought Index (NMDI), and the Soil-Adjusted Total Vegetation Index (SATVI). Based on this information, two datasets were prepared: (i) Dataset I only included multi-temporal Landsat 8 spectral bands (LS8), and (ii) Dataset II included the same information as Dataset I plus vegetation indices (LS8 + VIs). The integration of the vegetation indices into the classification scheme resulted in a significant improvement in the accuracy of Dataset II's classifications when compared to Dataset I (McNemar test: Z-value = 4.50), leading to a difference of 4.90% in overall accuracy and 0.06 in the Kappa value. For the montado ecosystem, adding vegetation indices in the classification process showed a relevant increment in producer and user accuracies of 3.64% and 6.26%, respectively. By using the variable importance function from the SGB algorithm, it was found that the six most prominent variables (from a total of 24 tested variables) were the following: EVI_summer; CRI1_spring; SWIR32_spring; B6_summer; B5_summer; and CIgreen_summer.

  4. Application of a Digital Soil Mapping Method in Producing Soil Orders on Mountain Areas of Hong Kong Based on Legacy Soil Data

    Institute of Scientific and Technical Information of China (English)

    SUN Xiao-Lin; ZHAO Yu-Guo; ZHANG Gan-Lin; WU Sheng-Chun; MAN Yu-Bon; WONG Ming-Hung

    2011-01-01

    Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods (decision tree analysis and linear discriminant analysis) were used, and their applications were compared. Much more effort was put on selecting soil covariates for modeling. First, analysis of variance (ANOVA) was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.

  5. ArcGIS和Adobe Illustrator在影像地图制作中的应用%Application of ArcGIS and Adobe Illustrator in Image Map Producing

    Institute of Scientific and Technical Information of China (English)

    陈盛银

    2013-01-01

    The expression effect of image maps which is produced by ArcGIS is not perfect. Adobe Illustrator does not support the spatial coordinates and spatial analysis. And its data processing is very complex. The combination of ArcGIS and Adobe Illustrator could be used to produce expressional richer image maps.%使用ArcGIS制作的影像地图,表达效果不够完美.而Adobe Illustrator不支持空间坐标和空间分析等,数据的处理过程比较复杂.将ArcGIS与Adobe Illustrator相结合,能够更高效地制作出表达效果更为丰富的影像地图.

  6. ANALYSIS OF IMAGERY-PRODUCING TECHNIQUES FOR DETECTION OF ANTI-PERSONNEL LANDMINES COVERED BY SHALLOW VEGETATION AND/OR SOIL - A HUMANITARIAN APPROACH

    Directory of Open Access Journals (Sweden)

    KHANDAKAR FARIDAR RAHMAN,

    2011-02-01

    Full Text Available The present paper provides a critical review about the various techniques in the detection of antipersonnel landmines used the recent past (from 1999 onwards. We have taken into consideration onlythose techniques which produce some kind of image and have been beneficial in detection of landmines hidden in shallow vegetation or soil. Our aim is to identify and analyse the effectiveness of suchtechniques in humanitarian de-mining operations in the developing countries where mine clearing prove to be very difficult due to lack of proper facilities and presence of huge population. Most of the images used and experimental results reproduced in this paper have been taken from existing works.

  7. A method for producing digital probabilistic seismic landslide hazard maps; an example from the Los Angeles, California, area

    Science.gov (United States)

    Jibson, Randall W.; Harp, Edwin L.; Michael, John A.

    1998-01-01

    The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24,000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10-m grid spacing in the ARC/INFO GIS platform. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure.

  8. International News Flows in the Post-Cold War World: Mapping the News and the News Producers.

    Science.gov (United States)

    Sreberny-Mohammadi, Annabelle

    1995-01-01

    Reviews the global political environment, major global news providers, and technologies of global news production. Argues for a multinational comparative mapping of international news representation in the 1990s. Outlines a major international venture to update and elaborate the 1979 UNESCO/IAMCR study of foreign news in the media of 29 countries,…

  9. Remote sensing, land cover changes, and vector-borne diseases: use of high spatial resolution satellite imagery to map the risk of occurrence of cutaneous leishmaniasis in Ghardaïa, Algeria.

    Science.gov (United States)

    Garni, Rafik; Tran, Annelise; Guis, Hélène; Baldet, Thierry; Benallal, Kamel; Boubidi, Said; Harrat, Zoubir

    2014-12-01

    Ghardaïa, central Algeria, experienced a major outbreak of cutaneous leishmaniasis (CL) in 2005. Two Leishmania species occur in this region: Leishmania major (MON-25) and Leishmania killicki (MON-301). The two species are transmitted respectively by the sandflies Phlebotomus papatasi and Phlebotomus sergenti and probably involve rodent reservoirs with different ecologies, suggesting distinct epidemiological patterns and distribution areas. The aims of this study were to establish risk maps for each Leishmania species in Ghardaïa, taking into account the specificities of their vectors and reservoirs biotopes, using land cover and topographical characteristics derived from remote sensing imagery. Using expert and bibliographic knowledge, habitats of vectors and reservoirs were mapped. Hazard maps, defined as areas of presence of both vectors and reservoirs, were then combined with vulnerability maps, defined as areas with human presence, to map the risk of CL occurrence due to each species. The vector habitat maps and risk maps were validated using available entomological data and epidemiological data. The results showed that remote sensing analysis can be used to map and differentiate risk areas for the two species causing CL and identify palm groves and areas bordering the river crossing the city as areas at risk of CL due to L. major, whereas more limited rocky hills on the outskirts of the city are identified as areas at risk of CL due to L. killicki. In the current context of urban development in Ghardaïa, this study provides useful information for the local authorities on the respective risk areas for CL caused by both parasites, in order to take prevention and control measures to prevent future CL outbreaks.

  10. National Land Cover Database 2001 (NLCD01)

    Science.gov (United States)

    LaMotte, Andrew E.

    2016-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  11. Which cities produce worldwide more excellent papers than can be expected? A new mapping approach--using Google Maps--based on statistical significance testing

    CERN Document Server

    Bornmann, Lutz

    2011-01-01

    The methods presented in this paper allow for a spatial analysis revealing centers of excellence around the world using programs that are freely available. Based on Web of Science data, field-specific excellence can be identified in cities where highly-cited papers were published. Compared to the mapping approaches published hitherto, our approach is more analytically oriented by allowing the assessment of an observed number of excellent papers for a city against the expected number. With this feature, this approach can not only identify the top performers in output but the "true jewels." These are cities locating authors who publish significantly more top cited papers than can be expected. As the examples in this paper show for physics, chemistry, and psychology, these cities do not necessarily have a high output of excellent papers.

  12. Rapid mapping of hurricane damage to forests

    Science.gov (United States)

    Erik M. Nielsen

    2009-01-01

    The prospects for producing rapid, accurate delineations of the spatial extent of forest wind damage were evaluated using Hurricane Katrina as a test case. A damage map covering the full spatial extent of Katrina?s impact was produced from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery using higher resolution training data. Forest damage...

  13. Forest Cover Types - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer portrays general forest cover types for the United States. Data were derived from Advanced Very High Resolution Radiometer (AVHRR) composite images...

  14. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  15. Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

    Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

  16. A 2-Mb YAC contig and physical map covering the chromosome 8q12 breakpoint cluster region in pleomorphic adenomas of the salivary glands.

    Science.gov (United States)

    Kas, K; Röijer, E; Voz, M; Meyen, E; Stenman, G; Van de Ven, W J

    1997-08-01

    Pleomorphic adenomas are benign epithelial tumors originating from the major and minor salivary glands. Extensive cytogenetic studies have demonstrated that they frequently show chromosome abnormalities involving chromosome 8, with consistent breakpoints at 8q12. In previous studies, we have shown that these breakpoints are located in a 9-cM interval between MOS/D8S285 and D8S260. Here, we describe directional chromosome walking studies starting from D8S260 as well as D8S285. Using the CEPH and ICRF YAC libraries, these studies resulted in the construction of two nonoverlapping YAC contigs of about 2 and 5 Mb, respectively. Initial fluorescence in situ hybridization (FISH) analysis suggested that the majority of 8q12 breakpoints clustered within the 2-Mb contig, which was mapped to the centromeric part of chromosome band 8q12. This contig has at least double coverage and consists of 34 overlapping YAC clones. The localization of the YACs was confirmed by FISH analysis. On the basis of mapping data of landmarks with an average spacing of 65 kb as well as restriction enzyme analysis, a long-range physical map was established for the chromosome region spanned by the 2-Mb contig. The relative positions of various known genes and expressed sequence tags within this contig were also determined. Subsequent FISH analyses of pleomorphic adenomas using YACs as well as cosmids revealed that all but two of the 8q12 breakpoints in the primary tumors tested mapped within a 300-kb interval between the MOS proto-oncogene and STS EM156. The target gene affected by the chromosome aberrations mapping within this interval was recently shown to be the PLAG1 gene, which encodes a novel zinc finger protein.

  17. An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica

    Directory of Open Access Journals (Sweden)

    Alfredo Fernández-Landa

    2016-07-01

    Full Text Available REDD+ implementation requires robust, consistent, accurate and transparent national land cover historical data and monitoring systems. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. The main aim of this paper is the creation of an operational framework for monitoring land cover dynamics based on Landsat imagery and open-source software. The methodology integrates the entire land cover and land cover change mapping processes to produce a consistent series of Land Cover maps. The consistency of the time series is achieved through the application of a single trained machine learning algorithm to radiometrically normalized imagery using iteratively re-weighted multivariate alteration detection (IR-MAD across all dates of the historical period. As a result, seven individual Land Cover maps of Costa Rica were produced from 1985/1986 to 2013/2014. Post-classification land cover change detection was performed to evaluate the land cover dynamics in Costa Rica. The validation of the land cover maps showed an overall accuracy of 87% for the 2013/2014 map, 93% for the 2000/2001 map and 89% for the 1985/1986 map. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. Forest age-classes were generated through a multi-temporal analysis of the maps. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented.

  18. Land Use and Land Cover, existing land use for Rolfe, IA, Published in 2004, 1:12000 (1in=1000ft) scale, MIDAS Council of Governments.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Hardcopy Maps information as of 2004. It is described...

  19. Land Use and Land Cover, Published in Not Provided, 1:2400 (1in=200ft) scale, La Paz County Community Development.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Hardcopy Maps information as of Not Provided. Data by...

  20. 基于判别空间条件熵加权的土地覆盖分类方法研究%A Weighted Method Using Conditional Entropy for Land Cover Mapping Based on Discriminant Space Model

    Institute of Scientific and Technical Information of China (English)

    游炯; 张景雄

    2012-01-01

    针对遥感专题类别信息的机理问题,从土地覆盖参考数据的偏差程度对分类精度的影响角度,提出了一种基于判别空间条件熵加权的土地覆盖分类方法.引入判别空间模型概念,基于此模型生成土地覆盖数据类别,并分析了土地覆盖信息类别与数据类别的语义偏差出现的深层次原因;计算信息类别与数据类别的对应关系矩阵,据此得到二者的条件熵,实现对土地覆盖信息类别与数据类别的语义偏差的量化;根据信息类别与数据类别的条件熵计算修正判别变量的权重因子,实现基于判别空间条件熵加权的土地覆盖分类.采用一景SPOT-5影像进行分类实验,并利用同一地区的Landsat 5 TM影像进行方法验证.实验表明,条件熵加权修正方法使土地覆盖分类精度有了显著提高,并对不同分辨率的遥感影像具有适用性.%In allusion to problems on the mechanism of thematic category information of remote sensing,and on the consideration of the semantic bias existed in different land cover reference data which has large influence on the classification accuracy, a weighted method using conditional entropy for land cover mapping based on discriminant space model is suggested in this paper. Discriminant space models,according to which land cover with respect to data classes can be generated,are introduced. Based on these models in discriminant space, the deep seated reasons of the semantic bias existed between land cover with respect to information classes and data classes are analyzed. Correspondence matrix between land cover with respect to information classes and data classes is generated,and the conditional entropies of land cover types with respect to information classes and data classes are also obtained, which realize the quantification of the semantic bias existed between land cover with respect to information classes and data classes. Then,weight factors to realize discriminant

  1. Evaluating the quality of the Digital Elevation Models produced from ASTER stereoscopy for topographic mapping in the Brazilian Amazon Region

    Directory of Open Access Journals (Sweden)

    Cleber G. de Oliveira

    2009-06-01

    Full Text Available Brazilian Amazon is a vast territory rich in natural renewable and non-renewable resources. Due to the adverse environmental condition (rain, cloud, dense vegetation and difficult access, topographic information is still poor, and when available needs to be up-dated or remapped. In this paper, the feasibility of using elevation generated from orbital ASTER- stereo-pairs images for topographic mapping was investigated for the mountainous relief in the Serra dos Carajás, Pará. The quality of information derived from these optical images was evaluated regarding field altimetric measurements. Precise topographic field information acquired from Global Positioning System (GPS was used as Ground Control Points (GCPs for the modeling of the stereoscopic Digital Elevation Models (DEMs and as Independent Check Points (ICPs for the calculation of elevation accuracies. The analysis was performed following two approaches: (1 the use of Root Mean Square Error (RMSE and (2 calculations of trend analysis and accuracy. The investigation has shown that the altimetric accuracy from ASTER fulfilled the Brazilian Map Accuracy Standards elevation requirements for 1:100,000 A Class. In addition, ASTER can provide up-dated planimetric information that is also necessary for cartographic production. Thus, when the environment condition allows the acquisition of stereo-pairs, the use of ASTER can be considered an alternative for semi-detailed topographic mapping in similar environments of the Brazilian Amazon.A Amazônia Brasileira é um rico e vasto território em recursos naturais renováveis e nãorenováveis. Devido às condições ambientais adversas (chuvas, nuvens, vegetação densa e difícil acesso, a informação topográfica ainda é escassa, e quando disponível necessita ser atualizada ou remapeada. Neste trabalho, a viabilidade de usar elevação para mapeamento topográfico por meio de imagens estereoscópicas orbitais ASTER foi investigada para relevo

  2. Mapping the decision points and climate information use of agricultural producers across the U.S. Corn Belt

    Directory of Open Access Journals (Sweden)

    Tonya Haigh

    2015-01-01

    Full Text Available The usefulness of climate information for agricultural risk management hinges on its availability and relevance to the producer when climate-sensitive decisions are being made. Climate information providers are challenged with the task of balancing forecast availability and lead time with acceptable forecast skill, which requires an improved understanding of the timing of agricultural decision making. Achieving a useful balance may also require an expansion of inquiry to include use of non-forecast climate information (i.e. historical climate information in agricultural decision making. Decision calendars have proven valuable for identifying opportunities for using different types of climate information. The extent to which decision-making time periods are localized versus generalized across major commodity-producing regions is yet unknown, though, which has limited their use in climate product development. Based on a 2012 survey of more than 4770 agricultural producers across the U.S. Corn Belt region, we found variation in the timing of decision-making points in the crop year based on geographic variation as well as crop management differences. Many key decisions in the cropping year take place during the preceding fall and winter, months before planting, raising questions about types of climate information that might be best inserted into risk management decisions at that time. We found that historical climate information and long term climate outlooks are less influential in agricultural risk management than current weather, short term forecasts, or monthly climate projections, even though they may, in fact, be more useful to certain types of decision making.

