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...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere....

  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 ...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere. (C) 2001 Elsevier Science B.V. All rights reserved.......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. Covering Materials for Anaerobic Digesters Producing Biogas

    International Nuclear Information System (INIS)

    Itodo, I. N.; Philips, T. K.

    2002-01-01

    The suitability of foam, concrete and clay soil as covering material on anaerobic digesters producing biogas was investigated using four batch-type digesters of 20 litres volume. The methane yield from the digesters was of the order: foam >control> concrete > clay soil. The digester covered with foam had the highest methane yield, best temperature control and most favourable pH conditions. It is most suitable as cover material on anaerobic digesters

  4. Carbon Assessment of Hawaii Land Cover Map (CAH_LandCover)

    Data.gov (United States)

    Department of the Interior — While there have been many maps produced that depict vegetation for the state of Hawai‘i only a few of these display land cover for all of the main Hawaiian Islands,...

  5. Nielsen number of a covering map

    Directory of Open Access Journals (Sweden)

    Jezierski Jerzy

    2006-01-01

    Full Text Available We consider a finite regular covering over a compact polyhedron and a map admitting a lift . We show some formulae expressing the Nielsen number as a linear combination of the Nielsen numbers of its lifts.

  6. 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.

  7. Land cover mapping of North and Central America—Global Land Cover 2000

    Science.gov (United States)

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

    The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

  8. 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).

  9. Nielsen number of a covering map

    Directory of Open Access Journals (Sweden)

    Jerzy Jezierski

    2006-02-01

    Full Text Available We consider a finite regular covering pH:X˜H→X over a compact polyhedron and a map f:X→X admitting a lift f˜:X˜H→X˜H. We show some formulae expressing the Nielsen number N(f as a linear combination of the Nielsen numbers of its lifts.

  10. 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.

  11. Next generation of global land cover characterization, mapping, and monitoring

    Science.gov (United States)

    Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

    2013-01-01

    Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

  12. A procedure to obtain a refined European land use/cover map

    NARCIS (Netherlands)

    Batista e Silva, F.; Lavalle, C.; Koomen, E.

    2013-01-01

    Available land use/cover maps differ in their spatial extent and in their thematic, spatial, and temporal resolutions. Due to the costs of producing such maps, there is usually a trade-off between spatial extent and resolution. The only European-wide, consistent, and multi-temporal land use/cover

  13. Land use and land cover mapping: City of Palm Bay, Florida

    Science.gov (United States)

    Barile, D. D.; Pierce, R.

    1977-01-01

    Two different computer systems were compared for use in making land use and land cover maps. The Honeywell 635 with the LANDSAT signature development program (LSDP) produced a map depicting general patterns, but themes were difficult to classify as specific land use. Urban areas were unclassified. The General Electric Image 100 produced a map depicting eight land cover categories classifying 68 percent of the total area. Ground truth, LSDP, and Image 100 maps were all made to the same scale for comparison. LSDP agreed with the ground truth 60 percent and 64 percent within the two test areas compared and Image 100 was in agreement 70 percent and 80 percent.

  14. 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

    a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input...... 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...

  15. Analysis of spatial distribution of land cover maps accuracy

    Science.gov (United States)

    Khatami, R.; Mountrakis, G.; Stehman, S. V.

    2017-12-01

    Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain

  16. Improving snow cover mapping in forests through the use of a canopy reflectance model

    International Nuclear Information System (INIS)

    Klein, A.G.; Hall, D.K.; Riggs, G.A.

    1998-01-01

    MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

  17. 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...

  18. 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 objects...... of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes ‘building’ (99%, 95% CI: 95%-100%) and ‘road and parking lot’ (90%, 95% CI: 83%-95%). Some...

  19. The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

    Science.gov (United States)

    Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.

    2017-12-01

    Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is

  20. Automatic crown cover mapping to improve forest inventory

    Science.gov (United States)

    Claude Vidal; Jean-Guy Boureau; Nicolas Robert; Nicolas Py; Josiane Zerubia; Xavier Descombes; Guillaume Perrin

    2009-01-01

    To automatically analyze near infrared aerial photographs, the French National Institute for Research in Computer Science and Control developed together with the French National Forest Inventory (NFI) a method for automatic crown cover mapping. This method uses a Reverse Jump Monte Carlo Markov Chain algorithm to locate the crowns and describe those using ellipses or...

  1. Mapping of Landscape Cover Using Remote Sensing and GIS in ...

    African Journals Online (AJOL)

    Humankind to fulfill its needs has put natural resources of the earth to a severe pressure. The rate of degradation and depletion of earth resources has accelerated tremendously in view of the overincreasing demographic pressure. Therefore, mapping of landscape cover types to evaluate it has been a great concern for ...

  2. South African National Land-Cover Change Map | Schoeman ...

    African Journals Online (AJOL)

    Globally, countries face a changing environment due to population growth, increase in agricultural production, increasing demand on natural resources, climate change and resultant degradation of the natural environment. One means of monitoring this changing scenario is through land-cover change mapping. Modern ...

  3. A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data

    Science.gov (United States)

    Stibig, H.-J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; ,; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C.

    2007-01-01

    Aim  Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.Location  The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.Methods  The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.Results  The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.Main conclusions  The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub

  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. A hierarchical approach of hybrid image classification for land use and land cover mapping

    Directory of Open Access Journals (Sweden)

    Rahdari Vahid

    2018-01-01

    Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

  6. 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.

  7. High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa

    Science.gov (United States)

    Tatem, Andrew J.; Noor, Abdisalan M.; von Hagen, Craig; Di Gregorio, Antonio; Hay, Simon I.

    2007-01-01

    Background Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas. Methodology/Principal Findings We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps. Conclusions We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available. PMID:18074022

  8. High resolution population maps for low income nations: combining land cover and census in East Africa.

    Directory of Open Access Journals (Sweden)

    Andrew J Tatem

    2007-12-01

    Full Text Available Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km(2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk and are freely available.

  9. A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model

    Directory of Open Access Journals (Sweden)

    Apisit Eiumnoh

    2013-10-01

    Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.

  10. 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

  11. 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.

  12. Mapping of the Land Cover Spatiotemporal Characteristics in Northern Russia Caused by Climate Change

    Science.gov (United States)

    Panidi, E.; Tsepelev, V.; Torlopova, N.; Bobkov, A.

    2016-06-01

    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.

  13. Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

    Science.gov (United States)

    Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

    2017-11-01

    Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

  14. 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 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 machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

  15. 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...

  16. 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...

  17. 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.

    2016-01-01

    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.

  18. 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.

  19. Assessment of the thematic accuracy of land cover maps

    DEFF Research Database (Denmark)

    Høhle, Joachim

    2015-01-01

    were applied (‘Decision Tree’ and ‘Support Vector Machine’) using only two attributes (height above ground and normalized difference vegetation index) which both are derived from the images. The assessment of the thematic accuracy applied a stratified design and was based on accuracy measures...... methods perform equally for five classes. Trees are classified with a much better accuracy and a smaller confidence interval by means of the decision tree method. Buildings are classified by both methods with an accuracy of 99% (95% CI: 95%-100%) using independent 3D checkpoints. The average width......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...

  20. Proposed hybrid-classifier ensemble algorithm to map snow cover area

    Science.gov (United States)

    Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

    2018-01-01

    Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

  1. 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

  2. Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

    Science.gov (United States)

    Spruce, J.; Bolten, J. D.; Srinivasan, R.

    2017-12-01

    This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling

  3. South African National Land-Cover Change Map

    African Journals Online (AJOL)

    Fritz Schoeman

    monitoring land-cover change at a national scale over time using EO data. 2. .... assist with final results reporting and analysis on a sub-national level. ..... South African Land-Cover Characteristics Database: A synopsis of the landscape.

  4. 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.

  5. Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

    Science.gov (United States)

    Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.

    2008-03-01

    Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

  6. 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%.

  7. 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

  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 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.

  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. CRED Cumulative Map of Percent Scleractinian Coral Cover at Alamagan

    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 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.

  14. CRED Cumulative Map of Percent Scleractinian Coral Cover at Asuncion

    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 Aguijan

    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 Pagan

    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. 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.

  18. Fusion Approaches for Land Cover Map Production Using High Resolution Image Time Series without Reference Data of the Corresponding Period

    Directory of Open Access Journals (Sweden)

    Benjamin Tardy

    2017-11-01

    Full Text Available Optical sensor time series images allow one to produce land cover maps at a large scale. The supervised classification algorithms have been shown to be the best to produce maps automatically with good accuracy. The main drawback of these methods is the need for reference data, the collection of which can introduce important production delays. Therefore, the maps are often available too late for some applications. Domain adaptation methods seem to be efficient for using past data for land cover map production. According to this idea, the main goal of this study is to propose several simple past data fusion schemes to override the current land cover map production delays. A single classifier approach and three voting rules are considered to produce maps without reference data of the corresponding period. These four approaches reach an overall accuracy of around 80% with a 17-class nomenclature using Formosat-2 image time series. A study of the impact of the number of past periods used is also done. It shows that the overall accuracy increases with the number of periods used. The proposed methods require at least two or three previous years to be used.

  19. 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.

  20. 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.

  1. Open land cover from OpenStreetMap and remote sensing

    Science.gov (United States)

    Schultz, Michael; Voss, Janek; Auer, Michael; Carter, Sarah; Zipf, Alexander

    2017-12-01

    OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011-2016, and 46% of the area was representative of 2016-2017.

  2. Comparison and assessment of coarse resolution land cover maps for Northern Eurasia

    Science.gov (United States)

    Dirk Pflugmacher; Olga N. Krankina; Warren B. Cohen; Mark A. Friedl; Damien Sulla-Menashe; Robert E. Kennedy; Peder Nelson; Tatiana V. Loboda; Tobias Kuemmerle; Egor Dyukarev; Vladimir Elsadov; Viacheslav I. Kharuk

    2011-01-01

    Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse...

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

    DEFF Research Database (Denmark)

    Skriver, Henning; Schou, Jesper; Dierking, Wolfgang

    2000-01-01

    during the growing season acquired a lot of data over a Danish agricultural site. The data acquisitions were co-ordinated with ground surveys to obtain a detailed land cover map. The test area contains a large number of different land cover classes, such as more than 10 different crop types, deciduous......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 1999...

  4. Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on “The Improvement of Land Cover Classification by Thermal Remote Sensing”. Remote Sens. 2015, 7(7, 8368–8390

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2015-10-01

    Full Text Available Much remote sensing (RS research focuses on fusing, i.e., combining, multi-resolution/multi-sensor imagery for land use/land cover (LULC classification. In relation to this topic, Sun and Schulz [1] recently found that a combination of visible-to-near infrared (VNIR; 30 m spatial resolution and thermal infrared (TIR; 100–120 m spatial resolution Landsat data led to more accurate LULC classification. They also found that using multi-temporal TIR data alone for classification resulted in comparable (and in some cases higher classification accuracies to the use of multi-temporal VNIR data, which contrasts with the findings of other recent research [2]. This discrepancy, and the generally very high LULC accuracies achieved by Sun and Schulz (up to 99.2% overall accuracy for a combined VNIR/TIR classification result, can likely be explained by their use of an accuracy assessment procedure which does not take into account the multi-resolution nature of the data. Sun and Schulz used 10-fold cross-validation for accuracy assessment, which is not necessarily inappropriate for RS accuracy assessment in general. However, here it is shown that the typical pixel-based cross-validation approach results in non-independent training and validation data sets when the lower spatial resolution TIR images are used for classification, which causes classification accuracy to be overestimated.

  5. Hybrid image classification technique for land-cover mapping in the Arctic tundra, North Slope, Alaska

    Science.gov (United States)

    Chaudhuri, Debasish

    Remotely sensed image classification techniques are very useful to understand vegetation patterns and species combination in the vast and mostly inaccessible arctic region. Previous researches that were done for mapping of land cover and vegetation in the remote areas of northern Alaska have considerably low accuracies compared to other biomes. The unique arctic tundra environment with short growing season length, cloud cover, low sun angles, snow and ice cover hinders the effectiveness of remote sensing studies. The majority of image classification research done in this area as reported in the literature used traditional unsupervised clustering technique with Landsat MSS data. It was also emphasized by previous researchers that SPOT/HRV-XS data lacked the spectral resolution to identify the small arctic tundra vegetation parcels. Thus, there is a motivation and research need to apply a new classification technique to develop an updated, detailed and accurate vegetation map at a higher spatial resolution i.e. SPOT-5 data. Traditional classification techniques in remotely sensed image interpretation are based on spectral reflectance values with an assumption of the training data being normally distributed. Hence it is difficult to add ancillary data in classification procedures to improve accuracy. The purpose of this dissertation was to develop a hybrid image classification approach that effectively integrates ancillary information into the classification process and combines ISODATA clustering, rule-based classifier and the Multilayer Perceptron (MLP) classifier which uses artificial neural network (ANN). The main goal was to find out the best possible combination or sequence of classifiers for typically classifying tundra type vegetation that yields higher accuracy than the existing classified vegetation map from SPOT data. Unsupervised ISODATA clustering and rule-based classification techniques were combined to produce an intermediate classified map which was

  6. 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.

  7. 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.

  8. 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

  9. Error and Uncertainty in the Accuracy Assessment of Land Cover Maps

    Science.gov (United States)

    Sarmento, Pedro Alexandre Reis

    Traditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the "real" land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps. None

  10. Land Cover Characterization and Mapping of South America for the Year 2010 Using Landsat 30 m Satellite Data

    Directory of Open Access Journals (Sweden)

    Chandra Giri

    2014-10-01

    Full Text Available Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (<5 m satellite data to validate the land cover product. The overall accuracy of the 2010 South American 30-m land cover map is 89% with a Kappa coefficient of 79%. Accuracy of barren areas needs to improve possibly using multi-temporal Landsat data. An update of land cover and change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.

  11. A procedure for merging land cover/use data from Landsat, aerial photography, and map sources - Compatibility, accuracy and cost

    Science.gov (United States)

    Enslin, W. R.; Tilmann, S. E.; Hill-Rowley, R.; Rogers, R. H.

    1977-01-01

    A method is developed to merge land cover/use data from Landsat, aerial photography and map sources into a grid-based geographic information system. The method basically involves computer-assisted categorization of Landsat data to provide certain user-specified land cover categories; manual interpretation of aerial photography to identify other selected land cover/use categories that cannot be obtained from Landsat data; identification of special features from aerial photography or map sources; merging of the interpreted data from all the sources into a computer compatible file under a standardized coding structure; and the production of land cover/use maps, thematic maps, and tabular data. The specific tasks accomplished in producing the merged land cover/use data file and subsequent output products are identified and discussed. It is shown that effective implementation of the merging method is critically dependent on selecting the 'best' data source for each user-specified category in terms of accuracy and time/cost tradeoffs.

  12. 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.

  13. 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

  14. Dominant Benthic Structure and Biological Cover Habitat Maps for West Maui and West Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic habitat maps depict dominant substrate type and biological cover in depths between 0 and ~150 m for two priority sites in the Main Hawaiian Islands; the NOAA...

  15. Gravity and isostatic anomaly maps of Greece produced

    Science.gov (United States)

    Lagios, E.; Chailas, S.; Hipkin, R. G.

    A gravity anomaly map of Greece was first compiled in the early 1970s [Makris and Stavrou, 1984] from all available gravity data collected by different Hellenic institutions. However, to compose this map the data had to be smoothed to the point that many of the smaller-wavelength gravity anomalies were lost. New work begun in 1987 has resulted in the publication of an updated map [Lagios et al., 1994] and an isostatic anomaly map derived from it.The gravity data cover the area between east longitudes 19° and 27° and north latitudes 32° and 42°, organized in files of 100-km squares and grouped in 10-km squares using UTM zone 34 coordinates. Most of the data on land come from the gravity observations of Makris and Stavrou [1984] with additional data from the Institute of Geology and Mining Exploration, the Public Oil Corporation of Greece, and Athens University. These data were checked using techniques similar to those used in compiling the gravity anomaly map of the United States, but the horizontal gradient was used as a check rather than the gravity difference. Marine data were digitized from the maps of Morelli et al. [1975a, 1975b]. All gravity anomaly values are referred to the IGSN-71 system, reduced with the standard Bouger density of 2.67 Mg/m3. We estimate the errors of the anomalies in the continental part of Greece to be ±0.9 mGal; this is expected to be smaller over fairly flat regions. For stations whose height has been determined by leveling, the error is only ±0.3 mGal. For the marine areas, the errors are about ±5 mGal [Morelli, 1990].

  16. 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

  17. 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.

  18. 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

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

    Science.gov (United States)

    López Saldaña, G.; Quaife, T. L.; Clifford, D.

    2014-12-01

    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 prototype land cover product was created for 2006 to 2008. Several machine learning classifiers were tested as well as different sets of input features going from the BRDF parameters to spectral Albedo. We will present the results of the time series development and the first exercises when creating the prototype land cover product.

  20. 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.

  1. Validation of Satellite Snow Cover Maps in North America and Norway

    Science.gov (United States)

    Hall, Dorothy K.; Solberg, Rune; Riggs, George A.

    2002-01-01

    Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.

  2. 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.

  3. Mapping Woodland Cover in the Miombo Ecosystem: A Comparison of Machine Learning Classifiers

    Directory of Open Access Journals (Sweden)

    Courage Kamusoko

    2014-06-01

    Full Text Available Miombo woodlands in Southern Africa are experiencing accelerated changes due to natural and anthropogenic disturbances. In order to formulate sustainable woodland management strategies in the Miombo ecosystem, timely and up-to-date land cover information is required. Recent advances in remote sensing technology have improved land cover mapping in tropical evergreen ecosystems. However, woodland cover mapping remains a challenge in the Miombo ecosystem. The objective of the study was to evaluate the performance of decision trees (DT, random forests (RF, and support vector machines (SVM in the context of improving woodland and non-woodland cover mapping in the Miombo ecosystem in Zimbabwe. We used Multidate Landsat 8 spectral and spatial dependence (Moran’s I variables to map woodland and non-woodland cover. Results show that RF classifier outperformed the SVM and DT classifiers by 4% and 15%, respectively. The RF importance measures show that multidate Landsat 8 spectral and spatial variables had the greatest influence on class-separability in the study area. Therefore, the RF classifier has potential to improve woodland cover mapping in the Miombo ecosystem.

  4. Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

    International Nuclear Information System (INIS)

    Cosentino, B.L.; Lillesand, T.M.

    1991-01-01

    Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

  5. Regional Quantitative Cover Mapping of Tundra Plant Functional Types in Arctic Alaska

    Directory of Open Access Journals (Sweden)

    Matthew J. Macander

    2017-10-01

    Full Text Available Ecosystem maps are foundational tools that support multi-disciplinary study design and applications including wildlife habitat assessment, monitoring and Earth-system modeling. Here, we present continuous-field cover maps for tundra plant functional types (PFTs across ~125,000 km2 of Alaska’s North Slope at 30-m resolution. To develop maps, we collected a field-based training dataset using a point-intercept sampling method at 225 plots spanning bioclimatic and geomorphic gradients. We stratified vegetation by nine PFTs (e.g., low deciduous shrub, dwarf evergreen shrub, sedge, lichen and summarized measurements of the PFTs, open water, bare ground and litter using the cover metrics total cover (areal cover including the understory and top cover (uppermost canopy or ground cover. We then developed 73 spectral predictors derived from Landsat satellite observations (surface reflectance composites for ~15-day periods from May–August and five gridded environmental predictors (e.g., summer temperature, climatological snow-free date to model cover of PFTs using the random forest data-mining algorithm. Model performance tended to be best for canopy-forming PFTs, particularly deciduous shrubs. Our assessment of predictor importance indicated that models for low-statured PFTs were improved through the use of seasonal composites from early and late in the growing season, particularly when similar PFTs were aggregated together (e.g., total deciduous shrub, herbaceous. Continuous-field maps have many advantages over traditional thematic maps, and the methods described here are well-suited to support periodic map updates in tandem with future field and Landsat observations.

  6. 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.

  7. 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

  8. 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...... for classification of land cover. A high degree of automation can be achieved. The obtained results of a practical example are checked with reference values derived from ortho-images in natural colour and from colour images using stereo-vision. An error matrix is applied in the evaluation of the results...

  9. 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

  10. 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.

  11. 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

  12. Effects of grain-producing cover crops on rice grain yield in Cabo Delgado, Mozambique

    Directory of Open Access Journals (Sweden)

    Adriano Stephan Nascente

    Full Text Available ABSTRACT Besides providing benefits to the environment such as soil protection, release of nutrients, soil moisture maintenance, and weed control, cover crops can increase food production for grain production. The aim of this study was to evaluate the production of biomass and grain cover crops (and its respective effects on soil chemical and physical attributes, yield components, and grain yield of rice in Mozambique. The study was conducted in two sites located in the province of Cabo Delgado, in Mozambique. The experimental design was a randomized block in a 2 × 6 factorial, with four repetitions. Treatments were carried out in two locations (Cuaia and Nambaua with six cover crops: Millet (Pennisetum glaucum L.; namarra bean (Lablab purpureus (L. Sweet, velvet beans (Mucuna pruriens L., oloco beans (Vigna radiata (L. R. Wilczek, cowpea (Vigna unguiculata L., and fallow. Cover crops provided similar changes in chemical and physical properties of the soil. Lablab purpureus, Vigna unguiculata, and Mucuna pruriens produced the highest dry matter biomass. Vigna unguiculada produced the highest amount of grains. Rice grain yields were similar under all cover crops and higher in Cuaia than Nambaua.

  13. Improving Land Cover Mapping: a Mobile Application Based on ESA Sentinel 2 Imagery

    Science.gov (United States)

    Melis, M. T.; Dessì, F.; Loddo, P.; La Mantia, C.; Da Pelo, S.; Deflorio, A. M.; Ghiglieri, G.; Hailu, B. T.; Kalegele, K.; Mwasi, B. N.

    2018-04-01

    The increasing availability of satellite data is a real value for the enhancement of environmental knowledge and land management. Possibilities to integrate different source of geo-data are growing and methodologies to create thematic database are becoming very sophisticated. Moreover, the access to internet services and, in particular, to web mapping services is well developed and spread either between expert users than the citizens. Web map services, like Google Maps or Open Street Maps, give the access to updated optical imagery or topographic maps but information on land cover/use - are not still provided. Therefore, there are many failings in the general utilization -non-specialized users- and access to those maps. This issue is particularly felt where the digital (web) maps could form the basis for land use management as they are more economic and accessible than the paper maps. These conditions are well known in many African countries where, while the internet access is becoming open to all, the local map agencies and their products are not widespread.

  14. 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...

  15. 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%.

  16. [Application of biotope mapping model integrated with vegetation cover continuity attributes in urban biodiversity conservation].

    Science.gov (United States)

    Gao, Tian; Qiu, Ling; Chen, Cun-gen

    2010-09-01

    Based on the biotope classification system with vegetation structure as the framework, a modified biotope mapping model integrated with vegetation cover continuity attributes was developed, and applied to the study of the greenbelts in Helsingborg in southern Sweden. An evaluation of the vegetation cover continuity in the greenbelts was carried out by the comparisons of the vascular plant species richness in long- and short-continuity forests, based on the identification of woodland continuity by using ancient woodland indicator species (AWIS). In the test greenbelts, long-continuity woodlands had more AWIS. Among the forests where the dominant trees were more than 30-year-old, the long-continuity ones had a higher biodiversity of vascular plants, compared with the short-continuity ones with the similar vegetation structure. The modified biotope mapping model integrated with the continuity features of vegetation cover could be an important tool in investigating urban biodiversity, and provide corresponding strategies for future urban biodiversity conservation.

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

    International Nuclear Information System (INIS)

    Yang, X; Leys, J

    2014-01-01

    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

  18. 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.

  19. Sampling and Mapping Soil Erosion Cover Factor for Fort Richardson, Alaska. Integrating Stratification and an Up-Scaling Method

    National Research Council Canada - National Science Library

    Wang, Guangxing; Gertner, George; Anderson, Alan B; Howard, Heidi

    2006-01-01

    When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and obtain an accurate map is required...

  20. Downscaling NASA Climatological Data to Produce Detailed Climate Zone Maps

    Science.gov (United States)

    Chandler, William S.; Hoell, James M.; Westberg, David J.; Whitlock, Charles H.; Zhang, Taiping; Stackhouse, P. W.

    2011-01-01

    The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of downscaling NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.

  1. Multitemporal Snow Cover Mapping in Mountainous Terrain for Landsat Climate Data Record Development

    Science.gov (United States)

    Crawford, Christopher J.; Manson, Steven M.; Bauer, Marvin E.; Hall, Dorothy K.

    2013-01-01

    A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM+ imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

  2. Calibration and Validation of Tundra Plant Functional Type Fractional Cover Mapping

    Science.gov (United States)

    Macander, M. J.; Nelson, P.; Frost, G. V., Jr.

    2017-12-01

    Fractional cover maps are being developed for selected tundra plant functional types (PFTs) across >500,000 sq. km of arctic Alaska and adjacent Canada at 30 m resolution. Training and validation data include a field-based training dataset based on point-intercept sampling method at hundreds of plots spanning bioclimatic and geomorphic gradients. We also compiled 50 blocks of 1-5 cm resolution RGB image mosaics in Alaska (White Mountains, North Slope, and Yukon-Kuskokwim Delta) and the Yukon Territory. The mosaics and associated surface and canopy height models were developed using a consumer drone and structure from motion processing. We summarized both the in situ measurements and drone imagery to determine cover of two PFTs: Low and Tall Deciduous Shrub, and Light Fruticose/Foliose Lichen. We applied these data to train 2 m (limited extent) and 30 m (wall to wall) maps of PFT fractional cover for shrubs and lichen. Predictors for 2 m models were commercial satellite imagery such as WorldView-2 and Worldview-3, analyzed on the ABoVE Science Cloud. Predictors for 30 m models were primarily reflectance composites and spectral metrics developed from Landsat imagery, using Google Earth Engine. We compared the performance of models developed from the in situ and drone-derived training data and identify best practices to improve the performance and efficiency of arctic PFT fractional cover mapping.

  3. Historical satellite data used to map Pan-Amazon forest cover

    Science.gov (United States)

    Kalluri, Satya; Desch, Arthur; Curry, Troy; Altstatt, Alice; Devers, Didier; Townshend, John; Tucker, Compton

    Deforestation in the Brazilian Amazon is well documented and the contributions of Brazilian deforestation to global change have been extensively discussed in both scientific and popular literature [e.g., Skole and Tucker, 1993]. However, deforestation within the non-Brazilian tropics of South America has received much less attention. The Pan-Amazon region covering Venezuela, Colombia, Ecuador, Peru, and Bolivia comprises ˜2 million km2 of tropical forest that is under increasing pressure from logging and development. Wall-to-wall high-resolution forest cover maps are needed to properly document the complex distribution patterns of deforestation in the Pan-Amazon [Tucker and Townshend, 2000]. The Deforestation Mapping Group at the University of Marylands Global Land Cover Facility is using Landsat data to generate tropical forest cover maps in this region (Figure l). The study shows that while rates of forest loss are generally lower than those in Brazil, there are hot spots where deforestation rates run as high as 2,200 km2 yr1.

  4. 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

    2018-01-01

    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, and 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

  5. Design of a High Resolution Open Access Global Snow Cover Web Map Service Using Ground and Satellite Observations

    Science.gov (United States)

    Kadlec, J.; Ames, D. P.

