Africa Land Cover Characteristics Data Base Version 2.0
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Land Cover Austin, TX This Enviroatlas Map Shows Land Cover for the Austin, TX Area at High Spatial Resolution (1-Meter Pixels)
• Austin, TX • New Haven, CT • Baltimore, MD • New York, NY • Birmingham, AL • Paterson, NJ • Brownsville, TX • Philadelphia, PA • Chicago, IL • Phoenix, AZ • Cleveland, OH • Pittsburgh, PA • Des Moines, IA • Portland, ME • Durham, NC • Portland, OR • Fresno, CA • Salt Lake City, UT • Green Bay, WI • Sonoma County, CA • Los Angeles, CA • St Louis, MO • Memphis, TN • Tampa, FL • Milwaukee, WI • Virginia Beach, VA • Minneapolis, MN • Washington, DC • New Bedford, MA • Woodbine, IA Meter Scale Urban Land Cover Austin, TX This EnviroAtlas map shows land cover for the Austin, TX area at high spatial resolution (1-meter pixels). The land cover classes are Water, Impervious Surface, Soil and Barren, Trees and Forest, Grass and Herbaceous, and Agriculture.1 Why is high resolution land cover important? Land cover data present a “birds-eye” view that can help identify important features, patterns and relationships in the landscape. The National Land Cover Dataset (NLCD)2 provides land cover for the entire contiguous U.S. at 30- meter pixel resolution. However, for some analyses, the density and heterogeneity of an urban landscape requires higher resolution land cover data. Meter Scale Urban Land Cover (MULC) data were developed to fulfill that need. In comparison, there are 900 MULC pixels for every one NLCD pixel. Anticipated users of MULC include city and regional planners, water authorities, wildlife and natural resource Figure 2: MULC for Austin, managers, public health officials, citizens, teachers, and TX. students. Potential applications of these data include the How can I use this information? assessment of wildlife corridors and riparian buffers, This data layer can be used alone or combined visually and stormwater management, urban heat island mitigation, access analytically with other spatial data layers. -
Large Scale High-Resolution Land Cover Mapping with Multi-Resolution Data
Large Scale High-Resolution Land Cover Mapping with Multi-Resolution Data Caleb Robinson Le Hou Kolya Malkin Georgia Institute of Technology Stony Brook University Yale University Rachel Soobitsky Jacob Czawlytko Bistra Dilkina Chesapeake Conservancy Chesapeake Conservancy University of Southern California Nebojsa Jojic∗ Microsoft Research Abstract uses include informing agricultural best management practices, monitoring forest change over time [10] and measuring urban In this paper we propose multi-resolution data fusion meth- sprawl [31]. However, land cover maps quickly fall out of ods for deep learning-based high-resolution land cover map- date and must be updated as construction, erosion, and other ping from aerial imagery. The land cover mapping problem, at processes act on the landscape. country-level scales, is challenging for common deep learning In this work we identify the challenges in automatic methods due to the scarcity of high-resolution labels, as well large-scale high-resolution land cover mapping and de- as variation in geography and quality of input images. On the velop methods to overcome them. As an application of other hand, multiple satellite imagery and low-resolution ground our methods, we produce the first high-resolution (1m) truth label sources are widely available, and can be used to land cover map of the contiguous United States. We have improve model training efforts. Our methods include: introduc- released code used for training and testing our models at ing low-resolution satellite data to smooth quality differences https://github.com/calebrob6/land-cover. in high-resolution input, exploiting low-resolution labels with a dual loss function, and pairing scarce high-resolution labels Scale and cost of existing data: Manual and semi-manual with inputs from several points in time. -
Tropical Deciduous Forests and Savannas