  3. Snow Cover Mapping in the Northern Area of Pakistan and Jammu Kashmir (hindu Kush Himalayas) Using Ndsi, Unmixing Method and Srtm dem Data

    Science.gov (United States)

    Kim, H.; Din, A. U.; Oki, K.; Takeuchi, W.; Oki, T.

    2015-12-01

    Snow area measurement is very important for hydrologists, glaciologists and for climate change researchers. Field measurement is very difficult as in case of a steep and in a complex terrain such as Himalayas, therefore we rely on remote sensing (both active and passive) data. Usually snow area is calculated from reflectance data using different snow index e.g. Normalize difference snow index (NDSI) and then it is translated into snow area. However, in most cases we are actually calculating the planimetric area or grid area of every pixel. The actual snow is along the surface of the terrain and proper estimation can only be done if actual surface area is calculated along the slope within each pixel. In the past, some researchers have introduced methodologies and optimized old mechanisms. However, the orographical impact in calculating snow area (fraction), especially in steep mountainous regions, still has many problems, and many times these problems are usually ignored which leads to under estimation of total snow amount. In this study we calculated the actual surface area from SRTM version 4.1 90m (at equator) processed DEM data provided by CGIAR-CSI. MODIS Reflectance (MOD09A1 L3 Product) composite data of 500m resolution for 2010 and 2011 in the northern areas of Pakistan, Jammu & Kashmir region where great Himalayas are stretched was used to calculate snow cover using NDSI index. Threshold of NDSI>0.4 was set to classify snow or no snow for the clear pixels and for further classification, unmixing method (subjective pixel method only) was used to calculate snow fraction within each pixel. Results shows that in a complex terrain such as Himalayas, ratio of surface to planimetric snow area is more than 50%. This means that it should be taken into consideration for more realistic snow amount estimation. Seasonal snow fraction histogram from unmixing method indicates that NDSI measures snow cover area by 1.86 times more in cold season (maximum snow area) and 1

  4. Mapping and modelling of changes in agricultural intensity in Europe

    NARCIS (Netherlands)

    Temme, A.J.A.M.; Verburg, P.H.

    2011-01-01

    Spatial maps of agricultural intensity are needed for analyses of environmental issues, including biodiversity changes. We present a method to produce such maps for Europe. While most studies beyond farm level focus on land cover change only, this paper focuses on spatial variation in land use

  5. Covering localization, mapping and evaluation of ducts, using Pipeline Current Mapper Methods (PCM); Localizacao, mapeamento e avaliacao de revestimento de dutos, utilizando o metodo Pipeline Current Mapper (PCM)

    Energy Technology Data Exchange (ETDEWEB)

    Furquim, Antonio Jorge [ESTEIO Engenharia e Aerolevantamentos S.A., Curitiba, PR (Brazil)

    2005-07-01

    Esteio Engenharia e Aerolevantamentos S.A., together with the PETROBRAS - Petroleo Brasileiro S.A., comes accomplishing the Location, Geo positioning, Mapping and Inspection of the Coating in more than 5.000 km of pipes in several areas of the country. The works come being executed seeking the obtaining of the real position of Ducts (They-Built) and the conditions in that meets the coating of the same ones. The risings base on the method Pipeline Current Mapper (PCM), using the equipment of production of Radio detection to locate and to inspect the conditions of the coating. This work presents the results, analyses, precision, benefits and difficulties found during the execution of the surveying. (author)

  6. A Mathematical Model of the Modified Atmosphere Packaging (MAP System for the Gas Transmission Rate of Fruit Produce

    Directory of Open Access Journals (Sweden)

    Li Li

    2010-01-01

    Full Text Available A mathematical model to predict oxygen, carbon dioxide, and water vapour exchanges in non-perforated and micro-perforated modified atmosphere packaging films has successfully been proposed. The transmission rate of gases was measured for films with thickness of 0.03 and 0.05 mm, perforation diameters of 0.5 and 2.0 mm, and temperatures of 0, 10 and 20 °C. Under most conditions, the increase in temperature and perforation diameter increased the transmission rate of oxygen, carbon dioxide, and water vapour, whereas the increase in film thickness decreased the transmission rate of the various gases. Validation of the proposed modified atmosphere packaging model was found to yield good prediction for gas concentrations and percentage losses in the mass of the produce after comparison with the experimental results of modified atmosphere packaging for tomato (Lycopersicon esculentum.

  7. Modeled conterminous United States Crop Cover datasets for 2000 - 2013

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  8. Modeled conterminous United States Crop Cover datasets for 2001

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  9. Modeled conterminous United States Crop Cover datasets for 2002

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  10. Modeled conterminous United States Crop Cover datasets for 2004

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  11. Modeled conterminous United States Crop Cover datasets for 2013

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  12. Modeled conterminous United States Crop Cover datasets for 2012

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  13. Modeled conterminous United States Crop Cover datasets for 2011

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  14. Modeled conterminous United States Crop Cover datasets for 2006

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  15. Modeled conterminous United States Crop Cover datasets for 2009

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The...

  16. Measurement of ion species produced due to bombardment of 450 eV N{sub 2}{sup +} ions with hydrocarbons-covered surface of tungsten: Formation of tungsten nitride

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, S. [Atomic Physics Laboratory, Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005 (India); Bhatt, P. [Inter University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi 110067 (India); Kumar, A. [Institute for Plasma Research, Bhat, Gandhinagar 382428 (India); Singh, B.K.; Singh, B.; Prajapati, S. [Atomic Physics Laboratory, Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005 (India); Shanker, R., E-mail: shankerorama@gmail.com [Atomic Physics Laboratory, Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005 (India)

    2016-08-01

    A laboratory experiment has been performed to study the ions that are produced due to collisions of 450 eV N{sub 2}{sup +} ions with a hydrocarbons-covered surface of polycrystalline tungsten at room temperature. Using a TOF mass spectrometry technique, the product ions formed in these collisions have been detected, identified and analyzed. Different ion–surface reaction processes, namely, neutralization, reflection, surface induced dissociation, surface induced chemical reactions and desorption are observed and discussed. Apart from the presence of desorbed aliphatic hydrocarbon and other ions, the mass spectra obtained from the considered collisions show the formation and sputtering of tungsten nitride (WN). A layer of WN on tungsten surface is known to decrease the sputtering of bulk tungsten in fusion devices more effectively than when the tungsten is bombarded with other seeding gases (He, Ar). It is further noted that there is a negligible diffusion of N in the bulk tungsten at room temperature.

  17. No Cover

    Science.gov (United States)

    Vargas, Dan

    2012-01-01

    Born and raised in Los Angeles, Dan Vargas spent his twenties going to punk shows at King's Palace, Club 88, the Cathay de Grand, the Vex, the Starwood, the Hong Kong Cafe, Base's Hall, and the Masque. He has produced for several bands and is currently a songwriter and singer for an LA rock band. In this article, he reflects on the…

  18. No Cover

    Science.gov (United States)

    Vargas, Dan

    2012-01-01

    Born and raised in Los Angeles, Dan Vargas spent his twenties going to punk shows at King's Palace, Club 88, the Cathay de Grand, the Vex, the Starwood, the Hong Kong Cafe, Base's Hall, and the Masque. He has produced for several bands and is currently a songwriter and singer for an LA rock band. In this article, he reflects on the…

  19. Covering R-trees

    CERN Document Server

    Berestovskii, V N

    2007-01-01

    We show that every inner metric space X is the metric quotient of a complete R-tree via a free isometric action, which we call the covering R-tree of X. The quotient mapping is a weak submetry (hence, open) and light. In the case of compact 1-dimensional geodesic space X, the free isometric action is via a subgroup of the fundamental group of X. In particular, the Sierpin'ski gasket and carpet, and the Menger sponge all have the same covering R-tree, which is complete and has at each point valency equal to the continuum. This latter R-tree is of particular interest because it is "universal" in at least two senses: First, every R-tree of valency at most the continuum can be isometrically embedded in it. Second, every Peano continuum is the image of it via an open light mapping. We provide a sketch of our previous construction of the uniform universal cover in the special case of inner metric spaces, the properties of which are used in the proof.

  20. Transient liquid-crystal technique used to produce high-resolution convective heat-transfer-coefficient maps

    Science.gov (United States)

    Hippensteele, Steven A.; Poinsatte, Philip E.

    1993-01-01

    In this transient technique the preheated isothermal model wall simulates the classic one-dimensional, semi-infinite wall heat transfer conduction problem. By knowing the temperature of the air flowing through the model, the initial temperature of the model wall, and the surface cooling rate measured at any location with time (using the fast-response liquid-crystal patterns recorded on video tape), the heat transfer coefficient can be calculated for the color isothermal pattern produced. Although the test was run transiently, the heat transfer coefficients are for the steady-state case. The upstream thermal boundary condition was considered to be isothermal. This transient liquid-crystal heat-transfer technique was used in a transient air tunnel in which a square-inlet, 3-to-1 exit transition duct was placed. The duct was preheated prior to allowing room temperature air to be suddenly drawn through it. The resulting isothermal contours on the duct surfaces were revealed using a surface coating of thermochromic liquid crystals that display distinctive colors at particular temperatures. A video record was made of the temperature and time data for all points on the duct surfaces during each test. The duct surfaces were uniformly heated using two heating systems: the first was an automatic temperature-controlled heater blanket completely surrounding the test duct like an oven, and the second was an internal hot-air loop through the inside of the test duct. The hot-air loop path was confined inside the test duct by insulated heat dams located at the inlet and exit ends of the test duct. A recirculating fan moved hot air into the duct inlet, through the duct, out of the duct exit, through the oven, and back to the duct inlet. The temperature nonuniformity of the test duct model wall was held very small. Test results are reported for two inlet Reynolds numbers of 200,000 and 1,150,000 (based on the square-inlet hydraulic diameter) and two free-stream turbulence

  1. Mekong Regional Land Cover Monitoring System Reference Methods

    Science.gov (United States)

    Saah, D.; Aekakkararungroj, A.; Phongsapan, K.; Towashiraporn, P.; Triepke, J.; Maus, P.; Tenneson, K.; Anderson, E.; Cutter, P. G.; Ganz, D.; Ate, P.; Markert, K. N.

    2016-12-01

    In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The assessment revealed that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems and accuracy assessment do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible. Many of the Lower Mekong countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. During this assessment, regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. This system is dependent on a sustainable source of field data that insures data quality and improves potential impact. Based on this need a collaborative workshop was held to create a robust regional reference data system that integrates results from field data, national inventories and high resolution imagery. The results presented here highlights the value of collaboratively developed systems that use data convergence to improve land cover mapping results for multiple end users.

  2. Mapping and improving frequency, accuracy, and interpretation of land cover change: Classifying coastal Louisiana with 1990, 1993, 1996, and 1999 Landsat Thematic Mapper image data

    Science.gov (United States)

    Nelson, G.; Ramsey, Elijah W.; Rangoonwala, A.

    2005-01-01

    Landsat Thematic Mapper images and collateral data sources were used to classify the land cover of the Mermentau River Basin within the chenier coastal plain and the adjacent uplands of Louisiana, USA. Landcover classes followed that of the National Oceanic and Atmospheric Administration's Coastal Change Analysis Program; however, classification methods needed to be developed to meet these national standards. Our first classification was limited to the Mermentau River Basin (MRB) in southcentral Louisiana, and the years of 1990, 1993, and 1996. To overcome problems due to class spectral inseparable, spatial and spectra continuums, mixed landcovers, and abnormal transitions, we separated the coastal area into regions of commonality and applying masks to specific land mixtures. Over the three years and 14 landcover classes (aggregating the cultivated land and grassland, and water and floating vegetation classes), overall accuracies ranged from 82% to 90%. To enhance landcover change interpretation, three indicators were introduced as Location Stability, Residence stability, and Turnover. Implementing methods substantiated in the multiple date MRB classification, we spatially extended the classification to the entire Louisiana coast and temporally extended the original 1990, 1993, 1996 classifications to 1999 (Figure 1). We also advanced the operational functionality of the classification and increased the credibility of change detection results. Increased operational functionality that resulted in diminished user input was for the most part gained by implementing a classification logic based on forbidden transitions. The logic detected and corrected misclassifications and mostly alleviated the necessity of subregion separation prior to the classification. The new methods provided an improved ability for more timely detection and response to landcover impact. ?? 2005 IEEE.

  3. Sganzerla Cover

    Directory of Open Access Journals (Sweden)

    Victor da Rosa

    2014-06-01

    Full Text Available http://dx.doi.org/10.5007/2175-7917.2014v19n1p158 Neste artigo, realizo uma leitura do cinema de Rogério Sganzerla, desde o clássico O bandido da luz vermelha até os documentários filmados na década de oitenta, a partir de duas noções centrais: cover e over. Para isso, parto de uma controvérsia com o ensaio de Ismail Xavier, Alegorias do subdesenvolvimento, em que o crítico realiza uma leitura do cinema brasileiro da década de sessenta através do conceito de alegoria; depois releio uma série de textos críticos do próprio Sganzerla, publicados em Edifício Sganzerla, procurando repensar as ideias de “herói vazio” ou “cinema impuro” e sugerindo assim uma nova relação do seu cinema com o tempo e a representação; então busco articular tais ideias com certos procedimentos de vanguarda, como a falsificação, a cópia, o clichê e a colagem; e finalmente procuro mostrar que, no cinema de Sganzerla, a partir principalmente de suas reflexões sobre Orson Welles, a voz é usada de maneira a deformar a interpretação naturalista.