    2014-12-01

    The aim of the presented work is creating a freely accessible, dynamic and re-usable snow cover map of the world by combining snow extent and snow depth datasets from multiple sources. The examined data sources are: remote sensing datasets (MODIS, CryoLand), weather forecasting model outputs (OpenWeatherMap, forecast.io), ground observation networks (CUAHSI HIS, GSOD, GHCN, and selected national networks), and user-contributed snow reports on social networks (cross-country and backcountry skiing trip reports). For adding each type of dataset, an interface and an adapter is created. Each adapter supports queries by area, time range, or combination of area and time range. The combined dataset is published as an online snow cover mapping service. This web service lowers the learning curve that is required to view, access, and analyze snow depth maps and snow time-series. All data published by this service are licensed as open data; encouraging the re-use of the data in customized applications in climatology, hydrology, sports and other disciplines. The initial version of the interactive snow map is on the website snow.hydrodata.org. This website supports the view by time and view by site. In view by time, the spatial distribution of snow for a selected area and time period is shown. In view by site, the time-series charts of snow depth at a selected location is displayed. All snow extent and snow depth map layers and time series are accessible and discoverable through internationally approved protocols including WMS, WFS, WCS, WaterOneFlow and WaterML. Therefore they can also be easily added to GIS software or 3rd-party web map applications. The central hypothesis driving this research is that the integration of user contributed data and/or social-network derived snow data together with other open access data sources will result in more accurate and higher resolution - and hence more useful snow cover maps than satellite data or government agency produced data by

  6. A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

    Science.gov (United States)

    Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

    2012-06-01

    Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

  7. Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

    Science.gov (United States)

    Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

    2017-01-01

    Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

  8. Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

    Science.gov (United States)

    Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

    2017-12-01

    Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

  9. Highlighting continued uncertainty in global land cover maps for the user community

    International Nuclear Information System (INIS)

    Fritz, Steffen; See, Linda; McCallum, Ian; Schill, Christian; Obersteiner, Michael; Van der Velde, Marijn; Boettcher, Hannes; Havlík, Petr; Achard, Frédéric

    2011-01-01

    In the last 10 years a number of new global datasets have been created and new, more sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5 are the most recent global land cover products available, where GlobCover (300 m) has the finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has decreased when comparing these two latest products. This disagreement is also evident spatially when examining maps of cropland and forest disagreement between GLC-2000, MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding these products, with a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This letter suggests that data sharing efforts and the provision of more in situ data for training, calibration and validation are very important conditions for improving future global land cover products.

  10. Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification

    Science.gov (United States)

    Michael Hoppus; Stan Arner; Andrew Lister

    2001-01-01

    A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...

  11. 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

  12. Land Cover Mapping Analysis and Urban Growth Modelling Using Remote Sensing Techniques in Greater Cairo Region—Egypt

    Directory of Open Access Journals (Sweden)

    Yasmine Megahed

    2015-09-01

    Full Text Available This study modeled the urban growth in the Greater Cairo Region (GCR, one of the fastest growing mega cities in the world, using remote sensing data and ancillary data. Three land use land cover (LULC maps (1984, 2003 and 2014 were produced from satellite images by using Support Vector Machines (SVM. Then, land cover changes were detected by applying a high level mapping technique that combines binary maps (change/no-change and post classification comparison technique. The spatial and temporal urban growth patterns were analyzed using selected statistical metrics developed in the FRAGSTATS software. Major transitions to urban were modeled to predict the future scenarios for year 2025 using Land Change Modeler (LCM embedded in the IDRISI software. The model results, after validation, indicated that 14% of the vegetation and 4% of the desert in 2014 will be urbanized in 2025. The urban areas within a 5-km buffer around: the Great Pyramids, Islamic Cairo and Al-Baron Palace were calculated, highlighting an intense urbanization especially around the Pyramids; 28% in 2014 up to 40% in 2025. Knowing the current and estimated urbanization situation in GCR will help decision makers to adjust and develop new plans to achieve a sustainable development of urban areas and to protect the historical locations.

  13. Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

    Science.gov (United States)

    Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

    2017-12-01

    The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

  14. Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

    Science.gov (United States)

    Hester, David Barry

    The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

  15. A Study on remote sensing method for drawing up and utilizing ecological and natural map - concentrated on drawing up of Land Cover Classification Map

    Energy Technology Data Exchange (ETDEWEB)

    Jun, Sung Woo; Chung, Sung Moon [Korea Environment Institute, Seoul (Korea)

    1998-12-01

    The drawing up of ecological and natural map, which is highly efficient using remote exploration method, was promoted in this study. As the first step of drawing up of ecological and natural map, this study is working on the drawing up of Land Cover using as a base map. Through the detailed and sufficient consideration on GAP analysis of USA, CORINE project of EU, and examples in Korea, it studied and proposed the Land Cover Classification system and method suitable for Korea. It will be helpful to draw up ecological and natural map by providing two strategies and principles for land cover classification. 26 refs., 33 figs., 9 tabs.

  16. 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.

  17. Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

    Science.gov (United States)

    Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

    2015-03-01

    The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

  18. Hydrograph sensitivity to estimates of map impervious cover: a WinHSPF BASINS case study

    Science.gov (United States)

    Endreny, Theodore A.; Somerlot, Christopher; Hassett, James M.

    2003-04-01

    The BASINS geographic information system hydrologic toolkit was designed to compute total maximum daily loads, which are often derived by combining water quantity estimates with pollutant concentration estimates. In this paper the BASINS toolkit PLOAD and WinHSPF sub-models are briefly described, and then a 0·45 km2 headwater watershed in the New York Croton River area is used for a case study illustrating a full WinHSPF implementation. The goal of the Croton study was to determine the sensitivity of WinHSPF hydrographs to changes in land cover map inputs. This scenario occurs when scaling the WinHSPF model from the smaller 0·45 km2 watershed to the larger 1000 km2 management basin of the entire Croton area. Methods used to test model sensitivity include first calibrating the WinHSPF hydrograph using research-monitored precipitation and discharge data together with high spatial resolution and accuracy land cover data of impervious and pervious areas, and then swapping three separate land cover files, known as GIRAS, MRLC, and DOQQ data, into the calibrated model. Research results indicated that the WinHSPF land cover swapping had peak flow sensitivity in December 2001 hydrographs between 35% underestimation and 20% overestimation, and that errors in land-cover-derived runoff ratios for storm totals and peak flows tracked with the land cover data estimates of impervious area.

  19. 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.

  20. TREE CANOPY COVER MAPPING USING LiDAR IN URBAN BARANGAYS OF CEBU CITY, CENTRAL PHILIPPINES

    Directory of Open Access Journals (Sweden)

    J. A. Ejares

    2016-06-01

    Full Text Available 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.

  1. 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.

  2. Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

    Science.gov (United States)

    Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

    2018-05-01

    Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

  3. Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

    Science.gov (United States)

    Xiao, T.

    2012-12-01

    One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

  4. 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.

  5. 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

  6. Utility of Mobile phones to support In-situ data collection for Land Cover Mapping

    Science.gov (United States)

    Oduor, P.; Omondi, S.; Wahome, A.; Mugo, R. M.; Flores, A.

    2017-12-01

    With the compelling need to create better monitoring tools for our landscapes to enhance better decision making processes, it becomes imperative to do so in much more sophisticated yet simple ways. Making it possible to leverage untapped potential of our "lay men" at the same time enabling us to respond to the complexity of the information we have to get out. SERVIR Eastern and Southern Africa has developed a mobile app that can be utilized with very little prior knowledge or no knowledge at all to collect spatial information on land cover. This set of in-situ data can be collected by masses because the tools is very simple to use, and have this information fed in classification algorithms than can then be used to map out our ever changing landscape. The LULC Mapper is a subset of JiMap system and is able to pull the google earth imagery and open street maps to enable user familiarize with their location. It uses phone GPS, phone network information to map location coordinates and at the same time gives the user sample picture of what to categorize their landscape. The system is able to work offline and when user gets access to internet they can push the information into an amazon database as bulk data. The location details including geotagged photos allows the data to be used in development of a lot of spatial information including land cover data. The app is currently available in Google Play Store and will soon be uploaded on Appstore for utilization by a wider community. We foresee a lot of potential in this tool in terms of making data collection cheaper and affordable. Taking advantage of the advances made in phone technology. We envisage to do a data collection campaign where we can have the tool used for crowdsourcing.

  7. Land use/land cover mapping using multi-scale texture processing of high resolution data

    Science.gov (United States)

    Wong, S. N.; Sarker, M. L. R.

    2014-02-01

    Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

  8. Land use/land cover mapping using multi-scale texture processing of high resolution data

    International Nuclear Information System (INIS)

    Wong, S N; Sarker, M L R

    2014-01-01

    Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road

  9. Carbon mapping of Argentine savannas: Using fractional tree cover to scale from field to region

    Science.gov (United States)

    González-Roglich, M.; Swenson, J. J.

    2015-12-01

    Programs which intend to maintain or enhance carbon (C) stocks in natural ecosystems are promising, but require detailed and spatially explicit C distribution models to monitor the effectiveness of management interventions. Savanna ecosystems are significant components of the global C cycle, covering about one fifth of the global land mass, but they have received less attention in C monitoring protocols. Our goal was to estimate C storage across a broad savanna ecosystem using field surveys and freely available satellite images. We first mapped tree canopies at 2.5 m resolution with a spatial subset of high resolution panchromatic images to then predict regional wall-to-wall tree percent cover using 30-m Landsat imagery and the Random Forests algorithms. We found that a model with summer and winter spectral indices from Landsat, climate and topography performed best. Using a linear relationship between C and % tree cover, we then predicted tree C stocks across the gradient of tree cover, explaining 87 % of the variability. The spatially explicit validation of the tree C model with field-measured C-stocks revealed an RMSE of 8.2 tC/ha which represented ~30% of the mean C stock for areas with tree cover, comparable to studies based on more advanced remote sensing methods, such as LiDAR and RADAR. Sample spatial distribution highly affected the performance of the RF models in predicting tree cover, raising concerns regarding the predictive capabilities of the model in areas for which training data is not present. The 50,000 km2 has ~41 Tg C, which could be released to the atmosphere if agricultural pressure intensifies in this semiarid savanna.

  10. 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

  11. Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

    Science.gov (United States)

    Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

    2017-01-01

    Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

  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. A TEMPORAL MAP IN GEOSTATIONARY ORBIT: THE COVER ETCHING ON THE EchoStar XVI ARTIFACT

    International Nuclear Information System (INIS)

    Weisberg, Joel M.; Paglen, Trevor

    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 disk containing 100 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 small spin-down rates. In this paper, we discuss our approach to the time map etched onto the cover and the scientific data shown on it, and we speculate on the uses that future scientists may have for its data. The other portions of the EchoStar XVI Artifact will be discussed elsewhere.

  14. A TEMPORAL MAP IN GEOSTATIONARY ORBIT: THE COVER ETCHING ON THE EchoStar XVI ARTIFACT

    Energy Technology Data Exchange (ETDEWEB)

    Weisberg, Joel M., E-mail: jweisber@carleton.edu [Department of Physics and Astronomy, Carleton College, Northfield, MN 55057 (United States); Paglen, Trevor, E-mail: trevor@paglen.com

    2012-10-01

    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 disk containing 100 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 small spin-down rates. In this paper, we discuss our approach to the time map etched onto the cover and the scientific data shown on it, and we speculate on the uses that future scientists may have for its data. The other portions of the EchoStar XVI Artifact will be discussed elsewhere.

  15. A GIS Software Toolkit for Monitoring Areal Snow Cover and Producing Daily Hydrologic Forecasts using NASA Satellite Imagery, Phase I

    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...

  16. 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...

  17. 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...

  18. Image analysis for facility siting: a comparison of low- and high-altitude image interpretability for land use/land cover mapping

    International Nuclear Information System (INIS)

    Borella, H.M.; Estes, J.E.; Ezra, C.E.; Scepan, J.; Tinney, L.R.

    1982-01-01

    For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both are-weighted and by-class accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs

  19. Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

    Science.gov (United States)

    Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.

    1982-01-01

    For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

  20. 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.

  1. Moss and lichen cover mapping at local and regional scales in the boreal forest ecosystem of central Canada

    Science.gov (United States)

    Rapalee, G.; Steyaert, L.T.; Hall, F.G.

    2001-01-01

    Mosses and lichens are important components of boreal landscapes [Vitt et al., 1994; Bubier et al., 1997]. They affect plant productivity and belowground carbon sequestration and alter the surface runoff and energy balance. We report the use of multiresolution satellite data to map moss and lichens over the BOREAS region at a 10 m, 30 m, and 1 km scales. Our moss and lichen classification at the 10 m scale is based on ground observations of associations among soil drainage classes, overstory composition, and cover type among four broad classes of ground cover (feather, sphagnum, and brown mosses and lichens). For our 30 m map, we used field observations of ground cover-overstory associations to map mosses and lichens in the BOREAS southern study area (SSA). To scale up to a 1 km (AVHRR) moss map of the BOREAS region, we used the TM SSA mosaics plus regional field data to identify AVHRR overstory-ground cover associations. We found that: 1) ground cover, overstory composition and density are highly correlated, permitting inference of moss and lichen cover from satellite-based land cover classifications; 2) our 1 km moss map reveals that mosses dominate the boreal landscape of central Canada, thereby a significant factor for water, energy, and carbon modeling; 3) TM and AVHRR moss cover maps are comparable; 4) satellite data resolution is important; particularly in detecting the smaller wetland features, lakes, and upland jack pine sites; and 5) distinct regional patterns of moss and lichen cover correspond to latitudinal and elevational gradients. Copyright 2001 by the American Geophysical Union.

  2. 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

  3. 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

  4. A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

    Science.gov (United States)

    Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

    2017-12-01

    Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

  5. A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

    Science.gov (United States)

    Smith, Kathryn E.L.; Nayegandhi, Amar; Brock, John C.

    2010-01-01

    -based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

  6. A method for mapping corn using the US Geological Survey 1992 National Land Cover Dataset

    Science.gov (United States)

    Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.

    2006-01-01

    Long-term exposure to elevated nitrate levels in community drinking water supplies has been associated with an elevated risk of several cancers including non-Hodgkin's lymphoma, colon cancer, and bladder cancer. To estimate human exposure to nitrate, specific crop type information is needed as fertilizer application rates vary widely by crop type. Corn requires the highest application of nitrogen fertilizer of crops grown in the Midwest US. We developed a method to refine the US Geological Survey National Land Cover Dataset (NLCD) (including map and original Landsat images) to distinguish corn from other crops. Overall average agreement between the resulting corn and other row crops class and ground reference data was 0.79 kappa coefficient with individual Landsat images ranging from 0.46 to 0.93 kappa. The highest accuracies occurred in Regions where corn was the single dominant crop (greater than 80.0%) and the crop vegetation conditions at the time of image acquisition were optimum for separation of corn from all other crops. Factors that resulted in lower accuracies included the accuracy of the NLCD map, accuracy of corn areal estimates, crop mixture, crop condition at the time of Landsat overpass, and Landsat scene anomalies.

  7. Change Detection Algorithm for the Production of Land Cover Change Maps over the European Union Countries

    Directory of Open Access Journals (Sweden)

    Sebastian Aleksandrowicz

    2014-06-01

    Full Text Available Contemporary satellite Earth Observation systems provide growing amounts of very high spatial resolution data that can be used in various applications. An increasing number of sensors make it possible to monitor selected areas in great detail. However, in order to handle the volume of data, a high level of automation is required. The semi-automatic change detection methodology described in this paper was developed to annually update land cover maps prepared in the context of the Geoland2. The proposed algorithm was tailored to work with different very high spatial resolution images acquired over different European landscapes. The methodology is a fusion of various change detection methods ranging from: (1 layer arithmetic; (2 vegetation indices (NDVI differentiating; (3 texture calculation; and methods based on (4 canonical correlation analysis (multivariate alteration detection (MAD. User intervention during the production of the change map is limited to the selection of the input data, the size of initial segments and the threshold for texture classification (optionally. To achieve a high level of automation, statistical thresholds were applied in most of the processing steps. Tests showed an overall change recognition accuracy of 89%, and the change type classification methodology can accurately classify transitions between classes.

  8. 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...

  9. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    Science.gov (United States)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  10. Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

    Science.gov (United States)

    Hill, R.; Calvin, W. M.; Harpold, A.

    2017-12-01

    Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

  11. Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Hassan Mohamed

    2018-05-01

    Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

  12. 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.

  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

  14. A new strategy for snow-cover mapping using remote sensing data and ensemble based systems techniques

    Science.gov (United States)

    Roberge, S.; Chokmani, K.; De Sève, D.

    2012-04-01

    The snow cover plays an important role in the hydrological cycle of Quebec (Eastern Canada). Consequently, evaluating its spatial extent interests the authorities responsible for the management of water resources, especially hydropower companies. The main objective of this study is the development of a snow-cover mapping strategy using remote sensing data and ensemble based systems techniques. Planned to be tested in a near real-time operational mode, this snow-cover mapping strategy has the advantage to provide the probability of a pixel to be snow covered and its uncertainty. Ensemble systems are made of two key components. First, a method is needed to build an ensemble of classifiers that is diverse as much as possible. Second, an approach is required to combine the outputs of individual classifiers that make up the ensemble in such a way that correct decisions are amplified, and incorrect ones are cancelled out. In this study, we demonstrate the potential of ensemble systems to snow-cover mapping using remote sensing data. The chosen classifier is a sequential thresholds algorithm using NOAA-AVHRR data adapted to conditions over Eastern Canada. Its special feature is the use of a combination of six sequential thresholds varying according to the day in the winter season. Two versions of the snow-cover mapping algorithm have been developed: one is specific for autumn (from October 1st to December 31st) and the other for spring (from March 16th to May 31st). In order to build the ensemble based system, different versions of the algorithm are created by varying randomly its parameters. One hundred of the versions are included in the ensemble. The probability of a pixel to be snow, no-snow or cloud covered corresponds to the amount of votes the pixel has been classified as such by all classifiers. The overall performance of ensemble based mapping is compared to the overall performance of the chosen classifier, and also with ground observations at meteorological

  15. Inundation Mapping for Heterogeneous Land Covers with Synthetic Aperture Radar and Auxiliary Data

    Science.gov (United States)

    Aristizabal, F.; Judge, J.

    2017-12-01

    Synthetic Aperture Radar (SAR) has been widely used to detect surface water inundation and provides an advantage over multi-spectral instruments due to cloud penetration and higher spatial resolutions. However, detecting inundation for densely vegetated and urban areas with SAR remains a challenge due to corner reflection and diffuse scattering. Additionally, flat urban surfaces such as roads exhibit similar backscatter coefficients as urban surface water. Differences between inundated and non-inundated backscatter over vegetated land covers of static spatial domains have been demonstrated in previous studies. However, these backscatter differences are sensitive to changes in water depth, soil moisture, SAR sensor parameters, terrain, and vegetation properties. These factors tend to make accurate inundation mapping of heterogeneous regions across varying spatial and temporal extents difficult with exclusive use of SAR. This study investigates the utility of auxiliary data specifically high-resolution (10m) terrain information in conjunction with SAR (10m) for detecting inundated areas. Digital elevation models provide an absolute elevation which could enhance inundation mapping given a limited study extent with similar topography. To counter this limitation, a hydrologically relevant terrain index is proposed known as the Height Above Nearest Drainage (HAND) which normalizes topography to the local relative elevation of the nearest point along the relevant drainage line. HAND has been used for assisting remote sensing inundation mapping in the pre-processing stage as a terrain correction tool and as a post-processing mask that eliminates areas of low inundation risk. While the latter technique is useful for reduction of commission errors, it does not employ HAND for reducing omission errors that can occur from dense vegetation, spectral noise, and urban features. Sentinel-1 dual-pol SAR as well as auxiliary HAND will be used as predictors by various supervised and

  16. MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites

    Directory of Open Access Journals (Sweden)

    G. Blöschl

    2012-07-01

    Full Text Available Numerous global and regional validation studies have examined MODIS snow mapping accuracy by using measurements at climate stations, which are mainly at open sites. MODIS accuracy in alpine and forested regions is, however, still not well understood. The main objective of this study is to evaluate MODIS (MOD10A1 and MYD10A1 snow cover products in a small experimental catchment by using extensive snow course measurements at open and forest sites. The MODIS accuracy is tested in the Jalovecky creek catchment (northern Slovakia in the period 2000–2011. The results show that the combined Terra and Aqua images enable snow mapping at an overall accuracy of 91.5%. The accuracies at forested, open and mixed land uses at the Červenec sites are 92.7%, 98.3% and 81.8%, respectively. The use of a 2-day temporal filter enables a significant reduction in the number of days with cloud coverage and an increase in overall snow mapping accuracy. In total, the 2-day temporal filter decreases the number of cloudy days from 61% to 26% and increases the snow mapping accuracy to 94%. The results indicate three possible factors leading to misclassification of snow as land: patchy snow cover, limited MODIS geolocation accuracy and mapping algorithm errors. Out of a total of 27 misclassification cases, patchy snow cover, geolocation issues and mapping errors occur in 12, 12 and 3 cases, respectively.

  17. Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data

    Science.gov (United States)

    Giri, Chandra; Long, Jordan

    2014-01-01

    Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.

  18. 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.

  19. Large-Area, High-Resolution Tree Cover Mapping with Multi-Temporal SPOT5 Imagery, New South Wales, Australia

    Directory of Open Access Journals (Sweden)

    Adrian Fisher

    2016-06-01

    Full Text Available Tree cover maps are used for many purposes, such as vegetation mapping, habitat connectivity and fragmentation studies. Small remnant patches of native vegetation are recognised as ecologically important, yet they are underestimated in remote sensing products derived from Landsat. High spatial resolution sensors are capable of mapping small patches of trees, but their use in large-area mapping has been limited. In this study, multi-temporal Satellite pour l’Observation de la Terre 5 (SPOT5 High Resolution Geometrical data was pan-sharpened to 5 m resolution and used to map tree cover for the Australian state of New South Wales (NSW, an area of over 800,000 km2. Complete coverages of SPOT5 panchromatic and multispectral data over NSW were acquired during four consecutive summers (2008–2011 for a total of 1256 images. After pre-processing, the imagery was used to model foliage projective cover (FPC, a measure of tree canopy density commonly used in Australia. The multi-temporal imagery, FPC models and 26,579 training pixels were used in a binomial logistic regression model to estimate the probability of each pixel containing trees. The probability images were classified into a binary map of tree cover using local thresholds, and then visually edited to reduce errors. The final tree map was then attributed with the mean FPC value from the multi-temporal imagery. Validation of the binary map based on visually assessed high resolution reference imagery revealed an overall accuracy of 88% (±0.51% standard error, while comparison against airborne lidar derived data also resulted in an overall accuracy of 88%. A preliminary assessment of the FPC map by comparing against 76 field measurements showed a very good agreement (r2 = 0.90 with a root mean square error of 8.57%, although this may not be representative due to the opportunistic sampling design. The map represents a regionally consistent and locally relevant record of tree cover for NSW, and

  20. Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992-2015)

    Science.gov (United States)

    Li, Wei; MacBean, Natasha; Ciais, Philippe; Defourny, Pierre; Lamarche, Céline; Bontemps, Sophie; Houghton, Richard A.; Peng, Shushi

    2018-01-01

    Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992-2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics

  1. 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.

  2. Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

    Science.gov (United States)

    Nelson, P.; Paradis, D. P.

    2017-12-01

    The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

  3. Snow Cover Mapping at the Continental to Global Scale Using Combined Visible and Passive Microwave Satellite Data

    Science.gov (United States)

    Armstrong, R. L.; Brodzik, M.; Savoie, M. H.

    2007-12-01

    Over the past several decades both visible and passive microwave satellite data have been utilized for snow mapping at the continental to global scale. Snow mapping using visible data has been based primarily on the magnitude of the surface reflectance, and in more recent cases on specific spectral signatures, while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. We describe the respective problems as well as the advantages and disadvantages of these two types of satellite data for snow cover mapping and demonstrate how a multi-sensor approach is optimal. For the period 1978 to present we combine data from the NOAA weekly snow charts with snow cover derived from the SMMR and SSM/I brightness temperature data. For the period since 2002 we blend NASA EOS MODIS and AMSR-E data sets. Our current product incorporates MODIS data from the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) with microwave-derived snow water equivalent (SWE) at 25 km, resulting in a blended product that includes percent snow cover in the larger grid cell whenever the microwave SWE signal is absent. Validation of AMSR-E at the brightness temperature level is provided through the comparison with data from the well-calibrated heritage SSM/I sensor over large homogeneous snow-covered surfaces (e.g. Dome C region, Antarctica). We also describe how the application of the higher frequency microwave channels (85 and 89 GHz)enhances accurate mapping of shallow and intermittent snow cover.

  4. 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...

  5. Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

    Science.gov (United States)

    Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

    2017-12-01

    Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

  6. Scleractinian Coral Cover Maps Derived from Classified in situ Seafloor Imagery for Select U.S. Locations in the Pacific from 2001 to 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Coral cover maps depict percentage of scleractinian (hard) coral cover along survey tracks, overlain on existing bathymetric grids and/or satellite images, for...

  7. QUALITY ASSESSMENT AND CONTROL OF OUTPUTS OF A NATIONWIDE AGRICULTURAL LAND COVER MAPPING PROGRAM USING LIDAR: PHIL-LIDAR 2 PARMAP EXPERIENCE

    Directory of Open Access Journals (Sweden)

    H. M. Pagkalinawan

    2017-11-01

    Full Text Available The Agricultural Resources Extraction from LiDAR Surveys (PARMAP project component of the Nationwide Detailed Resources Assessment using LiDAR (Phil-LiDAR 2 Program aims to produce detailed agricultural maps using LiDAR. Agricultural land cover at crop level was classified through object based image analysis using Support Vector Machine as classifier and LiDAR derivatives from point cloud (2 points per sq.m. and orthophoto (0.5-meter resolution as inputs. An accuracy of at least 90 %, assessed using validation points from the field and through image interpretation, was required before proceeding to post-processing and map lay-out. Knowledge sharing and capacity development facilitated by the University of the Philippines Diliman (UPD enabled partner universities across the Philippines to produce outputs for their assigned region. Considering output layers were generated by multiple teams working on different landscape complexities with some degree of data quality variability, quality checking is crucial to ensure accuracy standards were met. UPD PARMap devised a centralized and end-to-end scheme divided into four steps – land classification, GIS post-processing, schema application, and map lay-out. At each step, a block is reviewed and, subsequently, either approved or returned with documentation on required revisions. Turnaround time of review is at least one block (area ranging from 10 to 580 sq. km. per day. For coastal municipalities, an additional integration process to incorporate mapped coastal features was applied. Common problems observed during quality checking include misclassifications, gaps between features, incomplete attributes and missing map elements. Some issues are particular to specific blocks such as problematic LiDAR derivatives. UPD addressed these problems through discussion and mentoring visits to partner universities. As of March 2017, a total of 336 municipal agricultural maps have been turned-over to various

  8. Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

    Science.gov (United States)

    Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

    2018-05-01

    The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

  9. Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe

    Directory of Open Access Journals (Sweden)

    Maria Luisa Paracchini

    2013-09-01

    Full Text Available Pollination is a key ecosystem service as many crops but in particular, fruits and vegetables are partially dependent on pollinating insects to produce food for human consumption. Here we assessed how pollination services are delivered at the European scale. We used this assessment to estimate the relative contribution of wild pollinators to crop production. We developed an index of relative pollination potential, which is defined as the relative potential or relative capacity of ecosystems to support crop pollination. The model for relative pollination potential is based on the assumption that different habitats, but in particular forest edges, grasslands rich in flowers and riparian areas, offer suitable sites for wild pollinator insects. Using data of the foraging range of wild bees with short flight distances, we linked relative pollination potential to regional statistics of crop production. At aggregated EU level, the absence of insect pollination would result in a reduction of between 25% and 32% of the total production of crops which are partially dependent on insect pollination, depending on the data source used for the assessment. This production deficit decreases to 2.5% if only the relative pollination potential of a single guild of pollinators is considered. A strength of our approach is the spatially-explicit link between land cover based relative pollination potential and crop yield which enables a general assessment of the benefits that are derived from pollination services in Europe while providing insight where pollination gaps in the landscape occur.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. CRED Cumulative Map of Percent Scleractinian Coral Cover at Kure 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.

  15. 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.

  16. 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.

  17. CRED Cumulative Map of Percent Scleractinian Coral Cover at Laysan 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.

  18. CRED Cumulative Map of Percent Scleractinian Coral Cover at Eleven-Mile 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.

  19. 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.

  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 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.

  2. CRED Cumulative Map of Percent Scleractinian Coral Cover at Gardner Pinnacles, 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.

