{"id":1256,"date":"2017-03-28T18:33:32","date_gmt":"2017-03-28T18:33:32","guid":{"rendered":"http:\/\/pecora.asprs.org\/?p=1256"},"modified":"2017-09-07T22:02:07","modified_gmt":"2017-09-07T22:02:07","slug":"special-sessions","status":"publish","type":"post","link":"http:\/\/pecora.asprs.org\/pecora20\/special-sessions\/","title":{"rendered":"Special Sessions"},"content":{"rendered":"<p><section class=\"kc-elm kc-css-667145 kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-603057 kc_col-sm-8 kc_column kc_col-sm-8\"><div class=\"kc-col-container\"><div class=\"kc-elm kc-css-917603 kc-raw-code\"><style>\r\n.gdlr-blog-full .gdlr-blog-thumbnail {\r\n  display: none;\r\n  margin-bottom: 33px;\r\n  text-align: center;\r\n}\r\n.ten {\r\n  width: 100%;\r\n}\r\n.kc_accordion_header.ui-accordion-header.ui-state-active > a {\r\n  color: black;\r\n  font-size: 22px;\r\n  font-weight: bold;\r\n}\r\n.kc_accordion_header.ui-accordion-header > a {\r\n  color: black;\r\n  font-size: 22px;\r\n  font-weight: bold;\r\n}\r\n<\/style><\/div><\/div><\/div><div class=\"kc-elm kc-css-292404 kc_col-sm-4 kc_column kc_col-sm-4\"><div class=\"kc-col-container\">\n<div class=\"kc-elm kc-css-135692 kc-pro-button kc-button-main\">\n\t<a href=\"http:\/\/pecora.asprs.org\/pecora20\/wp-content\/uploads\/2017\/08\/Posters_proof2.pdf\">\n\t\t<span class=\"creative_title\">Download Posters List<\/span>\t<\/a>\n<\/div>\n<\/div><\/div><\/div><\/div><\/section><section class=\"kc-elm kc-css-698714 kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-611413 kc_col-sm-12 kc_column kc_col-sm-12\"><div class=\"kc-col-container\"><div class=\"kc-elm kc-css-53313 kc_text_block\"><\/p>\n<h4><strong>Training the Next Generation of Remote Sensing Scientists Through Undergraduate Research Opportunities. <\/strong><br \/>\nModerators:\u00a0 Rebecca L. Dodge and Robert L. Bolin, <em>Graduate School of Petroleum Geology<\/em><\/h4>\n<p>From cloud computing to no-cost Landsat data and low-cost data collected from Unmanned Aircraft Systems, remote sensing technology is changing faster than ever before at a time when the need for a highly trained and adaptive geospatial workforce is perhaps greater than ever. In this session, StateView panelists from AmericaView, a nationwide consortium dedicated to remote sensing research, outreach, and education, will share their successes in building the remote sensing workforce of tomorrow through a network of undergraduate research opportunities. StateViews may focus research on state-specific issues important to local and regional stakeholders, such as urban expansion, coastal studies, forestry, agriculture, or grazing; international research applications are also available.\u00a0\u00a0 Panelists will share lessons learned as well as valuable insights about recruiting, training, and mentoring undergraduate students on data processing, information extraction, and presentation skills.\u00a0 This will be followed by a Q&amp;A and discussion session.<\/p>\n<p><strong>Panelists:<\/strong><\/p>\n<ul>\n<li>Rebecca Dodge, <em>Robert L. Bolin Graduate School of Petroleum Geology<\/em><\/li>\n<li>Larry Biehl, <em>Purdue University<\/em><\/li>\n<li>Jarlath O\u2019Neil-Dunne, <em>University of Vermont<\/em><\/li>\n<li>Ramesh Sivanpillai, <em>University of Wyoming<\/em><\/li>\n<li>Yong Wang, <em>East Carolina University<\/em><\/li>\n<\/ul>\n<hr \/>\n<h4><strong>Petascale High Performance Computing<\/strong><br \/>\nModerator:\u00a0 Steve Swazee, <em>GITA Executive Director\/SharedGeo<\/em><\/h4>\n<p>With the growth of daily commercial, higher resolution, optical and radar satellite systems to the explosion of centimeter level cameras on Unmanned Aerial Systems, the question is not can one get imagery but how can one handle it all?\u00a0 Petascale High Performance Computing is a major emerging technology system that has bypassed traditional remote sensing computer workstation approaches. This panel is designed to facilitate a broad discussion of where the industry is today and where it is going in the future.