2/1/17 Tropical Coastal Communities Relationships to other tropical forest systems — specialized swamp forests: Tropical Coastal Forests Mangrove and beach forests § confined to tropical and & subtropical zones at the interface Tropical Deciduous Forests of terrestrial and saltwater Mangrove Forests Mangrove Forests § confined to tropical and subtropical § stilt roots - support ocean tidal zones § water temperature must exceed 75° F or 24° C in warmest month § unique adaptations to harsh Queensland, Australia environment - convergent Rhizophora mangle - red mangrove Moluccas Venezuela 1 2/1/17 Mangrove Forests Mangrove Forests § stilt roots - support § stilt roots - support § pneumatophores - erect roots for § pneumatophores - erect roots for O2 exchange O2 exchange § salt glands - excretion § salt glands - excretion § viviparous seedlings Rhizophora mangle - red mangrove Rhizophora mangle - red mangrove Xylocarpus (Meliaceae) & Rhizophora Mangrove Forests Mangrove Forests § 80 species in 30 genera (20 § 80 species in 30 genera (20 families) families) § 60 species OW& 20 NW § 60 species OW& 20 NW (Rhizophoraceae - red mangrove - Avicennia - black mangrove; inner Avicennia nitida (black mangrove, most common in Neotropics) boundary of red mangrove, better Acanthaceae) drained Rhizophora mangle - red mangrove Xylocarpus (Meliaceae) & Rhizophora 2 2/1/17 Mangrove Forests § 80 species in 30 genera (20 families) § 60 species OW& 20 NW Four mangrove families in one Neotropical mangrove community Avicennia - Rhizophora - Acanthanceae Rhizophoraceae -
Neotropical Rainforest Restoration: Comparing Passive, Plantation and Nucleation Approaches
UC Riverside UC Riverside Previously Published Works Title Neotropical rainforest restoration: comparing passive, plantation and nucleation approaches Permalink https://escholarship.org/uc/item/4hf3v06s Journal BIODIVERSITY AND CONSERVATION, 25(11) ISSN 0960-3115 Authors Bechara, Fernando C Dickens, Sara Jo Farrer, Emily C et al. Publication Date 2016-10-01 DOI 10.1007/s10531-016-1186-7 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Biodivers Conserv DOI 10.1007/s10531-016-1186-7 REVIEW PAPER Neotropical rainforest restoration: comparing passive, plantation and nucleation approaches 1,2 2 2 Fernando C. Bechara • Sara Jo Dickens • Emily C. Farrer • 2,3 2 2,4 Loralee Larios • Erica N. Spotswood • Pierre Mariotte • Katharine N. Suding2,5 Received: 17 April 2016 / Revised: 5 June 2016 / Accepted: 25 July 2016 Ó Springer Science+Business Media Dordrecht 2016 Abstract Neotropical rainforests are global biodiversity hotspots and are challenging to restore. A core part of this challenge is the very long recovery trajectory of the system: recovery of structure can take 20–190 years, species composition 60–500 years, and reestablishment of rare/endemic species thousands of years. Passive recovery may be fraught with instances of arrested succession, disclimax or emergence of novel ecosystems. In these cases, active restoration methods are essential to speed recovery and set a desired restoration trajectory. Tree plantation is the most common active approach to reestablish a high density of native tree species and facilitate understory regeneration. While this approach may speed the successional trajectory, it may not achieve, and possibly inhibit, a long-term restoration trajectory towards the high species diversity characteristic of these forests. -
Forest--Savanna Transition Zones
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Biogeosciences Discuss., 11, 4591–4636, 2014 Open Access www.biogeosciences-discuss.net/11/4591/2014/ Biogeosciences BGD doi:10.5194/bgd-11-4591-2014 Discussions © Author(s) 2014. CC Attribution 3.0 License. 11, 4591–4636, 2014 This discussion paper is/has been under review for the journal Biogeosciences (BG). Forest–savanna Please refer to the corresponding final paper in BG if available. transition zones Structural, physiognomic and E. M. Veenendaal et al. aboveground biomass variation in Title Page savanna-forest transition zones on three Abstract Introduction continents. How different are Conclusions References co-occurring savanna and forest Tables Figures formations? J I E. M. Veenendaal1, M. Torello-Raventos2, T. R. Feldpausch3, T. F. Domingues4, J I 5 3 2,25 3,6 7 8 F. Gerard , F. Schrodt , G. Saiz , C. A. Quesada , G. Djagbletey , A. Ford , Back Close J. Kemp9, B. S. Marimon10, B. H. Marimon-Junior10, E. Lenza10, J. A. Ratter11, L. Maracahipes10, D. Sasaki12, B. Sonké13, L. Zapfack13, D. Villarroel14, Full Screen / Esc M. Schwarz15, F. Yoko Ishida6,16, M. Gilpin3, G. B. Nardoto17, K. Affum-Baffoe18, L. Arroyo14, K. Bloomfield3, G. Ceca1, H. Compaore19, K. Davies2, A. Diallo20, Printer-friendly Version N. M. Fyllas3, J. Gignoux21, F. Hien20, M. Johnson3, E. Mougin22, P. Hiernaux22, Interactive Discussion T. Killeen14,23, D. Metcalfe8, H. S. Miranda17, M. Steininger24, K. Sykora1, M. I. Bird2, J. Grace4, S. Lewis3,26, O. L. Phillips3, and J. Lloyd16,27 4591 -