  3. 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.

  4. 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.

  5. 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.

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

  7. 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.

  8. 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.

  9. High spatial resolution mapping of land cover types in a priority area for conservation in the Brazilian savanna

    Science.gov (United States)

    Ribeiro, F.; Roberts, D. A.; Hess, L. L.; Davis, F. W.; Caylor, K. K.; Nackoney, J.; Antunes Daldegan, G.

    2017-12-01

    Savannas are heterogeneous landscapes consisting of highly mixed land cover types that lack clear distinct boundaries. The Brazilian Cerrado is a Neotropical savanna considered a biodiversity hotspot for conservation due to its biodiversity richness and rapid transformation of its landscape by crop and pasture activities. The Cerrado is one of the most threatened Brazilian biomes and only 2.2% of its original extent is strictly protected. Accurate mapping and monitoring of its ecosystems and adjacent land use are important to select areas for conservation and to improve our understanding of the dynamics in this biome. Land cover mapping of savannas is difficult due to spectral similarity between land cover types resulting from similar vegetation structure, floristically similar components, generalization of land cover classes, and heterogeneity usually expressed as small patch sizes within the natural landscape. These factors are the major contributor to misclassification and low map accuracies among remote sensing studies in savannas. Specific challenges to map the Cerrado's land cover types are related to the spectral similarity between classes of land use and natural vegetation, such as natural grassland vs. cultivated pasture, and forest ecosystem vs. crops. This study seeks to classify and evaluate the land cover patterns across an area ranked as having extremely high priority for future conservation in the Cerrado. The main objective of this study is to identify the representativeness of each vegetation type across the landscape using high to moderate spatial resolution imagery using an automated scheme. A combination of pixel-based and object-based approaches were tested using RapidEye 3A imagery (5m spatial resolution) to classify the Cerrado's major land cover types. The random forest classifier was used to map the major ecosystems present across the area, and demonstrated to have an effective result with 68% of overall accuracy. Post

  10. Using the Landsat Archive to Estimate and Map Changes in Agriculture, Forests, and other Land Cover Types in East Africa

    Science.gov (United States)

    Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.

    2017-12-01

    Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.

  11. Technique for large-scale structural mapping at uranium deposits i in non-metamorphosed sedimentary cover rocks

    International Nuclear Information System (INIS)

    Kochkin, B.T.

    1985-01-01

    The technique for large-scale construction (1:1000 - 1:10000), reflecting small amplitude fracture plicate structures, is given for uranium deposits in non-metamorphozed sedimentary cover rocks. Structure drill log sections, as well as a set of maps with the results of area analysis of hidden disturbances, structural analysis of iso-pachous lines and facies of platform mantle horizons serve as sour ce materials for structural mapplotting. The steps of structural map construction are considered: 1) structural carcass construction; 2) reconstruction of structure contour; 3) time determination of structure initiation; 4) plotting of an additional geologic load

  12. Sprite-producing Convective Storms within the Colorado Lightning Mapping Array

    Science.gov (United States)

    Lyons, W. A.; Cummer, S. A.; Rison, W.; Krehbiel, P. R.; Lang, T. J.; Rutledge, S. A.; Lu, G.; Stanley, M. A.; Ashcraft, T.; Nelson, T. E.

    2012-12-01

    The multi-year, multi-institution effort entitled Physical Origins of Coupling to the Upper Atmosphere from Lightning (PhOCAL), has among its goals to qualitatively understand the meteorology and lightning flash characteristics that produce the unusual and/or very energetic lightning responsible for phenomena such as sprites, halos, elves, blue jets and gigantic jets, collectively known as Transient Luminous Events (TLEs). A key task is to obtain simultaneous video, ideally with a high-speed imager (HSI), of both a TLE and its parent lightning discharge, within the domain of a 3-D Lightning Mapping Array (LMA). While conceptually simple, this task is logistically quite complicated. In 2012, a new 15-station Colorado LMA (COLMA) became operational, covering northeastern Colorado, with the Yucca Ridge Field Station (YRFS) near its western edge. The National Charge Moment Change Network (CMCN), which since 2007 has been documenting sprite-class +CGs (those with impulse change moment changes >100 C km), indicates that a strong gradient of energetic +CGs exists west-to-east through the COLMA, with the most likely region for sprite-producing storms being in the COLMA eastern fringes (western Kansas and Nebraska). Yet, on 8 and 25 June, 2012, intense convective systems formed in the COLMA along and just east of the Front Range, producing severe weather and intense lightning. On the 8th, four sprite parent +CGs were captured at 3000 fps from YRFS with the sprites confirmed by dual (conventional speed) cameras in New Mexico. In a second storm on the 25th, viewing conditions prevented +CG video acquisition, but sprites were logged over the COLMA and detailed reconstructions of the discharges are being made. The parent discharges often began as upward negative leaders propagating into a mid-level positive charge layer at 8-10 km. They often originated within or near the convective core before expanding outward into a stratiform region and involving several hundred square

  13. 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 ...

  14. GlobeLand30 as an alternative fine-scale global land cover map

    DEFF Research Database (Denmark)

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

    2016-01-01

    land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural...

  15. Land cover mapping and GIS processing for the Savannah River Site Database

    International Nuclear Information System (INIS)

    Christel, L.M.; Guber, A.L.

    1994-07-01

    The Savannah River Site (SRS) is owned by the U.S. Department of Energy and operated by Westinghouse Savannah River Company. Located in Barnwell, Aiken, and Allendale counties in South Carolina, SRS covers an area of approximately 77,700 hectares. Land cover information for SRS was interpreted from color and color infrared aerial photography acquired between 1980 and 1989. The data were then used as the source of the land cover data layer for the SRS sitewide Geographic Information System database. This database provides SRS managers with recent land use information and has been successfully used to support cost-effective site characterization and reclamation

  16. 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...

  17. 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.

  18. Multi-Sensor Approach to Mapping Snow Cover Using Data From NASA's EOS Aqua and Terra Spacecraft

    Science.gov (United States)

    Armstrong, R. L.; Brodzik, M. J.

    2003-12-01

    Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Over the past several decades both optical and passive microwave satellite data have been utilized for snow mapping at the regional to global scale. For the period 1978 to 2002, we have shown earlier that both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are, depending on season, less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Snow mapping using optical data is based on the magnitude of the surface reflectance while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Our previous work has defined the respective advantages and disadvantages of these two types of satellite data for snow cover mapping and it is clear that a blended product is optimal. We present a multi-sensor approach to snow mapping based both on historical data as well as data from current NASA EOS sensors. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets. An example of validation at the brightness temperature level is provided through the comparison of AMSR-E with data from the well-calibrated heritage SSM/I sensor over a large homogeneous snow-covered surface (Dome C, Antarctica). Prototype snow cover maps from AMSR-E compare well with maps derived from SSM/I. Our current blended product is being developed in the 25 km EASE-Grid while the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km

  19. 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.

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

    Science.gov (United States)

    Seo, B.; Bogner, C.; Poppenborg, P.; Martin, E.; Hoffmeister, M.; Jun, M.; Koellner, T.; Reineking, B.; Shope, C. L.; Tenhunen, J.

    2014-09-01

    Detailed data on land use and land cover constitute 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 the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea (doi:110.1594/PANGAEA.823677).

  1. 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.

  2. 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.

  3. 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...

  4. 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

  5. Detection and Mapping of Land Use and Land Cover Classes of a ...

    African Journals Online (AJOL)

    FIRST LADY

    Cover Classes of a Developing City in Southeastern. Region of Nigeria .... The emergence of small and medium sized agro-husbandry industries in the peripheral, semi- ..... lack of spatial specialization a hindrance to integrated land management and development .... Journal of Applied Sciences Asian Network for Scientific ...

  6. 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

  7. Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2018-01-01

    Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

  8. An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

    Science.gov (United States)

    Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

    2010-12-01

    Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical

  9. Mapping surface temperature variability on a debris-covered glacier with an unmanned aerial vehicle

    Science.gov (United States)

    Kraaijenbrink, P. D. A.; Litt, M.; Shea, J. M.; Treichler, D.; Koch, I.; Immerzeel, W.

    2016-12-01

    Debris-covered glacier tongues cover about 12% of the glacier surface in high mountain Asia and much of the melt water is generated from those glaciers. A thin layer of supraglacial debris enhances ice melt by lowering the albedo, while thicker debris insulates the ice and reduces melt. Data on debris thickness is therefore an important input for energy balance modelling of these glaciers. Thermal infrared remote sensing can be used to estimate the debris thickness by using an inverse relation between debris surface temperature and thickness. To date this has only been performed using coarse spaceborne thermal imagery, which cannot reveal small scale variation in debris thickness and its influence on the heterogeneous melt patterns on debris-covered glaciers. We deployed an unmanned aerial vehicle mounted with a thermal infrared sensor over the debris-covered Lirung Glacier in Nepal three times in May 2016 to reveal the spatial and temporal variability of surface temperature in high detail. The UAV survey matched a Landsat 8 overpass to be able to make a comparison with spaceborne thermal imagery. The UAV-acquired data is processed using Structure from Motion photogrammetry and georeferenced using DGPS-measured ground control points. Different surface types were distinguished by using data acquired by an additional optical UAV survey in order to correct for differences in surface emissivity. In situ temperature measurements and incoming solar radiation data are used to calibrate the temperature calculations. Debris thicknesses derived are validated by thickness measurements of a ground penetrating radar. Preliminary analysis reveals a spatially highly heterogeneous pattern of surface temperature over Lirung Glacier with a range in temperature of over 40 K. At dawn the debris is relatively cold and its temperature is influenced strongly by the ice underneath. Exposed to the high solar radiation at the high altitude the debris layer heats up very rapidly as sunrise

  10. Mapping Land Cover and Estimating the Grassland Structure in a Priority Area of the Chihuahuan Desert

    Directory of Open Access Journals (Sweden)

    Alberto Rodríguez-Maturino

    2017-10-01

    Full Text Available A field characterization of the grassland vegetation structure, represented by the coverage of grass canopy (CGC and the grass height, was carried out during three years (2009–2011 in a priority area for the conservation of grasslands of North America. Landsat Thematic Mapper (TM5 images were selected and the information of reflectance was obtained based on the geographical location of each field-sampling site. Linear models, constructed with field and satellite data, with high coefficients of determination for CGC (R2 = 0.81, R2 = 0.81 and R2 = 0.72 and grass height (R2 = 0.82, R2 = 0.79 and R2 = 0.73 were obtained. The maps showed a good level of CGC (>25% and grass height (>25 cm, except for the year 2009, which presented the lowest values of grass height in the area. According to the Kappa Index, a moderate concordance among the three CGC maps was presented (0.49–0.59. Conversely, weak and moderate concordances were found among the grass height maps (0.36–0.59. It was observed that areas with a high CGC do not necessarily correspond to areas with greater grass height values. Based on the data analyzed in this study, the grassland areas are highly dynamic, structurally heterogeneous and the spatial distribution of the variables does not show a definite pattern. From the information generated, it is possible to determine those areas that are the most important for monitoring to then establish effective strategies for the conservation of these grasslands and the protection of threatened migratory bird species.

  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. High-Precision Land-Cover-Land-Use GIS Mapping and Land Availability and Suitability Analysis for Grass Biomass Production in the Aroostook River Valley, Maine, USA

    Directory of Open Access Journals (Sweden)

    Chunzeng Wang

    2015-03-01

    Full Text Available High-precision land-cover-land-use GIS mapping was performed in four major townships in Maine’s Aroostook River Valley, using on-screen digitization and direct interpretation of very high spatial resolution satellite multispectral imagery (15–60 cm and high spatial resolution LiDAR data (2 m and the field mapping method. The project not only provides the first-ever high-precision land-use maps for northern Maine, but it also yields accurate hectarage estimates of different land-use types, in particular grassland, defined as fallow land, pasture, and hay field. This enables analysis of potential land availability and suitability for grass biomass production and other sustainable land uses. The results show that the total area of fallow land in the four towns is 7594 hectares, which accounts for 25% of total open land, and that fallow plots equal to or over four hectares in size total 4870, or 16% of open land. Union overlay analysis, using the Natural Resources Conservation Service (NRCS soil data, indicates that only a very small percentage of grassland (4.9% is on “poorly-drained” or “very-poorly-drained” soils, and that most grassland (85% falls into the “farmland of state importance” or “prime farmland” categories, as determined by NRCS. It is concluded that Maine’s Aroostook River Valley has an ample base of suitable, underutilized land for producing grass biomass.

  13. Evaluation and parameterization of ATCOR3 topographic correction method for forest cover mapping in mountain areas

    Science.gov (United States)

    Balthazar, Vincent; Vanacker, Veerle; Lambin, Eric F.

    2012-08-01

    A topographic correction of optical remote sensing data is necessary to improve the quality of quantitative forest cover change analyses in mountainous terrain. The implementation of semi-empirical correction methods requires the calibration of model parameters that are empirically defined. This study develops a method to improve the performance of topographic corrections for forest cover change detection in mountainous terrain through an iterative tuning method of model parameters based on a systematic evaluation of the performance of the correction. The latter was based on: (i) the general matching of reflectances between sunlit and shaded slopes and (ii) the occurrence of abnormal reflectance values, qualified as statistical outliers, in very low illuminated areas. The method was tested on Landsat ETM+ data for rough (Ecuadorian Andes) and very rough mountainous terrain (Bhutan Himalayas). Compared to a reference level (no topographic correction), the ATCOR3 semi-empirical correction method resulted in a considerable reduction of dissimilarities between reflectance values of forested sites in different topographic orientations. Our results indicate that optimal parameter combinations are depending on the site, sun elevation and azimuth and spectral conditions. We demonstrate that the results of relatively simple topographic correction methods can be greatly improved through a feedback loop between parameter tuning and evaluation of the performance of the correction model.

  14. A dataset mapping the potential biophysical effects of vegetation cover change

    Science.gov (United States)

    Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

    2018-02-01

    Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

  15. 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.

  16. Mapping Urban Green Infrastructure: A Novel Landscape-Based Approach to Incorporating Land Use and Land Cover in the Mapping of Human-Dominated Systems

    Directory of Open Access Journals (Sweden)

    Matthew Dennis

    2018-01-01

    Full Text Available Common approaches to mapping green infrastructure in urbanised landscapes invariably focus on measures of land use or land cover and associated functional or physical traits. However, such one-dimensional perspectives do not accurately capture the character and complexity of the landscapes in which urban inhabitants live. The new approach presented in this paper demonstrates how open-source, high spatial and temporal resolution data with global coverage can be used to measure and represent the landscape qualities of urban environments. Through going beyond simple metrics of quantity, such as percentage green and blue cover, it is now possible to explore the extent to which landscape quality helps to unpick the mixed evidence presented in the literature on the benefits of urban nature to human well-being. Here we present a landscape approach, employing remote sensing, GIS and data reduction techniques to map urban green infrastructure elements in a large U.K. city region. Comparison with existing urban datasets demonstrates considerable improvement in terms of coverage and thematic detail. The characterisation of landscapes, using census tracts as spatial units, and subsequent exploration of associations with social–ecological attributes highlights the further detail that can be uncovered by the approach. For example, eight urban landscape types identified for the case study city exhibited associations with distinct socioeconomic conditions accountable not only to quantities but also qualities of green and blue space. The identification of individual landscape features through simultaneous measures of land use and land cover demonstrated unique and significant associations between the former and indicators of human health and ecological condition. The approach may therefore provide a promising basis for developing further insight into processes and characteristics that affect human health and well-being in urban areas, both in the United

  17. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

    Science.gov (United States)

    LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

  18. Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe

    OpenAIRE

    Grazia Zulian; Joachim Maes; Maria Luisa Paracchini

    2013-01-01

    Pollination is a key ecosystem service as many crops but in particular, fruits and vegetables are partially dependent on pollinating insects to produce food for human consumption. Here we assessed how pollination services are delivered at the European scale. We used this assessment to estimate the relative contribution of wild pollinators to crop production. We developed an index of relative pollination potential, which is defined as the relative potential or relative capacity of ecosystems t...

  19. Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

    Science.gov (United States)

    Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

    1982-01-01

    Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

  20. Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

    Science.gov (United States)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

    Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

  1. 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

  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. Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques. [south carolina

    Science.gov (United States)

    Hoffer, R. M. (Principal Investigator)

    1979-01-01

    A literature review on radar and spectral band information was conducted and a NC-130 mission was flown carrying the NS001 scanner system which basically corresponds to the channel configuration of the proposed thematic mapper. Aerial photography and other reference data were obtained for the study site, an area approximately 290 sq miles in north central South Carolina. A cover type map was prepared and methods were devised for reformatting and geometrically correcting MSS CRT data. Arrangements were made to obtain LANDSAT data for dates approximating the NC-130 mission. Because of the waveband employed to obtain SEASAT radar data, it was decided to determine if X-band (2.40 cm to 3.75 cm wavelength) imagery is available.

  4. 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

    as input for modelling the wind conditions over a Danish near-coastal region. The flow model results were compared to alternative use of USGS land cover. Significant variations in the wind speed were found between the two atmospheric flow model results. Furthermore the wind speed from the flow model...... was compared to meteorological observations taken in a tall mast and from ground based remote-sensing wind profiling lidars. It is shown that simulations using CORINE provide better wind flow results close to the surface as compared to those using USGS on the investigated site. The next step towards...... improvement of flow model inputs is to investigate in further detail applied use of satellite maps in forested areas. 75% of new land-based wind farms are planned in or near forests in Europe. In forested areas the near surface atmospheric flow is more challenging to calculate than in regions with low...

  5. Can single classifiers be as useful as model ensembles to produce benthic seabed substratum maps?

    Science.gov (United States)

    Turner, Joseph A.; Babcock, Russell C.; Hovey, Renae; Kendrick, Gary A.

    2018-05-01

    Numerous machine-learning classifiers are available for benthic habitat map production, which can lead to different results. This study highlights the performance of the Random Forest (RF) classifier, which was significantly better than Classification Trees (CT), Naïve Bayes (NB), and a multi-model ensemble in terms of overall accuracy, Balanced Error Rate (BER), Kappa, and area under the curve (AUC) values. RF accuracy was often higher than 90% for each substratum class, even at the most detailed level of the substratum classification and AUC values also indicated excellent performance (0.8-1). Total agreement between classifiers was high at the broadest level of classification (75-80%) when differentiating between hard and soft substratum. However, this sharply declined as the number of substratum categories increased (19-45%) including a mix of rock, gravel, pebbles, and sand. The model ensemble, produced from the results of all three classifiers by majority voting, did not show any increase in predictive performance when compared to the single RF classifier. This study shows how a single classifier may be sufficient to produce benthic seabed maps and model ensembles of multiple classifiers.

  6. 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.

  7. Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

    Science.gov (United States)

    Tamiminia, H.; Homayouni, S.; Safari, A.

    2015-12-01

    Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

  8. 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

  9. Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

    Science.gov (United States)

    Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

    2017-12-01

    Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

  10. Meta-Analysis of Land Use / Land Cover Change Factors in the Conterminous US and Prediction of Potential Working Timberlands in the US South from FIA Inventory Plots and NLCD Cover Maps

    Science.gov (United States)

    Jeuck, James A.

    -analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products

  11. It's time for a crisper image of the Face of the Earth: Landsat and climate time series for massive land cover & climate change mapping at detailed resolution.

    Science.gov (United States)

    Pons, Xavier; Miquel, Ninyerola; Oscar, González-Guerrero; Cristina, Cea; Pere, Serra; Alaitz, Zabala; Lluís, Pesquer; Ivette, Serral; Joan, Masó; Cristina, Domingo; Maria, Serra Josep; Jordi, Cristóbal; Chris, Hain; Martha, Anderson; Juanjo, Vidal

    2014-05-01

    Combining climate dynamics and land cover at a relative coarse resolution allows a very interesting approach to global studies, because in many cases these studies are based on a quite high temporal resolution, but they may be limited in large areas like the Mediterranean. However, the current availability of long time series of Landsat imagery and spatially detailed surface climate models allow thinking on global databases improving the results of mapping in areas with a complex history of landscape dynamics, characterized by fragmentation, or areas where relief creates intricate climate patterns that can be hardly monitored or modeled at coarse spatial resolutions. DinaCliVe (supported by the Spanish Government and ERDF, and by the Catalan Government, under grants CGL2012-33927 and SGR2009-1511) is the name of the project that aims analyzing land cover and land use dynamics as well as vegetation stress, with a particular emphasis on droughts, and the role that climate variation may have had in such phenomena. To meet this objective is proposed to design a massive database from long time series of Landsat land cover products (grouped in quinquennia) and monthly climate records (in situ climate data) for the Iberian Peninsula (582,000 km2). The whole area encompasses 47 Landsat WRS2 scenes (Landsat 4 to 8 missions, from path 197 to 202 and from rows 30 to 34), and 52 Landsat WRS1 scenes (for the previous Landsat missions, 212 to 221 and 30 to 34). Therefore, a mean of 49.5 Landsat scenes, 8 quinquennia per scene and a about 6 dates per quinquennium , from 1975 to present, produces around 2376 sets resulting in 30 m x 30 m spatial resolution maps. Each set is composed by highly coherent geometric and radiometric multispectral and multitemporal (to account for phenology) imagery as well as vegetation and wetness indexes, and several derived topographic information (about 10 Tbyte of data). Furthermore, on the basis on a previous work: the Digital Climatic Atlas of

  12. 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...

  13. 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...

  14. 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

    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...

  15. Assessment of the mapping of fractional woody cover in southern African savannas using multi-temporal and polarimetric ALOS PALSAR L-band images

    CSIR Research Space (South Africa)

    Urbazaev, M

    2015-09-01

    Full Text Available cover maps. The LiDAR survey was carried out in April 2008 with the Carnegie Airborne Observatory (CAO, http://cao.ciw.edu). The highest correlations to the reference data were obtained from SAR backscatters of the dry season, followed by the wet season...

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

    Science.gov (United States)

    Pajander, Jari Pekka; Matero, Sanni; Sloth, Jakob; Wan, Feng; Rantanen, Jukka; Yang, Mingshi

    2015-06-01

    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. A series of lysozyme/mannitol formulations were spray-dried using a lab-scale spray dryer. Further, the surface temperature of drying droplet/particles was monitored using the DRYING KINETICS ANALYZER™ (DKA) with controllable drying conditions mimicking the spray-drying process to estimate the drying kinetics of the lysozyme/mannitol formulations. The mannitol polymorphism and the spatial distribution of lysozyme in the particles were examined using X-ray powder diffractometry (XRPD) and Raman microscopy. Partial Least Squares Discriminant Analysis was used for analyzing the Raman microscopy data. 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, whereas Raman analysis indicated that a mixture of α-mannitol and δ-mannitol was detected in the single particles from DKA. In addition Raman mapping indicated that the presence of lysozyme seemed to favor the appearance of α-mannitol in the particles from DKA evidenced by close proximity of lysozyme and mannitol in the particles. It suggested that the presence of lysozyme tend to induce metastable solid state forms upon the drying process.

  17. Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data

    Science.gov (United States)

    Beaumont, Benjamin; Grippa, Tais; Lennert, Moritz; Vanhuysse, Sabine; Stephenne, Nathalie; Wolff, Eléonore

    2017-07-01

    Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e., a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed.

  18. A fully automatic processing chain to produce Burn Scar Mapping products, using the full Landsat archive over Greece

    Science.gov (United States)

    Kontoes, Charalampos; Papoutsis, Ioannis; Herekakis, Themistoklis; Michail, Dimitrios; Ieronymidi, Emmanuela

    2013-04-01

    Remote sensing tools for the accurate, robust and timely assessment of the damages inflicted by forest wildfires provide information that is of paramount importance to public environmental agencies and related stakeholders before, during and after the crisis. The Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (IAASARS/NOA) has developed a fully automatic single and/or multi date processing chain that takes as input archived Landsat 4, 5 or 7 raw images and produces precise diachronic burnt area polygons and damage assessments over the Greek territory. The methodology consists of three fully automatic stages: 1) the pre-processing stage where the metadata of the raw images are extracted, followed by the application of the LEDAPS software platform for calibration and mask production and the Automated Precise Orthorectification Package, developed by NASA, for image geo-registration and orthorectification, 2) the core-BSM (Burn Scar Mapping) processing stage which incorporates a published classification algorithm based on a series of physical indexes, the application of two filters for noise removal using graph-based techniques and the grouping of pixels classified as burnt to form the appropriate pixels clusters before proceeding to conversion from raster to vector, and 3) the post-processing stage where the products are thematically refined and enriched using auxiliary GIS layers (underlying land cover/use, administrative boundaries, etc.) and human logic/evidence to suppress false alarms and omission errors. The established processing chain has been successfully applied to the entire archive of Landsat imagery over Greece spanning from 1984 to 2012, which has been collected and managed in IAASARS/NOA. The number of full Landsat frames that were subject of process in the framework of the study was 415. These burn scar mapping products are generated for the first time to such a temporal and spatial

  19. 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

  20. Rapid assessment and mapping of tree cover in southern African savanna woodlands using a new iPhone App and Landsat 8 imagery

    Science.gov (United States)

    Fuller, D. O.

    2016-12-01

    Tree cover is a key parameter in climate modeling. It strongly influences CO2 exchanges between the land surface and atmosphere and surface energy balance. We measured percent woody canopy cover (PWCC) in the savanna woodlands of eastern Zambia over a 10-day period in May 2016 using a new iPhone App (CanopyApp) and related these field measurements to Landsat 8 (L8) Band 4 (red) imagery acquired approximately the same time. We then used parameters from the band 4 digital numbers (DNs)-PWCC linear regression to derive a new map of PWCC for the entire L8 scene. Consistent with theory and previous empirical studies, we found that the relationship between L8 band 4 DNs- PWCC was negative and linear (r2 = 0.61, p reflectance was weaker (r2 = 0.46, p shadowing effects and other spatial inhomogeneities from variable soil and background reflectance. Our PWCC map agreed qualitatively with similar percent tree-cover maps based on Landsat level 1 products and past field studies in the area conducted using a hemispherical lens. Our results also compared favorably with other remote sensing studies that have used complex multivariate approaches to estimate tree cover, which suggests that use of a single L8 band 4 is sufficient to estimate PWCC when spectral contrast exists between the grass, soil and tree layers during the austral fall period in southern African savannas.

  1. 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.

  2. Removing non-urban roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

    Science.gov (United States)

    Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.

    2018-01-01

    Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

  3. From the Cover: Cell-replacement therapy for diabetes: Generating functional insulin-producing tissue from adult human liver cells

    Science.gov (United States)

    Sapir, Tamar; Shternhall, Keren; Meivar-Levy, Irit; Blumenfeld, Tamar; Cohen, Hamutal; Skutelsky, Ehud; Eventov-Friedman, Smadar; Barshack, Iris; Goldberg, Iris; Pri-Chen, Sarah; Ben-Dor, Lya; Polak-Charcon, Sylvie; Karasik, Avraham; Shimon, Ilan; Mor, Eytan; Ferber, Sarah

    2005-05-01

    Shortage in tissue availability from cadaver donors and the need for life-long immunosuppression severely restrict the large-scale application of cell-replacement therapy for diabetic patients. This study suggests the potential use of adult human liver as alternate tissue for autologous beta-cell-replacement therapy. By using pancreatic and duodenal homeobox gene 1 (PDX-1) and soluble factors, we induced a comprehensive developmental shift of adult human liver cells into functional insulin-producing cells. PDX-1-treated human liver cells express insulin, store it in defined granules, and secrete the hormone in a glucose-regulated manner. When transplanted under the renal capsule of diabetic, immunodeficient mice, the cells ameliorated hyperglycemia for prolonged periods of time. Inducing developmental redirection of adult liver offers the potential of a cell-replacement therapy for diabetics by allowing the patient to be the donor of his own insulin-producing tissue. pancreas | transdifferentiation

  4. Trajectory analysis of land use and land cover maps to improve spatial-temporal patterns, and impact assessment on groundwater recharge

    Science.gov (United States)

    Zomlot, Z.; Verbeiren, B.; Huysmans, M.; Batelaan, O.