\u00a0 The panelists represent a cross section of academic, business, and government sectors.<\/p>\n<p><strong>Panelists:<\/strong><\/p>\n<ul>\n<li>Chris Doescher, <em>U.S. Geological Survey<\/em><\/li>\n<li>Lanny Faleide, <em>Satshot.com<\/em><\/li>\n<li>Mark Korver, <em>Amazon Web Services<\/em><\/li>\n<li>Paul Morin, <em>University of Minnesota, Polar Geospatial Center<\/em><\/li>\n<li>Joel Schlagel, <em>U.S. Army Corps of Engineers<\/em><\/li>\n<\/ul>\n<hr \/>\n<h4><strong>Land Change Monitoring, Assessment, and Projection (LCMAP)<\/strong><\/h4>\n<p>The U.S. Geological Survey (USGS) has a long land cover history, starting with the 1976 landmark <em>A Land Use and Land Cover Classification System for use with Remote Sensor Data <\/em>and including global land cover mapping and the ongoing production of the National Land Cover Database.\u00a0 While these past projects have had a significant impact, land cover data needs are changing due to the demand for increasingly innovative and timely land cover products needed to meet the community\u2019s insatiable appetite for science-quality geospatial land cover and land change data.\u00a0 Recent research on the use of the unprecedented depth of the Landsat archive has resulted in the potential to generate higher quality results that include additional land cover variables, more detailed legends, and more frequent land cover and land change geospatial and statistical information. To capitalize on new capabilities, the USGS is working closely with researchers from Boston University and Texas Tech University to implement the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative.\u00a0 LCMAP is envisioned as an end-to-end capability that uses the rich Landsat record to continuously track and characterize changes in land cover, use, and condition and translate such information into assessments of current and historical processes of cover and change. LCMAP aims to generate science-quality land cover and land change products from current and near-real time Landsat data. All available Landsat data for any given location are used to characterize land cover and change at any point across the full Landsat record and to detect and characterize land cover and land change as it occurs.\u00a0 Three special sessions will lay out the foundations of LCMAP, review the initial progress toward developing a new generation of land cover and land change products, and examine how these new products are addressing land change applications.<\/p>\n<hr \/>\n<h4><strong>LCMAP1: Foundations<\/strong><br \/>\nModerator:\u00a0 Curtis Woodcock, <em>Boston University<\/em><\/h4>\n<p><strong>Land Change Monitoring, Assessment, and Projection (LCMAP): expanding the understanding and management of land change<\/strong><br \/>\nTom Loveland, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Large area annual land cover maps derived from analysis ready Landsat time series data<\/strong><br \/>\nZhe Zhu, <em>Texas Tech University<\/em><\/p>\n<p><strong>Analysis Ready Data:\u00a0 Reconditioning the Landsat archive to support time series investigations<\/strong><br \/>\nJohn Dwyer,<em> U.S. Geological Survey<\/em><\/p>\n<p><strong>Collection of National land cover and land change reference data for a 30+ year time series accuracy assessment<\/strong><br \/>\nBruce Pengra, <em>Stinger Ghaffarian Technologies<\/em><\/p>\n<p><strong>Accuracy assessment and area estimation for annual land-cover monitoring<\/strong><br \/>\nSteve Stehman, <em>SUNY College of Environmental Science &amp; Forestry<\/em><\/p>\n<hr \/>\n<h4><strong>LCMAP2: Initial Results<br \/>\n<\/strong>Moderators: Jim Vogelmann, <em>U.S. Geological Survey<\/em><\/h4>\n<p><strong>A new generation of U.S. land-cover products<\/strong><br \/>\nChristopher Barber,<em> ASRC Federal