Mapping Vegetation Types in a Savanna Ecosystem in Namibia: Concepts for Integrated Land Cover Assessments
Mapping Vegetation Types in a Savanna Ecosystem in Namibia: Concepts for Integrated Land Cover Assessments Christian H ttich Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Friedrich-Schiller-Universität Jena Mapping Vegetation Types in a Savanna Ecosystem in Namibia: Concepts for Integrated Land Cover Assessments Dissertation zur Erlangung des akademischen Grades doctor rerum naturalium (Dr. rer. nat.) vorgelegt dem Rat der Chemisch-Geowissenschaftlichen Fakult t der Friedrich-Schiller-Universit t Jena von Dipl.-Geogr. Christian H&ttich geboren am 12. Mai 19,9 in Jena 1 2 Gutachter- 1. .rof. Dr. Christiane Schmullius 2. .rof. Dr. Stefan Dech (Universit t /&rzburg) 0ag der 1ffentlichen 2erteidigung- 29.04.2011 3 Acknowledgements I _____________________________________________________________________________________ Ackno ledgements 0his dissertation would not have been possible without the help of a large number of people. First of all I want to thank the scientific committee of this work- .rof. Dr. Christiane Schmullius and .rof. Dr. Stefan Dech for their always present motivation and fruitful discussions. I am e9tremely grateful to my scientific mentor .rof. Dr. Martin Herold, for his never-ending receptiveness to numerous questions from my side, for his clear guidance for the definition of the main research issues, the frequent feedback regarding the structure and content of my research, and for his contagious enthusiasm for remote sensing of the environment. Acknowledgements are given to the former remote sensing team of “BIO0A S&d?- Dr. Ursula Gessner (DFD-DLR), Dr. Rene Colditz (COAABIO, Me9ico), Manfred Beil (DFD-DLR), and Dr. Michael Schmidt (COAABIO, Me9ico) for e9tremely fruitful discussions, criticism, and technical support during all phases of the dissertation. -
Ecological Land Cover and Natural Resources Inventory for the Kansas City Region
Ecological Land Cover and Natural Resources Inventory for the Kansas City Region 2. Ecological Land Cover Assessment and Natural Resource Inventory Methods This section describes the general approach and methodology used to complete the ecological classification and inventory for the Kansas City region. Applied Ecological Services, Inc. (AES) used the following tasks to complete the ecological survey and inventory, which are described in detail in the following sub-sections: 1. Data Assembly and Mapping: digital information from several government sources was used to establish baseline information about land cover in the region. 2. Field Reconnaissance: The digital information was validated and/or refined through field inspections and verifications. 3. Ecological Land Cover Classification Development: Using data from the data assembly and subsequent field reconnaissance, AES created an ecological classification representing existing natural resources in the region, a GIS-based information database, and a regional map of ecological land cover. 4. Data Extrapolation and Second Field Verification: The ecological classification involved an iterative process in which initial data were assembled, evaluated in the field, revised, and then re-evaluated in the field a second time. Final data were assembled after the second field reconnaissance, evaluated, and incorporated into the GIS program and the regional land cover map. Details of the methodology of this process are provided in Appendix A. This program was completed between June 2003 and June 2004. 2.1. Data Assembly and Base Mapping The initial phase of the ecological classification and inventory work involved data identification and assembly; the synthesis of data and creation of GIS base maps and graphics; and solicitation of input from local experts on the type and condition of natural resources in the Kansas City metropolitan area. -
Natural Resources Inventory