    2017-11-01

    Land use/land cover (LULC) change is a consequence of human-induced global environmental change. It is also considered one of the major factors affecting groundwater recharge. Uncertainties and inconsistencies in LULC maps are one of the difficulties that LULC timeseries analysis face and which have a significant effect on hydrological impact analysis. Therefore, an accuracy assessment approach of LULC timeseries is needed for a more reliable hydrological analysis and prediction. The objective of this paper is to assess the impact of land use uncertainty and to improve the accuracy of a timeseries of CORINE (coordination of information on the environment) land cover maps by using a new approach of identifying spatial-temporal LULC change trajectories as a pre-processing tool. This ensures consistency of model input when dealing with land-use dynamics and as such improves the accuracy of land use maps and consequently groundwater recharge estimation. As a case study the impact of consistent land use changes from 1990 until 2013 on groundwater recharge for the Flanders-Brussels region is assessed. The change trajectory analysis successfully assigned a rational trajectory to 99% of all pixels. The methodology is shown to be powerful in correcting interpretation inconsistencies and overestimation errors in CORINE land cover maps. The overall kappa (cell-by-cell map comparison) improved from 0.6 to 0.8 and from 0.2 to 0.7 for forest and pasture land use classes respectively. The study shows that the inconsistencies in the land use maps introduce uncertainty in groundwater recharge estimation in a range of 10-30%. The analysis showed that during the period of 1990-2013 the LULC changes were mainly driven by urban expansion. The results show that the resolution at which the spatial analysis is performed is important; the recharge differences using original and corrected CORINE land cover maps increase considerably with increasing spatial resolution. This study indicates

  5. Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in southern California

    Science.gov (United States)

    Sarah A. Lewis; Leigh B. Lentile; Andrew T. Hudak; Peter R. Robichaud; Penelope Morgan; Michael J. Bobbitt

    2007-01-01

    Wildfire effects on the ground surface are indicative of the potential for post-fire watershed erosion response. Areas with remaining organic ground cover will likely experience less erosion than areas of complete ground cover combustion or exposed mineral soil. The Simi and Old fires burned ~67,000 ha in southern California in 2003. Burn severity indices calculated...

  6. 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

  7. Moving from proprietary to open-source solutions for academic research in remote sensing: Example with semi-automated land cover mapping

    OpenAIRE

    Grippa, Taïs

    2017-01-01

    GRASS GIS has recently experienced significant improvements for Object-Based Image Analysis. At ULB the choice was made to combine GRASS GIS and Python in a semi-automated processing chain for land-cover mapping. The later proved its ability of being quickly customized in order to match the requirements of different projects. In order to promote the OSGEO software, we decided to make it freely available, allowing anyone interested to review, reuse and/or enhance it for further studies.

  8. 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...

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  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, Thomas 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. Producing Distribution Maps for a Spatially-Explicit Ecosystem Model Using Large Monitoring and Environmental Databases and a Combination of Interpolation and Extrapolation

    Directory of Open Access Journals (Sweden)

    Arnaud Grüss

    2018-01-01

    Full Text Available To be able to simulate spatial patterns of predator-prey interactions, many spatially-explicit ecosystem modeling platforms, including Atlantis, need to be provided with distribution maps defining the annual or seasonal spatial distributions of functional groups and life stages. We developed a methodology combining extrapolation and interpolation of the predictions made by statistical habitat models to produce distribution maps for the fish and invertebrates represented in the Atlantis model of the Gulf of Mexico (GOM Large Marine Ecosystem (LME (“Atlantis-GOM”. This methodology consists of: (1 compiling a large monitoring database, gathering all the fisheries-independent and fisheries-dependent data collected in the northern (U.S. GOM since 2000; (2 compiling a large environmental database, storing all the environmental parameters known to influence the spatial distribution patterns of fish and invertebrates of the GOM; (3 fitting binomial generalized additive models (GAMs to the large monitoring and environmental databases, and geostatistical binomial generalized linear mixed models (GLMMs to the large monitoring database; and (4 employing GAM predictions to infer spatial distributions in the southern GOM, and GLMM predictions to infer spatial distributions in the U.S. GOM. Thus, our methodology allows for reasonable extrapolation in the southern GOM based on a large amount of monitoring and environmental data, and for interpolation in the U.S. GOM accurately reflecting the probability of encountering fish and invertebrates in that region. We used an iterative cross-validation procedure to validate GAMs. When a GAM did not pass the validation test, we employed a GAM for a related functional group/life stage to generate distribution maps for the southern GOM. In addition, no geostatistical GLMMs were fit for the functional groups and life stages whose depth, longitudinal and latitudinal ranges within the U.S. GOM are not entirely covered by

  15. A methodology for producing small scale rural land use maps in semi-arid developing countries using orbital imagery

    Science.gov (United States)

    Vangenderen, J. L. (Principal Investigator); Lock, B. F.

    1976-01-01

    The author has identified the following significant results. Results have shown that it is feasible to design a methodology that can provide suitable guidelines for operational production of small scale rural land use maps of semiarid developing regions from LANDSAT MSS imagery, using inexpensive and unsophisticated visual techniques. The suggested methodology provides immediate practical benefits to map makers attempting to produce land use maps in countries with limited budgets and equipment. Many preprocessing and interpretation techniques were considered, but rejected on the grounds that they were inappropriate mainly due to the high cost of imagery and/or equipment, or due to their inadequacy for use in operational projects in the developing countries. Suggested imagery and interpretation techniques, consisting of color composites and monocular magnification proved to be the simplest, fastest, and most versatile methods.

  16. 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...

  17. Cartographic standards to improve maps produced by the Forest Inventory and Analysis program

    Science.gov (United States)

    Charles H. (Hobie) Perry; Mark D. Nelson

    2009-01-01

    The Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program is incorporating an increasing number of cartographic products in reports, publications, and presentations. To create greater quality and consistency within the national FIA program, a Geospatial Standards team developed cartographic design standards for FIA map...

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

    International Nuclear Information System (INIS)

    Pungkul, S; Suraswasdi, C; Phonekeo, V

    2014-01-01

    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

  19. the implications of land use/cover dynamics on resources

    African Journals Online (AJOL)

    2017-12-04

    Dec 4, 2017 ... Land use maps were produced using the GIS software packages of ... Keywords: Land use/cover, Dynamics, Remote Sensing Techniques, Geographic Information System, .... sporadic floods and landslides in Bambui which.

  20. 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.

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

    Czech Academy of Sciences Publication Activity Database

    Van´t Hof, A. E.; Marec, František; Saccheri, I. J.; Brakefield, P. M.; Zwaan, B. J.

    2008-01-01

    Roč. 3, č. 12 (2008), e3882 E-ISSN 1932-6203 R&D Projects: GA ČR GA206/06/1860 Institutional research plan: CEZ:AV0Z50070508 Keywords : Bicyclus anynana * cytogenetic characterization * AFLP-based genetic linkage mapping Subject RIV: EB - Genetics ; Molecular Biology

  2. On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales

    Science.gov (United States)

    Härer, Stefan; Bernhardt, Matthias; Siebers, Matthias; Schulz, Karsten

    2018-05-01

    Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.

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

    Science.gov (United States)

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

    2017-01-01

    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., <5 m) land cover datasets become more available for these areas, semi-or fully-automated methods for distinguishing...

  4. 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.

  5. 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.

  6. 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.

  7. Reconnaissance geologic mapping of a portion of the rain‐forest‐covered Guiana Shield, Northwestern Brazil, using SIR-B and digital aeromagnetic data

    Science.gov (United States)

    Pellon de Miranda, Fernando; McCafferty, Anne E.; Taranik, James V.

    1994-01-01

    This paper documents the result of an integrated analysis of spaceborne radar (SIR-B) and digital aeromagnetic data carried out in the heavily forested Guiana Shield. The objective of the research is to interpret the geophysical data base to its limit to produce a reconnaissance geologic map as an aid to ground work planning in a worst‐case setting. Linear geomorphic features were identified based on the interpretation of the SIR-B image. Digital manipulation of aeromagnetic data allowed the development of a color‐shaded relief map of reduced‐to‐pole magnetic anomalies, a terrace‐magnetization map, and a map showing the location of maximum values of the horizontal component of the pseudogravity gradient (magnetization boundary lines). The resultant end product was a reconnaissance geologic map where broad terrane categories were delineated and geologic faults with both topographic and magnetic expression were defined. The availability of global spaceborne radar coverage in the 1990s and the large number of existing digital aeromagnetic surveys in northwestern Brazil indicate that this approach can be potentially useful for reconnaissance geologic mapping elsewhere in the Guiana Shield.

  8. Clinical evaluations of complete autologous fibrin glue, produced by the CryoSeal® FS system, and polyglycolic acid sheets as wound coverings after oral surgery.

    Science.gov (United States)

    Kouketsu, Atsumu; Nogami, Shinnosuke; Yamada-Fujiwara, Minami; Nagai, Hirokazu; Yamauchi, Kensuke; Mori, Shiro; Miyashita, Hitoshi; Kawai, Tadashi; Matsui, Aritsune; Kataoka, Yoshihiro; Satomi, Norihisa; Ezoe, Yushi; Abe, Satoko; Takeda, Yuri; Tone, Takeshi; Hirayama, Bunnichi; Kurobane, Tsuyoshi; Tashiro, Kazuki; Yanagisawa, Yuta; Takahashi, Tetsu

    2017-09-01

    The CryoSeal ® FS System has been recently introduced as an automated device for the production of complete fibrin glue from autologous plasma, rather than from pool allogenic or cattle blood, to prevent viral infection and allergic reaction. We evaluated the effectiveness of complete autologous fibrin glue and polyglycolic acid (PGA) sheet wound coverings in mucosa defect oral surgery. Postoperative pain, scar contracture, ingestion, tongue dyskinesia, and postoperative bleeding were evaluated in 12 patients who underwent oral (including the tongue) mucosa excision, and received a PGA sheet and an autologous fibrin glue covering. They were compared with 12 patients who received a PGA sheet and commercial allogenic fibrin glue. All cases in the complete autologous fibrin glue group demonstrated good wound healing without complications such as local infection or incomplete cure. All evaluated clinical measures in this group were similar or superior to the commercial allogenic fibrin glue group. Coagulation and adhesion quality achieved with this method was comparable to that with a PGA sheet and commercial fibrin glue. Covering oral surgery wounds with complete autologous fibrin glue produced by an automated device was convenient, safe, and reduced the risk of viral infection and allergic reaction associated with conventional techniques. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  9. Mapping the Forest Type and Land Cover of Puerto Rico, a Component of the Caribbean Biodiversity Hotspot

    Science.gov (United States)

    Eileen Helmer; Olga Ramos; T. DEL M. LÓPEZ; Maya Quinones; W. DIAZ

    2002-01-01

    The Caribbean is one of the world’s centers of biodiversity and endemism. As in similar regions, many of its islands have complex topography, climate and soils, and ecological zones change over small areas. A segmented, supervised classification approach using Landsat TM imagery enabled us to develop the most detailed island-wide map of Puerto Rico’s extremely complex...

  10. Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

    Science.gov (United States)

    Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

    1981-01-01

    Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

  11. A procedure for merging land cover/use data from LANDSAT, aerial photography, and map sources: Compatibility, accuracy, and cost. Remote Sensing Project

    Science.gov (United States)

    Enslin, W. R.; Tilmann, S. E.; Hill-Rowley, R.; Rogers, R. H.

    1977-01-01

    Regional planning agencies are currently expressing a need for detailed land cover/use information to effectively meet the requirements of various federal programs. Individual data sources have advantages and limitations in fulfilling this need, both in terms of time/cost and technological capability. A methodology has been developed to merge land cover/use data from LANDSAT, aerial photography and map sources to maximize the effective use of a variety of data sources in the provision of an integrated information system for regional analysis. A test of the proposed inventory method is currently under way in four central Michigan townships. This test will evaluate the compatibility, accuracy and cost of the integrated method with reference to inventories developed from a single data source, and determine both the technological feasibility and analytical potential of such a system.

  12. Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

    Science.gov (United States)

    Ghrefat, Habes A.; Goodell, Philip C.

    2011-08-01

    The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen

  13. 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...

  14. 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...

  15. Mapping the energy footprint of produced water management in New Mexico

    Science.gov (United States)

    Zemlick, Katie; Kalhor, Elmira; Thomson, Bruce M.; Chermak, Janie M.; Sullivan Graham, Enid J.; Tidwell, Vincent C.

    2018-02-01

    Hydraulic fracturing (HF) and horizontal drilling have revolutionized the fossil fuel industry by enabling production from unconventional oil and gas (UOG) reserves. However, UOG development requires large volumes of water, and subsequent oil and gas production from both conventional and unconventional wells generate large volumes of produced water (PW). While PW is usually considered a waste product, its reuse may lessen demand for freshwater supplies, reduce costs for transportation and disposal, and reduce the risks for injection-induced seismicity. Whether this water is disposed of or treated and reused, both methods require significant amounts of energy. The objective of this study was to identify the primary energy demands of alternative water management strategies, and to characterize and quantify their geographic variability in four oil and gas producing basins in New Mexico using a single year of production. Results illustrate the importance of each component of each produced water management strategy in determining its total energy footprint. Based on 2015 production and water use data, the energy to extract fresh groundwater for hydraulic fracturing (34 GWh-th yr-1.) exceeds the energy that would be required if the same volume of PW were treated chemically (19 GWh-th yr-1.). In addition, the energy required to transport fresh water and dispose of PW (167 GWh-th yr-1.) is far greater than that required to move treated PW (8 GWh-th yr-1.) to a point of reuse. Furthermore, transportation distances, which contribute significantly to the total energy footprint of a given management strategy, are underestimated by nearly 50% state-wide. This indicates that reuse may be an even more energy efficient way to manage PW, even with energy-intensive treatment strategies like electrocoagulation. Reuse of PW for HF is not only more energy efficient than conventional management techniques, it also reduces both demand for scarce fresh water resources and

  16. 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....../particles was monitored using the DRYING KINETICS ANALYZER™ (DKA) with controllable drying conditions mimicking the spray-drying process to estimate the drying kinetics of the lysozyme/mannitol formulations. The mannitol polymorphism and the spatial distribution of lysozyme in the particles were examined using X......-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...

  17. Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: "The Forest Pulse".

    Science.gov (United States)

    Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M; Fa, John E; Farfán, Miguel Á; Romero, David; Real, Raimundo

    2016-12-01

    Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing

  18. 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.

  19. Evaluation of methods to produce an image library for automatic patient model localization for dose mapping during fluoroscopically guided procedures

    Science.gov (United States)

    Kilian-Meneghin, Josh; Xiong, Z.; Rudin, S.; Oines, A.; Bednarek, D. R.

    2017-03-01

    The purpose of this work is to evaluate methods for producing a library of 2D-radiographic images to be correlated to clinical images obtained during a fluoroscopically-guided procedure for automated patient-model localization. The localization algorithm will be used to improve the accuracy of the skin-dose map superimposed on the 3D patient- model of the real-time Dose-Tracking-System (DTS). For the library, 2D images were generated from CT datasets of the SK-150 anthropomorphic phantom using two methods: Schmid's 3D-visualization tool and Plastimatch's digitally-reconstructed-radiograph (DRR) code. Those images, as well as a standard 2D-radiographic image, were correlated to a 2D-fluoroscopic image of a phantom, which represented the clinical-fluoroscopic image, using the Corr2 function in Matlab. The Corr2 function takes two images and outputs the relative correlation between them, which is fed into the localization algorithm. Higher correlation means better alignment of the 3D patient-model with the patient image. In this instance, it was determined that the localization algorithm will succeed when Corr2 returns a correlation of at least 50%. The 3D-visualization tool images returned 55-80% correlation relative to the fluoroscopic-image, which was comparable to the correlation for the radiograph. The DRR images returned 61-90% correlation, again comparable to the radiograph. Both methods prove to be sufficient for the localization algorithm and can be produced quickly; however, the DRR method produces more accurate grey-levels. Using the DRR code, a library at varying angles can be produced for the localization algorithm.

  20. High spatial resolution mapping of the Cerrado's land cover and land use types in the priority area for conservation Chapada da Contagem, Brazil.

    Science.gov (United States)

    Ribeiro, F.; Roberts, D. A.; Davis, F. W.; Antunes Daldegan, G.; Nackoney, J.; Hess, L. L.

    2016-12-01

    The Brazilian savanna, Cerrado, is the second largest biome over South America and the most floristically diverse savanna in the world. This biome is considered a conservation hotspot in respect to its biodiversity importance and rapid transformation of its landscape. The Cerrado's natural vegetation has been severely transformed by agriculture and pasture activities. Currently it is the main agricultural frontier in Brazil and one of the most threatened Brazilian biomes. This scenario results in environmental impacts such as ecosystems fragmentation as well as losses in connectivity, biodiversity and gene flow, changes in the microclimate and energy, carbon and nutrients cycles, among others. The Priority Areas for Conservation is a governmental program from Brazil that identifies areas with high conservation priority. One of this program's recommendation is a natural vegetation map including their major ecosystem classes. This study aims to generate more precise information for the Cerrado's vegetation. The main objective of this study is to identify which ecosystems are being prioritized and/or threatened by land use, refining information for further protection. In order to test methods, the priority area for conservation Chapada da Contagem was selected as the study site. This area is ranked as "extremely high priority" by the government and is located in the Federal District and Goias State, Brazil. Satellites with finer spatial resolution may improve the classification of the Cerrado's vegetation. Remote sensing methods and two criteria were tested using RapidEye 3A imagery (5m spatial resolution) collected in 2014 in order to classify the Cerrado's major land cover types of this area, as well as its land use. One criterion considers the Cerrado's major terrestrial ecosystems, which are divided into forest, savanna and grassland. The other involves scaling it down to the major physiognomic groups of each ecosystem. Other sources of environmental dataset such

  1. Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data

    Science.gov (United States)

    Gibril, Mohamed Barakat A.; Idrees, Mohammed Oludare; Yao, Kouame; Shafri, Helmi Zulhaidi Mohd

    2018-01-01

    The growing use of optimization for geographic object-based image analysis and the possibility to derive a wide range of information about the image in textual form makes machine learning (data mining) a versatile tool for information extraction from multiple data sources. This paper presents application of data mining for land-cover classification by fusing SPOT-6, RADARSAT-2, and derived dataset. First, the images and other derived indices (normalized difference vegetation index, normalized difference water index, and soil adjusted vegetation index) were combined and subjected to segmentation process with optimal segmentation parameters obtained using combination of spatial and Taguchi statistical optimization. The image objects, which carry all the attributes of the input datasets, were extracted and related to the target land-cover classes through data mining algorithms (decision tree) for classification. To evaluate the performance, the result was compared with two nonparametric classifiers: support vector machine (SVM) and random forest (RF). Furthermore, the decision tree classification result was evaluated against six unoptimized trials segmented using arbitrary parameter combinations. The result shows that the optimized process produces better land-use land-cover classification with overall classification accuracy of 91.79%, 87.25%, and 88.69% for SVM and RF, respectively, while the results of the six unoptimized classifications yield overall accuracy between 84.44% and 88.08%. Higher accuracy of the optimized data mining classification approach compared to the unoptimized results indicates that the optimization process has significant impact on the classification quality.

  2. 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.

  3. Map showing principal drainage basins, principal runoff-producing areas, and selected stream flow data in the Kaiparowits coal-basin area, Utah

    Science.gov (United States)

    Price, Don

    1978-01-01

    This is one of a series of maps that describe the geology and related natural resources in the Kaiparowits coal-basin area. Streamflow records used to compile this map and the accompanying table were collected by the U.S. Geological Survey in cooperation with the Utah State Engineer and the Utah Department of Transportation. The principal runoff-producing areas were delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Information about Lake Powell was furnished by the U.S. Bureau of Reclamation.

  4. Increasing the availability of national mapping products.

    Science.gov (United States)

    Roney, J.I.; Ogilvie, B.C.

    1981-01-01

    A discussion of the means employed by the US Geological Survey to facilitate map usage, covering aspects of project Map Accessibility Program including special rolled and folded map packaging, new market testing, parks and campgrounds program, expanded map dealer program, new booklet-type State sales index and catalog and new USGS map reference code. The USGS is seen as the producer of a tremendous nation-wide inventory of topographic and related map products available in unprecedented types, formats and scales, and as endeavouring to increase access to its products. The new USGS map reference code is appended. -J.C.Stone

  5. 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

  6. 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

  7. Carbon steel protection in G.S. (Girlder sulfide) plants. Iron sulfide scales formation on surfaces covered by fabrication produced films. Pt. 4

    International Nuclear Information System (INIS)

    Burkart, A.L.

    1986-04-01

    This work describes the assays aimed to passivate the steel carbon of the process pipings. This steel is marked by the ASTM A 333 G6 and is chemically similar to those of isotopic exchange towers which corrode in contact with in-water hydrogen sulfide solutions forming iron sulfide protective layers. The differences between both materials lie in the surface characteristics to be passivated. The steel of towers has an internal side covered by paint which shall be removed prior to passivation. The steel's internal side shall be covered by a film formed during the fabrication process and constituted by calcinated wastes and iron oxides (magnetite, hematite and wustite). This film interferes in the formation process of passivating layers of pyrrhotite and pyrite. The possibility to passivate the pipes in their actual state was evaluated since it would result highly laborious and expensive to eliminate the film. (Author) [es

  8. Taxonomic classification of world map units in crop producing areas of Argentina and Brazil with representative US soil series and major land resource areas in which they occur

    Science.gov (United States)

    Huckle, H. F. (Principal Investigator)

    1980-01-01

    The most probable current U.S. taxonomic classification of the soils estimated to dominate world soil map units (WSM)) in selected crop producing states of Argentina and Brazil are presented. Representative U.S. soil series the units are given. The map units occurring in each state are listed with areal extent and major U.S. land resource areas in which similar soils most probably occur. Soil series sampled in LARS Technical Report 111579 and major land resource areas in which they occur with corresponding similar WSM units at the taxonomic subgroup levels are given.

  9. Seafloor mapping of large areas using multibeam system - Indian experience

    Digital Repository Service at National Institute of Oceanography (India)

    Kodagali, V.N.; KameshRaju, K.A; Ramprasad, T.

    averaged and merged to produce large area maps. Maps were generated in the scale of 1 mil. and 1.5 mil covering area of about 2 mil. sq.km in single map. Also, depth contour interval were generated. A computer program was developed to convert the depth data...

  10. 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...

  11. 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,…

  12. Car Covers | Outdoor Covers Canada

    OpenAIRE

    Covers, Outdoor

    2018-01-01

    Protect your car from the elements with Ultimate Touch Car Cover. The multi-layer non-woven fabric is soft on the finish and offers 4 seasons all weather protection.https://outdoorcovers.ca/car-covers/

  13. Producing a satellite-derived map and modelling Spartina alterniflora expansion for Willapa Bay in Washington State

    Science.gov (United States)

    Berlin, Cynthia Jane

    1998-12-01

    This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential

  14. Focus on CSIR research in water resources: improved methods for aquifer vulnerability assessments and protocols (AVAP) for producing vulnerability maps, taking into account information on soils

    CSIR Research Space (South Africa)

    Colvin, C

    2007-08-01

    Full Text Available for Aquifer Vulnerability Assessments and Protocols (AVAP) for producing vulnerability maps, taking into account information on soils Groundwater resources are increas- ingly threatened by pollution. The AVAP project was initiated to develop improved... characteristics. Both intrinsic and specific vulnerability are taken into account. The approach used to determine the vulnerability of the in- termediate zone involved the descrip- tion and quantification of the factors that influence vulnerability (unsatu...

  15. Spatial-temporal development of the mangrove vegetation cover on a hydraulic landfill (Via Expressa Sul, Florianópolis, SC): mapping and interpretation of digital aerophotographs, and quantitative analysis

    OpenAIRE

    Anderson Tavares de Melo; Eduardo Juan Soriano-Sierra; Luiz Antônio Paulino

    2011-01-01

    The implementation of a hydraulic landfill along the southern expressway (Via Expressa Sul), in the central-south region of Santa Catarina Island, started in 1995 and was completed in 1997. The landfill provided the mangrove vegetation a new environment to colonize, which has developed rapidly during this short period of time. This study mapped the vegetation cover of this region using aerial photographs from five years (1994, 1997, 2002, 2004 and 2007), which demonstrated the spatial-tempora...

  16. Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

    Science.gov (United States)

    Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.

    2014-06-01

    Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.

  17. Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

    International Nuclear Information System (INIS)

    Deilmai, B Rokni; Ahmad, B Bin; Zabihi, H

    2014-01-01

    Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification

  18. CRED Cumulative Map of Percent Scleractinian Coral Cover along towed camera sled tracks and AUV dive tracks at Rota Island, Commonwealth of the Northern Mariana Islands

    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. Optical data were collected by CRED...

  19. Evaluating The Land Use And Land Cover Dynamics In Borena ...

    African Journals Online (AJOL)

    The integration of satellite remote sensing and GIS was an effective approach for analyzing the direction, rate, and spatial pattern of land use change. Three land use and land cover maps were produced by analyzing remotely sensed images of Landsat satellite imageries at three time points (1972,1985,and 2003) .

  20. MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

    Science.gov (United States)

    Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

    2017-08-15

    Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  1. Landfill Top Covers

    DEFF Research Database (Denmark)

    Scheutz, Charlotte; Kjeldsen, Peter

    2011-01-01

    The purpose of the final cover of a landfill is to contain the waste and to provide for a physical separation between the waste and the environment for protection of public health. Most landfill covers are designed with the primary goal to reduce or prevent infiltration of precipitation...... into the landfill in order to minimize leachate generation. In addition the cover also has to control the release of gases produced in the landfill so the gas can be ventilated, collected and utilized, or oxidized in situ. The landfill cover should also minimize erosion and support vegetation. Finally the cover...... 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...

  2. Mean flow produced by small-amplitude vibrations of a liquid bridge with its free surface covered with an insoluble surfactant

    Science.gov (United States)

    Carrión, Luis M.; Herrada, Miguel A.; Montanero, José M.; Vega, José M.

    2017-09-01

    As is well known, confined fluid systems subject to forced vibrations produce mean flows, called in this context streaming flows. These mean flows promote an overall mass transport in the fluid that has consequences in the transport of passive scalars and surfactants, when these are present in a fluid interface. Such transport causes surfactant concentration inhomogeneities that are to be counterbalanced by Marangoni elasticity. Therefore, the interaction of streaming flows and Marangoni convection is expected to produce new flow structures that are different from those resulting when only one of these effects is present. The present paper focuses on this interaction using the liquid bridge geometry as a paradigmatic system for the analysis. Such analysis is based on an appropriate post-processing of the results obtained via direct numerical simulation of the system for moderately small viscosity, a condition consistent with typical experiments of vibrated millimetric liquid bridges. It is seen that the flow patterns show a nonmonotone behavior as the Marangoni number is increased. In addition, the strength of the mean flow at the free surface exhibits two well-defined regimes as the forcing amplitude increases. These regimes show fairly universal power-law behaviors.

  3. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Snow Cover/Depth (SCD) Binary Map Environmental Data Record (EDR) from IDPS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Binary Snow Cover (BSC) from the Visible Infrared Imaging Radiometer Suite...

  4. Estimation of snow cover distribution in Beas basin, Indian Himalaya ...

    Indian Academy of Sciences (India)

    In the present paper, a methodology has been developed for the mapping of snow cover in Beas ... Different snow cover mapping methods using snow indices are compared to find the suitable ... cover are important factors for human activities,.

  5. GREX/COVER-PLASTEX: an experiment to analyze the space-time structure of extensive air showers produced by primary cosmic rays of 1015 eV

    International Nuclear Information System (INIS)

    Agnetta, G.; Ambrosio, M.; Beaman, J.; Barbarino, G.C.; Biondo, B.; Catalano, O.; Colesanti, L.; Dali, G.; Guarino, F.; Lauro, A.; Lloyd-Evans, J.; Mangano, A.; Popova, L.; Watson, A.A.