Inuteq<\/em><\/p>\n<p><strong>A new generation of U.S. land change products<\/strong><br \/>\nJim Vogelmann,<em> U.S. Geological Survey<\/em><\/p>\n<p><strong>A new generation of land change products: implications for studying carbon stocks and fluxes in the Pacific Northwest<br \/>\n<\/strong>Ben Sleeter, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Deconstructing developed and forested areas in the Chesapeake Bay watershed<br \/>\n<\/strong>Peter Claggett, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Comparing Land Cover Trends Project\u2019s normalized annual change and LCMAP\u2019s annual change in the Puget Lowland Ecoregion<\/strong><br \/>\nRoger Auch, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Forest harvest patterns in the Cascade Mountains, Washington, 1985-2014<\/strong><br \/>\nChris Soulard, <em>U.S. Geological Survey<\/em><\/p>\n<hr \/>\n<h4><strong>LCMAP3: Time Series Research and Development<br \/>\n<\/strong>Moderator: Curtis Woodcock, <em>Boston University<\/em><\/h4>\n<p><strong>Exploring the Landsat archive using time series analysis<\/strong><br \/>\nCurtis Woodcock, <em>Boston University<\/em><\/p>\n<p><strong>Using a 30-year Landsat time series of Arctic and Boreal North America to investigate climate change impacts on disturbance, phenology, and productivity<\/strong><br \/>\nDamien Sulla-Menashe, <em>Boston University<\/em><\/p>\n<p><strong>Impact of climate variability on Landsat time series and implications for change monitoring<\/strong><br \/>\nChris Holden, <em>Boston University<\/em><\/p>\n<p><strong>Monitoring tropical forest degradation using time series analysis of Landsat data<\/strong><br \/>\nEric Bullock, <em>Boston University<\/em><\/p>\n<p><strong>Using time series and statistical inference methods to estimate unbiased land cover change areas in the Colombian Amazon<\/strong><br \/>\nPaulo Arevalo, <em>Boston University<\/em><\/p>\n<hr \/>\n<h4><strong>Landsat-derived Global Cropland Products @ 30-m (LGCP30)<\/strong><br \/>\nModerators: Prasad S. Thenkabail, <em>U.S. Geological Survey<\/em> and Russell G. Congalton, <em>University of New Hampshire<\/em><\/h4>\n<p>This special session will present and discuss the world\u2019s first Landsat-derived 30-m global cropland products @ 30-m (LGCP30). The focus will be on Landsat-derived global cropland extent @ 30-m (LGCE30) (https:\/\/croplands.org\/app\/map). This product maps the entire world\u2019s 1.8 billion hectares of croplands at 30-m resolution. The presentations in the session will discuss methods and approaches used in LGCE30. Cropland mapping algorithms (CMAs) including several machine learning algorithms (MLAs) were used on 2-3 years of 16-day Landsat data cubes to derive LGCE30 using Google Earth Engine (GEE) cloud computing. Cropland areas computed for every country in the world as well as cropland areas of sub-national administrative boundaries will be discussed and compared with conventional statistics. Exhaustive discussions on accuracies, errors, and uncertainties will take place- providing error matrices with overall-producer\u2019s, user\u2019s, and weighted overall accuracies of some 80+ zones of the world.<\/p>\n<p><strong>Global 30-m cropland extent map for the nominal year 2015: derived using Landsat-8 time-series data and machine learning algorithms computed on google earth engine cloud<\/strong><br \/>\nPrasad S. Thenkabail, U.S. Geological Survey<\/p>\n<p><strong>Evaluating the Performance of Various Sampling Strategies Used to Assess the Accuracy of Large Area Crop Maps<\/strong><br \/>\nRussell G. Congalton, University of New Hampshire<\/p>\n<p><strong>An Automated Crop Intensity Algorithm (ACIA) for global cropland intensity mapping at nominal 30-m using Landsat-8 and Sentinel-2 time-series data<br \/>\nand Google Earth Engine<\/strong><br \/>\nJun Xiong, Bay Area Environmental Research Institute (BAERI)<\/p>\n<p><strong>Mapping cropland extent