2013-03-31 NRMI: NATURAL RESOURCE MONITORING ITEMS OF INTEREST
This Issue: Detecting and Monitoring, Informal Settlements, Favelas, and Slums (Part 4 of 4) and Some Other Good Things
DETECTING AND MONITORING, INFORMAL SETTLEMENTS, FAVELAS, AND SLUMS (Part 4 of 4) – Last November, a list member asked, “Could some of you lend some assistance by identifying some OSINT (Open Source Intelligence) sources that can be used to detect and monitor the presence of slum/informal settlements/favelas, development? Any information you provide will be much appreciated.” Here are some sites that may be of interest:
Parbhoo, Chetna. 2009, An Ontology-driven Sensor Web Application for Detecting and Classifying Informal Settlements. 328 p. Book listing.
Parham, Ded. 2012. The segregated classes: spatial and social relationships in slums. 19 p.
Paudyal, Dev Raj; McDougall, Kevin. 2010. Spatial Data Infrastructure for Pro-poor Land Management. 11 p.
Pereira, Julio Roberto. 2011. Targeting deprivation through qualitative and quantitative indicators. Case study of Kisumu Kenya. Thesis 86 p.
Potsiou, Chryssy. 2010. Rapid Urbanization and Mega Cities: The Need for Spatial Information Management. Research study by FIG Commission 3. 91 p.
Rhinane, Hassan et al.2011. Detecting Slums from SPOT Data in Casablanca Morocco Using an Object Based Approach. Journal of Geographic Information System 3, 217-224.
Schilderman, Theo. 2002. Strengthening the knowledge and information systems of the urban poor. DFID. 53 p.
Shah, Nilopa. 2012. Characterizing Slums and Slum-Dwellers: Exploring Household-level Indonesian Data. 37 p.
Shamsuddoha, Md; Chowdhury, Rezaul Karim. 2009. Climate Change Induced Forced Migrants: in need of dignified recognition under a new protocol. 10 p.
Shekhar, Sulochana. 2012. Detecting Slums from Quick Bird Data in Pune using an Object Oriented Approach. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8
Shekhar, Sulochana. 2012. Modeling the probably growth of slums by using Geoinformatics. Indian J. Innovations Dev.1(8): 11 p.
Sietchiping, Remy. 2004, A Geographic Information Systems and Cellular Automata-Based Model of Informal Settlement Growth. Submitted in total fulfillment of the requirements of the degree of Doctor of Philosophy. 272 p.
Silveira, Marcelo Teixeira. 2012. Building 3D Detection and Extraction in Informal Settlement Areas. Abstract.
Sobhlan, Zafar. 2008. Out of place, out of time.
Stasolla, M.;Gamba, P. 2007. Exploiting spatial patterns for informal settlement detection in arid environments using optical spaceborne data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36 (3/W49A).
Stefanidis, Anthony et al. 2012. Social Media and the Emergence of Open-Source Geospatial Intelligence. 18 p.
Stellmacher, Glen.L. 2011. Mapping Kibera: New Strategies for Mapping and Improving the Slum. ARCH 442 Middle East & Africa Seminar. Final Independent Research Report. 22 p.
Sur, Ujjwal et al.2004? Identification / Mapping of Slum Environment using IKONOS Satellite Data: A Case Study of Dehradun, India. 4 p.
Syaiful, Achmad; Rahmy, Widyastri Atsary n.d. Slum Open Source Database Network. Arte-Polis 3 International Conference - Creative Collaboration and the Making of Place. Abstract.
Thomson, Curtis N. 1998? Remote Sensing of Informal Housing Settlements in Metropolitan Bangkok. 18 p.
Truscello, Ben. N.d.. Mapping Africa’s Largest Slum.
Tsai, Yu Hsin et al. 2011. Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery. Remote Sens. 3, 2707-2726.
Turkstra, Jan; Raithelhuber, Martin. 2005. Urban Slum Mentioning. 13 p.
UN-Habitat. 2006. State of the World’s Cities 2006/7. The Millennium Urban Sustainability: 30 Years of Shaping the Habitat Agenda. 108 p.
UN-HABITAT.2002. Expert Group Meeting on Urban Indicators - Secure Tenure, Slums and Global Sample of Cities 33 p.
UNODC. 2011. Introductory Handbook on Policing Urban Space. Criminal Justice Handbook Series. 118 p.
UNPD. 2008. An overview of urbanization, internal migration, population distribution and development in the world. UN/POP/EGM-URB/2008/01 . 34 p.
Veljanovski, Tatjana. et al.2012. Object-Based Image Analysis of VHR Satellite Imagery for Population Estimation in Informal Settlement Kibera-Nairobi, Kenya. 29 p.
Verma, Ravindra Kumar et al. n.d.Application of remote sensing and GIS technique for efficient urban planning in India. 23 p.
Weber, Christiane. 2008? From slums detection to slum definition…Urban remote sensing: recent technological and methodological developments 63 p.
Young, Gina. 2010. Socioeconomic analysis of informal settlement growth in Dar es Salamm: the concept for an agent based model. Thesis. 139 p.