    1995-01-01

    A novel experimental installation is described in which the traditional method of detecting extensive air showers with scintillation counters is significantly extended by the addition of limited streamer tube hodoscopes (LST) and layers of resistive plate counters (RPC). Runs with the scintillator array, GREX, at Haverah Park have demonstrated the power of the LST hodoscopes to determine the direction of arrival of muons, electrons and photons in air showers while the RPC system permits the relative arrival time of individual particles and the temporal thickness and structure of the shower disc to be obtained. The potential of these technical advances for studying the longitudinal profile of air showers produced by primaries of about 1000 TeV is briefly discussed. First measurements of thickness and time profile of EAS front are also reported. (orig.)

  6. National Land Cover Database (NLCD) Land Cover Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Land Cover Collection is produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...

  7. 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.

  8. 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

  9. 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.

  10. Maps From Mud—Using the Multiple Scenario Approach to Reconstruct Land Cover Dynamics From Pollen Records: A Case Study of Two Neolithic Landscapes

    Directory of Open Access Journals (Sweden)

    M. Jane Bunting

    2018-04-01

    Full Text Available Pollen records contain a wide range of information about past land cover, but translation from the pollen diagram to other formats remains a challenge. In this paper, we present LandPolFlow, a software package enabling Multiple Scenario Approach (MSA based land cover reconstruction from pollen records for specific landscapes. It has two components: a basic Geographic Information System which takes grids of landscape constraints (e.g., topography, geology and generates possible “scenarios” of past land cover using a combination of probabilistic and deterministic placement rules to distribute defined plant communities within the landscape, and a pollen dispersal and deposition model which simulates pollen loading at specified points within each scenario and compares that statistically with actual pollen assemblages from the same location. Goodness of fit statistics from multiple pollen site locations are used to identify which scenarios are likely reconstructions of past land cover. We apply this approach to two case studies of Neolithisation in Britain, the first from the Somerset Levels and Moors and the second from Mainland, Orkney. Both landscapes contain significant evidence of Neolithic activity, but present contrasting contexts. In Somerset, wet-preserved Neolithic remains such as trackways are abundant, but little dry land settlement archaeology is known, and the pre-Neolithic landscape was extensively wooded. In Orkney, the Neolithic archaeology includes domestic and monumental stone-built structures forming a UNESCO World Heritage Site, and the pre-Neolithic landscape was largely treeless. Existing pollen records were collated from both landscapes and correlated within new chronological frameworks (presented elsewhere. This allowed pollen data to be grouped into 200 year periods, or “timeslices,” for reconstruction of land cover through time using the MSA. Reconstruction suggests that subtle but clear and persistent impacts of

  11. 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.

  12. 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.

  13. a Free and Open Source Tool to Assess the Accuracy of Land Cover Maps: Implementation and Application to Lombardy Region (italy)

    Science.gov (United States)

    Bratic, G.; Brovelli, M. A.; Molinari, M. E.

    2018-04-01

    The availability of thematic maps has significantly increased over the last few years. Validation of these maps is a key factor in assessing their suitability for different applications. The evaluation of the accuracy of classified data is carried out through a comparison with a reference dataset and the generation of a confusion matrix from which many quality indexes can be derived. In this work, an ad hoc free and open source Python tool was implemented to automatically compute all the matrix confusion-derived accuracy indexes proposed by literature. The tool was integrated into GRASS GIS environment and successfully applied to evaluate the quality of three high-resolution global datasets (GlobeLand30, Global Urban Footprint, Global Human Settlement Layer Built-Up Grid) in the Lombardy Region area (Italy). In addition to the most commonly used accuracy measures, e.g. overall accuracy and Kappa, the tool allowed to compute and investigate less known indexes such as the Ground Truth and the Classification Success Index. The promising tool will be further extended with spatial autocorrelation analysis functions and made available to researcher and user community.

  14. Mapping and analysis land-use and land-cover changes during 1996-2016 in Lubuk Kertang mangrove forest, North Sumatra, Indonesia

    Science.gov (United States)

    Basyuni, M.; Fitri, A.; Harahap, Z. A.

    2018-03-01

    Mangrove forest plays a significant role for biogeochemical carbon cycle in the context of climate change along the tropical coastal area. The present study analyzed the land-use and land-cover changes from 1996, 2006 and 2016 in Lubuk Kertang mangrove forest, Langkat, North Sumatra, Indonesia. Mangrove diversity in Lubuk Kertang consists of fifteen species, Acanthus ilicifolius, Avicennia marina, A. lanata, A. officinalis, Bruguiera gymnorrhiza, B. sexangula, Ceriops tagal, Excoecaria agallocha, Lumnitzera racemosa, L. littorea, R. apiculata, R. mucronata, Scyphiphora hydrophyllacea, Sonneratia caseolaris, and Xylocarpus granatum. The land use/land cover consists of seven classes namely, mangrove forest, river, residential, paddy field, oil palm plantation, aquaculture, and open space area. A land use change matrix showed that the decrease of mangrove forest 109.4 ha from 1996-2006 converted to aquaculture 51.5 ha (47.1%). By contrast, mangrove lost 291.2 ha during 2006-2016, with main driver deforestation was oil palm plantation 128.1 ha (44%). During twenty years mangrove forest has been lost more than 400.4 ha, which is equal to 20.02 ha/year. On the other hand, oil palm plantation and aquaculture have been increased 155.3 ha and 114.1 ha during 1996-2016, respectively, suggested that both land-uses are mainly responsible for mangrove deforestation. These data are likely to contribute towards coastal management planning and practice and mitigating actions for emission reduction scenario.

  15. 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.

  16. 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)

  17. Fine mapping of the latency-related gene of herpes simplex virus type 1: alternative splicing produces distinct latency-related RNAs containing open reading frames

    International Nuclear Information System (INIS)

    Wechsler, S.L.; Nesburn, A.B.; Watson, R.; Slanina, S.M.; Ghiasi, H.

    1988-01-01

    The latency-related (LR) gene of herpes simplex virus type 1 (HSV-1) is transcriptionally active during HSV-1 latency, producing at least two LR-RNAs. The LR gene partially overlaps the immediate-early gene ICP0 and is transcribed in the opposite direction from ICP0, producing LR-RNAs that are complementary (antisense) to ICP0 mRNA. The LR gene is thought to be involved in HSV-1 latency. The authors report here the time mapping and partial sequence analysis of this HSV-1 LR gene. 32 P-labeled genomic DNA restriction fragments and synthetic oligonucleotides were used as probes for in situ hybridizations and Northern (RNA) blot hybridizations of RNA from trigeminal ganglia of rabbits latently infected with HSV-1. The two most abundant LR-RNAs appeared to share their 5' and 3' ends and to be produced by alternative splicing. These LR-RNAs were approximately 2 and 1.3 to 1.5 kilobases in length and were designated LR-RNA 1 and LF-RNA 2, respectively. LR-RNA 1 appeared to have at least one intron removed, while LR-RNA 2 appeared to have at least two introns removed. The LR-RNAs contained two potential long open reading frames, suggesting the possibility that one or more of the LR-RNAs may be a functional mRNA

  18. 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.

  19. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

  20. Single-edition quadrangle maps

    Science.gov (United States)

    ,

    1998-01-01

    In August 1993, the U.S. Geological Survey's (USGS) National Mapping Division and the U.S. Department of Agriculture's Forest Service signed an Interagency Agreement to begin a single-edition joint mapping program. This agreement established the coordination for producing and maintaining single-edition primary series topographic maps for quadrangles containing National Forest System lands. The joint mapping program saves money by eliminating duplication of effort by the agencies and results in a more frequent revision cycle for quadrangles containing national forests. Maps are revised on the basis of jointly developed standards and contain normal features mapped by the USGS, as well as additional features required for efficient management of National Forest System lands. Single-edition maps look slightly different but meet the content, accuracy, and quality criteria of other USGS products. The Forest Service is responsible for the land management of more than 191 million acres of land throughout the continental United States, Alaska, and Puerto Rico, including 155 national forests and 20 national grasslands. These areas make up the National Forest System lands and comprise more than 10,600 of the 56,000 primary series 7.5-minute quadrangle maps (15-minute in Alaska) covering the United States. The Forest Service has assumed responsibility for maintaining these maps, and the USGS remains responsible for printing and distributing them. Before the agreement, both agencies published similar maps of the same areas. The maps were used for different purposes, but had comparable types of features that were revised at different times. Now, the two products have been combined into one so that the revision cycle is stabilized and only one agency revises the maps, thus increasing the number of current maps available for National Forest System lands. This agreement has improved service to the public by requiring that the agencies share the same maps and that the maps meet a

  1. Map Archive Mining: Visual-Analytical Approaches to Explore Large Historical Map Collections

    Directory of Open Access Journals (Sweden)

    Johannes H. Uhl

    2018-04-01

    Full Text Available Historical maps are unique sources of retrospective geographical information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographical information contained in such data archives makes it possible to extend geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives (e.g., more than 200,000 map sheets in the United States Geological Survey topographic map archive and the low graphical quality of older, manually-produced map sheets, the process to extract geographical information from these map archives needs to be automated to the highest degree possible. To understand the potential challenges (e.g., salient map characteristics and data quality variations in automating large-scale information extraction tasks for map archives, it is useful to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of georeferenced map sheets at different map scales. Such preliminary analytical steps are often neglected or ignored in the map processing literature but represent critical phases that lay the foundation for any subsequent computational processes including recognition. Exemplified for the United States Geological Survey topographic map and the Sanborn fire insurance map archives, we demonstrate how such preliminary analyses can be systematically conducted using traditional analytical and cartographic techniques, as well as visual-analytical data mining tools originating from machine learning and data science.

  2. 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.

  3. Spatial-temporal development of the mangrove vegetation cover on a hydraulic landfill (Via Expressa Sul, Florianópolis, SC: mapping and interpretation of digital aerophotographs, and quantitative analysis

    Directory of Open Access Journals (Sweden)

    Anderson Tavares de Melo

    2011-12-01

    Full Text Available The implementation of a hydraulic landfill along the southern expressway (Via Expressa Sul, in the central-south region of Santa Catarina Island, started in 1995 and was completed in 1997. The landfill provided the mangrove vegetation a new environment to colonize, which has developed rapidly during this short period of time. This study mapped the vegetation cover of this region using aerial photographs from five years (1994, 1997, 2002, 2004 and 2007, which demonstrated the spatial-temporal evolution of the vegetation since the year before the implementation of the landfill (1994 to its recent state (2007. The data from this study allowed changes in the surface of three bands of vegetation, a band of trees (Laguncularia racemosa and Avicennia schaueriana, a band of the seagrass praturá (Spartina alterniflora and a transition band (companions of mangrove species and restinga plants, to be quantified.

  4. AVALIAÇÃO E MAPEAMENTO DA COBERTURA VEGETAL DA REGIÃO CENTRAL DA CIDADE DE JUIZ DE FORA – MG - EVALUATION AND MAPPING OF REGION CENTRAL VEGETATION COVER OF JUIZ DE FORA – MG

    Directory of Open Access Journals (Sweden)

    Isabela Fernanda Moraes de Paula

    2017-04-01

    proposed by Jim (1989, in the analysis of the shape and spatial distribution of vegetation cover. In this sense, the results achieved show that most regions of the central area of the city of Juiz de Fora are less than desirable in vegetation cover, requiring investments, mainly in the areas of urban integration, whose percentage of areas covered by vegetation in respect of all covers only 2%. It is noteworthy that the higher the population density, the lower the percentage of vegetation cover, it can be said that the vegetation cover in the central area of the city of Juiz de Fora is fragmented, discontinuous and presents many "empty spaces". In the mapping carried out was found 15.401% of areas covered by woody vegetation, about 1.694% of shrub and 8.59% of undergrowth. The largest expanses of green spots are scattered in between, scattered throughout the area and disconnect with each other. Therefore, its measurement, classification and spatial distribution are of paramount importance as it become essential basis for improvements and planning in the context of urban areas.

  5. 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

  6. Sganzerla Cover

    Directory of Open Access Journals (Sweden)

    Victor da Rosa

    2014-06-01

    Full Text Available 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.

  7. The National Map - Orthoimagery

    Science.gov (United States)

    Mauck, James; Brown, Kim; Carswell, William J.

    2009-01-01

    Orthorectified digital aerial photographs and satellite images of 1-meter (m) pixel resolution or finer make up the orthoimagery component of The National Map. The process of orthorectification removes feature displacements and scale variations caused by terrain relief and sensor geometry. The result is a combination of the image characteristics of an aerial photograph or satellite image and the geometric qualities of a map. These attributes allow users to: *Measure distance *Calculate areas *Determine shapes of features *Calculate directions *Determine accurate coordinates *Determine land cover and use *Perform change detection *Update maps The standard digital orthoimage is a 1-m or finer resolution, natural color or color infra-red product. Most are now produced as GeoTIFFs and accompanied by a Federal Geographic Data Committee (FGDC)-compliant metadata file. The primary source for 1-m data is the National Agriculture Imagery Program (NAIP) leaf-on imagery. The U.S. Geological Survey (USGS) utilizes NAIP imagery as the image layer on its 'Digital- Map' - a new generation of USGS topographic maps (http://nationalmap.gov/digital_map). However, many Federal, State, and local governments and organizations require finer resolutions to meet a myriad of needs. Most of these images are leaf-off, natural-color products at resolutions of 1-foot (ft) or finer.

  8. Break Lines, This data was produced for the USGS according to specific project requirements. The Lidar derived breaklines cover Somerset County and the Western portion of Wicomico County, Maryland. Inland streams, rivers, lakes, ponds and tidal features are present., Published in 2012, Not Applicable scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Break Lines dataset current as of 2012. This data was produced for the USGS according to specific project requirements. The Lidar derived breaklines cover Somerset...

  9. Knockdown of MAP4 and DNAL1 produces a post-fusion and pre-nuclear translocation impairment in HIV-1 replication

    International Nuclear Information System (INIS)

    Gallo, Daniel E.; Hope, Thomas J.

    2012-01-01

    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.

  10. Planimetric Features Generalization for the Production of Small-Scale Map by Using Base Maps and the Existing Algorithms

    Directory of Open Access Journals (Sweden)

    M. Modiri

    2014-10-01

    Full Text Available Cartographic maps are representations of the Earth upon a flat surface in the smaller scale than it’s true. Large scale maps cover relatively small regions in great detail and small scale maps cover large regions such as nations, continents and the whole globe. Logical connection between the features and scale map must be maintained by changing the scale and it is important to recognize that even the most accurate maps sacrifice a certain amount of accuracy in scale to deliver a greater visual usefulness to its user. Cartographic generalization, or map generalization, is the method whereby information is selected and represented on a map in a way that adapts to the scale of the display medium of the map, not necessarily preserving all intricate geographical or other cartographic details. Due to the problems facing small-scale map production process and the need to spend time and money for surveying, today’s generalization is used as executive approach. The software is proposed in this paper that converted various data and information to certain Data Model. This software can produce generalization map according to base map using the existing algorithm. Planimetric generalization algorithms and roles are described in this article. Finally small-scale maps with 1:100,000, 1:250,000 and 1:500,000 scale are produced automatically and they are shown at the end.

  11. 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.

  12. 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

  13. 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

    Directory of Open Access Journals (Sweden)

    F. Xu

    2017-08-01

    Full Text Available 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

  14. Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

    Science.gov (United States)

    Smith, J. LaRue; Damar, Nancy A.; Charlet, David A.; Westenburg, Craig L.

    2014-01-01

    DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

  15. Simultaneous comparison and assessment of eight remotely sensed maps of Philippine forests

    Science.gov (United States)

    Estoque, Ronald C.; Pontius, Robert G.; Murayama, Yuji; Hou, Hao; Thapa, Rajesh B.; Lasco, Rodel D.; Villar, Merlito A.

    2018-05-01

    This article compares and assesses eight remotely sensed maps of Philippine forest cover in the year 2010. We examined eight Forest versus Non-Forest maps reclassified from eight land cover products: the Philippine Land Cover, the Climate Change Initiative (CCI) Land Cover, the Landsat Vegetation Continuous Fields (VCF), the MODIS VCF, the MODIS Land Cover Type product (MCD12Q1), the Global Tree Canopy Cover, the ALOS-PALSAR Forest/Non-Forest Map, and the GlobeLand30. The reference data consisted of 9852 randomly distributed sample points interpreted from Google Earth. We created methods to assess the maps and their combinations. Results show that the percentage of the Philippines covered by forest ranges among the maps from a low of 23% for the Philippine Land Cover to a high of 67% for GlobeLand30. Landsat VCF estimates 36% forest cover, which is closest to the 37% estimate based on the reference data. The eight maps plus the reference data agree unanimously on 30% of the sample points, of which 11% are attributable to forest and 19% to non-forest. The overall disagreement between the reference data and Philippine Land Cover is 21%, which is the least among the eight Forest versus Non-Forest maps. About half of the 9852 points have a nested structure such that the forest in a given dataset is a subset of the forest in the datasets that have more forest than the given dataset. The variation among the maps regarding forest quantity and allocation relates to the combined effects of the various definitions of forest and classification errors. Scientists and policy makers must consider these insights when producing future forest cover maps and when establishing benchmarks for forest cover monitoring.

  16. Expanding Thurston maps

    CERN Document Server

    Bonk, Mario

    2017-01-01

    This monograph is devoted to the study of the dynamics of expanding Thurston maps under iteration. A Thurston map is a branched covering map on a two-dimensional topological sphere such that each critical point of the map has a finite orbit under iteration. It is called expanding if, roughly speaking, preimages of a fine open cover of the underlying sphere under iterates of the map become finer and finer as the order of the iterate increases. Every expanding Thurston map gives rise to a fractal space, called its visual sphere. Many dynamical properties of the map are encoded in the geometry of this visual sphere. For example, an expanding Thurston map is topologically conjugate to a rational map if and only if its visual sphere is quasisymmetrically equivalent to the Riemann sphere. This relation between dynamics and fractal geometry is the main focus for the investigations in this work.

  17. Geotechnical Mapping of An-Najaf City, Iraq

    Directory of Open Access Journals (Sweden)

    Nadher Hassan Al-Baghdadi

    2016-12-01

    Full Text Available The present paper submits a set geotechnical maps for the area of An-Najaf city, by using contour lines to represent the different geotechnical properties of the soil. The present research work is very important step toward preparing a geotechnical database for this region, to complete the geotechnical database over all the country, (Iraq. Using such a database is very important in geotechincal investigation, reconnaissance phase, of construction projects. Within this phase of site investigation, numbers, depths and locations of the boreholes needed, will be determined. A well known commercial software (SURFER 11, was used to produce the all the contour maps of geotechnical properties presented herein. A forty nine (49 contour maps were produced to cover the variations, within the geotechnical properties of the soil, to produce realistic description to these soil properties. Both Google maps and Universal Transverse Mercator coordinate system (UTM have been used in the contour maps for easy use.

  18. On parabolic external maps

    DEFF Research Database (Denmark)

    Lomonaco, Luna; Petersen, Carsten Lunde; Shen, Weixiao

    2017-01-01

    We prove that any C1+BV degree d ≥ 2 circle covering h having all periodic orbits weakly expanding, is conjugate by a C1+BV diffeomorphism to a metrically expanding map. We use this to connect the space of parabolic external maps (coming from the theory of parabolic-like maps) to metrically expan...

  19. Operational monitoring of land-cover change using multitemporal remote sensing data

    Science.gov (United States)

    Rogan, John

    2005-11-01

    Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation

  20. Police Stations, City of Wichita Police Department substation locations. 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 Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Police Stations dataset current as of 2008. City of Wichita Police Department substation locations. Cover is derived from Emergency Facilities (scEfac) cover. Used...

  1. PG-2 photogrammetric plotter: a rapid and accurate means of mapping surface effects produced by subsurface nuclear testing at the Nevada Test Site, Nevada

    International Nuclear Information System (INIS)

    Van de Werken, M.G.

    1983-01-01

    Since October 1981, the US Geological Survey has been using the Kern PG-2 photogrammetric plotter to map surface effects using post-test aerial photographs. The main goal of this pilot program was to compare the two mapping methods and to determine if field observations are necessary. Preliminary results indicate that only questionable small-scale features need to be field checked. Mapping on the plotter is highly reliable if aerial photographs obtained immediately after detonation are used. If photography is delayed, surface effects may be obliterated by natural processes and construction activities. Disadvantages to the plotter method relate to the quality and coverage of aerial photographs. The main problem concerns the scale of aerial photographs. Because of the large scale, the photographs lack adequate control points to properly orient the photographs to a map base. In addition, the paper print photographs used were often distorted. Once the problems were recognized and corrected, the method was greatly improved. Generally, the PG-2 offers a precise method for determining the distribution of surface effects

  2. Combining the VAS 3D interpolation method and Wind Atlas methodology to produce a high-resolution wind resource map for the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Hanslian, David; Hošek, Jiří

    2015-01-01

    Roč. 77, May (2015), s. 291-299 ISSN 0960-1481 Institutional support: RVO:68378289 Keywords : wind resource map * wind field modelling * wind measurements * wind climatology * Czech Republic * WAsP Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.404, year: 2015 http://www.sciencedirect.com/science/article/pii/S0960148114008398#

  3. Developing a New North American Land Cover Product at 30m Resolution: Methods, Results and Future Plans

    Science.gov (United States)

    Homer, C.; Colditz, R. R.; Latifovic, R.; Llamas, R. M.; Pouliot, D.; Danielson, P.; Meneses, C.; Victoria, A.; Ressl, R.; Richardson, K.; Vulpescu, M.

    2017-12-01

    Land cover and land cover change information at regional and continental scales has become fundamental for studying and understanding the terrestrial environment. With recent advances in computer science and freely available image archives, continental land cover mapping has been advancing to higher spatial resolution products. The North American Land Change Monitoring System (NALCMS) remains the principal provider of seamless land cover maps of North America. Founded in 2006, this collaboration among the governments of Canada, Mexico and the United States has released two previous products based on 250m MODIS images, including a 2005 land cover and a 2005-2010 land cover change product. NALCMS has recently completed the next generation North America land cover product, based upon 30m Landsat images. This product now provides the first ever 30m land cover produced for the North American continent, providing 19 classes of seamless land cover. This presentation provides an overview of country-specific image classification processes, describes the continental map production process, provides results for the North American continent and discusses future plans. NALCMS is coordinated by the Commission for Environmental Cooperation (CEC) and all products can be obtained at their website - www.cec.org.

  4. Mapping Brazilian Cropland Expansion, 2000-2013

    Science.gov (United States)

    Zalles, V.; Hansen, M.; Potapov, P.

    2016-12-01

    Brazil is one of the world's leading producers and exporters of agricultural goods. Despite undergoing significant increases in its cropland area in the last decades, it remains one of the countries with the most potential for further agricultural expansion. Most notably, the expansion in production areas of commodity crops such as soybean, corn, and sugarcane has become the leading cause of land cover conversion in Brazil. Natural land covers, such as the Amazon and Cerrado forests, have been negatively affected by this agricultural expansion, causing carbon emissions, biodiversity loss, altered water cycles, and many other disturbances to ecosystem services. Monitoring of change in cropland area extent can provide relevant information to decision makers seeking to understand and manage land cover change drivers and their impacts. In this study, the freely-available Landsat archive was leveraged to produce a large-scale, methodologically consistent map of cropland cover at 30 m. resolution for the entire Brazilian territory in the year 2000. Additionally, we mapped cropland expansion from 2000 to 2013, and used statistical sampling techniques to accurately estimate cropland area per Brazilian state. Using the Global Forest Change product produced by Hansen et al. (2013), we can disaggregate forest cover loss due to cropland expansion by year, revealing spatiotemporal trends that could advance our understanding of the drivers of forest loss.

  5. 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...

  6. 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...

  7. Quantifying Savanna Woody Cover in the Field and on Historical ...

    African Journals Online (AJOL)

    jed1z

    ... mapping woody cover on such imagery in bush encroachment studies are the use of traditional pixel-based ... cover by testing it against detailed field validation data. We then assess ..... Mexico', Remote Sensing of Environment, vol. 93, pp.

  8. 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.

  9. 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

  10. 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.

    Science.gov (United States)

    Uboldi, Cristina; Guidi, Elena; Roperto, Sante; Russo, Valeria; Roperto, Franco; Di Meo, Giulia Pia; Iannuzzi, Leopoldo; Floriot, Sandrine; Boussaha, Mekki; Eggen, André; Ferretti, Luca

    2006-05-23

    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. 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. 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, especially of vesical papillomavirus-associated cancers of

  11. Modeling percent tree canopy cover: a pilot study

    Science.gov (United States)

    John W. Coulston; Gretchen G. Moisen; Barry T. Wilson; Mark V. Finco; Warren B. Cohen; C. Kenneth Brewer

    2012-01-01

    Tree canopy cover is a fundamental component of the landscape, and the amount of cover influences fire behavior, air pollution mitigation, and carbon storage. As such, efforts to empirically model percent tree canopy cover across the United States are a critical area of research. The 2001 national-scale canopy cover modeling and mapping effort was completed in 2006,...

  12. 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.

  13. Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

    Science.gov (United States)

    Gilani, H.; Xu, X.; Jain, A. K.

    2017-12-01

    South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution

  14. 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, Thomas 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

  15. 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

  16. Open land use map

    OpenAIRE

    Mildorf, T.; Charvát, K.; Jezek, J.; Templer, Simon; Malewski, Christian

    2014-01-01

    Open Land Use Map is an initiative that has been started by the Plan4business project and that will be extended as part of the SDI4Apps project in the future. This service aims to create an improved worldwide land use map. The initial map will be prepared using the CORINE Land Cover, Global Cover dataset and Open Street Map. Contributors, mainly volunteers, will able to change the geometry and assign up-to-date land use according to the HILUCS specification. For certain regions more detailed ...

  17. Spectral signature selection for mapping unvegetated soils

    Science.gov (United States)

    May, G. A.; Petersen, G. W.

    1975-01-01

    Airborne multispectral scanner data covering the wavelength interval from 0.40-2.60 microns were collected at an altitude of 1000 m above the terrain in southeastern Pennsylvania. Uniform training areas were selected within three sites from this flightline. Soil samples were collected from each site and a procedure developed to allow assignment of scan line and element number from the multispectral scanner data to each sampling location. These soil samples were analyzed on a spectrophotometer and laboratory spectral signatures were derived. After correcting for solar radiation and atmospheric attenuation, the laboratory signatures were compared to the spectral signatures derived from these same soils using multispectral scanner data. Both signatures were used in supervised and unsupervised classification routines. Computer-generated maps using the laboratory and multispectral scanner derived signatures resulted in maps that were similar to maps resulting from field surveys. Approximately 90% agreement was obtained between classification maps produced using multispectral scanner derived signatures and laboratory derived signatures.

  18. 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.

  19. Determinants of woody cover in African savannas

    Science.gov (United States)

    Sankaran, M.; Hanan, N.P.; Scholes, Robert J.; Ratnam, J.; Augustine, D.J.; Cade, B.S.; Gignoux, J.; Higgins, S.I.; Le, Roux X.; Ludwig, F.; Ardo, J.; Banyikwa, F.; Bronn, A.; Bucini, G.; Caylor, K.K.; Coughenour, M.B.; Diouf, A.; Ekaya, W.; Feral, C.J.; February, E.C.; Frost, P.G.H.; Hiernaux, P.; Hrabar, H.; Metzger, K.L.; Prins, H.H.T.; Ringrose, S.; Sea, W.; Tews, J.; Worden, J.; Zambatis, N.

    2005-01-01

    Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties 1-3. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover1,2,4,5, but perceptions differ on which of these are the primary drivers of savanna structure. Here we show, using data from 854 sites across Africa, that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than ???650 mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered 'stable' systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of ???650 mm, savannas are 'unstable' systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation 6 may considerably affect their distribution and dynamics. ?? 2005 Nature Publishing Group.