  4. Cover Picture.

    Science.gov (United States)

    Breuning; Ruben; Lehn; Renz; Garcia; Ksenofontov; Gütlich; Wegelius; Rissanen

    2000-07-17

    The cover picture shows how both, fine arts and science, avail themselves of a system of intertwined symbolic and iconic languages. They make use of a common set of abstracted signs to report on their results. Thus, already in 1925, Wassily Kandinsky painted a masterpiece (bottom), which now, 75 years later, might be regarded as a blueprint for a scientific project. In his painting, Kandinsky pictured a grid-shaped sign that resembles in effect an actual molecular switch. Apparently following an enigmatic protocol, the groups of Lehn and Gütlich (see p. 2504 ff. for more details) constructed a grid-type inorganic architecture that operates as a three-level magnetic switch (center) triggered by three external perturbations (p, T, hnu). The switching principle is based on the spin-crossover phenomenon of Fe(II) ions and can be monitored by Mössbauer spectroscopy (left) and magnetic measurements (rear). Maybe not by chance, the English translation of the title of the painting "signs" is a homonym of "science", since both presented works are a product of the insatiable curiosity of man and his untiring desire to recognize his existence.

  5. IceMap250—Automatic 250 m Sea Ice Extent Mapping Using MODIS Data

    Directory of Open Access Journals (Sweden)

    Charles Gignac

    2017-01-01

    Full Text Available The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflective/emissive bands. Hybrid cloud-masking using both the MOD35 mask and a visibility mask, combined with downscaling of Bands 3–7 to 250 m, are utilized to delineate sea ice extent using a decision tree approach. IceMap250 was tested on scenes from the freeze-up, stable cover, and melt seasons in the Hudson Bay complex, in Northeastern Canada. IceMap250 first product is a daily composite sea ice presence map at 250 m. Validation based on comparisons with photo-interpreted ground-truth show the ability of the algorithm to achieve high classification accuracy, with kappa values systematically over 90%. IceMap250 second product is a weekly clear sky map that provides a synthesis of 7 days of daily composite maps. This map, produced using a majority filter, makes the sea ice presence map even more accurate by filtering out the effects of isolated classification errors. The synthesis maps show spatial consistency through time when compared to passive microwave and national ice services maps.

  6. Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

    Science.gov (United States)

    Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

    2017-08-01

    The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be

  7. Consistent forest change maps 1981 – 2000 from the AVHRR time series. Case studies for South America and Indonesia

    NARCIS (Netherlands)

    Eberenz, J.; Herold, M.; Verbesselt, J.; Wijaya, A.; Lindquist, E.; Defourny, P.; Gibbs, H.K.; Arino, O.; Achard, F.

    2015-01-01

    This study predicts global forest cover change for the 1980s and 1990s from AVHRR time series metrics in order to show how the series of consistent land cover maps for climate modeling produced by the ESA climate change initiative land cover project can be extended back in time. A Random Forest mode

  8. Determining coniferous forest cover and forest fragmentation with NOAA-9 advanced very high resolution radiometer data

    Science.gov (United States)

    Ripple, William J.

    1995-01-01

    NOAA-9 satellite data from the Advanced Very High Resolution Radiometer (AVHRR) were used in conjunction with Landsat Multispectral Scanner (MSS) data to determine the proportion of closed canopy conifer forest cover in the Cascade Range of Oregon. A closed canopy conifer map, as determined from the MSS, was registered with AVHRR pixels. Regression was used to relate closed canopy conifer forest cover to AVHRR spectral data. A two-variable (band) regression model accounted for more variance in conifer cover than the Normalized Difference Vegetation Index (NDVI). The spectral signatures of various conifer successional stages were also examined. A map of Oregon was produced showing the proportion of closed canopy conifer cover for each AVHRR pixel. The AVHRR was responsive to both the percentage of closed canopy conifer cover and the successional stage in these temperate coniferous forests in this experiment.

  9. Determination of Land Cover/land Use Using SPOT 7 Data with Supervised Classification Methods

    Science.gov (United States)

    Bektas Balcik, F.; Karakacan Kuzucu, A.

    2016-10-01

    Land use/ land cover (LULC) classification is a key research field in remote sensing. With recent developments of high-spatial-resolution sensors, Earth-observation technology offers a viable solution for land use/land cover identification and management in the rural part of the cities. There is a strong need to produce accurate, reliable, and up-to-date land use/land cover maps for sustainable monitoring and management. In this study, SPOT 7 imagery was used to test the potential of the data for land cover/land use mapping. Catalca is selected region located in the north west of the Istanbul in Turkey, which is mostly covered with agricultural fields and forest lands. The potentials of two classification algorithms maximum likelihood, and support vector machine, were tested, and accuracy assessment of the land cover maps was performed through error matrix and Kappa statistics. The results indicated that both of the selected classifiers were highly useful (over 83% accuracy) in the mapping of land use/cover in the study region. The support vector machine classification approach slightly outperformed the maximum likelihood classification in both overall accuracy and Kappa statistics.

  10. Midwest Cover Crops Field Guide

    Science.gov (United States)

    Producers who want to prevent soil erosion, improve nutrient cycling, sustain their soils, and protect/maintain the environment have been returning to a very old practice: planting cover crops. Cover crops are effective tools for reducing soil erosion and increasing nutrient recycling on farmlands, ...

  11. Capabilities and limitations of Landsat and land cover data for aboveground woody biomass estimation of Uganda

    NARCIS (Netherlands)

    Avitabile, V.; Baccini, A.; Friedl, M.A.; Schmullius, C.

    2012-01-01

    Aboveground woody biomass for circa-2000 is mapped at national scale in Uganda at 30-m spatial resolution on the basis of Landsat ETM + images, a National land cover dataset and field data using an object-oriented approach. A regression tree-based model (Random Forest) produces good results (cross-v

  12. Using satellite data in map design and production

    Science.gov (United States)

    Hutchinson, John A.

    2002-01-01

    Satellite image maps have been produced by the U.S. Geological Survey (USGS) since shortly after the launch of the first Landsat satellite in 1972. Over the years, the use of image data to design and produce maps has developed from a manual and photographic process to one that incorporates geographic information systems, desktop publishing, and digital prepress techniques. At the same time, the content of most image-based maps produced by the USGS has shifted from raw image data to land cover or other information layers derived from satellite imagery, often portrayed in combination with shaded relief.

  13. Knockdown of MAP4 and DNAL1 produces a post-fusion and pre-nuclear translocation impairment in HIV-1 replication.

    Science.gov (United States)

    Gallo, Daniel E; Hope, Thomas J

    2012-01-05

    DNAL1 and MAP4 are both microtubule-associated proteins. These proteins were identified as HIV-1 dependency factors in a screen with wild-type HIV-1. In this study we demonstrate that knockdown using DNAL1 and MAP4 siRNAs and shRNAs inhibits HIV-1 infection regardless of envelope. Using a fusion assay, we show that DNAL1 and MAP4 do not impact fusion. By assaying for late reverse transcripts and 2-LTR circles, we show that DNAL1 and MAP4 inhibit both by approximately 50%. These results demonstrate that DNAL1 and MAP4 impact reverse transcription but not nuclear translocation. DNAL1 and MAP4 knockdown cells do not display cytoskeletal defects. Together these experiments indicate that DNAL1 and MAP4 may exert their functions in the HIV life cycle at reverse transcription, prior to nuclear translocation.

  14. Mapping Deeply

    OpenAIRE

    Denis Wood

    2015-01-01

    This is a description of an avant la lettre deep mapping project carried out by a geographer and a number of landscape architecture students in the early 1980s. Although humanists seem to take the “mapping” in deep mapping more metaphorically than cartographically, in this neighborhood mapping project, the mapmaking was taken literally, with the goal of producing an atlas of the neighborhood. In this, the neighborhood was construed as a transformer, turning the stuff of the world (gas, wate...

  15. Concepts and Key Techniques for 30 m Global Land Cover Mapping%全球30 m地表覆盖遥感制图的总体技术

    Institute of Scientific and Technical Information of China (English)

    陈军; 何超英; 武昊; 陆苗; 陈晋; 廖安平; 曹鑫; 陈利军; 陈学泓; 彭舒; 韩刚; 张宏伟

    2014-01-01

    针对全球30 m分辨率地表覆盖遥感制图这一世界性难题,提出了以多源影像最优化处理、参考资料服务化整合、覆盖类型精细化提取、产品质量多元化检核为主线的总体研究思路,研发了影像几何与辐射重建、异质异构服务化集成、对象化分层分类、知识化检核处理等主体技术方法;用于制定了相应数据产品规范、生产技术规范,研发了多项生产型软件,用于研制了2000和2010两个基准年的全球30 m地表覆盖数据产品,将空间分辨率提高了1个数量级。%Global land cover (GLC)characterization and monitoring at fine resolution is a key task and big challenge for both earth observation and geomatics societies in the world .Recently the first operational 30 m GLC mapping project has been completed by China .It is based on the optimum selection and processing of landsat-like satellite imagery for full global coverage ,service-oriented integration of all available reference data and auxiliary information , object-based precise land cover characterization ,and knowledge-based data quality controlling .The key techniques developed include the multi-type imagery geometric processing and radiometric reconstruction ,integration of heterogeneous data and external services ,object-based thematic-layer classification , and knowledge-based spatio-temporal consistency verification . The technical guide lines and software tools have been further developed for supporting the operational 30 m GLC mapping of the years 2000 and 2010 .

  16. MODIS land cover uncertainty in regional climate simulations

    Science.gov (United States)

    Li, Xue; Messina, Joseph P.; Moore, Nathan J.; Fan, Peilei; Shortridge, Ashton M.

    2017-02-01

    MODIS land cover datasets are used extensively across the climate modeling community, but inherent uncertainties and associated propagating impacts are rarely discussed. This paper modeled uncertainties embedded within the annual MODIS Land Cover Type (MCD12Q1) products and propagated these uncertainties through the Regional Atmospheric Modeling System (RAMS). First, land cover uncertainties were modeled using pixel-based trajectory analyses from a time series of MCD12Q1 for Urumqi, China. Second, alternative land cover maps were produced based on these categorical uncertainties and passed into RAMS. Finally, simulations from RAMS were analyzed temporally and spatially to reveal impacts. Our study found that MCD12Q1 struggles to discriminate between grasslands and croplands or grasslands and barren in this study area. Such categorical uncertainties have significant impacts on regional climate model outputs. All climate variables examined demonstrated impact across the various regions, with latent heat flux affected most with a magnitude of 4.32 W/m2 in domain average. Impacted areas were spatially connected to locations of greater land cover uncertainty. Both biophysical characteristics and soil moisture settings in regard to land cover types contribute to the variations among simulations. These results indicate that formal land cover uncertainty analysis should be included in MCD12Q1-fed climate modeling as a routine procedure.

  17. Topographic mapping

    Science.gov (United States)

    ,

    2008-01-01

    The U.S. Geological Survey (USGS) produced its first topographic map in 1879, the same year it was established. Today, more than 100 years and millions of map copies later, topographic mapping is still a central activity for the USGS. The topographic map remains an indispensable tool for government, science, industry, and leisure. Much has changed since early topographers traveled the unsettled West and carefully plotted the first USGS maps by hand. Advances in survey techniques, instrumentation, and design and printing technologies, as well as the use of aerial photography and satellite data, have dramatically improved mapping coverage, accuracy, and efficiency. Yet cartography, the art and science of mapping, may never before have undergone change more profound than today.

  18. Some Semi - Equivelar Maps

    CERN Document Server

    Upadhyay, Ashish K; Maity, Dipendu

    2011-01-01

    Semi-Equivelar maps are generalizations of Archimedean Solids (as are equivelar maps of the Platonic solids) to the surfaces other than $2-$Sphere. We classify some semi equivelar maps on surface of Euler characteristic -1 and show that none of these are vertex transitive. We establish existence of 12-covered triangulations for this surface. We further construct double cover of these maps to show existence of semi-equivelar maps on the surface of double torus. We also construct several semi-equivelar maps on the surfaces of Euler characteristics -8 and -10 and on non-orientable surface of Euler characteristics -2.