Natural Resources Inventory Columbia Metropolitan Planning Area Review Draft (10-1-10) NATURAL RESOURCES INVENTORY Review Draft (10-1-10) City of Columbia, Missouri October 1, 2010 - Blank - Preface for Review Document The NRI area covers the Metropolitan Planning Area defined by the Columbia Area Transportation Study Organization (CATSO), which is the local metropolitan planning organization. The information contained in the Natural Resources Inventory document has been compiled from a host of public sources. The primary data focus of the NRI has been on land cover and tree canopy, which are the product of the classification work completed by the University of Missouri Geographic Resource Center using 2007 imagery acquired for this project by the City of Columbia. The NRI uses the area’s watersheds as the geographic basis for the data inventory. Landscape features cataloged include slopes, streams, soils, and vegetation. The impacts of regulations that manage the landscape and natural resources have been cataloged; including the characteristics of the built environment and the relationship to undeveloped property. Planning Level of Detail NRI data is designed to support planning and policy level analysis. Not all the geographic data created for the Natural Resources Inventory can be used for accurate parcel level mapping. The goal is to produce seamless datasets with a spatial quality to support parcel level mapping to apply NRI data to identify the individual property impacts. There are limitations to the data that need to be made clear to avoid misinterpretations. Stormwater Buffers: The buffer data used in the NRI are estimates based upon the stream centerlines, not the high water mark specified in City and County stormwater regulations. -
Changes in Global Terrestrial Live Biomass Over the 21St Century
advances.sciencemag.org/cgi/content/full/7/27/eabe9829/DC1 Supplementary Materials for Changes in global terrestrial live biomass over the 21st century Liang Xu, Sassan S. Saatchi*, Yan Yang, Yifan Yu, Julia Pongratz, A. Anthony Bloom, Kevin Bowman, John Worden, Junjie Liu, Yi Yin, Grant Domke, Ronald E. McRoberts, Christopher Woodall, Gert-Jan Nabuurs, Sergio de-Miguel, Michael Keller, Nancy Harris, Sean Maxwell, David Schimel *Corresponding author. Email: [email protected] Published 2 July 2021, Sci. Adv. 7, eabe9829 (2021) DOI: 10.1126/sciadv.abe9829 This PDF file includes: Figs. S1 to S10 Tables S1 to S7 Supplementary Materials Supplementary Figures & Tables Fig. S1. Flow chart of procedures estimating global live biomass carbon stocks. It includes the organizations of input data forming training samples for regional and spatio-temporal models, spatially continuous annual remote sensing data sets as predictor layers, the models used, and the final output products at 10km resolution. Fig. S2. Ecoregion maps used in this study. (A) Regional land cover types by separating the biomes based on continents; (B) Combined land cover types aggregated to a total of 5 vegetation classes globally. Maps were derived from the MODIS IGBP (International Geosphere-Biosphere Programme) land cover product. We selected the data in 2001 as the base map for the inclusion of forest clearing and fire events in their original classes. Detailed description of each class can be found in Table S1. Fig. S3. Regional carbon stock series from 2000 to 2019. The land cover classes were derived from MODIS LC product (Fig. S2) and divided continentally to show regional effects. -
The Tropical Rainforest Grades K-2 and 3-5 Through the Activities Provided, Children Are Introduced to the Components of the Rainforest
Activity The Tropical Packet Rainforest Table Introduction to the Teacher Activity Packets 3 of Contents Meeting the Needs of the NYC Teacher 6 Introduction to the Rainforest 8 Concepts, Objectives and Vocabulary for Grades K - 2 10 Concepts, Objectives and Vocabulary for Grades 3 - 5 12 Pre-trip Activities: Grades K - 2 1. What is a Rainforest? 14 2. What Does a Rainforest Look Like? 16 3. What Lives in a Rainforest? 19 4. Endangered Animals of the Rainforests 22 5. Rainforest Products 30 6. Fruit from the Rainforest 33 Grades 3 - 5 7. Where are Rainforests Found? 35 8. Life in the Layers of the Rainforest 39 9. People of the Rainforest 43 10. The Costs of Extinction 47 11. How Fast is Extinction Happening? 49 12. Saving the Rainforest 53 13. Bromeliads are Products of the Rainforest 55 What to do after your trip to the Zoo 57 References for the Rainforest 59 Feedback Questionnaire 60 Funding for Activity Packets provided by: • SI Bank and Trust Community Foundation • In memory of Norbert H. Leeseberg 1 STATEN ISLAND ZOO Acknowledgements Thanks to the following people involved in the two - year development of the Teacher Guides and Student Activity Packets. These packets are a symbol of the Staten Island Zoological Society’s dedication to provide science education to the children of the New York City and surrounding area. Clay Wollney............Curriculum Writer Harry Strano III....... Director of Education, Editor Karin Jakubowski... Former Assistant Director of Education, Editor Lorraine Austin........Former Director of Education, Editor Ellen Palm...............Graphics Coordinator, Designer and Illustrator Wendy Jackelow......Illustrator We are grateful to Vincent N. -