  20. Study by Hall probe mapping of the trapped flux modification produced by local heating in YBCO HTS bulks for different surface/volume ratios

    International Nuclear Information System (INIS)

    Laurent, Ph; Mathieu, J-P; Mattivi, B; Fagnard, J-F; Meslin, S; Noudem, J G; Ausloos, M; Cloots, R; Vanderbemden, Ph

    2005-01-01

    The aim of this report is to compare the trapped field distribution under a local heating created at the sample edge for different sample morphologies. Hall probe mappings of the magnetic induction trapped in YBCO bulk samples maintained out of thermal equilibrium were performed on YBCO bulk single domains, YBCO single domains with regularly spaced hole arrays, and YBCO superconducting foams. The capability of heat draining was quantified by two criteria: the average induction decay and the size of the thermally affected zone caused by a local heating of the sample. Among the three investigated sample shapes, the drilled single domain displays a trapped induction which is weakly affected by the local heating while displaying a high trapped field. Finally, a simple numerical modelling of the heat flux spreading into a drilled sample is used to suggest some design rules about the hole configuration and their size

  1. 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...

  2. 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.

  3. An automated approach to mapping corn from Landsat imagery

    Science.gov (United States)

    Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.; Hoffer, R.M.

    2004-01-01

    Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

  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. Building a Continental Scale Land Cover Monitoring Framework for Australia

    Science.gov (United States)

    Thankappan, Medhavy; Lymburner, Leo; Tan, Peter; McIntyre, Alexis; Curnow, Steven; Lewis, Adam

    2012-04-01

    Land cover information is critical for national reporting and decision making in Australia. A review of information requirements for reporting on national environmental indicators identified the need for consistent land cover information to be compared against a baseline. A Dynamic Land Cover Dataset (DLCD) for Australia has been developed by Geoscience Australia and the Australian Bureau of Agriculture and Resource Economics and Sciences (ABARES) recently, to provide a comprehensive and consistent land cover information baseline to enable monitoring and reporting for sustainable farming practices, water resource management, soil erosion, and forests at national and regional scales. The DLCD was produced from the analysis of Enhanced Vegetation Index (EVI) data at 250-metre resolution derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period from 2000 to 2008. The EVI time series data for each pixel was modelled as 12 coefficients based on the statistical, phenological and seasonal characteristics. The time series were then clustered in coefficients spaces and labelled using ancillary information on vegetation and land use at the catchment scale. The accuracy of the DLCD was assessed using field survey data over 25,000 locations provided by vegetation and land management agencies in State and Territory jurisdictions, and by ABARES. The DLCD is seen as the first in a series of steps to build a framework for national land cover monitoring in Australia. A robust methodology to provide annual updates to the DLCD is currently being developed at Geoscience Australia. There is also a growing demand from the user community for land cover information at better spatial resolution than currently available through the DLCD. Global land cover mapping initiatives that rely on Earth observation data offer many opportunities for national and international programs to work in concert and deliver better outcomes by streamlining efforts on development and

  6. Flood maps in Europe - methods, availability and use

    Science.gov (United States)

    de Moel, H.; van Alphen, J.; Aerts, J. C. J. H.

    2009-03-01

    To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC) at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood risk management plans. This paper gives an overview of existing flood mapping practices in 29 countries in Europe and shows what maps are already available and how such maps are used. Roughly half of the countries considered have maps covering as good as their entire territory, and another third have maps covering significant parts of their territory. Only five countries have very limited or no flood maps available yet. Of the different flood maps distinguished, it appears that flood extent maps are the most commonly produced floods maps (in 23 countries), but flood depth maps are also regularly created (in seven countries). Very few countries have developed flood risk maps that include information on the consequences of flooding. The available flood maps are mostly developed by governmental organizations and primarily used for emergency planning, spatial planning, and awareness raising. In spatial planning, flood zones delimited on flood maps mainly serve as guidelines and are not binding. Even in the few countries (e.g. France, Poland) where there is a legal basis to regulate floodplain developments using flood zones, practical problems are often faced which reduce the mitigating effect of such binding legislation. Flood maps, also mainly extent maps, are also created by the insurance industry in Europe and used to determine insurability, differentiate premiums, or to assess long-term financial solvency. Finally, flood maps are also produced by international river commissions. With respect to the EU Flood Directive, many countries already have a good starting point to map

  7. Flood maps in Europe – methods, availability and use

    Directory of Open Access Journals (Sweden)

    J. C. J. H. Aerts

    2009-03-01

    Full Text Available To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood risk management plans. This paper gives an overview of existing flood mapping practices in 29 countries in Europe and shows what maps are already available and how such maps are used. Roughly half of the countries considered have maps covering as good as their entire territory, and another third have maps covering significant parts of their territory. Only five countries have very limited or no flood maps available yet. Of the different flood maps distinguished, it appears that flood extent maps are the most commonly produced floods maps (in 23 countries, but flood depth maps are also regularly created (in seven countries. Very few countries have developed flood risk maps that include information on the consequences of flooding. The available flood maps are mostly developed by governmental organizations and primarily used for emergency planning, spatial planning, and awareness raising. In spatial planning, flood zones delimited on flood maps mainly serve as guidelines and are not binding. Even in the few countries (e.g. France, Poland where there is a legal basis to regulate floodplain developments using flood zones, practical problems are often faced which reduce the mitigating effect of such binding legislation. Flood maps, also mainly extent maps, are also created by the insurance industry in Europe and used to determine insurability, differentiate premiums, or to assess long-term financial solvency. Finally, flood maps are also produced by international river commissions. With respect to the EU Flood Directive, many countries already have a good starting

  8. Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

    Science.gov (United States)

    Fuller, Douglas O; Parenti, Michael S; Gad, Adel M; Beier, John C

    2012-01-01

    Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes.

  9. Analyzing velocity map images to distinguish the primary methyl photofragments from those produced upon C-Cl bond photofission in chloroacetone at 193 nm

    Science.gov (United States)

    Alligood, Bridget W.; Straus, Daniel B.; Butler, Laurie J.

    2011-07-01

    We use a combination of crossed laser-molecular beam scattering experiments and velocity map imaging experiments to investigate the three primary photodissociation channels of chloroacetone at 193 nm: C-Cl bond photofission yielding CH3C(O)CH2 radicals, C-C bond photofission yielding CH3CO and CH2Cl products, and C-CH3 bond photofission resulting in CH3 and C(O)CH2Cl products. Improved analysis of data previously reported by our group quantitatively identifies the contribution of this latter photodissociation channel. We introduce a forward convolution procedure to identify the portion of the signal, derived from the methyl image, which results from a two-step process in which C-Cl bond photofission is followed by the dissociation of the vibrationally excited CH3C(O)CH2 radicals to CH3 + COCH2. Subtracting this from the total methyl signal identifies the methyl photofragments that result from the CH3 + C(O)CH2Cl photofission channel. We find that about 89% of the chloroacetone molecules undergo C-Cl bond photofission to yield CH3C(O)CH2 and Cl products; approximately 8% result in C-C bond photofission to yield CH3CO and CH2Cl products, and the remaining 2.6% undergo C-CH3 bond photofission to yield CH3 and C(O)CH2Cl products.

  10. 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...

  11. 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...

  12. Text 2 Mind Map

    OpenAIRE

    Iona, John

    2017-01-01

    This is a review of the web resource 'Text 2 Mind Map' www.Text2MindMap.com. It covers what the resource is, and how it might be used in Library and education context, in particular for School Librarians.

  13. A Comparison of Novel Optical Remote Sensing-Based Technologies for Forest-Cover/Change Monitoring

    Directory of Open Access Journals (Sweden)

    Gillian V. Lui

    2015-03-01

    Full Text Available Remote sensing is gaining considerable traction in forest monitoring efforts, with the Carnegie Landsat Analysis System lite (CLASlite software package and the Global Forest Change dataset (GFCD being two of the most recently developed optical remote sensing-based tools for analysing forest cover and change. Due to the relatively nascent state of these technologies, their abilities to classify land cover and monitor forest dynamics have yet to be evaluated against more established approaches. Here, we compared maps of forest cover and change produced by the more traditional supervised classification approach with those produced by CLASlite and the GFCD, working with imagery collected over Sierra Leone, West Africa. CLASlite maps of forest change from 2001–2007 and 2007–2014 exhibited the highest overall accuracies (79.1% and 89.6%, respectively and, importantly, the greatest capacity to discriminate natural from planted mature forest growth. CLASlite’s comparative advantage likely derived from its more robust sub-pixel classification logic and numerous user-defined parameters, which resulted in classified products with greater site relevance than those of the two other classification approaches. In light of today’s continuously growing body of analytical toolsets for remotely sensed data, our study importantly elucidates the ways in which methodological processes and limitations inherent in certain classification tools can impact the maps they are capable of producing, and demonstrates the need to understand and weigh such factors before any one tool is selected for a given application.

  14. Braids and coverings selected topics

    CERN Document Server

    Hansen, Vagn Lundsgaard

    1989-01-01

    This book is based on a graduate course taught by the author at the University of Maryland, USA. The lecture notes have been revised and augmented by examples. The work falls into two strands. The first two chapters develop the elementary theory of Artin Braid groups both geometrically and via homotopy theory, and discuss the link between knot theory and the combinatorics of braid groups through Markov's Theorem. The final two chapters give a detailed investigation of polynomial covering maps, which may be viewed as a homomorphism of the fundamental group of the base space into the Artin braid

  15. Application of Modis Data to Assess the Latest Forest Cover Changes of Sri Lanka

    Science.gov (United States)

    Perera, K.; Herath, S.; Apan, A.; Tateishi, R.

    2012-07-01

    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 isolated pockets of

  16. Bacterially produced Pt-GFP as ratiometric dual-excitation sensor for in planta mapping of leaf apoplastic pH in intact Avena sativa and Vicia faba.

    Science.gov (United States)

    Geilfus, Christoph-Martin; Mühling, Karl H; Kaiser, Hartmut; Plieth, Christoph

    2014-01-01

    Ratiometric analysis with H(+)-sensitive fluorescent sensors is a suitable approach for monitoring apoplastic pH dynamics. For the acidic range, the acidotropic dual-excitation dye Oregon Green 488 is an excellent pH sensor. Long lasting (hours) recordings of apoplastic pH in the near neutral range, however, are more problematic because suitable pH indicators that combine a good pH responsiveness at a near neutral pH with a high photostability are lacking. The fluorescent pH reporter protein from Ptilosarcus gurneyi (Pt-GFP) comprises both properties. But, as a genetically encoded indicator and expressed by the plant itself, it can be used almost exclusively in readily transformed plants. In this study we present a novel approach and use purified recombinant indicators for measuring ion concentrations in the apoplast of crop plants such as Vicia faba L. and Avena sativa L. Pt-GFP was purified using a bacterial expression system and subsequently loaded through stomata into the leaf apoplast of intact plants. Imaging verified the apoplastic localization of Pt-GFP and excluded its presence in the symplast. The pH-dependent emission signal stood out clearly from the background. PtGFP is highly photostable, allowing ratiometric measurements over hours. By using this approach, a chloride-induced alkalinizations of the apoplast was demonstrated for the first in oat. Pt-GFP appears to be an excellent sensor for the quantification of leaf apoplastic pH in the neutral range. The presented approach encourages to also use other genetically encoded biosensors for spatiotemporal mapping of apoplastic ion dynamics.

  17. Digital Bedrock Compilation: A Geodatabase Covering Forest Service Lands in California

    Science.gov (United States)

    Elder, D.; de La Fuente, J. A.; Reichert, M.

    2010-12-01

    This digital database contains bedrock geologic mapping for Forest Service lands within California. This compilation began in 2004 and the first version was completed in 2005. Second publication of this geodatabase was completed in 2010 and filled major gaps in the southern Sierra Nevada and Modoc/Medicine Lake/Warner Mountains areas. This digital map database was compiled from previously published and unpublished geologic mapping, with source mapping and review from California Geological Survey, the U.S. Geological Survey and others. Much of the source data was itself compilation mapping. This geodatabase is huge, containing ~107,000 polygons and ~ 280,000 arcs. Mapping was compiled from more than one thousand individual sources and covers over 41,000,000 acres (~166,000 km2). It was compiled from source maps at various scales - from ~ 1:4,000 to 1:250,000 and represents the best available geologic mapping at largest scale possible. An estimated 70-80% of the source information was digitized from geologic mapping at 1:62,500 scale or better. Forest Service ACT2 Enterprise Team compiled the bedrock mapping and developed a geodatabase to store this information. This geodatabase supports feature classes for polygons (e.g, map units), lines (e.g., contacts, boundaries, faults and structural lines) and points (e.g., orientation data, structural symbology). Lookup tables provide detailed information for feature class items. Lookup/type tables contain legal values and hierarchical groupings for geologic ages and lithologies. Type tables link coded values with descriptions for line and point attributes, such as line type, line location and point type. This digital mapping is at the core of many quantitative analyses and derivative map products. Queries of the database are used to produce maps and to quantify rock types of interest. These include the following: (1) ultramafic rocks - where hazards from naturally occurring asbestos are high, (2) granitic rocks - increased

  18. Mapping out Map Libraries

    Directory of Open Access Journals (Sweden)

    Ferjan Ormeling

    2008-09-01

    Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

  19. 基于ArcGIS分幅制作及输出使用林地现状图的方法研究%Method of Producing and Outputting Status Map of Used Forest Land Based on ArcGIS

    Institute of Scientific and Technical Information of China (English)

    韦强; 黄磊

    2017-01-01

    This paper describes the basic requirements of the present situation of the forest land map,such as the scale scale,the land area standard,the small line label,the figure number,the land annotation,the chart,the corridor decoration and the color of the land.This paper discusses a series of presentations,such as the preparation of the base map,the creation of a custom face slice layer,the establishment of a small class and the division layer correspondence,data driven page setup,production boundary.With ArcGIS software data-driven pages and factory mapping module sub-frame to produce forest land map can dynamically loaded map number,dynamic page definition query and dynamic loading small class notes,and also can improve the efficiency of mapping,shorten cycle.%阐述成图比例尺、用地范围标注,小班线标注、图幅号、地块注记、接图表、图廊整饰、地类色彩等分幅制作林地现状图的基本要求.藉此论述了准备底图,创建自定义面状分幅图层,建立小班与分幅图层对应关系,数据驱动页面设置,制作界线,地块标注等一系列现状图分幅制作方法和步骤,借助ArcGIS软件数据驱动页面和工厂化制图模块分幅制作林地现状图,可实现动态化加载图幅号、动态化页面定义查询和动态化加载小班注记表,可以提高制图效率、缩短出图周期.

  20. 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.

  1. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data

    Science.gov (United States)

    Churches, Christopher E.; Wampler, Peter J.; Sun, Wanxiao; Smith, Andrew J.

    2014-08-01

    This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates.

  2. Armored Geomembrane Cover Engineering

    Directory of Open Access Journals (Sweden)

    Kevin Foye

    2011-06-01

    Full Text Available Geomembranes are an important component of modern engineered barriers to prevent the infiltration of stormwater and runoff into contaminated soil and rock as well as waste containment facilities—a function generally described as a geomembrane cover. This paper presents a case history involving a novel implementation of a geomembrane cover system. Due to this novelty, the design engineers needed to assemble from disparate sources the design criteria for the engineering of the cover. This paper discusses the design methodologies assembled by the engineering team. This information will aid engineers designing similar cover systems as well as environmental and public health professionals selecting site improvements that involve infiltration barriers.

  3. 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....

  4. 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...

  5. EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

    Science.gov (United States)

    This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network, and along water bodies such as lakes and ponds that are connected via flow to the streams, that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006 National Land Cover Dataset (NLCD) for each Watershed Boundary Dataset (WBD) 12-digit hydrological unit (HUC) in the conterminous United States. 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).

  6. Covered Bridge Security Manual

    Science.gov (United States)

    Brett Phares; Terry Wipf; Ryan Sievers; Travis Hosteng

    2013-01-01

    The design, construction, and use of covered timber bridges is all but a lost art in these days of pre-stressed concrete, high-performance steel, and the significant growth both in the volume and size of vehicles. Furthermore, many of the existing covered timber bridges are preserved only because of their status on the National Registry of Historic Places or the...

  7. An Assessment of Existing Methodologies to Retrieve Snow Cover Fraction from MODIS Data

    Directory of Open Access Journals (Sweden)

    Théo Masson

    2018-04-01

    Full Text Available The characterization of snow extent is critical for a wide range of applications. Since 1966, snow maps at different spatial resolutions have been produced using various satellite sensor images. Nowadays, the most widely used products are likely those derived from Moderate-Resolution Imaging Spectroradiometer (MODIS data, which cover the whole Earth at a near-daily frequency. There are a variety of snow mapping methods for MODIS data, based on different methodologies and applied at different spatial resolutions. Up to now, all these products have been tested and evaluated separately. This study aims to compare the methods currently available for retrieving snow from MODIS data. The focus is on fractional snow cover, which represents the snow cover area at the subpixel level. We examine the two main approaches available for generating such products from MODIS data; namely, linear regression of the Normalized Difference Snow Index (NDSI and spectral unmixing (SU. These two approaches have resulted in several methods, such as MOD10A1 (the NSIDC MODIS snow product for NDSI regression, and MODImLAB for SU. The assessment of these approaches was carried out using higher resolution binary snow maps (i.e., showing the presence or absence of snow at spatial resolutions of 10, 20, and 30 m, produced by SPOT 4, SPOT 5, and LANDSAT-8, respectively. Three areas were selected in order to provide landscape diversity: the French Alps (117 dates, the Pyrenees (30 dates, and the Moroccan Atlas (24 dates. This study investigates the impact of reference maps on accuracy assessments, and it is suggested that NDSI-based high spatial resolution reference maps advantage NDSI medium-resolution snow maps. For MODIS snow maps, the results show that applying an NDSI approach to accurate surface reflectance corrected for topographic and atmospheric effects generally outperforms other methods for the global retrieval of snow cover area. The improvements to the newer version

  8. Towards Seamless Validation of Land Cover Data

    Science.gov (United States)

    Chuprikova, Ekaterina; Liebel, Lukas; Meng, Liqiu

    2018-05-01

    This article demonstrates the ability of the Bayesian Network analysis for the recognition of uncertainty patterns associated with the fusion of various land cover data sets including GlobeLand30, CORINE (CLC2006, Germany) and land cover data derived from Volunteered Geographic Information (VGI) such as Open Street Map (OSM). The results of recognition are expressed as probability and uncertainty maps which can be regarded as a by-product of the GlobeLand30 data. The uncertainty information may guide the quality improvement of GlobeLand30 by involving the ground truth data, information with superior quality, the know-how of experts and the crowd intelligence. Such an endeavor aims to pave a way towards a seamless validation of global land cover data on the one hand and a targeted knowledge discovery in areas with higher uncertainty values on the other hand.

  9. Maps and plans reliability in tourism activities

    Directory of Open Access Journals (Sweden)

    Олександр Донцов

    2016-10-01

    Full Text Available The paper is devoted to creation of an effective system of mapping at all levels of tourist-excursion functioning that will boost the promotion of tourist product in a domestic and foreign tourist market. The State Scientific - Production Enterprise «Kartographia» actively participates in cartographic tourism provision by producing travel pieces, survey, large-scale, route maps, atlases, travel guides, city plans. They produce maps covering different content of the territory of Ukraine, its individual regions, cities interested in tourist excursions. The list and scope of cartographic products has been prepared for publication and released for the last five years. The development of new types of tourism encourages publishers to create various cartographic products for the needs of tourists guaranteeing high accuracy, reliability of information, ease of use. A variety of scientific and practical problems in tourism and excursion activities that are solved using maps and plans makes it difficult to determine the criteria for assessing their reliability. The author proposes to introduce the concept of «relevance» - as maps suitability to solving specific problems. The basis of the peer review is suitability of maps for the objective results release criteria: appropriateness of the target maps tasks (area, theme, destination; accuracy of given parameters (projection, scale, height interval; year according to the shooting of location or mapping; selection methods, methods of results measurement processing algorithm; availability of assistive devices (instrumentation, computer technology, simulation devices. These criteria provide the reliability and accuracy of the result as acceptable to consumers as possible. The author proposes a set of measures aimed at improving the content, quality and reliability of cartographic production.

  10. Farmland Mapping and Monitoring 2004 Mosaic

    Data.gov (United States)

    California Natural Resource Agency — The Farmland Mapping and Monitoring Program (FMMP) produces maps and statistical data used for analyzing impacts on California's agricultural resources. Agricultural...

  11. 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.

  12. 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.

  13. Evapotranspiration (ET) covers.

    Science.gov (United States)

    Rock, Steve; Myers, Bill; Fiedler, Linda

    2012-01-01

    Evapotranspiration (ET) cover systems are increasingly being used at municipal solid waste (MSW) landfills, hazardous waste landfills, at industrial monofills, and at mine sites. Conventional cover systems use materials with low hydraulic permeability (barrier layers) to minimize the downward migration of water from the surface to the waste (percolation), ET cover systems use water balance components to minimize percolation. These cover systems rely on soil to capture and store precipitation until it is either transpired through vegetation or evaporated from the soil surface. Compared to conventional membrane or compacted clay cover systems, ET cover systems are expected to cost less to construct. They are often aesthetic because they employ naturalized vegetation, require less maintenance once the vegetative system is established, including eliminating mowing, and may require fewer repairs than a barrier system. All cover systems should consider the goals of the cover in terms of protectiveness, including the pathways of risk from contained material, the lifecycle of the containment system. The containment system needs to be protective of direct contact of people and animals with the waste, prevent surface and groundwater water pollution, and minimize release of airborne contaminants. While most containment strategies have been based on the dry tomb strategy of keeping waste dry, there are some sites where adding or allowing moisture to help decompose organic waste is the current plan. ET covers may work well in places where complete exclusion of precipitation is not needed. The U.S. EPA Alternative Cover Assessment Program (ACAP), USDOE, the Nuclear Regulatory Commission, and others have researched ET cover design and efficacy, including the history of their use, general considerations in their design, performance, monitoring, cost, current status, limitations on their use, and project specific examples. An on-line database has been developed with information

  14. Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data

    Science.gov (United States)

    Sanford, Ward E.; Selnick, David L.

    2013-01-01

    Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.

  15. 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...

  16. 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...

  17. 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...

  18. The Effect Of Land Cover/Land Use On Groundwater Resources In Southern Egypt (Luxor Area): Remote Sensing And Field Studies

    International Nuclear Information System (INIS)

    Faid, A.M.; Hinz, E.A.; Montgomery, H.

    2003-01-01

    The impact of land cover/land use on groundwater can be critical. Land cover / land use maps give an early warning for planners and developers to protect groundwater resources from depletion and preserve its sustain ability. These land cover / land use maps can be used for the planning of groundwater development to prevent the deterioration of the aquifer. The Research Institute for Groundwater of Egypt (RIGW) has carried out hydrogeological studies in 1990 to evaluate the potentiality of groundwater in Luxor area in southern Egypt close to the Nile valley. The region is characterized by a rapid and continuous increase in land reclamation and development on the fringes which surround the already heavily cultivated land within the Nile valley. This presented a need for continuous monitoring and information updating over a vast region in a short time and at a reasonable cost. This study illustrates how remote sensing techniques can be effectively used for monitoring changes in land cover / land use in an effort to aid groundwater management. Landsat Thematic Mapper (TM) data collected in 1984 and 2000 were processed and analyzed over the study area to produce land cover/land use maps. The Normalized Difference Vegetation Index (NDVI) technique is used for Landsat TM images of to quantify areas which are covered by vegetation. Results indicated significant increase in cultivated areas. Remote sensing results are compared with iso-piezo metric maps and iso-salinity maps that were produced in 1984 and 2000. Comparison of these maps indicates groundwater depletion and salinity increase from 1984 to 2000. We relate this to the increase of the area being cultivated

  19. The Improvement of Land Cover Classification by Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Liya Sun

    2015-06-01

    Full Text Available Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.

  20. Data mining algorithms for land cover change detection: a review

    Indian Academy of Sciences (India)

    Sangram Panigrahi

    2017-11-24

    Nov 24, 2017 ... values, poor quality measurement, high resolution and high dimensional data. The land cover .... These data sets also include quality assurance information, ...... 2012 A new data mining framework for forest fire mapping.

  1. BOREAS SERM Forest Cover Data of Saskatchewan in Vector Format

    Data.gov (United States)

    National Aeronautics and Space Administration — A condensed forest cover type digital map of Saskatchewan and is a product of the Saskatchewan Environment and Resource Management, Forestry Branch-Inventory Unit...

  2. Effect of Feature Dimensionality on Object-based Land Cover ...

    African Journals Online (AJOL)

    Myburgh, G, Mnr

    features, it has not been demonstrated with land cover mapping in an ... classifiers were chosen for benchmarking as the latter is the most commonly .... Additional open-source libraries were acquired to complete the implementation of the.

  3. Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

    Science.gov (United States)

    Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

  4. Generating a National Land Cover Dataset for Mexico at 30m Spatial Resolution in the Framework of the NALCMS Project.

    Science.gov (United States)

    Llamas, R. M.; Colditz, R. R.; Ressl, R.; Jurado Cruz, D. A.; Argumedo, J.; Victoria, A.; Meneses, C.

    2017-12-01

    The North American Land Change Monitoring System (NALCMS) is a tri-national initiative for mapping land cover across Mexico, United States and Canada, integrating efforts of institutions from the three countries. At the continental scale the group released land cover and change maps derived from MODIS image mosaics at 250m spatial resolution for 2005 and 2010. Current efforts are based on 30m Landsat images for 2010 ± 1 year. Each country uses its own mapping approach and sources for ancillary data, while ensuring that maps are produced in a coherent fashion across the continent. This paper presents the methodology and final land cover map of Mexico for the year 2010 that was later integrated into a continental map. The principal input for Mexico was the Monitoring Activity Data for Mexico (MAD-MEX) land cover map (version 4.3), derived from all available mostly cloud-free images for the year 2010. A total of 35 classes were regrouped to 15 classes of the NALCMS legend present in Mexico. Next, various issues of the automatically generated MAD-MEX land cover mosaic were corrected, such as: filling areas of no data due no cloud-free observation or gaps in Landsat 7 ETM+ images, filling inland water bodies which were left unclassified due to masking issues, relabeling isolated unclassified of falsely classified pixels, structural mislabeling due to data gaps, reclassifying areas of adjacent scenes with significant class disagreements and correcting obvious misclassifications, mostly of water and urban areas. In a second step minor missing areas and rare class snow and ice were digitized and a road network was added. A product such as NALCMS land cover map at 30m for North America is an unprecedented effort and will be without doubt an important source of information for many users around the world who need coherent land cover data over a continental domain as an input for a wide variety of environmental studies. The product release to the general public is expected

  5. Using a Similarity Matrix Approach to Evaluate the Accuracy of Rescaled Maps

    Directory of Open Access Journals (Sweden)

    Peijun Sun

    2018-03-01

    Full Text Available Rescaled maps have been extensively utilized to provide data at the appropriate spatial resolution for use in various Earth science models. However, a simple and easy way to evaluate these rescaled maps has not been developed. We propose a similarity matrix approach using a contingency table to compute three measures: overall similarity (OS, omission error (OE, and commission error (CE to evaluate the rescaled maps. The Majority Rule Based aggregation (MRB method was employed to produce the upscaled maps to demonstrate this approach. In addition, previously created, coarser resolution land cover maps from other research projects were also available for comparison. The question of which is better, a map initially produced at coarse resolution or a fine resolution map rescaled to a coarse resolution, has not been quantitatively investigated. To address these issues, we selected study sites at three different extent levels. First, we selected twelve regions covering the continental USA, then we selected nine states (from the whole continental USA, and finally we selected nine Agriculture Statistical Districts (ASDs (from within the nine selected states as study sites. Crop/non-crop maps derived from the USDA Crop Data Layer (CDL at 30 m as base maps were used for the upscaling and existing maps at 250 m and 1 km were utilized for the comparison. The results showed that a similarity matrix can effectively provide the map user with the information needed to assess the rescaling. Additionally, the upscaled maps can provide higher accuracy and better represent landscape pattern compared to the existing coarser maps. Therefore, we strongly recommend that an evaluation of the upscaled map and the existing coarser resolution map using a similarity matrix should be conducted before deciding which dataset to use for the modelling. Overall, extending our understanding on how to perform an evaluation of the rescaled map and investigation of the applicability

  6. Global Land Survey Impervious Mapping Project Web Site

    Science.gov (United States)

    DeColstoun, Eric Brown; Phillips, Jacqueline

    2014-01-01

    The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

  7. 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

  8. 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

  9. Optimal shortening of uniform covering arrays.

    Directory of Open Access Journals (Sweden)

    Jose Torres-Jimenez

    Full Text Available Software test suites based on the concept of interaction testing are very useful for testing software components in an economical way. Test suites of this kind may be created using mathematical objects called covering arrays. A covering array, denoted by CA(N; t, k, v, is an N × k array over [Formula: see text] with the property that every N × t sub-array covers all t-tuples of [Formula: see text] at least once. Covering arrays can be used to test systems in which failures occur as a result of interactions among components or subsystems. They are often used in areas such as hardware Trojan detection, software testing, and network design. Because system testing is expensive, it is critical to reduce the amount of testing required. This paper addresses the Optimal Shortening of Covering ARrays (OSCAR problem, an optimization problem whose objective is to construct, from an existing covering array matrix of uniform level, an array with dimensions of (N - δ × (k - Δ such that the number of missing t-tuples is minimized. Two applications of the OSCAR problem are (a to produce smaller covering arrays from larger ones and (b to obtain quasi-covering arrays (covering arrays in which the number of missing t-tuples is small to be used as input to a meta-heuristic algorithm that produces covering arrays. In addition, it is proven that the OSCAR problem is NP-complete, and twelve different algorithms are proposed to solve it. An experiment was performed on 62 problem instances, and the results demonstrate the effectiveness of solving the OSCAR problem to facilitate the construction of new covering arrays.