and areas of Australia at 30-m resolution using multi-year time-series Landsat data and Random Forest machine learning algorithm through Google Earth Engine (GEE) Cloud Computing <\/strong><br \/>\nPardhasaradhi Teluguntla,\u00a0Bay Area Environmental Research Institute (BAERI)<\/p>\n<p><strong>Mapping Croplands of Southeast Asia, Japan, and North and South Korea using Landsat 30-m time-series, random forest algorithm<\/strong><br \/>\nAdam Oliphant, U.S. Geological Survey<\/p>\n<hr \/>\n<h4><\/h4>\n<h4><strong>Evolution of global land cover mapping: history and new developments<br \/>\n<\/strong>Moderators:\u00a0 Zhiliang Zhu and Brad Reed, <em>U.S. Geological Survey<\/em><\/h4>\n<p>Land cover maps of the world from paper media to digital formats have been produced over the millennium. These products featured prominently in the<br \/>\ndevelopment of the world we know today, and the research and development of global land cover maps are still a critical scientific endeavor in our continued effort to understand the world better. In the recent history, a variety of well-known global land cover maps or databases have been developed using advanced remote sensing methods, which having given the scientific community important lessons learned from the development of the products and findings from applications of the land cover information. This session is designed as a unique forum for scientists who have played a role in developing and advancing the field of global land cover mapping to review the history of the development, highlight recent achievements, discuss key issues and knowledge gaps still facing us today, and providing outlooks for future science needs. The audience will learn about global land cover mapping history, recent developments, theoretical treatments, methodology reviews, applications, and global collaborations.<\/p>\n<p><strong>Reflections on the IGBP DISCover Global Land Cover Project<\/strong><br \/>\nDr. Thomas Loveland,<em> U.S. Geological Survey<\/em><\/p>\n<p><strong>Landsat gone global, going global, still going\u2026<\/strong><br \/>\nAlan Belward, <em>Joint Research Centre, European Commission<\/em><\/p>\n<p><strong>A strategy for global land cover monitoring using Landsat and Sentinel 2<\/strong><br \/>\nMatthew C. Hansen, <em>University of Maryland<\/em><\/p>\n<p><strong>A brief and personal history of global land-cover data: Have we evolved from too little to too much?<\/strong><br \/>\nElaine Matthews, <em>National Aeronautics and Space Administration<\/em><\/p>\n<p><strong>Automated global land cover mapping \u2013 from-GLC-2 and a new mapping portal in support of flexible mapping with Landsat data<\/strong><br \/>\nPeng Gong, <em>Tsinghua University, China<\/em><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<hr \/>\n<h4><strong>Great Lakes Remote Sensing<br \/>\n<\/strong>Moderator: Brandon Krumwiede,\u00a0The Baldwin Group<\/h4>\n<p>The Great Lakes represents about 20% of the world\u2019s available surface freshwater.\u00a0 When the Polar ice caps and Greenland melt into the ocean, the percentage approaches 50% (assuming the volume does not change) making the Great Lakes a substantial global resource to manage for future generations.\u00a0 This session will highlight a few unique remote sensing approaches for the Great Lakes Basin which will more accurately characterize changes over time at a sub-meter scale using a variety of sensors.\u00a0 The long-term challenge is how to integrate approaches across borders to provide systematic daily multi-sensor views of the Great Lakes Basin.