  19. A global dataset of crowdsourced land cover and land use reference data.

    Science.gov (United States)

    Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F; Danylo, Olha; Sturn, Tobias; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael

    2017-06-13

    Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

  20. Three-dimensional (3D) coseismic deformation map produced by the 2014 South Napa Earthquake estimated and modeled by SAR and GPS data integration

    Science.gov (United States)

    Polcari, Marco; Albano, Matteo; Fernández, José; Palano, Mimmo; Samsonov, Sergey; Stramondo, Salvatore; Zerbini, Susanna

    2016-04-01

    In this work we present a 3D map of coseismic displacements due to the 2014 Mw 6.0 South Napa earthquake, California, obtained by integrating displacement information data from SAR Interferometry (InSAR), Multiple Aperture Interferometry (MAI), Pixel Offset Tracking (POT) and GPS data acquired by both permanent stations and campaigns sites. This seismic event produced significant surface deformation along the 3D components causing several damages to vineyards, roads and houses. The remote sensing results, i.e. InSAR, MAI and POT, were obtained from the pair of SAR images provided by the Sentinel-1 satellite, launched on April 3rd, 2014. They were acquired on August 7th and 31st along descending orbits with an incidence angle of about 23°. The GPS dataset includes measurements from 32 stations belonging to the Bay Area Regional Deformation Network (BARDN), 301 continuous stations available from the UNAVCO and the CDDIS archives, and 13 additional campaign sites from Barnhart et al, 2014 [1]. These data constrain the horizontal and vertical displacement components proving to be helpful for the adopted integration method. We exploit the Bayes theory to search for the 3D coseismic displacement components. In particular, for each point, we construct an energy function and solve the problem to find a global minimum. Experimental results are consistent with a strike-slip fault mechanism with an approximately NW-SE fault plane. Indeed, the 3D displacement map shows a strong North-South (NS) component, peaking at about 15 cm, a few kilometers far from the epicenter. The East-West (EW) displacement component reaches its maximum (~10 cm) south of the city of Napa, whereas the vertical one (UP) is smaller, although a subsidence in the order of 8 cm on the east side of the fault can be observed. A source modelling was performed by inverting the estimated displacement components. The best fitting model is given by a ~N330° E-oriented and ~70° dipping fault with a prevailing

  1. Efficient construction of a physical map by Fiber-FISH of the CLN5 region: Refined assignment and long-range contig covering the critical region on 13q22

    Energy Technology Data Exchange (ETDEWEB)

    Klockars, T.; Savukoski, M.; Isosomppi, J. [National Public Health Institute, Helsinki (Finland)] [and others

    1996-07-01

    The variant form of late infantile neuronal ceroid lipofuscinosis (vLINCL, locus definition CLN5) represents a progressive brain disease with autosomal recessive inheritance. We have previously assigned the CLN5 locus to chromosome 13q21.1-132 between markers D13S160 and D13S162 by linkage analysis in Finnish families. The information on ancient recombination events obtained from linkage disequilibrium provided an efficient tool for further refining the assignment of the CLN5 locus. Isolation of two novel (CA){sub n} markers, COLAC1 and AC224, resulted in a dramatic restriction of the critical DNA region. We utilized the Fiber-FISH technique to orient and order the large DNA clones isolated by STSs and were able to eliminate almost totally the restriction digestion and PFGE step in the construction of the long-range DNA contig. Both linkage disequilibrium data and Fiber-FISH analyses assigned the CLN5 locus to a well-defined 200-kb region. Here we report a complete physical map of about 350 kb covering the critical chromosomal region of CLN5, which will facilitate the final isolation of the CLN5 gene. 31 refs., 4 figs., 2 tabs.

  2. Global Land Cover Characterization: 1992-1993

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey (USGS) has a long history of involvement in multi-scale, and multi-temporal land cover characterization and mapping of the world. During...

  3. Assessing Hydrologic Impacts of Future Land Cover Change ...

    Science.gov (United States)

    Long‐term land‐use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed on the San Pedro River Basin to characterize hydrologic impacts from future urban growth through time. This methodology was then expanded and utilized to characterize the changing hydrology on the South Platte River Basin. Future urban growth is represented by housingdensity maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land‐Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and describe a methodology for adapting the ICLUS data for use in AGWA as anapproach to evaluate basin‐wide impacts of development on water‐quantity and ‐quality, 2) present initial results from the application of the methodology to

  4. Assessing Hydrologic Impacts of Future Land Cover Change ...

    Science.gov (United States)

    Long‐term land‐use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed on the San Pedro River Basin to characterize hydrologic impacts from future urban growth through time. This methodology was then expanded and utilized to characterize the changing hydrology on the South Platte River Basin. Future urban growth is represented by housingdensity maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land‐Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and describe a methodology for adapting the ICLUS data for use in AGWA as anapproach to evaluate basin‐wide impacts of development on water‐quantity and ‐quality, 2) present initial results from the application of the methodology to

  5. Mapping global cropland and field size.

    Science.gov (United States)

    Fritz, Steffen; See, Linda; McCallum, Ian; You, Liangzhi; Bun, Andriy; Moltchanova, Elena; Duerauer, Martina; Albrecht, Fransizka; Schill, Christian; Perger, Christoph; Havlik, Petr; Mosnier, Aline; Thornton, Philip; Wood-Sichra, Ulrike; Herrero, Mario; Becker-Reshef, Inbal; Justice, Chris; Hansen, Matthew; Gong, Peng; Abdel Aziz, Sheta; Cipriani, Anna; Cumani, Renato; Cecchi, Giuliano; Conchedda, Giulia; Ferreira, Stefanus; Gomez, Adriana; Haffani, Myriam; Kayitakire, Francois; Malanding, Jaiteh; Mueller, Rick; Newby, Terence; Nonguierma, Andre; Olusegun, Adeaga; Ortner, Simone; Rajak, D Ram; Rocha, Jansle; Schepaschenko, Dmitry; Schepaschenko, Maria; Terekhov, Alexey; Tiangwa, Alex; Vancutsem, Christelle; Vintrou, Elodie; Wenbin, Wu; van der Velde, Marijn; Dunwoody, Antonia; Kraxner, Florian; Obersteiner, Michael

    2015-05-01

    A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

  6. Land Cover Differences in Soil Carbon and Nitrogen at Fort Benning, Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Garten Jr., C.T.

    2004-02-09

    Land cover characterization might help land managers assess the impacts of management practices and land cover change on attributes linked to the maintenance and/or recovery of soil quality. However, connections between land cover and measures of soil quality are not well established. The objective of this limited investigation was to examine differences in soil carbon and nitrogen among various land cover types at Fort Benning, Georgia. Forty-one sampling sites were classified into five major land cover types: deciduous forest, mixed forest, evergreen forest or plantation, transitional herbaceous vegetation, and barren land. Key measures of soil quality (including mineral soil density, nitrogen availability, soil carbon and nitrogen stocks, as well as properties and chemistry of the O-horizon) were significantly different among the five land covers. In general, barren land had the poorest soil quality. Barren land, created through disturbance by tracked vehicles and/or erosion, had significantly greater soil density and a substantial loss of carbon and nitrogen relative to soils at less disturbed sites. We estimate that recovery of soil carbon under barren land at Fort Benning to current day levels under transitional vegetation or forests would require about 60 years following reestablishment of vegetation. Maps of soil carbon and nitrogen were produced for Fort Benning based on a 1999 land cover map and field measurements of soil carbon and nitrogen stocks under different land cover categories.

  7. Enhanced National Land Cover Data 1992 (NLCDe 92)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The enhanced National Land Cover Data 1992 ("NLCDe 92") served as the primary source for nationally consistent mapped land cover during the first decade of sampling...

  8. Land cover dynamics in Wa Municipality, Upper West Region of Ghana

    Directory of Open Access Journals (Sweden)

    M.S. Aduah

    2012-06-01

    Full Text Available Land cover change is pervasive in urban areas and can destabilise the ecosystem with negative consequences. To manage land effectively and to protect its cover, there is the need for a reliable inventory. GIS and remote sensing technology has become a standard in producing land cover maps worldwide. Therefore, in this study GIS and remote sensing was used to map the land cover of Wa Municipality of the Upper West Region of Ghana. Two Landsat 5 images of 1986 and 2011 were used. The images were pre-processed, subset to the study area and classified using the maximum likelihood classification algorithm. The map accuracies for the classes of interest; built-up, bare land and vegetation were not less than 70%. The land cover maps generated indicated that built-up area has increased by 34% whiles total size of bare land has increased by 47% from 1986 to 2011.These increases have reduced the total area of vegetated land by 10%. Therefore, if the current rate of degradation is not controlled, biodiversity of Wa and its surrounding areas would be lost in the near future. Also the degradation can intensify floods and droughts and other effects of climate change. The current study has demonstrated the effectiveness of GIS and remote sensing in studying environmental changes taking place in semi-arid regions. The application of remote sensing technologies should be intensified especially in the developing world to continue to provide vital data needed to manage the environment in a sustainable manner.

  9. 2005 Kansas Land Cover Patterns, Level I, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The Upper Kansas River Watershed Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period as part of a...

  10. 2005 Kansas Land Cover Patterns, Level IV, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while...

  11. North American Land Cover Characteristics ? 1-Kilometer Resolution - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer is an Arc/INFO grid map of land cover characteristics for North America, excluding Hawaii, and including the Caribbean and most of Mexico. The nominal...

  12. LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

    Science.gov (United States)

    See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

    2016-04-01

    The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

  13. The Effect of Illumination and Viewing Geometry and Forest Canopies on the Estimation of Snow Cover Using Remote Sensing

    Science.gov (United States)

    Liu, J.; Woodcock, C. E.; Melloh, R. A.; Davis, R. E.

    2003-12-01

    With the exception of cloud cover, the largest obstacle to producing a global daily snow cover product using remotely sensed data is the presence of the forests, which cover much of the seasonally snow-covered portion of the world. The presence of the forest canopy influences the radiance received by the sensor in such a way that the proportion of viewable snow within a pixel changes as a function of forest properties, topography and viewing position. To explore the potential effects of sun angle and viewing geometry of satellite systems such as NOAA AVHRR and MODIS on snow cover estimation, a program has been written to estimate viewable gap fractions (VGF) across landscapes based on the Li-Strahler geometric-optical (GO) bidirectional reflectance distribution function (BRDF) model. It computes a VGF map for a specified illumination and viewing geometry using maps of forest cover and species and terrain images of slope and aspect. This study explores the effect of illumination and viewing geometry and forest properties on the VGF for the Fool's Creek Intensive Study Area (ISA) in Fraser Experimental Forest, Colorado. Intensive field measurements of the required parameters for the GO model and maps of forest properties are used to generate maps of viewable gap fractions. Hemispherical photos are used to validate model results. The results improve our understanding of the way forest canopies influence the estimation of snow cover using remotely sensed data.

  14. Managing cover crops: an economic perspective

    Science.gov (United States)

    Common reasons given by producers as to why they do not adopt cover crops are related to economics: time, labor, and cost required for planting and managing cover crops. While many of the agronomic benefits of cover crops directly relate to economics, there are costs associated with adopting the pra...

  15. Using MERIS for mountain vegetation mapping and monitoring in Sweden

    OpenAIRE

    Reese, Heather; Nilsson, Mats; Olsson, Håkan

    2007-01-01

    The objective of this study is to apply ENVISAT MERIS data in mapping mountain vegetation in Sweden. The Swedish mountain vegetation is characterized by mosaics of different land cover types; a single MERIS pixel (300 meter IFOV) can consist of several of these different land cover types. “Hard” classifications which produce a single thematic class per pixel often give a low accuracy. While many different unmixing methods are reviewed in the literature, the use of regression trees is reported...

  16. Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

    Science.gov (United States)

    Hansen, M.C.; Egorov, Alexey; Potapov, P.V.; Stehman, S.V.; Tyukavina, A.; Turubanova, S.A.; Roy, David P.; Goetz, S.J.; Loveland, T.R.; Ju, J.; Kommareddy, A.; Kovalskyy, Valeriy; Forsyth, C.; Bents, T.

    2014-01-01

    Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by

  17. From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach.

    Science.gov (United States)

    Fyfe, Ralph M; Woodbridge, Jessie; Roberts, Neil

    2015-03-01

    Maps of continental-scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time-scales. User groups with an interest in past land cover include the climate modelling community, socio-ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan-European land cover change for the period 9000 bp to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 bp through reduction in broad-leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan-European scale moved outside the range of previous background variability from 4000 bp onwards. From 2200 bp land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 bp. Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover-climate interactions, and the origins of the modern cultural landscape.

  18. Comparative genomic mapping of the bovine Fragile Histidine Triad (FHIT tumour suppressor gene: characterization of a 2 Mb BAC contig covering the locus, complete annotation of the gene, analysis of cDNA and of physiological expression profiles

    Directory of Open Access Journals (Sweden)

    Boussaha Mekki

    2006-05-01

    Full Text Available Abstract Background The Fragile Histidine Triad gene (FHIT is an oncosuppressor implicated in many human cancers, including vesical tumors. FHIT is frequently hit by deletions caused by fragility at FRA3B, the most active of human common fragile sites, where FHIT lays. Vesical tumors affect also cattle, including animals grazing in the wild on bracken fern; compounds released by the fern are known to induce chromosome fragility and may trigger cancer with the interplay of latent Papilloma virus. Results The bovine FHIT was characterized by assembling a contig of 78 BACs. Sequence tags were designed on human exons and introns and used directly to select bovine BACs, or compared with sequence data in the bovine genome database or in the trace archive of the bovine genome sequencing project, and adapted before use. FHIT is split in ten exons like in man, with exons 5 to 9 coding for a 149 amino acids protein. VISTA global alignments between bovine genomic contigs retrieved from the bovine genome database and the human FHIT region were performed. Conservation was extremely high over a 2 Mb region spanning the whole FHIT locus, including the size of introns. Thus, the bovine FHIT covers about 1.6 Mb compared to 1.5 Mb in man. Expression was analyzed by RT-PCR and Northern blot, and was found to be ubiquitous. Four cDNA isoforms were isolated and sequenced, that originate from an alternative usage of three variants of exon 4, revealing a size very close to the major human FHIT cDNAs. Conclusion A comparative genomic approach allowed to assemble a contig of 78 BACs and to completely annotate a 1.6 Mb region spanning the bovine FHIT gene. The findings confirmed the very high level of conservation between human and bovine genomes and the importance of comparative mapping to speed the annotation process of the recently sequenced bovine genome. The detailed knowledge of the genomic FHIT region will allow to study the role of FHIT in bovine cancerogenesis

  19. What Medicare Covers

    Science.gov (United States)

    ... What Part A covers Medicare Part A hospital insurance covers inpatient hospital care, skilled nursing facility, hospice, lab tests, surgery, ... Medicare Covers Drug Coverage (Part D) Supplements & Other Insurance Claims & ... doctors, providers, hospitals & plans Where can I get covered medical items? ...

  20. Mapping Hurricane Rita inland storm tide

    Science.gov (United States)

    Berenbrock, Charles; Mason, Jr., Robert R.; Blanchard, Stephen F.; Simonovic, Slobodan P.

    2009-01-01

    Flood-inundation data are most useful for decision makers when presented in the context of maps of effected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems (GIS) provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3-hour intervals from midnight (0000 hour) through noon (1200 hour) on September 24, 2005. The improved maps depict storm-tide elevations and the extent of flooding. The extent of storm-tide inundation from the improved maximum storm-tide map was compared to the extent of flood-inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross-section profile that parallels the Louisiana coast was developed from the maximum storm-tide map and included FEMA high-water marks.