CHAPTER 13 Importance of Land Cover and Biophysical Data In
CHAPTER 13 Importance of Land Cover and Biophysical Data in Landscape-Based Environmental Assessments K. Bruce Jones, U.S. Geological Survey, Biology Discipline, Reston, Virginia USA ABSTRACT Land cover and other digital biophysical data play important roles in environmental assessments rela- tive to a large number of environmental themes and issues. These data have become especially impor- tant given the pace and extent of land cover change across the globe and world-wide concern for issues such as global climate change. However, land cover and digital biophysical data by themselves are not sufficient for broad-scale environmental assessments. These data must be combined with in situ data collected from comprehensive research and monitoring programs to derive and interpret broad-scale environmental condition. I summarize important uses of land cover and other biophysical data in en- vironmental assessments and emphasize the importance of spatially explicit integration of these data to address critical environmental issues. I also discuss the importance of comprehensive, regional and national in-situ data in the development of landscape indicators and models and the need to maintain and develop new in-situ monitoring programs. Key words: Land cover, environmental assessments, landscape indicators, biophysical data, multi- scale analysis INTRODUCTION Spatially continuous digital databases on land cover and other important biophysical attributes (soils, elevation, topography, etc.) have become increasingly available via websites and data portals. Coupled with advances in computer technology, including processing speed, data capacity, software development (e.g., geographic information systems and statistical programs), and distributed network capabilities, this availability now makes it possible to conduct environmental assessments at multiple scales over relatively large geographic areas (Wascher 2005, Jones et al. -
Classification and Description of World Formation Types
United States Department of Agriculture Classification and Description of World Formation Types Don Faber-Langendoen, Todd Keeler-Wolf, Del Meidinger, Carmen Josse, Alan Weakley, David Tart, Gonzalo Navarro, Bruce Hoagland, Serguei Ponomarenko, Gene Fults, Eileen Helmer Forest Rocky Mountain General Technical Service Research Station Report RMRS-GTR-346 August 2016 Faber-Langendoen, D.; Keeler-Wolf, T.; Meidinger, D.; Josse, C.; Weakley, A.; Tart, D.; Navarro, G.; Hoagland, B.; Ponomarenko, S.; Fults, G.; Helmer, E. 2016. Classification and description of world formation types. Gen. Tech. Rep. RMRS-GTR-346. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 222 p. Abstract An ecological vegetation classification approach has been developed in which a combi- nation of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types. This approach can help support international, national, and subnational classifica- tion efforts. The classification structure was largely developed by the Hierarchy Revisions Working Group (HRWG), which contained members from across the Americas. The HRWG was authorized by the U.S. Federal Geographic Data Committee (FGDC) to devel- op a revised global vegetation classification to replace the earlier versions of the structure that guided the U.S. National Vegetation Classification and International Vegetation Classification, which formerly relied on the UNESCO (1973) global classification (see FGDC 1997; Grossman and others 1998). This document summarizes the develop- ment of the upper formation levels. We first describe the history of the Hierarchy Revisions Working Group and discuss the three main parameters that guide the clas- sification—it focuses on vegetated parts of the globe, on existing vegetation, and includes (but distinguishes) both cultural and natural vegetation for which parallel hierarchies are provided.