<\/p>\n<p><strong>An Overview of the Binational Great Lakes Wetlands Remote Sensing Project<br \/>\n<\/strong>Brian Huberty, <em>U.S. Fish &amp; Wildlife Service<\/em><\/p>\n<p><strong>High resolution Optical and Radar Mapping and Monitoring of Coastal Great Lakes Wetlands to Inform Wetland Management Decisions<br \/>\n<\/strong>Laura Bourgeau-Chavez, <em>Michigan Technological University<\/em><\/p>\n<p><strong>Creating high temporal frequency digital surface models in the Great Lakes Basin<br \/>\n<\/strong>James Klassen, <em>SharedGeo<\/em><\/p>\n<p><strong>Dynamic Watercourse Hydrography Updating in Minnesota\u2019s Lake Superior Coastal Watersheds<br \/>\n<\/strong>Jennifer Corcoran, <em>Minnesota Department of Natural Resources, Resource Assessment<\/em><\/p>\n<hr \/>\n<h4><strong>Landsat Archive, Product Plans, and Data Continuity<br \/>\n<\/strong>Moderators: Jennifer Lacey,\u00a0U.S. Geological Survey<\/h4>\n<p>Landsat represents the world\u2019s longest continuously acquired collection of space-based moderate-resolution land remote sensing data. The Landsat program has taken several actions to expand the USGS archive holdings, further the science use, and ensure Landsat data continuity. Through the Landsat Global Archive Consolidation Project and increased satellite acquisitions, archive holdings have reached over 7 million scenes. This special session includes five topics that provide an archive status, science data product status and plans, and future mission plans for continuing Landsat\u2019s irreplaceable record.<\/p>\n<p><strong>Ensuring Proper Storage for Earth Science Data Used for Decisions: The USGS Process to Certify Trusted Digital Repositories<\/strong><br \/>\nJohn Faundeen, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Landsat Archive Status and the Landsat Global Archive Consolidation<\/strong><br \/>\nKristi Kline, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Landsat Collections and Future Landsat Standard Product Plans<\/strong><br \/>\nBrian Sauer, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>Continuity and Improvements with Landsat 9<\/strong><br \/>\nJim Nelson,\u00a0<em>U.S. Geological Survey<\/em><\/p>\n<p><strong>An outlook for sustainable land imaging at the USGS Land Remote Sensing Program<\/strong><br \/>\nPeter Doucette, <em>U.S. Geological Survey<\/em><\/p>\n<hr \/>\n<h4><strong>Creating a Healthy Remote Sensing Education Pipeline: Moving from K-12 to University<br \/>\n<\/strong>Moderator:\u00a0 Lindi Quackenbush, <em>State University of New York College of Environmental Science and Forestry<\/em><\/h4>\n<p>The remote sensing field is growing and changing rapidly. \u00a0Deployment of novel sensors requires greater prerequisite knowledge and development of new processing methods. In order to ensure we have a well-trained workforce able to advance this field, we need to create a pipeline of students who can engage in advanced study in remote sensing. \u00a0There are a wide range of activities that can be used to facilitate development of interest and skills at an early level to support advanced undergraduate or graduate study and stimulate interest in remote sensing as both art and science. This session will bring together panelists from members of the AmericaView consortium to present their experiences in a range of pipeline topics including K-12 outreach, service learning, STEM literacy, and curriculum development.<\/p>\n<p><strong>Panelists:<\/strong><\/p>\n<ul>\n<li>Lindi Quackenbush, <em>State University of New York College of Environmental Science and Forestry<\/em><\/li>\n<li>Ken Boykin, <em>New Mexico State University<\/em><\/li>\n<li>James Campbell, <em>Virginia Tech<\/em><\/li>\n<li>Amber Imai-Hong, <em>Hawaii Space Grant Consortium, University of Hawaii at Manoa<\/em><\/li>\n<li>JB Sharma, <em>University of North Georgia<\/em><\/li>\n<li>Chandi Witharana, <em>University of Connecticut<\/em><\/li>\n<li>Brent Yantis, <em>University of Louisiana at Lafayette<\/em><\/li>\n<\/ul>\n<hr \/>\n<h4><strong>Calibration of Satellite Imagery<br \/>\n<\/strong>Moderator:\u00a0 Dennis Helder, <em>U.S. Geological Survey<\/em><\/h4>\n<p>Calibration of satellite imagery is the necessary first step before data users can extract useful, quantifiable information from the imagery.