  10. 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...

  11. 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

  12. 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...

  13. On Covering Approximation Subspaces

    Directory of Open Access Journals (Sweden)

    Xun Ge

    2009-06-01

    Full Text Available Let (U';C' be a subspace of a covering approximation space (U;C and X⊂U'. In this paper, we show that and B'(X⊂B(X∩U'. Also, iff (U;C has Property Multiplication. Furthermore, some connections between outer (resp. inner definable subsets in (U;C and outer (resp. inner definable subsets in (U';C' are established. These results answer a question on covering approximation subspace posed by J. Li, and are helpful to obtain further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.

  14. Design and analysis for thematic map accuracy assessment: Fundamental principles

    Science.gov (United States)

    Stephen V. Stehman; Raymond L. Czaplewski

    1998-01-01

    Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...

  15. The Land Cover Dynamics and Conversion of Agricultural Land in Northwestern Bangladesh, 1973-2003.

    Science.gov (United States)

    Pervez, M.; Seelan, S. K.; Rundquist, B. C.

    2006-05-01

    The importance of land cover information describing the nature and extent of land resources and changes over time is increasing; this is especially true in Bangladesh, where land cover is changing rapidly. This paper presents research into the land cover dynamics of northwestern Bangladesh for the period 1973-2003 using Landsat satellite images in combination with field survey data collected in January and February 2005. Land cover maps were produced for eight different years during the study period with an average 73 percent overall classification accuracy. The classification results and post-classification change analysis showed that agriculture is the dominant land cover (occupying 74.5 percent of the study area) and is being reduced at a rate of about 3,000 ha per year. In addition, 6.7 percent of the agricultural land is vulnerable to temporary water logging annually. Despite this loss of agricultural land, irrigated agriculture increased substantially until 2000, but has since declined because of diminishing water availability and uncontrolled extraction of groundwater driven by population pressures and the extended need for food. A good agreement (r = 0.73) was found between increases in irrigated land and the depletion of the shallow groundwater table, a factor affecting widely practiced small-scale irrigation in northwestern Bangladesh. Results quantified the land cover change patterns and the stresses placed on natural resources; additionally, they demonstrated an accurate and economical means to map and analyze changes in land cover over time at a regional scale, which can assist decision makers in land and natural resources management decisions.

  16. Mapping Forage Resources Using Earth Observation Data: A Case Study to Assess the Relationship Between Herbaceous and Woody Cover Components as Determinants of Large Herbivore Distribution in Sub-Saharan Africa

    Science.gov (United States)

    Hanan, N. P.; Kahiu, M. N.

    2016-12-01

    Grazing systems are important for survival of humans, livestock and wildlife in Sub-Saharan Africa (SSA). They are mainly found in the arid and semi-arid regions and are characterized by naturally occurring tree-grass vegetation mixtures ("savannas"), low and erratic rainfall, low human populations, and scanty water resources. Due to the scarce population and perceived low resource base they have been marginalized for decades, if not centuries. However, their economic and environmental significance, particularly their role as foraging lands for livestock and wildlife cannot be underrated. SSA natural grazing systems comprise a significant source of livelihood, where millions of people depend on pastoralism as a source of food and income. Further, the African savannas support diverse flora and charismatic large herbivore and carnivore guilds. The above considerations motivate a more detailed study of the composition, temporal and spatial variability of foraging resources in SSA arid and semi-arid regions. We have therefore embarked on a research to map Africa foraging resources by partitioning MODIS total leaf area index (LAIA) time series into its woody (LAIW) and herbaceous (LAIH) constituents as proxies for grazing and browsing resources, respectively. Using the portioned LAI estimates we will develop a case study to assess how forage resources affect distribution and abundance of large herbivores in Africa. In our case study we explore two separate but related hypothesis: i) small and medium sized mammalian herbivore numbers will peak at intermediate biomass (LAIH for grazers and LAIW for browsers), since they optimize on forage quantity and quality. Conversely, large-body mammalian herbivores have the ability to process high quantity-low quality food, hence, we hypothesize that ii) larger herbivores will tend to be more common in high forage areas irrespective of forage quality. We will use LAIH and LAIW retrievals to compute annual average leaf area duration

  17. 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 ...

  18. Monitoring land Cover Changes and Fragmentation dynamics in the ...

    African Journals Online (AJOL)

    Monitoring land Cover Changes and Fragmentation dynamics in the subtropical thicket of the Eastern Cape Province, South Africa. ... Baseline land use/cover maps and fragmentation analyses in a temporal framework are valuable for gaining insights into, among other things, carbon stock change trends. Keywords: Land ...

  19. 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.

  20. Mapeamento da antiga cobertura vegetal de várzea do Baixo Amazonas a partir de imagens históricas (1975-1981 do Sensor MSS-Landsat Mapping ancient vegetation cover of the Amazon floodplain using historical MSS/Landsat images (1975-1981

    Directory of Open Access Journals (Sweden)

    Vivian Fróes Renó

    2011-03-01

    -classification techniques. The resulting map was organized four classes of land cover types: floodplain forest, non-forest floodplain vegetation, bare soil, and open water. Map accuracy was estimated from two types of ground data 1 sample points describing ground cover classes not subjected to major changes, such as permanent water bodies, and identifying indicators of the 30 year old vegetation type landscape (72 points; 2 interviews with community early residents for memory recovery of information on the vegetation cover existing in the 1970 (44 interviews. Altogether, 116 information points was collected along the study area. These points were used to calculate the Kappa Index for agreement between the four field-verified classes and the automatic classification, with value (0.78 indicates the good quality of the floodplain vegetation cover map. The region had 8650 km2 coverage of floodplain forest at the time of image acquisition.

  1. Cartographie de corps stériles sous couverture quaternaire par méthode de résistivités électriques dans le gisement phosphaté de Sidi Chennane (Maroc)Sterile bodies mapping under Quaternary cover using resistivity-sounding method in the phosphatic bearing of Sidi Chennane (Morocco)

    Science.gov (United States)

    Kchikach, Azzouz; Jaffal, Mohammed; Aı̈fa, Tahar; Bahi, Lahcen

    In the Ouled Abdoun sedimentary basin (Morocco), the phosphatic series is composed of regular interbedded phosphatic and marly limestone layers. Some phosphatic deposits in this basin show sterile bodies causing two kinds of problems: (1) as they are hard, compact and masked by a Quaternary cover, they disturb the exploitation in some yards and give bad reserve calculations; (2) even the use of wells and mechanical boreholes did not evidence their delimitation. Therefore, electric prospecting method has been used to evidence their geometrical shape. Petrographical and geometrical studies on these sterile bodies allowed us to choose the appropriate geophysical method to map them. The electrical resistivity survey that we used in the Sidi Chennane area shows that this technique is a good tool to contour these sterile bodies. This method is now considered as useful to the mining engineers to get round them during the exploitation. To cite this article: A. Kchikach et al., C. R. Geoscience 334 (2002) 379-386.

  2. 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

  3. 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

  4. 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...

  5. 2005 Kansas Land Cover Patterns, Level IV, Kansas River Watershed (1,000m 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...

  6. Alternative cover design

    International Nuclear Information System (INIS)

    1988-11-01

    The special study on Alternative Cover Designs is one of several studies initiated by the US Department of Energy (DOE) in response to the proposed US Environmental Protection Agency (EPA) groundwater standards. The objective of this study is to investigate the possibility of minimizing the infiltration of precipitation through stabilized tailings piles by altering the standard design of covers currently used on the Uranium Mill Tailings Remedial Action (UMTRA) Project. Prior. to the issuance of the proposed standards, UMTRA Project piles had common design elements to meet the required criteria, the most important of which were for radon diffusion, long-term stability, erosion protection, and groundwater protection. The standard pile covers consisted of three distinct layers. From top to bottom they were: rock for erosion protection; a sand bedding layer; and the radon barrier, usually consisting of a clayey sand material, which also functioned to limit infiltration into the tailings. The piles generally had topslopes from 2 to 4 percent and sideslopes of 20 percent

  7. Land Use and Land Cover (LULC) Change Detection in Islamabad and its Comparison with Capital Development Authority (CDA) 2006 Master Plan

    Science.gov (United States)

    Hasaan, Zahra

    2016-07-01

    Remote sensing is very useful for the production of land use and land cover statistics which can be beneficial to determine the distribution of land uses. Using remote sensing techniques to develop land use classification mapping is a convenient and detailed way to improve the selection of areas designed to agricultural, urban and/or industrial areas of a region. In Islamabad city and surrounding the land use has been changing, every day new developments (urban, industrial, commercial and agricultural) are emerging leading to decrease in vegetation cover. The purpose of this work was to develop the land use of Islamabad and its surrounding area that is an important natural resource. For this work the eCognition Developer 64 computer software was used to develop a land use classification using SPOT 5 image of year 2012. For image processing object-based classification technique was used and important land use features i.e. Vegetation cover, barren land, impervious surface, built up area and water bodies were extracted on the basis of object variation and compared the results with the CDA Master Plan. The great increase was found in built-up area and impervious surface area. On the other hand vegetation cover and barren area followed a declining trend. Accuracy assessment of classification yielded 92% accuracies of the final land cover land use maps. In addition these improved land cover/land use maps which are produced by remote sensing technique of class definition, meet the growing need of legend standardization.

  8. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

    Science.gov (United States)

    Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Votava, Petr; Roy, Anshuman; Mukhopadhyay, Supratik; Nemani, Ramakrishna

    2015-01-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  9. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery using a Probabilistic Learning Framework

    Science.gov (United States)

    Basu, S.; Ganguly, S.; Michaelis, A.; Votava, P.; Roy, A.; Mukhopadhyay, S.; Nemani, R. R.

    2015-12-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  10. Land cover fire proneness in Europe

    Directory of Open Access Journals (Sweden)

    Mario Gonzalez Pereira

    2014-12-01

    Full Text Available Aim of study: This study aims to identify and characterize the spatial and temporal evolution of the types of vegetation that are most affected by forest fires in Europe. The characterization of the fuels is an important issue of the fire regime in each specific ecosystem while, on the other hand, fire is an important disturbance for global vegetation dynamics.Area of study: Southern European countries: Portugal, Spain, France, Italy and Greece.Material and Methods: Corine Land Cover maps for 2000 and 2006 (CLC2000, CLC2006 and burned area (BA perimeters, from 2000 to 2013 in Europe are combined to access the spatial and temporal evolution of the types of vegetation that are most affected by wild fires using descriptive statistics and Geographical Information System (GIS techniques.Main results: The spatial and temporal distribution of BA perimeters, vegetation and burnt vegetation by wild fires was performed and different statistics were obtained for Mediterranean and entire Europe, confirming the usefulness of the proposed land cover system. A fire proneness index is proposed to assess the fire selectivity of land cover classes. The index allowed to quantify and to compare the propensity of vegetation classes and countries to fire.Research highlights: The usefulness and efficiency of the land cover classification scheme and fire proneness index. The differences between northern Europe and southern Europe and among the Mediterranean region in what concerns to vegetation cover, fire incidence, area burnt in land cover classes and fire proneness between classes for the different countries.Keywords: Fire proneness; Mixed forests; Land cover/land use; Fire regime; Europe; GIS; Corine land cover

  11. Mapping invasive alien Acacia dealbata Link using ASTER multispectral imagery: a case study in central-eastern of Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Martins, F.; Alegria, C.; Artur, G.

    2016-07-01

    Aim of the study: Acacia dealbata is an alien invasive species that is widely spread in Portugal. The main goal of this study was to produce an accurate and detailed map for this invasive species using ASTER multispectral imagery. Area of study: The central-eastern zone of Portugal was used as study area. This whole area is represented in an ASTER scene covering about 321.1 x 103 ha. Material and methods: ASTER imagery of two dates (flowering season and dry season) were classified by applying three supervised classifiers (Maximum Likelihood, Support Vector Machine and Artificial Neural Networks) to five different land cover classifications (from most generic to most detailed land cover categories). The spectral separability of the land cover categories was analyzed and the accuracy of the 30 produced maps compared. Main results: The highest classification accuracy for acacia mapping was obtained using the flowering season imagery, the Maximum Likelihood classifier and the most detailed land cover classification (overall accuracy of 86%; Kappa statistics of 85%; acacia class Kappa statistics of 100%). As a result, the area occupied by acacia was estimated to be approximated 24,770 ha (i.e. 8% of the study area). Research highlights: The methodology explored proved to be a cost-effective solution for acacia mapping in central-eastern of Portugal. The obtained map enables a more accurate and detailed identification of this species’ invaded areas due to its spatial resolution (minimum mapping unit of 0.02 ha) providing a substantial improvement comparably to the existent national land cover maps to support monitoring and control activities. (Author)

  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...... tree is isomorphic to T? We prove that in the general setting, CST is NP-complete, which implies that the tree edit distance considered here is also NP-hard, even when both input trees having diameters bounded by 10. We also show that, when the number of distinct stars is bounded by a constant k, CTS...

  13. Alternate cover materials

    International Nuclear Information System (INIS)

    1988-09-01

    As an effort to enhance compliance with the proposed US Environmental Protection Agency (EPA) groundwater standards, several special studies are being performed by the Technical Assistance Contractor (TAC) to identify and evaluate various design features that may reduce groundwater-related releases from tailings piles. The objective of this special study is to assess the suitability of using alternate cover materials (other than geomembranes) as infiltration barriers in Uranium Mill Tailings Remedial Action (UMTRA) Project piles to minimize leachate generation. The materials evaluated in this study include various types of asphalts, concretes, and a sodium bentonite clay/polypropylene liner system

  14. Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

    2017-10-01

    Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375

  15. Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

    2017-01-01

    Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data

  16. Methods for converting continuous shrubland ecosystem component values to thematic National Land Cover Database classes

    Science.gov (United States)

    Rigge, Matthew B.; Gass, Leila; Homer, Collin G.; Xian, George Z.

    2017-10-26

    The National Land Cover Database (NLCD) provides thematic land cover and land cover change data at 30-meter spatial resolution for the United States. Although the NLCD is considered to be the leading thematic land cover/land use product and overall classification accuracy across the NLCD is high, performance and consistency in the vast shrub and grasslands of the Western United States is lower than desired. To address these issues and fulfill the needs of stakeholders requiring more accurate rangeland data, the USGS has developed a method to quantify these areas in terms of the continuous cover of several cover components. These components include the cover of shrub, sagebrush (Artemisia spp), big sagebrush (Artemisia tridentata spp.), herbaceous, annual herbaceous, litter, and bare ground, and shrub and sagebrush height. To produce maps of component cover, we collected field data that were then associated with spectral values in WorldView-2 and Landsat imagery using regression tree models. The current report outlines the procedures and results of converting these continuous cover components to three thematic NLCD classes: barren, shrubland, and grassland. To accomplish this, we developed a series of indices and conditional models using continuous cover of shrub, bare ground, herbaceous, and litter as inputs. The continuous cover data are currently available for two large regions in the Western United States. Accuracy of the “cross-walked” product was assessed relative to that of NLCD 2011 at independent validation points (n=787) across these two regions. Overall thematic accuracy of the “cross-walked” product was 0.70, compared to 0.63 for NLCD 2011. The kappa value was considerably higher for the “cross-walked” product at 0.41 compared to 0.28 for NLCD 2011. Accuracy was also evaluated relative to the values of training points (n=75,000) used in the development of the continuous cover components. Again, the “cross-walked” product outperformed NLCD

  17. Generalized Smooth Transition Map Between Tent and Logistic Maps

    Science.gov (United States)

    Sayed, Wafaa S.; Fahmy, Hossam A. H.; Rezk, Ahmed A.; Radwan, Ahmed G.

    There is a continuous demand on novel chaotic generators to be employed in various modeling and pseudo-random number generation applications. This paper proposes a new chaotic map which is a general form for one-dimensional discrete-time maps employing the power function with the tent and logistic maps as special cases. The proposed map uses extra parameters to provide responses that fit multiple applications for which conventional maps were not enough. The proposed generalization covers also maps whose iterative relations are not based on polynomials, i.e. with fractional powers. We introduce a framework for analyzing the proposed map mathematically and predicting its behavior for various combinations of its parameters. In addition, we present and explain the transition map which results in intermediate responses as the parameters vary from their values corresponding to tent map to those corresponding to logistic map case. We study the properties of the proposed map including graph of the map equation, general bifurcation diagram and its key-points, output sequences, and maximum Lyapunov exponent. We present further explorations such as effects of scaling, system response with respect to the new parameters, and operating ranges other than transition region. Finally, a stream cipher system based on the generalized transition map validates its utility for image encryption applications. The system allows the construction of more efficient encryption keys which enhances its sensitivity and other cryptographic properties.

  18. Rohingya Refugee Crisis and Forest Cover Change in Teknaf, Bangladesh

    Directory of Open Access Journals (Sweden)

    Mohammad Mehedy Hassan

    2018-04-01

    Full Text Available Following a targeted campaign of violence by Myanmar military, police, and local militias, more than half a million Rohingya refugees have fled to neighboring Bangladesh since August 2017, joining thousands of others living in overcrowded settlement camps in Teknaf. To accommodate this mass influx of refugees, forestland is razed to build spontaneous settlements, resulting in an enormous threat to wildlife habitats, biodiversity, and entire ecosystems in the region. Although reports indicate that this rapid and vast expansion of refugee camps in Teknaf is causing large scale environmental destruction and degradation of forestlands, no study to date has quantified the camp expansion extent or forest cover loss. Using remotely sensed Sentinel-2A and -2B imagery and a random forest (RF machine learning algorithm with ground observation data, we quantified the territorial expansion of refugee settlements and resulting degradation of the ecological resources surrounding the three largest concentrations of refugee camps—Kutupalong–Balukhali, Nayapara–Leda and Unchiprang—that developed between pre- and post-August of 2017. Employing RF as an image classification approach for this study with a cross-validation technique, we obtained a high overall classification accuracy of 94.53% and 95.14% for 2016 and 2017 land cover maps, respectively, with overall Kappa statistics of 0.93 and 0.94. The producer and user accuracy for forest cover ranged between 92.98–98.21% and 96.49–92.98%, respectively. Results derived from the thematic maps indicate a substantial expansion of refugee settlements in the three refugee camp study sites, with an increase of 175 to 1530 hectares between 2016 and 2017, and a net growth rate of 774%. The greatest camp expansion is observed in the Kutupalong–Balukhali site, growing from 146 ha to 1365 ha with a net increase of 1219 ha (total growth rate of 835% in the same time period. While the refugee camps’ occupancy

  19. Angola Seismicity MAP

    Science.gov (United States)

    Neto, F. A. P.; Franca, G.

    2014-12-01

    The purpose of this job was to study and document the Angola natural seismicity, establishment of the first database seismic data to facilitate consultation and search for information on seismic activity in the country. The study was conducted based on query reports produced by National Institute of Meteorology and Geophysics (INAMET) 1968 to 2014 with emphasis to the work presented by Moreira (1968), that defined six seismogenic zones from macro seismic data, with highlighting is Zone of Sá da Bandeira (Lubango)-Chibemba-Oncócua-Iona. This is the most important of Angola seismic zone, covering the epicentral Quihita and Iona regions, geologically characterized by transcontinental structure tectono-magmatic activation of the Mesozoic with the installation of a wide variety of intrusive rocks of ultrabasic-alkaline composition, basic and alkaline, kimberlites and carbonatites, strongly marked by intense tectonism, presenting with several faults and fractures (locally called corredor de Lucapa). The earthquake of May 9, 1948 reached intensity VI on the Mercalli-Sieberg scale (MCS) in the locality of Quihita, and seismic active of Iona January 15, 1964, the main shock hit the grade VI-VII. Although not having significant seismicity rate can not be neglected, the other five zone are: Cassongue-Ganda-Massano de Amorim; Lola-Quilengues-Caluquembe; Gago Coutinho-zone; Cuima-Cachingues-Cambândua; The Upper Zambezi zone. We also analyzed technical reports on the seismicity of the middle Kwanza produced by Hidroproekt (GAMEK) region as well as international seismic bulletins of the International Seismological Centre (ISC), United States Geological Survey (USGS), and these data served for instrumental location of the epicenters. All compiled information made possible the creation of the First datbase of seismic data for Angola, preparing the map of seismicity with the reconfirmation of the main seismic zones defined by Moreira (1968) and the identification of a new seismic

  20. Land Cover Classification Using ALOS Imagery For Penang, Malaysia

    International Nuclear Information System (INIS)

    Sim, C K; Abdullah, K; MatJafri, M Z; Lim, H S

    2014-01-01

    This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach

  1. National Level Assessment of Mangrove Forest Cover in Pakistan

    Science.gov (United States)

    Abbas, S.; Qamer, F. M.; Hussain, N.; Saleem, R.; Nitin, K. T.

    2011-09-01

    . GIS and Remote Sensing based technologies and methods are in use to map forest cover since the last two decades in Pakistan. The national level forest cover studies based upon satellite images include, Forestry Sector Master Plan (FSMP) and National Forest & Range Resources Assessment Study (NFRRAS). In FSMP, the mangrove forest extent was visually determined from Landsat images of 1988 - 1991, and was estimated to be 155,369 ha; whereas, in NFRRAS, Landsat images of 1997 - 2001 were automated processed and the mangroves areas was estimated to be 158,000 ha. To our knowledge, a comprehensive assessment of current mangroves cover of Pakistan has not been made over the last decade, although the mangroves ecosystems have become the focus of intention in context of recent climate change scenarios. This study was conducted to support the informed decision making for sustainable development in coastal areas of Pakistan by providing up-todate mangroves forest cover assessment of Pakistan. Various types of Earth Observation satellite images and processing methods have been tested in relation to mangroves mapping. Most of the studies have applied classical pixel - based approached, there are a few studies which used object - based methods of image analysis to map the mangroves ecosystems. Object - based methods have the advantage of incorporating spatial neighbourhood properties and hierarchical structures into the classification process to produce more accurate surface patterns recognition compared with classical pixel - based approaches. In this research, we applied multi-scale hierarchical approach of object-based methods of image analysis to ALOS - AVNIR-2 images of the year 2008-09 to map the land cover in the mangroves ecosystems of Pakistan. Considering the tide height and phonological effects of vegetation, particularly the algal mats, these data sets were meticulously chosen. Incorporation of multi-scale hierarchical structures made it easy to effectively discriminate

  2. Vegetation classification and distribution mapping report Mesa Verde National Park

    Science.gov (United States)

    Thomas, Kathryn A.; McTeague, Monica L.; Ogden, Lindsay; Floyd, M. Lisa; Schulz, Keith; Friesen, Beverly A.; Fancher, Tammy; Waltermire, Robert G.; Cully, Anne

    2009-01-01

    during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

  3. Simulated impacts of land cover change on summer climate in the Tibetan Plateau

    International Nuclear Information System (INIS)

    Li Qian; Xue Yongkang

    2010-01-01

    The Tibetan Plateau (TP) is a key region of land-atmosphere interactions with severe eco-environment degradation. This study uses an atmospheric general circulation model, NCEP GCM/SSiB, to present the major TP summer climate features for six selected ENSO years and preliminarily assess the possible impact of land cover change on the summer circulation over the TP. Compared to Reanalysis II data, the GCM using satellite derived vegetation properties generally reproduces the main 6-year-mean TP summer circulation features despite some discrepancies in intensity and geographic locations of some climate features. Two existing vegetation maps with very different land cover conditions over the TP, one with bare ground and one with vegetation cover, derived from satellite derived data, are tested and produce clearer climate signals due to land cover change. It shows that land cover change from vegetated land to bare ground decreases the radiation absorbed by the surface and results in weaker surface thermal effects, which lead to lower atmospheric temperature, as well as weaker vertical ascending motion, low-layer cyclonic, upper level anticyclonic, and summer monsoon circulation. These changes in circulation cause a decrease in the precipitation in the southeastern TP.

  4. Do cover crop mixtures have the same ability to suppress weeds as competitive monoculture cover crops?

    Directory of Open Access Journals (Sweden)

    Brust, Jochen

    2014-02-01

    Full Text Available An increasing number of farmers use cover crop mixtures instead of monoculture cover crops to improve soil and crop quality. However, only little information is available about the weed suppression ability of cover crop mixtures. Therefore, two field experiments were conducted in Baden-Württemberg between 2010 and 2012, to compare growth and weed suppression of monoculture cover crops and cover crop mixtures. In the first experiment, heterogeneous results between yellow mustard and the cover crop mixture occurred. For further research, a field experiment was conducted in 2012 to compare monocultures of yellow mustard and hemp with three cover crop mixtures. The evaluated mixtures were: “MELO”: for soil melioration; “BETA”: includes only plant species with no close relation to main cash crops in Central Europe and “GPS”: for usage as energy substrate in spring. Yellow mustard, MELO, BETA and GPS covered 90% of the soil in less than 42 days and were able to reduce photosynthetically active radiation (PAR on soil surface by more than 96% after 52 days. Hemp covered 90% of the soil after 47 days and reduced PAR by 91% after 52 days. Eight weeks after planting, only BETA showed similar growth to yellow mustard which produced the highest dry matter. The GPS mixture had comparatively poor growth, while MELO produced similar dry matter to hemp. Yellow mustard, MELO and BETA reduced weed growth by 96% compared with a no cover crop control, while hemp and GPS reduced weeds by 85% and 79%. In spring, weed dry matter was reduced by more than 94% in plots with yellow mustard and all mixtures, while in hemp plots weeds were only reduced by 71%. The results suggest that the tested cover crop mixtures offer similar weed suppression ability until spring as the monoculture of the competitive yellow mustard.

  5. Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece

    Directory of Open Access Journals (Sweden)

    Ioannis Manakos

    2014-12-01

    Full Text Available The National Geomatics Center of China (NGCC produced Global Land Cover (GlobalLand30 maps with 30 m spatial resolution for the years 2000 and 2009–2010, responding to the need for harmonized, accurate, and high-resolution global land cover data. This study aims to assess the mapping accuracy of the land surface water layer of GlobalLand30 for 2009–2010. A representative Mediterranean region, situated in Greece, is considered as the case study area, with 2009 as the reference year. The assessment is realized through an object-based comparison of the GlobalLand30 water layer with the ground truth and visually interpreted data from the Hellenic Cadastre fine spatial resolution (0.5 m orthophoto map layer. GlobCover 2009, GlobCorine 2009, and GLCNMO 2008 corresponding thematic layers are utilized to show and quantify the progress brought along with the increment of the spatial resolution, from 500 m to 300 m and finally to 30 m with the newly produced GlobalLand30 maps. GlobalLand30 detected land surface water areas show a 91.9% overlap with the reference data, while the coarser resolution products are restricted to lower accuracies. Validation is extended to the drainage network elements, i.e., rivers and streams, where GlobalLand30 outperforms the other global map products, as well.