  1. Live Coral Cover Index Testing and Application with Hyperspectral Airborne Image Data

    Directory of Open Access Journals (Sweden)

    Karen E. Joyce

    2013-11-01

    Full Text Available Coral reefs are complex, heterogeneous environments where it is common for the features of interest to be smaller than the spatial dimensions of imaging sensors. While the coverage of live coral at any point in time is a critical environmental management issue, image pixels may represent mixed proportions of coverage. In order to address this, we describe the development, application, and testing of a spectral index for mapping live coral cover using CASI-2 airborne hyperspectral high spatial resolution imagery of Heron Reef, Australia. Field surveys were conducted in areas of varying depth to quantify live coral cover. Image statistics were extracted from co-registered imagery in the form of reflectance, derivatives, and band ratios. Each of the spectral transforms was assessed for their correlation with live coral cover, determining that the second derivative around 564 nm was the most sensitive to live coral cover variations(r2 = 0.63. Extensive field survey was used to transform relative to absolute coral cover, which was then applied to produce a live coral cover map of Heron Reef. We present the live coral cover index as a simple and viable means to estimate the amount of live coral over potentially thousands of km2 and in clear-water reefs.

  2. Mapping in the cloud

    CERN Document Server

    Peterson, Michael P

    2014-01-01

    This engaging text provides a solid introduction to mapmaking in the era of cloud computing. It takes students through both the concepts and technology of modern cartography, geographic information systems (GIS), and Web-based mapping. Conceptual chapters delve into the meaning of maps and how they are developed, covering such topics as map layers, GIS tools, mobile mapping, and map animation. Methods chapters take a learn-by-doing approach to help students master application programming interfaces and build other technical skills for creating maps and making them available on the Internet. Th

  3. Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative

    Science.gov (United States)

    Poulter, B.; MacBean, N.; Hartley, A.; Khlystova, I.; Arino, O.; Betts, R.; Bontemps, S.; Boettcher, M.; Brockmann, C.; Defourny, P.; Hagemann, S.; Herold, M.; Kirches, G.; Lamarche, C.; Lederer, D.; Ottlé, C.; Peters, M.; Peylin, P.

    2015-07-01

    Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land cover data sets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily transferable to the requirements of earth system models. In 2009, the European Space Agency launched the Climate Change Initiative (CCI), with land cover (LC_CCI) as 1 of 13 essential climate variables targeted for research development. The LC_CCI was implemented in three phases: first responding to a survey of user needs; developing a global, moderate-resolution land cover data set for three time periods, or epochs (2000, 2005, and 2010); and the last phase resulting in a user tool for converting land cover to plant functional type equivalents. Here we present the results of the LC_CCI project with a focus on the mapping approach used to convert the United Nations Land Cover Classification System to plant functional types (PFTs). The translation was performed as part of consultative process among map producers and users, and resulted in an open-source conversion tool. A comparison with existing PFT maps used by three earth system modeling teams shows significant differences between the LC_CCI PFT data set and those currently used in earth system models with likely consequences for modeling terrestrial biogeochemistry and land-atmosphere interactions. The main difference between the new LC_CCI product and PFT data sets used currently by three different dynamic global vegetation modeling teams is a reduction in high-latitude grassland cover, a reduction in tropical tree cover and an expansion in temperate forest cover in Europe. The LC_CCI tool is flexible for users to modify land cover to PFT conversions and will evolve as phase 2 of the European Space Agency CCI program continues.

  4. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  5. Urban land cover thematic disaggregation, employing datasets from multiple sources and RandomForests modeling

    Science.gov (United States)

    Gounaridis, Dimitrios; Koukoulas, Sotirios

    2016-09-01

    Urban land cover mapping has lately attracted a vast amount of attention as it closely relates to a broad scope of scientific and management applications. Late methodological and technological advancements facilitate the development of datasets with improved accuracy. However, thematic resolution of urban land cover has received much less attention so far, a fact that hampers the produced datasets utility. This paper seeks to provide insights towards the improvement of thematic resolution of urban land cover classification. We integrate existing, readily available and with acceptable accuracies datasets from multiple sources, with remote sensing techniques. The study site is Greece and the urban land cover is classified nationwide into five classes, using the RandomForests algorithm. Results allowed us to quantify, for the first time with a good accuracy, the proportion that is occupied by each different urban land cover class. The total area covered by urban land cover is 2280 km2 (1.76% of total terrestrial area), the dominant class is discontinuous dense urban fabric (50.71% of urban land cover) and the least occurring class is discontinuous very low density urban fabric (2.06% of urban land cover).

  6. Produtividade e qualidade da uva 'Cabernet Sauvignon'produzida sob cobertura de plástico em cultivo orgânico Productivity and quality of grape 'Cabernet Sauvignon' produced in organic sistem under plastic covering

    Directory of Open Access Journals (Sweden)

    Alessandra Maria Detoni

    2007-01-01

    quality of the grape 'Cabernet Sauvignon' cultivated under covering of plastic in organic production system. The experiment was accomplished in an organic orchard in the west area of the state of Paraná; the plants were conducted in espalier system, with plastic covering in the planting line. It was evaluated tenor of soluble solids (SS, titrable acidity (TA, pH, total antocyanins, productivity, number of bunches for plant and medium bunch weight. They were not found significant differences in the tenor of SS (17.3ºBrix, however the fruits under the covering presented larger tenors of TA and pH, 1.14 g 100 mL-1 and 3.4 respectively, that those picked from plants without the plastic covering, which presented TA of 0.87 g 100 mL-1 and pH of 3.5. The largest tenor of total antocyanins was verified in the plants out of the covering, with 22.8 mg L-1. In the protected plants, the production was larger (1769 g plant-1 than in the plants without covering (492 g plant-1, which presented high index of diseases. It is concluded that the plastic covering makes possible the cultivation of grape 'Cabernet Sauvignon' in the organic production system, for providing a decrease in the incidence of diseases.

  7. URBAN LAND COVER/USE CHANGE DETECTION USING HIGH RESOLUTION SPOT 5 AND SPOT 6 IMAGES AND URBAN ATLAS NOMENCLATURE

    Directory of Open Access Journals (Sweden)

    S. S. Akay

    2016-06-01

    Full Text Available Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI, Difference Water Index (NDWI maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy

  8. Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

    Science.gov (United States)

    Akay, S. S.; Sertel, E.

    2016-06-01

    Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was

  9. Mapping the Natchez Trace Parkway

    Science.gov (United States)

    Rangoonwala, Amina; Bannister, Terri; Ramsey, Elijah W.

    2011-01-01

    Based on a National Park Service (NPS) landcover classification, a landcover map of the 715-km (444-mile) NPS Natchez Trace Parkway (hereafter referred to as the "Parkway") was created. The NPS landcover classification followed National Vegetation Classification (NVC) protocols. The landcover map, which extended the initial landcover classification to the entire Parkway, was based on color-infrared photography converted to 1-m raster-based digital orthophoto quarter quadrangles, according to U.S. Geological Survey mapping standards. Our goal was to include as many alliance classes as possible in the Parkway landcover map. To reach this goal while maintaining a consistent and quantifiable map product throughout the Parkway extent, a mapping strategy was implemented based on the migration of class-based spectral textural signatures and the congruent progressive refinement of those class signatures along the Parkway. Progressive refinement provided consistent mapping by evaluating the spectral textural distinctiveness of the alliance-association classes, and where necessary, introducing new map classes along the Parkway. By following this mapping strategy, the use of raster-based image processing and geographic information system analyses for the map production provided a quantitative and reproducible product. Although field-site classification data were severely limited, the combination of spectral migration of class membership along the Parkway and the progressive classification strategy produced an organization of alliances that was internally highly consistent. The organization resulted from the natural patterns or alignments of spectral variance and the determination of those spectral patterns that were compositionally similar in the dominant species as NVC alliances. Overall, the mapped landcovers represented the existent spectral textural patterns that defined and encompassed the complex variety of compositional alliances and associations of the Parkway. Based

  10. NOS Bathymetric Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection of bathymetric contour maps which represent the seafloor topography includes over 400 individual titles and covers US offshore areas including Hawaii...

  11. APPLICATION OF MODIS DATA TO ASSESS THE LATEST FOREST COVER CHANGES OF SRI LANKA

    Directory of Open Access Journals (Sweden)

    K. Perera

    2012-07-01

    Full Text Available Assessing forest cover of Sri Lanka is becoming important to lower the pressure on forest lands as well as man-elephant conflicts. Furthermore, the land access to north-east Sri Lanka after the end of 30 years long civil war has increased the need of regularly updated land cover information for proper planning. This study produced an assessment of the forest cover of Sri Lanka using two satellite data based maps within 23 years of time span. For the old forest cover map, the study used one of the first island-wide digital land cover classification produced by the main author in 1988. The old land cover classification was produced at 80 m spatial resolution, using Landsat MSS data. A previously published another study by the author has investigated the application feasibility of MODIS and Landsat MSS imagery for a selected sub-section of Sri Lanka to identify the forest cover changes. Through the light of these two studies, the assessment was conducted to investigate the application possibility of MODIS 250 m over a small island like Sri Lanka. The relation between the definition of forest in the study and spatial resolution of the used satellite data sets were considered since the 2012 map was based on MODIS data. The forest cover map of 1988 was interpolated into 250 m spatial resolution to integrate with the GIS data base. The results demonstrated the advantages as well as disadvantages of MODIS data in a study at this scale. The successful monitoring of forest is largely depending on the possibility to update the field conditions at regular basis. Freely available MODIS data provides a very valuable set of information of relatively large green patches on the ground at relatively real-time basis. Based on the changes of forest cover from 1988 to 2012, the study recommends the use of MODIS data as a resalable method to forest assessment and to identify hotspots to be re-investigated. It's noteworthy to mention the possibility of uncounted small

  12. Creation of Regional Habitat Cover Maps: Application of the NE Terrestrial Habitat Classification System: Completion of Virginia & Maryland Piedmont and Coastal Plain to be consistent with rest of region

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This project completed the comprehensive wildlife habitat map of the eastern region, including all states from Maine to Virginia, west to New York, Pennsylvania and...

  13. On Geometric Correction Method of BJ-1 Panchromatic Image Covering Kingdom of Lesotho

    Institute of Scientific and Technical Information of China (English)

    Shunxi; LIU; Zhongwu; WANG; Wei; HAO; Rongbin; WANG

    2014-01-01

    The purpose is to find a suitable geometric correction method of BJ-1 panchromatic image covering Kingdom of Lesotho.The methods are carrying out two geo-correction experiments based on the push-broom model and the projective transform model for BJ-1 small satellite real panchromatic covering flat and mountain area of Lesotho.Results show that the projective transform model has equal or higher accuracy compared to the push-broom model.Conclusion is the projective transform model can be used in producing land use image map.

  14. 2005 Kansas Land Cover Patterns, Level I, Kansas River Watershed (1,000m buffer)

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period. The map is designed to be explicitly...

  15. 2005 Kansas Land Cover Patterns, Level I, State of Kansas (300m buffer)

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period. The map is designed to be explicitly...

  16. Characterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South Africa

    Directory of Open Access Journals (Sweden)

    Zahn Münch

    2017-02-01

    Full Text Available Land cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014, to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1 from existing data (2000; and (2 through object-based image analysis (2014 of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%, the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.

  17. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data.

    Science.gov (United States)

    Soffianian, Alireza; Madanian, Maliheh

    2015-08-01

    Changes in land cover and land use reveal the effects of natural and human processes on the Earth's surface. These changes are predicted to exert the greatest environmental impacts in the upcoming decades. The purpose of the present study was to monitor land cover changes using Multispectral Scanner Sensor (MSS) and multitemporal Landsat Thematic Mapper (TM) data from the counties of Isfahan Province, Iran, during 1975, 1990, and 2010. The maximum likelihood supervised classification method was applied to map land cover. Postclassification change detection technique was also used to produce change images through cross-tabulation. Classification results were improved using ancillary data, visual interpretation, and local knowledge about the area. The overall accuracy of land cover change maps ranged from 88 to 90.6%. Kappa coefficients associated with the classification were 0.81 for 1975, 0.84 for 1990, and 0.85 for 2010 images. This study monitored changes related to conversion of agricultural land to impervious surfaces, undeveloped land to agricultural land, agricultural land to impervious surfaces, and undeveloped land to impervious surfaces. The analyses of land cover changes during the study period revealed the significant development of impervious surfaces in counties of Isfahan Province as a result of population growth, traffic conditions, and industrialization. The image classification indicated that agricultural lands increased from 2520.96 km(2) in 1975 to 4103.85 km(2) in 2010. These land cover changes were evaluated in different counties of Isfahan Province.

  18. 涤纶包覆纱纬弹色织面料的生产技术要点%Technology Key Points of Producing Polyester Covered Weft Elastic Yarn-dyed Fabric

    Institute of Scientific and Technical Information of China (English)

    马顺彬; 蔡永东; 葛龙德

    2011-01-01

    介绍涤纶包覆纱纬弹色织面料的设计及生产要点,通过设计每花经纱根数和全幅花数、合理设计布边组织及每筘穿入数、合理调节主辅喷嘴引纬气压、适当增加上机张力、合理调节开口时间等技术措施,使织造过程中布幅稳定,布面均匀,无纬缩,织物有弹性,织机效率达95%以上,入库一等品率在97%以上.%Design and production key points of polyester covered weft elastic yarn-dyed fabric were introduced.Each flower warp number and whole flower number was designed. Selvage structure and warp numbers per reed were designed rationally. Weft-inserting pressure of main and auxiliary nozzle were adjusted rationally. Loom tension was increased properly. Shed timing was set rationally. Finally fabric width is stable in production,fabric surface is even, no kinky weft,fabric is elastic,loom efficiency could reach above 95% and first class-product rate could reach above 97%.

  19. Landfill Top Covers

    DEFF Research Database (Denmark)

    Scheutz, Charlotte; Kjeldsen, Peter

    2011-01-01

    the landfill section has been filled or several years later depending on the settlement patterns. Significant differential settlements may disturb the functioning of the top cover. The specific design of the cover system depends on the type of waste landfilled (municipal, hazardous, or inert waste...... such as lowpermeability clay soils and geomembranes are required. The avoidance of water input to organic waste may impede the microbial stabilization processes including gas generation. Therefore watertight top covers may be in conflict with the purposes of reactor landfills (see Chapter 10.6). At some sites covers...... sometimes are made to include components for recirculation of landfill leachate (see Section 10.9.2 for more details). The top cover is an important factor in the water management of landfills. Details about water infiltration through top covers and its influence on the hydrology of the landfill is covered...