\u00a0 Thus, it is paramount that the calibration step achieve an accuracy and precision that significantly exceeds that required by the applications derived from satellite imagery.\u00a0 Calibration is normally divided into geometric calibration and radiometric calibration \u2013 essentially putting the pixels in the right place and giving them the right value.\u00a0 In this session both types of calibration will be addressed from a variety of perspectives.\u00a0 Status and improvements for calibration of various sensor types will be discussed, and insights will be given on new calibration approaches that promise improved accuracy for optical sensors in both the reflective and thermal regions.<\/p>\n<p><strong>Augmented Two Line Elements for Landsat Ephemeris Data<br \/>\n<\/strong>Mark Lubke, <em>Stinger Ghaffarian Technologies<\/em><\/p>\n<p><strong>Geometric Verification Algorithm (GVERIFY) to Validate the Accuracy of Landsat Multispectral Scanner and Thematic Mapper Data<\/strong><br \/>\nMark Lubke, <em>Stinger Ghaffarian Technologies<\/em><\/p>\n<p><strong>Lifetime Temporal Validation and Absolute Calibration of the EO-1 Hyperion Sensor<\/strong><br \/>\nXin Jing, <em>South Dakota State University<\/em><\/p>\n<p><strong>Compact Thermal Imager Calibrator (CTIC) for Landsat-like Missions<\/strong><br \/>\nMary Pagnutti, Innovative Imaging &amp; Research<\/p>\n<p><strong>Landsat-8 Thermal Infrared Sensor Radiometric Calibration Status<\/strong><br \/>\nJulia Barsi, <em>SSAI<\/em><\/p>\n<p><strong>Ground-based Artificial Light Source Radiometric Calibration of the VIIRS Day-Night Band High Gain Stage Early Results<\/strong><br \/>\nRobert E. Ryan, <em>Innovative Imaging &amp; Research<\/em><\/p>\n<hr \/>\n<h4><strong>National-scale Data Coordinated within the Multi-Resolution Land Characteristics Consortium (MRLC)<br \/>\n<\/strong>Moderator:\u00a0 Collin Homer<\/h4>\n<p>The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five National products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Program (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). This session will overview the current status and future plans of these MRL C products.<\/p>\n<p><strong>The National Land Cover Database, Delivering Land Cover Change Data for the Nation since 2001: History, Status and Future Plans<br \/>\n<\/strong>Collin Homer, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>NOAA\u2019s Focus on the Coasts: Bringing High Resolution Land Cover Mapping to the Multi-Resolution Land Characteristics Consortium<\/strong><br \/>\nNate Herold, <em>National Oceanic and Atmospheric Administration<\/em><\/p>\n<p><strong>10 Years of Annual National Land Cover Products \u2013 the Cropland Data Layer<\/strong><br \/>\nRick Mueller, <em>U.S. Department of Agriculture<\/em><\/p>\n<p><strong>NLCD Tree Canopy Cover Data Product<\/strong><br \/>\nGreg Liknes, <em>U.S. Forest Service<\/em><\/p>\n<p><strong>LANDFIRE Remap \u2013 Developing a New Baseline Product Suite<\/strong><br \/>\nBirgit Petersen,<em> U.S. Geological Survey<\/em><\/p>\n<hr \/>\n<h4><strong>National Land Cover Dataset (NLCD):\u00a0 Past, Present, and Future<br \/>\n<\/strong>Moderator: Collin Homer<\/h4>\n<p>This session will overview the design, products and status for NLCD 2016 and future programmatic plans for NLCD. NLCD 2016 products include land cover and urban imperviousness re-mapped for 2001-2016, tree canopy produced for 2011- 2016, and new 2016 products of percent shrub, bare ground and\u00a0 herbaceousness. NLCD 2016 is expected to be more accurate and comprehensive than any previous NLCD release, and will offer users an unprecedented set of land cover and land cover change products designed to continue, expand and advance NLCD applications.