  6. 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

    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...

  7. Mapping of Landscape Cover Using Remote Sensing and GIS in ...

    African Journals Online (AJOL)

    Tadesse

    present study, Remote Sensing (RS) and Geographical Information System (GIS) techniques were used. Remotely sensed .... growing stock in Tahno range of Dehradun Forest Division. Okhandiara (2008) .... areas on an image by identifying 'training' sites of known targets and then extrapolating those spectral signatures to ...

  8. Mapping of Landscape Cover Using Remote Sensing and GIS in ...

    African Journals Online (AJOL)

    If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs. Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link ...

  9. Mapping of Landscape Cover Using Remote Sensing and GIS in ...

    African Journals Online (AJOL)

    Tadesse

    Department of Biology, College of Natural and Computational Sciences, P.O. Box 3044, ... of degradation and depletion of earth resources has accelerated ... know how much area is suitable for wildlife species and what areas are affected due to ..... features like roads, railway lines, crossing of canal etc. on each other.

  10. Historical Topographic Map Collection bookmark

    Science.gov (United States)

    Fishburn, Kristin A.; Allord, Gregory J.

    2017-06-29

    The U.S. Geological Survey (USGS) National Geospatial Program is scanning published USGS 1:250,000-scale and larger topographic maps printed between 1884, the inception of the topographic mapping program, and 2006. The goal of this project, which began publishing the historical scanned maps in 2011, is to provide a digital repository of USGS topographic maps, available to the public at no cost. For more than 125 years, USGS topographic maps have accurately portrayed the complex geography of the Nation. The USGS is the Nation’s largest producer of printed topographic maps, and prior to 2006, USGS topographic maps were created using traditional cartographic methods and printed using a lithographic printing process. As the USGS continues the release of a new generation of topographic maps (US Topo) in electronic form, the topographic map remains an indispensable tool for government, science, industry, land management planning, and leisure.

  11. EVALUATION AND MAPPING OF RANGELANDS DEGRADATION USING REMOTELY SENSED DATA

    Directory of Open Access Journals (Sweden)

    Majid Ajorlo

    2005-05-01

    Full Text Available The empirical and scientifically documents prove that misuse of natural resource causes degradation in it. So natural resources conservation is important in approaching sustainable development aims. In current study, Landsat Thematic Mapper images and grazing gradient method have been used to map the extent and degree of rangeland degradation. In during ground-based data measuring, factors such as vegetation cover, litter, plant diversity, bare soil, and stone & gravels were estimated as biophysical indicators of degradation. The next stage, after geometric correction and doing some necessary pre-processing practices on the study area’s images; the best and suitable vegetation index has been selected to map rangeland degradation among the Normalized Difference Vegetation Index (NDVI, Soil Adjusted Vegetation Index (SAVI, and Perpendicular Vegetation Index (PVI. Then using suitable vegetation index and distance parameter was produced the rangelands degradation map. The results of ground-based data analysis reveal that there is a significant relation between increasing distance from critical points and plant diversity and also percentage of litter. Also there is significant relation between vegetation cover percent and distance from village, i.e. the vegetation cover percent increases by increasing distance from villages, while it wasn’t the same around the stock watering points. The result of analysis about bare soil and distance from critical point was the same to vegetation cover changes manner. Also there wasn’t significant relation between stones & gravels index and distance from critical points. The results of image processing show that, NDVI appears to be sensitive to vegetation changes along the grazing gradient and it can be suitable vegetation index to map rangeland degradation. The degradation map shows that there is high degradation around the critical points. These areas need urgent attention for soil conservation. Generally, it

  12. Ionospheric TEC Weather Map Over South America

    Science.gov (United States)

    Takahashi, H.; Wrasse, C. M.; Denardini, C. M.; Pádua, M. B.; de Paula, E. R.; Costa, S. M. A.; Otsuka, Y.; Shiokawa, K.; Monico, J. F. Galera; Ivo, A.; Sant'Anna, N.

    2016-11-01

    Ionospheric weather maps using the total electron content (TEC) monitored by ground-based Global Navigation Satellite Systems (GNSS) receivers over South American continent, TECMAP, have been operationally produced by Instituto Nacional de Pesquisas Espaciais's Space Weather Study and Monitoring Program (Estudo e Monitoramento Brasileiro de Clima Especial) since 2013. In order to cover the whole continent, four GNSS receiver networks, (Rede Brasileiro de Monitoramento Contínuo) RBMC/Brazilian Institute for Geography and Statistics, Low-latitude Ionospheric Sensor Network, International GNSS Service, and Red Argentina de Monitoreo Satelital Continuo, in total 140 sites, have been used. TECMAPs with a time resolution of 10 min are produced in 12 h time delay. Spatial resolution of the map is rather low, varying between 50 and 500 km depending on the density of the observation points. Large day-to-day variabilities of the equatorial ionization anomaly have been observed. Spatial gradient of TEC from the anomaly trough (total electron content unit, 1 TECU = 1016 el m-2 (TECU) 80) causes a large ionospheric range delay in the GNSS positioning system. Ionospheric plasma bubbles, their seeding and development, could be monitored. This plasma density (spatial and temporal) variability causes not only the GNSS-based positioning error but also radio wave scintillations. Monitoring of these phenomena by TEC mapping becomes an important issue for space weather concern for high-technology positioning system and telecommunication.

  13. Interest rates mapping

    Science.gov (United States)

    Kanevski, M.; Maignan, M.; Pozdnoukhov, A.; Timonin, V.

    2008-06-01

    The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space-time and maturity. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well.

  14. The National Map - Missouri Pilot Project

    Science.gov (United States)

    ,

    2001-01-01

    Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

  15. The National Map - Delaware Pilot Project

    Science.gov (United States)

    ,

    2001-01-01

    Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

  16. The National Map - Pennsylvania Pilot Project

    Science.gov (United States)

    ,

    2001-01-01

    Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

  17. The National Map - Texas Pilot Project

    Science.gov (United States)

    ,

    2001-01-01

    Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

  18. The National Map - Florida Pilot Project

    Science.gov (United States)

    ,

    2001-01-01

    Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

  19. SAR China Land Mapping Project: Development, Production and Potential Applications

    International Nuclear Information System (INIS)

    Zhang, Lu; Guo, Huadong; Liu, Guang; Fu, Wenxue; Yan, Shiyong; Song, Rui; Ji, Peng; Wang, Xinyuan

    2014-01-01

    Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change

  20. The projective heat map

    CERN Document Server

    Schwartz, Richard Evan

    2017-01-01

    This book introduces a simple dynamical model for a planar heat map that is invariant under projective transformations. The map is defined by iterating a polygon map, where one starts with a finite planar N-gon and produces a new N-gon by a prescribed geometric construction. One of the appeals of the topic of this book is the simplicity of the construction that yet leads to deep and far reaching mathematics. To construct the projective heat map, the author modifies the classical affine invariant midpoint map, which takes a polygon to a new polygon whose vertices are the midpoints of the original. The author provides useful background which makes this book accessible to a beginning graduate student or advanced undergraduate as well as researchers approaching this subject from other fields of specialty. The book includes many illustrations, and there is also a companion computer program.

  1. Ogallala Aquifer Mapping Program

    International Nuclear Information System (INIS)

    1984-10-01

    A computerized data file has been established which can be used efficiently by the contour-plotting program SURFACE II to produce maps of the Ogallala aquifer in 17 counties of the Texas Panhandle. The data collected have been evaluated and compiled into three sets, from which SURFACE II can generate maps of well control, aquifer thickness, saturated thickness, water level, and the difference between virgin (pre-1942) and recent (1979 to 1981) water levels. 29 figures, 1 table

  2. Maps for the future.

    Directory of Open Access Journals (Sweden)

    Cristina D’Alessandro-Scarpari

    2005-05-01

    Full Text Available Geographers’ relations with maps have a long story of attraction and repulsion. The map has always fascinated Geographers (even before the institutionalization of the discipline as a powerful tool, able to demarcate territories, to produce different visions of them and to transform them by the actions they may cause or influence. Sometimes for strategic reasons Geographers have also denigrated cartography as a secondary and technical form of knowledge, a tool merely for understanding and ...

  3. Construction of a reference genetic linkage map for carnation (Dianthus caryophyllus L.).

    Science.gov (United States)

    Yagi, Masafumi; Yamamoto, Toshiya; Isobe, Sachiko; Hirakawa, Hideki; Tabata, Satoshi; Tanase, Koji; Yamaguchi, Hiroyasu; Onozaki, Takashi

    2013-10-26

    Genetic linkage maps are important tools for many genetic applications including mapping of quantitative trait loci (QTLs), identifying DNA markers for fingerprinting, and map-based gene cloning. Carnation (Dianthus caryophyllus L.) is an important ornamental flower worldwide. We previously reported a random amplified polymorphic DNA (RAPD)-based genetic linkage map derived from Dianthus capitatus ssp. andrezejowskianus and a simple sequence repeat (SSR)-based genetic linkage map constructed using data from intraspecific F2 populations; however, the number of markers was insufficient, and so the number of linkage groups (LGs) did not coincide with the number of chromosomes (x = 15). Therefore, we aimed to produce a high-density genetic map to improve its usefulness for breeding purposes and genetic research. We improved the SSR-based genetic linkage map using SSR markers derived from a genomic library, expression sequence tags, and RNA-seq data. Linkage analysis revealed that 412 SSR loci (including 234 newly developed SSR loci) could be mapped to 17 linkage groups (LGs) covering 969.6 cM. Comparison of five minor LGs covering less than 50 cM with LGs in our previous RAPD-based genetic map suggested that four LGs could be integrated into two LGs by anchoring common SSR loci. Consequently, the number of LGs corresponded to the number of chromosomes (x = 15). We added 192 new SSRs, eight RAPD, and two sequence-tagged site loci to refine the RAPD-based genetic linkage map, which comprised 15 LGs consisting of 348 loci covering 978.3 cM. The two maps had 125 SSR loci in common, and most of the positions of markers were conserved between them. We identified 635 loci in carnation using the two linkage maps. We also mapped QTLs for two traits (bacterial wilt resistance and anthocyanin pigmentation in the flower) and a phenotypic locus for flower-type by analyzing previously reported genotype and phenotype data. The improved genetic linkage maps and SSR markers developed

  4. Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

    Science.gov (United States)

    Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

    2015-03-01

    The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

  5. On the structure of finite-sheeted coverings of compact connected groups

    OpenAIRE

    Grigorian, S. A.; Gumerov, R. N.

    2004-01-01

    Finite-sheeted covering mappings onto compact connected groups are studied. It is shown that a finite-sheeted covering mapping from a connected Hausdorff topological space onto a compact connected abelian group G must be a homeomorphism provided that the character group of G admits division by the degree of given covering mapping. Using this result, we obtain criteria of triviality for finite coverings of G in terms of its character group and means on G. In order to establish these facts, for...

  6. Allegheny County Land Cover Areas

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Land Cover dataset demarcates 14 land cover types by area; such as Residential, Commercial, Industrial, Forest, Agriculture, etc. If viewing this description on...

  7. 2005 Kansas Land Cover Patterns, Level I, State of Kansas (300m buffer) and 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...

  8. On approximating restricted cycle covers

    NARCIS (Netherlands)

    Manthey, Bodo

    2008-01-01

    A cycle cover of a graph is a set of cycles such that every vertex is part of exactly one cycle. An $L$-cycle cover is a cycle cover in which the length of every cycle is in the set $L$. The weight of a cycle cover of an edge-weighted graph is the sum of the weights of its edges. We come close to

  9. Gainesville's urban forest canopy cover

    Science.gov (United States)

    Francisco Escobedo; Jennifer A. Seitz; Wayne Zipperer

    2009-01-01

    Ecosystem benefits from trees are linked directly to the amount of healthy urban forest canopy cover. Urban forest cover is dynamic and changes over time due to factors such as urban development, windstorms, tree removals, and growth. The amount of a city's canopy cover depends on its land use, climate, and people's preferences. This fact sheet examines how...

  10. A Semi-Automated Machine Learning Algorithm for Tree Cover Delineation from 1-m Naip Imagery Using a High Performance Computing Architecture

    Science.gov (United States)

    Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.

    2014-12-01

    Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.

  11. Forest cover of Champaign County, Illinois in 1993

    Science.gov (United States)

    Jesus Danilo Chinea; Louis R. Iverson

    1997-01-01

    The forest cover of Champaign County, in east-central Illinois, was mapped from 1993 aerial photography and entered in a geographical information system database. One hundred and six forest patches cover 3,380 ha. These patches have a mean area of 32 ha, a mean perimeter of 4,851 m, a mean perimeter to area ratio of 237, a fractal dimension of 1.59, and a mean nearest...

  12. Construction of an almond linkage map in an Australian population Nonpareil × Lauranne

    Science.gov (United States)

    2010-01-01

    Background Despite a high genetic similarity to peach, almonds (Prunus dulcis) have a fleshless fruit and edible kernel, produced as a crop for human consumption. While the release of peach genome v1.0 provides an excellent opportunity for almond genetic and genomic studies, well-assessed segregating populations and the respective saturated genetic linkage maps lay the foundation for such studies to be completed in almond. Results Using an almond intraspecific cross between 'Nonpareil' and 'Lauranne' (N × L), we constructed a moderately saturated map with SSRs, SNPs, ISSRs and RAPDs. The N × L map covered 591.4 cM of the genome with 157 loci. The average marker distance of the map was 4.0 cM. The map displayed high synteny and colinearity with the Prunus T × E reference map in all eight linkage groups (G1-G8). The positions of 14 mapped gene-anchored SNPs corresponded approximately with the positions of homologous sequences in the peach genome v1.0. Analysis of Mendelian segregation ratios showed that 17.9% of markers had significantly skewed genotype ratios at the level of P almond map, which is highly syntenic and collinear with the Prunus reference map and peach genome V1.0. Therefore, the well-assessed almond population reported here can be used to investigate the traits of interest under Australian growing conditions, and provides more information on the almond genome for the international community. PMID:20932335

  13. Producing cement

    Energy Technology Data Exchange (ETDEWEB)

    Stone, E G

    1923-09-12

    A process and apparatus are described for producing Portland cement in which pulverized shale is successively heated in a series of inclined rotary retorts having internal stirrers and oil gas outlets, which are connected to condensers. The partially treated shale is removed from the lowermost retort by a conveyor, then fed separately or conjointly into pipes and thence into a number of vertically disposed retorts. Each of these retorts may be fitted interiorly with vertical arranged conveyors which elevate the shale and discharge it over a lip, from whence it falls to the bottom of the retorts. The lower end of each casing is furnished with an adjustable discharge door through which the spent shale is fed to a hopper, thence into separate trucks. The oil gases generated in the retorts are exhausted through pipes to condensers. The spent shale is conveyed to a bin and mixed while hot with ground limestone. The admixed materials are then ground and fed to a rotary kiln which is fired by the incondensible gases derived from the oil gases obtained in the previous retorting of the shale. The calcined materials are then delivered from the rotary kiln to rotary coolers. The waste gases from the kiln are utilized for heating the retorts in which the ground shale is heated for the purpose of extracting therefrom the contained hydrocarbon oils and gases.

  14. ASSESSING LAND COVER CHANGES CAUSED BY GRANITE QUARRYING USING REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    R. S. Moeletsi

    2017-11-01

    Full Text Available Dimension stone quarrying in the area between Rustenburg and Brits in the North West Province of South Africa has been in existence for over 70 decades. The unique characteristics of the granite deposits in South Africa resulted in making the country a global producer of the granite rocks. This led to intensified quarrying activities between Rustenburg and Brits town. However, this surface mining method, has a potential to impact the environment in a negative way causing loss in vegetation, depletion of natural resources, loss of scenic beauty and contamination of surface water resources. To assess the land cover changes caused by granite quarrying activities, remotely sensed data in the form of Landsat images between 1998 and 2015 were used. Supervised classification was used to create maps. Accuracy assessment using Google EarthTM as a reference data yielded an overall accuracy of 78 %. The post classification change detection method was used to assess land cover changes within the granite quarries. Granite quarries increased by 1174.86 ha while formation of quarry lakes increased to 5.3 ha over the 17-year period. Vegetation cover decreased by 1308 ha in area while 18.3 ha bare land was lost during the same period. This study demonstrated the utility of remote sensing to detect changes in land cover within granite quarries.

  15. Land use and land cover dynamics on the campus of Federal University of Lavras from 1964 to 2009

    Directory of Open Access Journals (Sweden)

    Elizabeth Ferreira

    2013-03-01

    Full Text Available This study identified, quantified and analyzed changes in land use and cover on the campus of Federal University of Lavras campus, located in Lavras city (Minas Gerais State. The 2009 QuickBird satellite imagery and 1985, 1979, 1971, 1964 vertical aerial photographs were used to produce a set of land use and land cover maps. The work started with the orthorectification of the QuickBird satellite imagery and vertical aerial photographs. The identification and definition of land cover and land use classes were obtained from field surveys in 2009. First, the land cover and land use maps were made from that information. Finally, the quantification and analysis of changes were performed at the imagery time range. The results showed that in 2009 the "urbanized area class" of the campus reached 65.79 ha and that the most significant increase of this class occurred between the years 1964 (6.24 ha and 1971 (24.4 ha. The smallest area of "forest land class" found on the campus was 38.38 ha in 1971, and from 1979 on this situation has been improved reaching 113.18 ha of "forest land class" in 2009. For the "water class" there was not any dam constructed yet in the campus before 1971. Most of the campus area, previously used for "agricultural land class" had a significant reduction within this category, from 384.19 ha in 1964 to 271.16 ha in 2009.

  16. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 4, Southeast United States: CNPY01_4

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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) Imperviousness Layer Tile 3, Southwest United States: IMPV01_3

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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) Tree Canopy Layer Tile 2, Northeast United States: CNPY01_2

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 4, Southeast United States: IMPV01_4

    Science.gov (United States)

    Wieczorek, Michael; LaMotte, Andrew E.

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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.

  20. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 1, Northwest United States: CNPY01_1

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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

  1. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 2, Northeast United States: IMPV01_2

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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.

  2. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 1, Northwest United States: IMPV01_1

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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.

  3. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 3, Southwest United States: CNPY01_3

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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.

  4. Mathematical Foundation for Plane Covering Using Hexagons

    Science.gov (United States)

    Johnson, Gordon G.

    1999-01-01

    This work is to indicate the development and mathematical underpinnings of the algorithms previously developed for covering the plane and the addressing of the elements of the covering. The algorithms are of interest in that they provides a simple systematic way of increasing or decreasing resolution, in the sense that if we have the covering in place and there is an image superimposed upon the covering, then we may view the image in a rough form or in a very detailed form with minimal effort. Such ability allows for quick searches of crude forms to determine a class in which to make a detailed search. In addition, the addressing algorithms provide an efficient way to process large data sets that have related subsets. The algorithms produced were based in part upon the work of D. Lucas "A Multiplication in N Space" which suggested a set of three vectors, any two of which would serve as a bases for the plane and also that the hexagon is the natural geometric object to be used in a covering with a suggested bases. The second portion is a refinement of the eyeball vision system, the globular viewer.

  5. CORINE land cover and floristic variation in a Mediterranean wetland.

    Science.gov (United States)

    Giallonardo, Tommaso; Landi, Marco; Frignani, Flavio; Geri, Francesco; Lastrucci, Lorenzo; Angiolini, Claudia

    2011-11-01

    The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.

  6. Generalized N-coupled maps with invariant measure in Bose ...

    Indian Academy of Sciences (India)

    chronization problem of an array of the linearly coupled map lattices of ... groups and graphs and also in the design of experiments, coding theory, partition ... coupled map lattice which covers internal and external couplings in a form of asso-.

  7. Development of a 30 m Spatial Resolution Land Cover of Canada: Contribution to the Harmonized North America Land Cover Dataset

    Science.gov (United States)

    Pouliot, D.; Latifovic, R.; Olthof, I.

    2017-12-01

    Land cover is needed for a large range of environmental applications regarding climate impacts and adaption, emergency response, wildlife habitat, air quality, water yield, etc. In Canada a 2008 user survey revealed that the most practical scale for provision of land cover data is 30 m, nationwide, with an update frequency of five years (Ball, 2008). In response to this need the Canada Centre for Remote Sensing has generated a 30 m land cover of Canada for the base year 2010 as part of a planned series of maps at the recommended five year update frequency. This land cover is the Canadian contribution to the North American Land Change Monitoring System initiative, which seeks to provide harmonized land cover across Canada, the United States, and Mexico. The methodology developed in this research utilized a combination of unsupervised and machine learning techniques to map land cover, blend results between mapping units, locally optimize results, and process some thematic attributes with specific features sets. Accuracy assessment with available field data shows it was on average 75% for the five study areas assessed. In this presentation an overview of the unique processing aspects, example results, and initial accuracy assessment will be discussed.

  8. Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data

    Science.gov (United States)

    Mei, Alessandro; Manzo, Ciro; Fontinovo, Giuliano; Bassani, Cristiana; Allegrini, Alessia; Petracchini, Francesco

    2016-10-01

    The Lampedusa Island displays important socio-economic criticalities related to an intensive touristic activity, which implies an increase in electricity consumption and waste production. An adequate island conversion to a more environmental, sustainable community needs to be faced by the local Management Plans establishment. For this purpose, several thematic datasets have to be produced and evaluated. Socio-economic and bio-ecological components as well as land cover/use assessment are some of the main topics to be managed within the Decision Support Systems. Considering the lack of Land Cover (LC) and vegetation change detection maps in Lampedusa Island (Italy), this paper focuses on the retrieval of these topics by remote sensing techniques. The analysis was carried out by Landsat 5 TM and Landsat 8 OLI multispectral images from 1984 to 2014 in order to obtain spatial and temporal information of changes occurred in the island. Firstly, imagery was co-registered and atmospherically corrected; secondly, it was then classified for land cover and vegetation distribution analysis with the use of QGIS and Saga GIS open source softwares. The Maximum Likelihood Classifier (MLC) was used for LC maps production, while the Normalized Difference Vegetation Index (NDVI) was used for vegetation examination and distribution. Topographic maps, historical aerial photos, ortophotos and field data are merged in the GIS for accuracy assessment. Finally, change detection of MLC and NDVI are provided respectively by Post-Classification Comparison (PCC) and Image Differencing (ID). The provided information, combined with local socio-economic parameters, is essential for the improvement of environmental sustainability of anthropogenic activities in Lampedusa.

  9. Generating Topographic Map Data from Classification Results

    Directory of Open Access Journals (Sweden)

    Joachim Höhle

    2017-03-01

    Full Text Available The use of classification results as topographic map data requires cartographic enhancement and checking of the geometric accuracy. Urban areas are of special interest. The conversion of the classification result into topographic map data of high thematic and geometric quality is subject of this contribution. After reviewing the existing literature on this topic, a methodology is presented. The extraction of point clouds belonging to line segments is solved by the Hough transform. The mathematics for deriving polygons of orthogonal, parallel and general line segments by least squares adjustment is presented. A unique solution for polylines, where the Hough parameters are optimized, is also given. By means of two data sets land cover maps of six classes were produced and then enhanced by the proposed method. The classification used the decision tree method applying a variety of attributes including object heights derived from imagery. The cartographic enhancement is carried out with two different levels of quality. The user’s accuracies for the classes “impervious surface” and “building” were above 85% in the “Level 1” map of Example 1. The geometric accuracy of building corners at the “Level 2” maps is assessed by means of reference data derived from ortho-images. The obtained root mean square errors (RMSE of the generated coordinates (x, y were RMSEx = 1.2 m and RMSEy = 0.7 m (Example 1 and RMSEx = 0.8 m and RMSEy = 1.0 m (Example 2 using 31 and 62 check points, respectively. All processing for Level 1 (raster data could be carried out with a high degree of automation. Level 2 maps (vector data were compiled for the classes “building” and “road and parking lot”. For urban areas with numerous classes and of large size, universal algorithms are necessary to produce vector data fully automatically. The recent progress in sensors and machine learning methods will support the generation of topographic map data of high

  10. Mapping seabird sensitivity to offshore wind farms.

    Directory of Open Access Journals (Sweden)

    Gareth Bradbury

    Full Text Available We present a Geographic Information System (GIS tool, SeaMaST (Seabird Mapping and Sensitivity Tool, to provide evidence on the use of sea areas by seabirds and inshore waterbirds in English territorial waters, mapping their relative sensitivity to offshore wind farms. SeaMaST is a freely available evidence source for use by all connected to the offshore wind industry and will assist statutory agencies in assessing potential risks to seabird populations from planned developments. Data were compiled from offshore boat and aerial observer surveys spanning the period 1979-2012. The data were analysed using distance analysis and Density Surface Modelling to produce predicted bird densities across a grid covering English territorial waters at a resolution of 3 km×3 km. Coefficients of Variation were estimated for each grid cell density, as an indication of confidence in predictions. Offshore wind farm sensitivity scores were compiled for seabird species using English territorial waters. The comparative risks to each species of collision with turbines and displacement from operational turbines were reviewed and scored separately, and the scores were multiplied by the bird density estimates to produce relative sensitivity maps. The sensitivity maps reflected well the amassed distributions of the most sensitive species. SeaMaST is an important new tool for assessing potential impacts on seabird populations from offshore development at a time when multiple large areas of development are proposed which overlap with many seabird species' ranges. It will inform marine spatial planning as well as identifying priority areas of sea usage by marine birds. Example SeaMaST outputs are presented.

  11. Mapping seabird sensitivity to offshore wind farms.

    Science.gov (United States)

    Bradbury, Gareth; Trinder, Mark; Furness, Bob; Banks, Alex N; Caldow, Richard W G; Hume, Duncan

    2014-01-01

    We present a Geographic Information System (GIS) tool, SeaMaST (Seabird Mapping and Sensitivity Tool), to provide evidence on the use of sea areas by seabirds and inshore waterbirds in English territorial waters, mapping their relative sensitivity to offshore wind farms. SeaMaST is a freely available evidence source for use by all connected to the offshore wind industry and will assist statutory agencies in assessing potential risks to seabird populations from planned developments. Data were compiled from offshore boat and aerial observer surveys spanning the period 1979-2012. The data were analysed using distance analysis and Density Surface Modelling to produce predicted bird densities across a grid covering English territorial waters at a resolution of 3 km×3 km. Coefficients of Variation were estimated for each grid cell density, as an indication of confidence in predictions. Offshore wind farm sensitivity scores were compiled for seabird species using English territorial waters. The comparative risks to each species of collision with turbines and displacement from operational turbines were reviewed and scored separately, and the scores were multiplied by the bird density estimates to produce relative sensitivity maps. The sensitivity maps reflected well the amassed distributions of the most sensitive species. SeaMaST is an important new tool for assessing potential impacts on seabird populations from offshore development at a time when multiple large areas of development are proposed which overlap with many seabird species' ranges. It will inform marine spatial planning as well as identifying priority areas of sea usage by marine birds. Example SeaMaST outputs are presented.

  12. Covariance mapping of two-photon double core hole states in C 2 H 2 and C 2 H 6 produced by an x-ray free electron laser

    International Nuclear Information System (INIS)

    Mucke, M; Motomura, K; Bozek, J D; Schorb, S; Messerschmidt, M; Glownia, J M; Cryan, J P; Coffee, R N; Takahashi, O; Prince, K C; Feifel, R; Univ. of Gothenburg

    2015-01-01

    Few-photon ionization and relaxation processes in acetylene (C 2 H 2 ) and ethane (C 2 H 6 ) were investigated at the linac coherent li