  20. Physical map of polyoma viral DNA fragments produced by cleavage with a restriction enzyme from Haemophilus aegyptius, endonuclease R-HaeIII.

    Science.gov (United States)

    Summers, J

    1975-04-01

    Digestion of polyoma viral DNA with a restriction enzyme from Haemophilus aegyptius generates at least 22 unique fragments. The fragments have been characterized with respect to size and physical order on the polyoma genome, and the 5' to 3' orientation of the (+) and (-) strands has been determined. A method for specific radiolabeling of adjacent fragments was employed to establish the fragment order. This technique may be useful for ordering the fragments produced by digestion of complex DNAs.

  1. Landfill Top Covers

    DEFF Research Database (Denmark)

    Scheutz, Charlotte; Kjeldsen, Peter

    2011-01-01

    is landscaped in order to fit into the surrounding area/environment or meet specific plans for the final use of the landfill. To fulfill the above listed requirements landfill covers are often multicomponent systems which are placed directly on top of the waste. The top cover may be placed immediately after...... the landfill section has been filled or several years later depending on the settlement patterns. Significant differential settlements may disturb the functioning of the top cover. The specific design of the cover system depends on the type of waste landfilled (municipal, hazardous, or inert waste...... however, top covers may be the only environmental protection measure. In some landfill regulations (for instance the Subtitle D landfills receiving municipal solid waste in the USA) it is required to minimize infiltration into the waste layers. Therefore top covers containing liner components...

  2. Percent Forest Cover

    Data.gov (United States)

    U.S. Environmental Protection Agency — Forests provide economic and ecological value. High percentages of forest cover (FORPCT) generally indicate healthier ecosystems and cleaner surface water. More...

  3. Saturated Domino Coverings

    CERN Document Server

    Buchanan, Andrew; Ryba, Alex

    2011-01-01

    A domino covering of a board is saturated if no domino is redundant. We introduce the concept of a fragment tiling and show that a minimal fragment tiling always corresponds to a maximal saturated domino covering. The size of a minimal fragment tiling is the domination number of the board. We define a class of regular boards and show that for these boards the domination number gives the size of a minimal X-pentomino covering. Natural sequences that count maximal saturated domino coverings of square and rectangular boards are obtained. These include the new sequences A193764, A193765, A193766, A193767, and A193768 of OEIS.

  4. Percent Forest Cover (Future)

    Data.gov (United States)

    U.S. Environmental Protection Agency — Forests provide economic and ecological value. High percentages of forest cover (FORPCTFuture) generally indicate healthier ecosystems and cleaner surface water....

  5. Snow water equivalent mapping in Norway

    Science.gov (United States)

    Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

    2003-04-01

    In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

  6. Mapping of neural activity produced by thermal pain in the healthy human spinal cord and brain stem: a functional magnetic resonance imaging study.

    Science.gov (United States)

    Cahill, Catherine M; Stroman, Patrick W

    2011-04-01

    Functional magnetic resonance imaging (fMRI) has greatly advanced our current understanding of pain, although most studies to date have focused on imaging of cortical structures. In the present study, we have used fMRI at 3 T to investigate the neural activity evoked by thermal sensation and pain (42 °C and 46 °C) throughout the entire lower neuroaxis from the first synapse in the spinal cord rostral to the thalamus in healthy subjects. The results demonstrate that noxious thermal stimulation (46 °C) produces consistent activity within various structures known to be involved in the pain matrix including the dorsal spinal cord, reticular formation, periaqueductal gray and rostral ventral medulla. However, additional areas of activity were evident that are not considered to be part of the pain matrix, including the olivary nucleus. Thermal stimulation (42 °C) reported as either not painful or mildly painful produced quantitative, but not qualitative, differences in neuronal activity depending on the order of experiments. Activity was greater in the spinal cord and brain stem in earlier experiments, compared with repeated experiments after the more noxious (46 °C) stimulus had been applied. This study provides significant insight into how the lower neuroaxis integrates and responds to pain in humans. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Thematic accuracy of the National Land Cover Database (NLCD) 2001 land cover for Alaska

    Science.gov (United States)

    Selkowitz, D.J.; Stehman, S.V.

    2011-01-01

    The National Land Cover Database (NLCD) 2001 Alaska land cover classification is the first 30-m resolution land cover product available covering the entire state of Alaska. The accuracy assessment of the NLCD 2001 Alaska land cover classification employed a geographically stratified three-stage sampling design to select the reference sample of pixels. Reference land cover class labels were determined via fixed wing aircraft, as the high resolution imagery used for determining the reference land cover classification in the conterminous U.S. was not available for most of Alaska. Overall thematic accuracy for the Alaska NLCD was 76.2% (s.e. 2.8%) at Level II (12 classes evaluated) and 83.9% (s.e. 2.1%) at Level I (6 classes evaluated) when agreement was defined as a match between the map class and either the primary or alternate reference class label. When agreement was defined as a match between the map class and primary reference label only, overall accuracy was 59.4% at Level II and 69.3% at Level I. The majority of classification errors occurred at Level I of the classification hierarchy (i.e., misclassifications were generally to a different Level I class, not to a Level II class within the same Level I class). Classification accuracy was higher for more abundant land cover classes and for pixels located in the interior of homogeneous land cover patches. ?? 2011.

  8. A genetic map of Peromyscus with chromosomal assignment of linkage groups (a Peromyscus genetic map).

    Science.gov (United States)

    Kenney-Hunt, Jane; Lewandowski, Adrienne; Glenn, Travis C; Glenn, Julie L; Tsyusko, Olga V; O'Neill, Rachel J; Brown, Judy; Ramsdell, Clifton M; Nguyen, Quang; Phan, Tony; Shorter, Kimberly R; Dewey, Michael J; Szalai, Gabor; Vrana, Paul B; Felder, Michael R

    2014-04-01

    The rodent genus Peromyscus is the most numerous and species-rich mammalian group in North America. The naturally occurring diversity within this genus allows opportunities to investigate the genetic basis of adaptation, monogamy, behavioral and physiological phenotypes, growth control, genomic imprinting, and disease processes. Increased genomic resources including a high quality genetic map are needed to capitalize on these opportunities. We produced interspecific hybrids between the prairie deer mouse (P. maniculatus bairdii) and the oldfield mouse (P. polionotus) and scored meiotic recombination events in backcross progeny. A genetic map was constructed by genotyping of backcross progeny at 185 gene-based and 155 microsatellite markers representing all autosomes and the X-chromosome. Comparison of the constructed genetic map with the molecular maps of Mus and Rattus and consideration of previous results from interspecific reciprocal whole chromosome painting allowed most linkage groups to be unambiguously assigned to specific Peromyscus chromosomes. Based on genomic comparisons, this Peromyscus genetic map covers ~83% of the Rattus genome and 79% of the Mus genome. This map supports previous results that the Peromyscus genome is more similar to Rattus than Mus. For example, coverage of the 20 Rattus autosomes and the X-chromosome is accomplished with only 28 segments of the Peromyscus map, but coverage of the 19 Mus autosomes and the X-chromosome requires 40 chromosomal segments of the Peromyscus map. Furthermore, a single Peromyscus linkage group corresponds to about 91% of the rat and only 76% of the mouse X-chromosomes.

  9. Land Cover Trends Project

    Science.gov (United States)

    Acevedo, William

    2006-01-01

    The Land Cover Trends Project is designed to document the types, rates, causes, and consequences of land cover change from 1973 to 2000 within each of the 84 U.S. Environmental Protection Agency (EPA) Level III ecoregions that span the conterminous United States. The project's objectives are to: * Develop a comprehensive methodology using probability sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper (ETM) data for estimating regional land cover change. * Characterize the spatial and temporal characteristics of conterminous U.S. land cover change for five periods from 1973 to 2000 (nominally 1973, 1980, 1986, 1992, and 2000). * Document the regional driving forces and consequences of change. * Prepare a national synthesis of land cover change.

  10. Flat covers of modules

    CERN Document Server

    Xu, Jinzhong

    1996-01-01

    Since the injective envelope and projective cover were defined by Eckmann and Bas in the 1960s, they have had great influence on the development of homological algebra, ring theory and module theory. In the 1980s, Enochs introduced the flat cover and conjectured that every module has such a cover over any ring. This book provides the uniform methods and systematic treatment to study general envelopes and covers with the emphasis on the existence of flat cover. It shows that Enochs' conjecture is true for a large variety of interesting rings, and then presents the applications of the results. Readers with reasonable knowledge in rings and modules will not have difficulty in reading this book. It is suitable as a reference book and textbook for researchers and graduate students who have an interest in this field.

  11. Mapping Deeply

    Directory of Open Access Journals (Sweden)

    Denis Wood

    2015-08-01

    Full Text Available This is a description of an avant la lettre deep mapping project carried out by a geographer and a number of landscape architecture students in the early 1980s. Although humanists seem to take the “mapping” in deep mapping more metaphorically than cartographically, in this neighborhood mapping project, the mapmaking was taken literally, with the goal of producing an atlas of the neighborhood. In this, the neighborhood was construed as a transformer, turning the stuff of the world (gas, water, electricity into the stuff of individual lives (sidewalk graffiti, wind chimes, barking dogs, and vice versa. Maps in the central transformer section of the atlas were to have charted this process in action, as in one showing the route of an individual newspaper into the neighborhood, then through the neighborhood to a home, and finally, as trash, out of the neighborhood in a garbage truck; though few of these had been completed when the project concluded in 1986. Resurrected in 1998 in an episode on Ira Glass’ This American Life, the atlas was finally published, as Everything Sings: Maps for a Narrative Atlas, in 2010 (and an expanded edition in 2013.

  12. Normal family of quasimeromorphic mappings

    Institute of Scientific and Technical Information of China (English)

    SUN; Daochun(孙道椿); YANG; Lo(杨乐)

    2003-01-01

    The more general quasimeromorphic mappings are studied with the geometric method. The necessary and sufficient conditions for the normality of the family of quasimeromorphic mappings are discussed. We proved two inequalities on the covering surface and obtained some normal criteria on quasimeromorphic mappings with them. Obviously, these criteria hold for meromorphic functions.

  13. GIS and Remote Sensing for Malaria Risk Mapping, Ethiopia

    Science.gov (United States)

    Ahmed, A.

    2014-11-01

    Integrating malaria data into a decision support system (DSS) using Geographic Information System (GIS) and remote sensing tool can provide timely information and decision makers get prepared to make better and faster decisions which can reduce the damage and minimize the loss caused. This paper attempted to asses and produce maps of malaria prone areas including the most important natural factors. The input data were based on the geospatial factors including climatic, social and Topographic aspects from secondary data. The objective of study is to prepare malaria hazard, Vulnerability, and element at risk map which give the final output, malaria risk map. The malaria hazard analyses were computed using multi criteria evaluation (MCE) using environmental factors such as topographic factors (elevation, slope and flow distance to stream), land use/ land cover and Breeding site were developed and weighted, then weighted overlay technique were computed in ArcGIS software to generate malaria hazard map. The resulting malaria hazard map depicts that 19.2 %, 30.8 %, 25.1 %, 16.6 % and 8.3 % of the District were subjected to very high, high, moderate, low and very low malaria hazard areas respectively. For vulnerability analysis, health station location and speed constant in Spatial Analyst module were used to generate factor maps. For element at risk, land use land cover map were used to generate element at risk map. Finally malaria risk map of the District was generated. Land use land cover map which is the element at risk in the District, the vulnerability map and the hazard map were overlaid. The final output based on this approach is a malaria risk map, which is classified into 5 classes which is Very High-risk area, High-risk area, Moderate risk area, Low risk area and Very low risk area. The risk map produced from the overlay analysis showed that 20.5 %, 11.6 %, 23.8 %, 34.1 % and 26.4 % of the District were subjected to very high, high, moderate, low and very low

  14. Mapping lichen color-groups in western Arctic Alaska using seasonal Landsat composites

    Science.gov (United States)

    Nelson, P.; Macander, M. J.; Swingley, C. S.

    2016-12-01

    Mapping lichens at a landscape scale has received increased recent interest due to fears that terricolous lichen mats, primary winter caribou forage, may be decreasing across the arctic and boreal zones. However, previous efforts have produced taxonomically coarse, total lichen cover maps or have covered relatively small spatial extents. Here we attempt to map lichens of differing colors as species proxies across northwestern Alaska to produce the finest taxonomic and spatial- grained lichen maps covering the largest spatial extent to date. Lichen community sampling in five western Alaskan National Parks and Preserves from 2007-2012 generated 328 FIA-style 34.7 m radius plots on which species-level macrolichen community structure and abundance was estimated. Species were coded by color and plot lichen cover was aggregated by plot as the sum of the cover of each species in a color group. Ten different lichen color groupings were used for modeling to deduce which colors were most detectable. Reflectance signatures of each plot were extracted from a series of Landsat composites (circa 2000-2010) partitioned into two-week intervals from June 1 to Sept. 15. Median reflectance values for each band in each pixel were selected based on filtering criteria to reduce likelihood of snow cover. Lichen color group cover was regressed against plot reflectance plus additional abiotic predictors in two different data mining algorithms. Brown and grey lichens had the best models explaining approximately 40% of lichen cover in those color groups. Both data mining techniques produced similarly good fitting models. Spatial patterns of lichen color-group cover show distinctly different ecological patterns of these color-group species proxies.

  15. National Land Cover Database 2001 (NLCD01) Tile 1, Northwest United States: NLCD01_1

    Science.gov (United States)

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  16. National Land Cover Database 2001 (NLCD01) Tile 4, Southeast United States: NLCD01_4

    Science.gov (United States)

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  17. National Land Cover Database 2001 (NLCD01) Tile 3, Southwest United States: NLCD01_3

    Science.gov (United States)

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg).The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  18. National Land Cover Database 2001 (NLCD01) Tile 2, Northeast United States: NLCD01_2

    Science.gov (United States)

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  19. Covering folded shapes

    Directory of Open Access Journals (Sweden)

    Oswin Aichholzer

    2014-05-01

    Full Text Available Can folding a piece of paper flat make it larger? We explore whether a shape S must be scaled to cover a flat-folded copy of itself. We consider both single folds and arbitrary folds (continuous piecewise isometries \\(S\\to\\mathbb{R}^2\\. The underlying problem is motivated by computational origami, and is related to other covering and fixturing problems, such as Lebesgue's universal cover problem and force closure grasps. In addition to considering special shapes (squares, equilateral triangles, polygons and disks, we give upper and lower bounds on scale factors for single folds of convex objects and arbitrary folds of simply connected objects.