<\/p>\n<p><strong>NLCD Past and Present Product Comparison<\/strong><br \/>\nJon Dewitz, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>NLCD 2016 Landcover Design<\/strong><br \/>\nSuming Jin, <em>ASRC Federal InuTeq, Contractor to the U.S. Geological Survey<\/em><\/p>\n<p><strong>NLCD 2016 Imperviousness Product<\/strong><br \/>\nJon Dewitz, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>NLCD 2016 Shrub and Grass Products<\/strong><br \/>\nCollin Homer, <em>U.S. Geological Survey<\/em><\/p>\n<p><strong>NLCD Future Plans<\/strong><br \/>\nGeorge Xian, <em>U.S. Geological Survey<\/em><\/p>\n<p class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial; vertical-align: baseline;\">\n<\/div><\/div><\/div><\/div><\/div><\/section><section class=\"kc-elm kc-css-131798 kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-116600 kc_col-sm-12 kc_column kc_col-sm-12\"><div class=\"kc-col-container\"><div class=\"kc-elm kc-css-961519 kc_text_block\"><\/p>\n<h4><strong>Geospatial Munch and Meet!<\/strong><\/h4>\n<p>Come have lunch and meet industry leaders in geospatial technologies and sciences! The Early Career Professionals Council, Education and Professional Development Committee, Student Advisory Council, and the Corporate (Sustaining) Members Council have joined forces to bring a fun lunchtime experience focusing on getting to know your peers and learning more about what ASPRS has to offer. During the lunch hour, subject matter experts will give short talks about:<\/p>\n<ul>\n<li>Major advancements and innovations in GIS\/RS\/P science<\/li>\n<li>How to become an ASPRS Certified Professional<\/li>\n<li>Free and Paid Web Trainings<\/li>\n<li>Where to find reference\/study material<\/li>\n<li>AND MUCH MORE!!<\/li>\n<\/ul>\n<p>We look forward to joining you for lunch on Thursday. Come prepared to take notes on the presentation to win prizes!<\/p>\n<p class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial; vertical-align: baseline;\">\n<\/div><\/div><\/div><\/div><\/div><\/section><section class=\"kc-elm kc-css-44740 kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-78229 kc_col-sm-12 kc_column kc_col-sm-12\"><div class=\"kc-col-container\"><div class=\"kc-elm kc-css-367322 kc_text_block\"><\/p>\n<p class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial; vertical-align: baseline;\">\n<\/div><\/div><\/div><\/div><\/div><\/section><section class=\"kc-elm kc-css-852160 kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-324495 kc_col-sm-12 kc_column kc_col-sm-12\"><div class=\"kc-col-container\"><div class=\"kc-elm kc-css-350463 kc_text_block\"><\/p>\n<p class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial; vertical-align: baseline;\">\n<\/div><\/div><\/div><\/div><\/div><\/section><section class=\"kc-elm kc_row\"><div class=\"kc-row-container  kc-container\"><div class=\"kc-wrap-columns\"><div class=\"kc-elm kc-css-613328 kc_col-sm-12 kc_column kc_col-sm-12\"><div class=\"kc-col-container\"><div class=\"kc-elm kc_text_block\"><\/p>\n<p>\n<\/div><\/div><\/div><\/div><\/div><\/section><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":624,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19,1],"tags":[],"class_list":["post-1256","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured-home","category-uncategorized"],"_links":{"self":[{"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/posts\/1256","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/comments?post=1256"}],"version-history":[{"count":24,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/posts\/1256\/revisions"}],"predecessor-version":[{"id":1301,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/posts\/1256\/revisions\/1301"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/media\/624"}],"wp:attachment":[{"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/media?parent=1256"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/categories?post=1256"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/pecora.asprs.org\/pecora20\/wp-json\/wp\/v2\/tags?post=1256"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}