  20. 911 Call Center (PSAP) Service Areas, Master coverage of "atom" features used as a source to generate several derivative layers for the Sheriff RMS and E-911 map rolls. Cover is painstakingly maintained interactively by GIS staff. All atom boundaries are snapped to the road centerline cover, Published in 2008, 1:1200 (1in=100ft) scale, Sedgwick County, Kansas.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This 911 Call Center (PSAP) Service Areas dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Published Reports/Deeds information as of...

  1. Fire Stations, Fire station locations within Sedgwick County. Cover is derived from Emergency Facilities (scEfac) cover. Used for Public Safety map rolls. Primary attributes include station number, address, mailing city, type and name., Published in 2008, 1:1200 (1in=100ft) scale, Sedgwick County, Kansas.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Fire Stations dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Other information as of 2008. It is described as 'Fire station...

  2. Use of Sentinels to aid the global monitoring of snow cover

    Science.gov (United States)

    Pulliainen, Jouni; Salminen, Miia; Luojus, Kari; Metsämäki, Sari; Lemmetyinen, Juha; Takala, Matias; Cohen, Juval; Böttcher, Kristine

    2014-05-01

    Earth observation instruments onboard Sentinel satellites provide a unique opportunity for the monitoring and investigation of global snow processes. The issue of the possible decay of seasonal snow cover is highly relevant for climate research. In addition to water cycle, the extent and amount of snow affects to surface albedo, and indirectly to carbon cycling. The latter issue includes snow-induced changes in permafrost regions (active layer characteristics), as well as the effect of snow (melt) to vegetation growth and soil respiration. Recent advances in ESA DUE GlobSnow project have shown that by combining data from optical satellite sensors and passive microwave instruments advanced Climate Data Records (CDR) on seasonal snow cover can be produced, extending to time periods of over 30 years. The combined snow cover products provide information both on Snow Extent (SE) and Snow Water Equivalent (SWE) on a daily basis. The applicable instruments providing historical data for CDR generation include such microwave radiometers as SMMR, AMSR and SSMI/I, and such optical sensors as AVHRR, AATSR and VIIRS. Sentinel 3, especially its SLSTR instrument, is a prominent tool for expanding the snow CDR for forthcoming years. The developed global snow cover monitoring methodology, demonstrated and discussed here, derives the SWE information from passive microwave data (accompanied with in situ observations of snow depth at synoptic weather stations). The snow extent and fractional snow cover (FSC) on ground is derived from optical satellite data, in order to accurately map the continental line of seasonal snow cover, and to map regions of ephemeral snow cover. An advanced feature in the developed methodology is the provision of uncertainty information on snow cover characteristics associated with each individual satellite data footprint on ground and moment of time. In addition to assisting the generation and extension of the global snow cover CDR, Sentinel missions provide

  3. Percent Wetland Cover

    Data.gov (United States)

    U.S. Environmental Protection Agency — Wetlands act as filters, removing or diminishing the amount of pollutants that enter surface water. Higher values for percent of wetland cover (WETLNDSPCT) may be...

  4. Percent of Impervious Cover

    Data.gov (United States)

    U.S. Environmental Protection Agency — High amounts of impervious cover (parking lots, rooftops, roads, etc.) can increase water runoff, which may directly enter surface water. Runoff from roads often...

  5. Percent Wetland Cover (Future)

    Data.gov (United States)

    U.S. Environmental Protection Agency — Wetlands act as filters, removing or diminishing the amount of pollutants that enter surface water. Higher values for percent of wetland cover (WETLNDSPCT) may be...

  6. Projected 2020 Land Cover

    Data.gov (United States)

    U.S. Environmental Protection Agency — Projected 2020 land cover was developed to provide one scenario of development in the year 2020. It was used to generate several metrics to compare to 1992 metrics...

  7. Moving from Envisat MERIS to Sentinel-3 to Provide Consistent Global Land Cover Time Series at 300 M up to 2016: The Land Cover Component of the ESA Climate Change Initiative

    Science.gov (United States)

    Defourny, Pierre; Bontemps, Sophie; Boettcher, Martin; Brockmann, Carten; De Maet, Thomas; Kirches, Grit; Lamarche, Celine; Van Bogaert, Eric; Ramoino, Fabrizio; Arino, Olivier

    2015-12-01

    At the end of 2015, Sentinel-3 will be launched. With its two instruments OLCI (Ocean Land Colour Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer), the successor of the Envisat MERIS sensor will allow ensuring the continuity of global land cover maps production initiated in the CCI Land Cover project. At the end of its 3-year Phase, the project delivered a first database made of three global land cover maps representative of three 5-year epochs (2000, 2005 and 2010) based on MERIS time series. One requirement for the second phase of the project is to extend the dataset in the future and to produce an additional global land cover map covering the 2015 epoch. That will be done relying on the coming Sentinel-3 sensor, which is the only one that can ensure continuity in the global acquisition of medium spatial resolution time series on daily intervals. Waiting for Sentinel-3, the project will rely on PROBA-V time series.

  8. Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing based Estimates of Impervious Surface Cover

    Science.gov (United States)

    Chormanski, Jaroslaw; Van de Voorde, Tim; De Roeck, Tim; Batelaan, Okke; Canters, Frank

    2008-01-01

    The amount and intensity of runoff on catchment scale are strongly determined by the presence of impervious land-cover types, which are the predominant cover types in urbanized areas. This paper examines the impact of different methods for estimating impervious surface cover on the prediction of peak discharges, as determined by a fully distributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe River catchment in the southeastern part of Brussels. The study shows that detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, produces substantially different estimates of peak discharges than traditional approaches based on expert judgment of average imperviousness for different types of urban land use. The study also demonstrates that sub-pixel estimation of imperviousness may be a useful alternative for more expensive high-resolution mapping for rainfall-runoff modelling at catchment scale.

  9. EnviroAtlas - Fresno, CA - Riparian Buffer Land Cover by Block Group

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of different land cover types within 15- and 50-meters of hydrologically connected streams, rivers, and other water bodies within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  10. Plant functional type classification for Earth System Models: results from the European Space Agency's Land Cover Climate Change Initiative

    Directory of Open Access Journals (Sweden)

    B. Poulter

    2015-01-01

    Full Text Available Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land-cover datasets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily transferable to the requirements of earth system models. In 2009, the European Space Agency launched the Climate Change Initiative (CCI, with land cover (LC_CCI as one of thirteen Essential Climate Variables targeted for research development. The LC_CCI was implemented in three phases, first responding to a survey of user needs, then developing a global, moderate resolution, land-cover dataset for three time periods, or epochs, 2000, 2005, and 2010, and the last phase resulting in a user-tool for converting land cover to plant functional type equivalents. Here we present the results of the LC_CCI project with a focus on the mapping approach used to convert the United Nations Land Cover Classification System to plant functional types (PFT. The translation was performed as part of consultative process among map producers and users and resulted in an open-source conversion tool. A comparison with existing PFT maps used by three-earth system modeling teams shows significant differences between the LC_CCI PFT dataset and those currently used in earth system models with likely consequences for modeling terrestrial biogeochemistry and land–atmosphere interactions. The LC_CCI tool is flexible for users to modify land cover to PFT conversions and will evolve as Phase 2 of the European Space Agency CCI program continues.

  11. Web Mapping Using Logo on Map

    Directory of Open Access Journals (Sweden)

    Ximing Hou

    2012-12-01

    Full Text Available The newly proposed Logo on Map (LoM system consists of three modules: picture extraction module (PEM, logo matching module (LMM and web mapping module (WMM. Since the first two modules were covered in our previous paper, the third module WMM is described here to present a complete LoM system. Current research is focused on geo-location distribution of brands on Google Maps. Pictures taken by ordinary people are extracted using Picture Extraction Module (PEM. The pictures containing relevant logos are obtained via Logo Matching Module (LMM. Brand distributions are overlaid on Google Maps. In this paper, GPS and brands are briefly described, and the implementation of Web Mapping Module (WMM based on Google Maps API is detailed. Then several experiments are carried out on the selected top brands. Finally the LMM-pictures are mapped on the Google Maps and the geographical distributions of the brands are visualised. Brand uniqueness is discussed and conclusion is drawn that with unique brand names web mapping can visually reflect the real economic activities of a company in the world.

  12. Novice to Expert Cognition During Geologic Bedrock Mapping

    Science.gov (United States)

    Petcovic, H. L.; Libarkin, J.; Hambrick, D. Z.; Baker, K. M.; Elkins, J. T.; Callahan, C. N.; Turner, S.; Rench, T. A.; LaDue, N.

    2011-12-01

    novices in our sample, but not for the experts. For experienced mappers, we found a significant correlation between GCI scores and the thoroughness with which they covered the map area, plus a relationship between speed and map accuracy such that faster mappers produced better maps. However, fast novice mappers tended to produce the worst maps. Successful mappers formed a mental model of the underlying geologic structure immediately to early in the mapping task, then spent field time collecting observations to confirm, disconfirm, or modify their initial model. In contrast, the least successful mappers (all inexperienced) rarely generated explanations or models of the underlying geologic structure in the field.

  13. National Land Cover Database 2001 Version 2: 1985-2006

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database 2001 Version 2 (NLCD 2001 Version 2) is being compiled across all 50 states and Puerto Rico as a cooperative mapping effort of the...

  14. National Land Cover Database 2001 Version 2: 1985-2006

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database 2001 Version 2 (NLCD 2001 Version 2) is being compiled across all 50 states and Puerto Rico as a cooperative mapping effort of the...

  15. Farmland Mapping and Monitoring 2004 Mosaic

    Data.gov (United States)

    California Department of Resources — The Farmland Mapping and Monitoring Program (FMMP) produces maps and statistical data used for analyzing impacts on California's agricultural resources. Agricultural...

  16. Mapping known and potential mineral occurrences and host rocks in the Bonnifield Mining District using minimal cloud- and snow-cover ASTER data: Chapter E in Recent U.S. Geological Survey studies in the Tintina Gold Province, Alaska, United States, and Yukon, Canada--results of a 5-year project

    Science.gov (United States)

    Hubbard, Bernard E.; Dusel-Bacon, Cynthia; Rowan, Lawrence C.; Eppinger, Robert G.; Gough, Larry P.; Day, Warren C.

    2007-01-01

    On July 8, 2003, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor acquired satellite imagery of a 60-kilometer-wide swath covering a portion of the Bonnifield mining district within the southernmost part of the Tintina Gold Province, Alaska, under unusually favorable conditions of minimal cloud and snow cover. Although rocks from more than eight different lithotectonic terranes are exposed within the extended swath of data, we focus on volcanogenic massive sulfides (VMS) and porphyry deposits within the Yukon-Tanana terrane (YTT), the largest Mesozoic accretionary terrane exposed between the Denali fault system to the south of Fairbanks and the Tintina fault system to the north of Fairbanks. Comparison of thermal-infrared region (TIR) decorrelation stretch data to available geologic maps indicates that rocks from the YTT contain a wide range of rock types ranging in composition from mafic metavolcanic rocks to felsic rock types such as metarhyolites, pelitic schists, and quartzites. The nine-band ASTER visible-near-infrared region--short-wave infrared region (VNIR-SWIR) reflectance data and spectral matched-filter processing were used to map hydrothermal alteration patterns associated with VMS and porphyry deposit types. In particular, smectite, kaolinite, opaline silica, jarosite and (or) other ferric iron minerals defined narrow (less than 250-meter diameter) zonal patterns around Red Mountain and other potential VMS targets. Using ASTER we identified some of the known mineral deposits in the region, as well as mineralogically similar targets that may represent potential undiscovered deposits. Some known deposits were not identified and may have been obscured by vegetation or snow cover or were too small to be resolved.

  17. AFLP linkage map of the Japanese quail Coturnix japonica

    Directory of Open Access Journals (Sweden)

    Beaumont Catherine

    2003-09-01

    Full Text Available Abstract The quail is a valuable farm and laboratory animal. Yet molecular information about this species remains scarce. We present here the first genetic linkage map of the Japanese quail. This comprehensive map is based solely on amplified fragment length polymorphism (AFLP markers. These markers were developed and genotyped in an F2 progeny from a cross between two lines of quail differing in stress reactivity. A total of 432 polymorphic AFLP markers were detected with 24 TaqI/EcoRI primer combinations. On average, 18 markers were produced per primer combination. Two hundred and fifty eight of the polymorphic markers were assigned to 39 autosomal linkage groups plus the ZW sex chromosome linkage groups. The linkage groups range from 2 to 28 markers and from 0.0 to 195.5 cM. The AFLP map covers a total length of 1516 cM, with an average genetic distance between two consecutive markers of 7.6 cM. This AFLP map can be enriched with other marker types, especially mapped chicken genes that will enable to link the maps of both species and make use of the powerful comparative mapping approach. This AFLP map of the Japanese quail already provides an efficient tool for quantitative trait loci (QTL mapping.

  18. Climate under cover

    CERN Document Server

    Takakura, Tadashi

    2002-01-01

    1.1. INTRODUCTION Plastic covering, either framed or floating, is now used worldwide to protect crops from unfavorable growing conditions, such as severe weather and insects and birds. Protected cultivation in the broad sense, including mulching, has been widely spread by the innovation of plastic films. Paper, straw, and glass were the main materials used before the era of plastics. Utilization of plastics in agriculture started in the developed countries and is now spreading to the developing countries. Early utilization of plastic was in cold regions, and plastic was mainly used for protection from the cold. Now plastic is used also for protection from wind, insects and diseases. The use of covering techniques started with a simple system such as mulching, then row covers and small tunnels were developed, and finally plastic houses. Floating mulch was an exception to this sequence: it was introduced rather recently, although it is a simple structure. New development of functional and inexpensive films trig...

  19. Accuracy assessment of seven global land cover datasets over China

    Science.gov (United States)

    Yang, Yongke; Xiao, Pengfeng; Feng, Xuezhi; Li, Haixing

    2017-03-01

    Land cover (LC) is the vital foundation to Earth science. Up to now, several global LC datasets have arisen with efforts of many scientific communities. To provide guidelines for data usage over China, nine LC maps from seven global LC datasets (IGBP DISCover, UMD, GLC, MCD12Q1, GLCNMO, CCI-LC, and GlobeLand30) were evaluated in this study. First, we compared their similarities and discrepancies in both area and spatial patterns, and analysed their inherent relations to data sources and classification schemes and methods. Next, five sets of validation sample units (VSUs) were collected to calculate their accuracy quantitatively. Further, we built a spatial analysis model and depicted their spatial variation in accuracy based on the five sets of VSUs. The results show that, there are evident discrepancies among these LC maps in both area and spatial patterns. For LC maps produced by different institutes, GLC 2000 and CCI-LC 2000 have the highest overall spatial agreement (53.8%). For LC maps produced by same institutes, overall spatial agreement of CCI-LC 2000 and 2010, and MCD12Q1 2001 and 2010 reach up to 99.8% and 73.2%, respectively; while more efforts are still needed if we hope to use these LC maps as time series data for model inputting, since both CCI-LC and MCD12Q1 fail to represent the rapid changing trend of several key LC classes in the early 21st century, in particular urban and built-up, snow and ice, water bodies, and permanent wetlands. With the highest spatial resolution, the overall accuracy of GlobeLand30 2010 is 82.39%. For the other six LC datasets with coarse resolution, CCI-LC 2010/2000 has the highest overall accuracy, and following are MCD12Q1 2010/2001, GLC 2000, GLCNMO 2008, IGBP DISCover, and UMD in turn. Beside that all maps exhibit high accuracy in homogeneous regions; local accuracies in other regions are quite different, particularly in Farming-Pastoral Zone of North China, mountains in Northeast China, and Southeast Hills. Special

  20. Exploring geospatial techniques for spatiotemporal change detection in land cover dynamics along Soan River, Pakistan.

    Science.gov (United States)

    Bashir, Hafsa; Ahmad, Sheikh Saeed

    2017-05-01

    Classification of land cover dynamics via satellite imagery has played indispensible services in developing effective management strategies for evaluation and management of water resources. The present study employed geospatial techniques, i.e., integrated GIS and remote sensing for effectual land change study. Hybrid classification approach was applied using ERDAS Imagine 11 to detect changes in land cover dynamics using satellite imagery of Landsat 4, 5 TM, Landsat 7 ETM, and Landsat 8 OLI for the years of 1992, 2002, and 2015, respectively. The study area was classified into four categories, i.e., vegetation, water body, barren, and urban area. Resultant maps, overlay maps, and post classification comparison maps were produced using ArcGIS 10.2 indicated remarkable shrinkage of water body up to 58.81%, reduction in vegetation area 53.24%, and increase in urban and barren area to 49.04 and 137.32%, respectively. The significant changes in land cover dynamics of Soan River are posing threats to its survival. Therefore, proper management, policies, and development of land use inventory are needs of the hour for saving Soan River.

  1. Determining Trends in Impervious Cover for the Mobile Bay, AL Region for 1974-2008, Based on a Landsat Time Series

    Science.gov (United States)

    Spruce, Joseph P.; Smoot, James; Ellis, Jean; Swann, Roberta

    2011-01-01

    This presentation will discuss the development and use of Landsat-based impervious cover products in conjunction with land use land cover change products to assess multi-decadal urbanization across the Mobile Bay region at regional and watershed scales. This nationally important coastal region has undergone a variety of ephemeral and permanent land use land cover change since the mid-1970s, including gradual but consequential increases in urban surface cover. This urban sprawl corresponds with increased regional percent impervious cover. The region s coastal zone managers are concerned about the increasing percent impervious cover, since it can negatively influence water quality and is an important consideration for coastal conservation and restoration work. In response, we processed multi-temporal Landsat data to compute maps of percent impervious cover for multiple dates from 1974 through 2008, roughly at 5-year intervals. Each year of product was classified using one single date of leaf-on and leaf-off Landsat data in conjunction with Cubist software. We are assessing Landsat impervious cover product accuracy through comparisons to available reference data, including available NLCD impervious cover products from the USGS, raw Landsat data, plus higher spatial resolution aerial and satellite data. In particular, we are quantitatively comparing the 2008 Landsat impervious cover products to those from QuickBird 2.4-meter multispectral data. Initial visual comparisons with the QuickBird impervious cover product suggest that the 2008 Landsat product tends to underestimate impervious cover for high density urban areas and to overestimate impervious cover in established residential subdivisions mixed with forested cover. Landsat TM and ETM data appears to produce more accurate impervious cover products compared to those using lower resolution Landsat MSS data. Although imperfect, these Landsat impervious cover products have helped the Mobile Bay National Estuary

  2. Reusable pipe flange covers

    Energy Technology Data Exchange (ETDEWEB)

    Holden, James Elliott (Simpsonville, SC); Perez, Julieta (Houston, TX)

    2001-01-01

    A molded, flexible pipe flange cover for temporarily covering a pipe flange and a pipe opening includes a substantially round center portion having a peripheral skirt portion depending from the center portion, the center portion adapted to engage a front side of the pipe flange and to seal the pipe opening. The peripheral skirt portion is formed to include a plurality of circumferentially spaced tabs, wherein free ends of the flexible tabs are formed with respective through passages adapted to receive a drawstring for pulling the tabs together on a back side of the pipe flange.

  3. Land cover classification using random forest with genetic algorithm-based parameter optimization

    Science.gov (United States)

    Ming, Dongping; Zhou, Tianning; Wang, Min; Tan, Tian

    2016-07-01

    Land cover classification based on remote sensing imagery is an important means to monitor, evaluate, and manage land resources. However, it requires robust classification methods that allow accurate mapping of complex land cover categories. Random forest (RF) is a powerful machine-learning classifier that can be used in land remote sensing. However, two important parameters of RF classification, namely, the number of trees and the number of variables tried at each split, affect classification accuracy. Thus, optimal parameter selection is an inevitable problem in RF-based image classification. This study uses the genetic algorithm (GA) to optimize the two parameters of RF to produce optimal land cover classification accuracy. HJ-1B CCD2 image data are used to classify six different land cover categories in Changping, Beijing, China. Experimental results show that GA-RF can avoid arbitrariness in the selection of parameters. The experiments also compare land cover classification results by using GA-RF method, traditional RF method (with default parameters), and support vector machine method. When the GA-RF method is used, classification accuracies, respectively, improved by 1.02% and 6.64%. The comparison results show that GA-RF is a feasible solution for land cover classification without compromising accuracy or incurring excessive time.

  4. 100-Meter Resolution Land Cover of Hawaii - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for Hawaii, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land cover data were derived from...

  5. 100-Meter Resolution Land Cover of Alaska - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for Alaska, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land cover data were derived from...

  6. Olympic Maps Available

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Beijing is publishing a set of Olympic maps covering everything from the location of sporting venues to the city’s history As soon as Zhou Liyi hopped off the train from Shanghai to Beijing, he hurried to Wangfujing Xinhua Book Store,one of the largest of its kind in Beijing,to buy an Olympic map. Zhou is a Shanghai resident who came to Beijing on business and plans to return as a

  7. Analysis of engineering drawings and raster map images

    CERN Document Server

    Henderson, Thomas C

    2013-01-01

    Presents up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps Discusses automatic engineering drawing and map analysis techniques Covers detailed accounts of the use of unsupervised segmentation algorithms to map images

  8. Mapping Priorities to Focus Cropland Mapping Activities: Fitness Assessment of Existing Global, Regional and National Cropland Maps

    Directory of Open Access Journals (Sweden)

    François Waldner

    2015-06-01

    Full Text Available Timely and accurate information on the global cropland extent is critical for applications in the fields of food security, agricultural monitoring, water management, land-use change modeling and Earth system modeling. On the one hand, it gives detailed location information on where to analyze satellite image time series to assess crop condition. On the other hand, it isolates the agriculture component to focus food security monitoring on agriculture and to assess the potential impacts of climate change on agricultural lands. The cropland class is often poorly captured in global land cover products due to its dynamic nature and the large variety of agro-systems. The overall objective was to evaluate the current availability of cropland datasets in order to propose a strategic planning and effort distribution for future cropland mapping activities and, therefore, to maximize their impact. Following a very comprehensive identification and collection of national to global land cover maps, a multi-criteria analysis was designed at the country level to identify the priority areas for cropland mapping. As a result, the analysis highlighted priority regions, such as Western Africa, Ethiopia, Madagascar and Southeast Asia, for the remote sensing community to focus its efforts. A Unified Cropland Layer at 250 m for the year 2014 was produced combining the fittest products. It was assessed using global validation datasets and yields an overall accuracy ranging from 82%–94%. Masking cropland areas with a global forest map reduced the commission errors from 46% down to 26%. Compared to the GLC-Share and the International Institute for Applied Systems Analysis-International Food Policy Research Institute (IIASA-IFPRI cropland maps, significant spatial disagreements were found, which might be attributed to discrepancies in the cropland definition. This advocates for a shared definition of cropland, as well as global validation datasets relevant for the

  9. Extraction of Benthic Cover Information from Video Tows and Photographs Using Object-Based Image Analysis

    Science.gov (United States)

    Estomata, M. T. L.; Blanco, A. C.; Nadaoka, K.; Tomoling, E. C. M.

    2012-07-01

    Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES) was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU), which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA), which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05).

  10. EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

    Full Text Available Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU, which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA, which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05.

  11. Covering tree with stars

    DEFF Research Database (Denmark)

    Baumbach, Jan; Guo, Jian-Ying; Ibragimov, Rashid

    2013-01-01

    We study the tree edit distance problem with edge deletions and edge insertions as edit operations. We reformulate a special case of this problem as Covering Tree with Stars (CTS): given a tree T and a set of stars, can we connect the stars in by adding edges between them such that the resulting ...

  12. Covering tree with stars

    DEFF Research Database (Denmark)

    Baumbach, Jan; Guo, Jiong; Ibragimov, Rashid

    2015-01-01

    We study the tree edit distance problem with edge deletions and edge insertions as edit operations. We reformulate a special case of this problem as Covering Tree with Stars (CTS): given a tree T and a set of stars, can we connect the stars in by adding edges between them such that the resulting ...

  13. Covering All Options

    Science.gov (United States)

    Kennedy, Mike

    2011-01-01

    The day a school opens its doors for the first time, the flooring will be new and untarnished. When the flooring is in such pristine condition, many flooring materials--carpeting, vinyl, terrazzo, wood or some other surface--will look good. But school and university planners who decide what kind of material covers the floors of their facilities…

  14. CORINE Land Cover 2006

    DEFF Research Database (Denmark)

    Stjernholm, Michael

    "CORINE land cover" er en fælleseuropæisk kortlægning af arealanvendelse/arealdække. Arealanvendelse/arealdække er i Danmark kortlagt efter CORINE metode og klasseopdeling med satellitbilleder fra 3 forskellige tidsperioder, fra begyndelsen af 1990'erne (CLC90), fra år 2000 (CLC2000) og fra år 2006...

  15. CORINE Land Cover 2006

    DEFF Research Database (Denmark)

    Stjernholm, Michael

    "CORINE land cover" er en fælleseuropæisk kortlægning af arealanvendelse/arealdække. Arealanvendelse/arealdække er i Danmark kortlagt efter CORINE metode og klasseopdeling med satellitbilleder fra 3 forskellige tidsperioder, fra begyndelsen af 1990'erne (CLC90), fra år 2000 (CLC2000) og fra år 2006...

  16. USGS Topo Base Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS Topo is a topographic tile cache base map that combines the most current data (Boundaries, Names, Transportation, Elevation, Hydrography, Land Cover, and other...

  17. Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

    Science.gov (United States)

    Paneque-Gálvez, Jaime; Mas, Jean-François; Moré, Gerard; Cristóbal, Jordi; Orta-Martínez, Martí; Luz, Ana Catarina; Guèze, Maximilien; Macía, Manuel J.; Reyes-García, Victoria

    2013-08-01

    Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines - SVM), and hybrid (unsupervised-supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different

  18. Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

    Science.gov (United States)

    Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

    2015-01-01

    Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

  19. Analysis of forest cover change at Khadimnagar National Park, Sylhet, Bangladesh, using Landsat TM and GIS data

    Institute of Scientific and Technical Information of China (English)

    Mohammad Redowan; Sharmin Akter; Nusrat Islam

    2014-01-01

    We mapped the forest cover of Khadimnagar National Park (KNP) of Sylhet Forest Division and estimated forest change over a period of 22 years (1988-2010) using Landsat TM images and other GIS data. Supervised classification and Normalized Difference Vegetation Index (NDVI) image classification approaches were applied to the im-ages to produce three cover classes, viz. dense forest, medium dense forest, and bare land. The change map was produced by differencing classified imageries of 1988 and 2010 as before image and after image, respectively, in ERDAS IMAGINE. Error matrix and kappa statistics were used to assess the accuracy of the produced maps. Overall map accuracies resulting from supervised classification of 1988 and 2010 imageries were 84.6% (Kappa 0.75) and 87.5% (Kappa 0.80), respec-tively. Forest cover statistics resulting from supervised classification showed that dense forest and bare land declined from 526 ha (67%) to 417 ha (59%) and 105 ha (13%) to 8 ha (1%), respectively, whereas medium dense forest increased from 155 ha (20%) to 317 ha (40%). Forest cover change statistics derived from NDVI classification showed that dense forest declined from 525 ha (67%) to 421 ha (54%) while medium dense forest increased from 253 ha (32%) to 356 ha (45%). Both supervised and NDVI classification approaches showed similar trends of forest change, i.e. decrease of dense forest and increase of medium dense forest, which indicates dense forest has been converted to medium dense forest. Area of bare land was unchanged. Illicit felling, encroachment, and settlement near forests caused the dense forest decline while short and long rotation plantations raised in various years caused the increase in area of medium dense forest. Protective measures should be under-taken to check further degradation of forest at KNP.

  20. 2005 Kansas Land Cover Patterns, Level IV, State of Kansas (300m buffer)

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while...