SOME OTHER PUBLICATIONS/URLS OF INTEREST
Foster, Aylson. 2013.Declining Forests In The Eastern United States As Seen From Space. National Geographic News Watch.
García, Mauricio Labrador et al. 2013.Satellites pour la Télédétection appliquée à la gestion territoriale. Project SATELMAC, Programme de Coopération Transnational Madère – Açores - Canaries -2007-2013 (PCT-MAC).65 p. From Artur Gil, Applied GIS RS List.
Glenn, N.F. et al. 2010. Errors in LiDAR-derived shrub height and crown area on sloped terrain, Journal of Arid Environments. 6 p.
Hossler, Katie; Bouchard, Virginie. 2010. Soil development and establishment of carbon-based properties in created freshwater marshes. Ecological Applications 20:539–553.
Junttila, Virpi et al. 2011.Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory. Forest Ecology and Management. 292:75-85
Kim, Yunsuk et al 2009. Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data. Remote Sensing of Environment. 113: 2499-2510.
Köhl, Michael et al. 2011. Implications of sampling design and sample size for national carbon accounting systems. Carbon Balance and Management.6:10
Lacher, T.E., et al.. 2012. The IUCN global assessments: partnerships, collaboration and data sharing for biodiversity science and policy. Conserv. Lett. 5(5):327-333. Abstract.
Li, Yuzhen. 2009. Towards Small-footprint Airborne LiDAR-assisted Large Scale Operational Forest Inventory - A case study of integrating LiDAR data into Forest Inventory and Analysis in Kenai Peninsula, Alaska. Dissertation. University of Washington. 118 p.
Lindenmayer, D.B., et al. 2012. Value of long-term ecological studies. Austral Ecol. 37(7):745-757. Abstract.
Lloyd, Colin R; et al.. 2013 Providing low-budget estimations of carbon sequestration and greenhouse gas emissions in agricultural wetlands Environ. Res. Lett. 8 015010 (13pp).
Lõhmus, P., et al. 2012. Old selectively cut forests can host rich lichen communities - lessons from an exhaustive field survey. Nova Hedwigia 95(3-4):493-515. Abstract.
Marcott, Shaun A. et al. 2013. A Reconstruction of Regional and Global Temperature for the Past 11,300 Years. Abstract.
Sumberg, J. et al. 2013. Why agronomy in the developing world has become contentious. Agriculture and Human Values 30: 71-83. From Sebastião Kengen, Brazil.
Wang, Le; Wu, Changshan. 2010. Population estimation using remote sensing and GIS technologies. Int. J. Remote Sensing 31(21): 5569-5570. Abstract.
World Bank. 2011. Guide to climate change adaptation in cities.106 p.
KEEPING UP-TO-DATE – PRODUCTS, NEWSLETTERS, EMAIL LISTS, JOURNALS. See also http://botany.si.edu/puhttps://www.createspace.com/3489254bs/bcn/links.cfm, http://scholar.google.com/, and Directory of Open Access Journals. http://www.doaj.org/doaj?func=findJournals.
UNEDP's Environmental Data Explorer - UNEDP's Environmental Data Explorer is the authoritative source for data sets used by UNEP and its partners in the Global Environment Outlook (GEO) report and other integrated environment assessments. Its online database holds more than 500 different variables, as national, subregional, regional and global statistics or as geospatial data sets (maps), covering themes like Freshwater, Population, Forests, Emissions, Climate, Disasters, Health and GDP. Display them on-the-fly as maps, graphs, data tables or download the data in different formats. For full details see: http://free-gis-data.blogspot.com/2013/02/unedp-environmental-data-explorer.html. From Shaan W., IFL.
8-9 May 2013. Persuasive Communication and Presentation of Environmental Projects. Sacramento, California, USA. NWETC Course. This course is also available on other dates and at different locations See https://www.nwetc.org/course-catalog/com-410-may-8-9-2013
MOVING AHEAD – OPPORTUNITIES – See also: Scholarships-Positions, Forestry, Arboriculture, Agriculture, Agronomy & Natural Resource Management Jobs at http://www.earthworks-jobs.com/forest.htm, Riley Guide to Agriculture, Forestry, & Farming Jobs http://www.rileyguide.com/agric.html, Finding Your Dream Job in Natural Resources http://www.cyber-sierra.com/nrjobs/, http://www.nature.com/naturejobs/index.html The Job Seekers Guide for International and Environmental Careers http://timresch.net/ejobs/index.htm and Scholarship Listing http://www.scholarshiplisting.com/.
Call for Papers: PE&RS special issue on remote sensing of soils for environmental assessment & management - A special call for papers has been announced by the American Society for Photogrammetry and Remote Sensing for the April 2014 issue of Photogrammetric Engineering & Remote Sensing entitled, “Remote Sensing of Soils for Environmental Assessment and Management.” Imaging systems integrated with complex analytical methods will revolutionize the way we inventory and manage soil resources across a wide range of scientific disciplines and application domains. This special issue will highlight systems and methods that directly benefit environmental professionals who focus on imaging and geospatial information for improved understanding, management, and monitoring of soil resources. http://www.asprs.org/PE-RS-Submissions-Policy-and-Guidelines/Call-for-Papers-Remote-Sensing-of-Soils-for-Environmental-Assessment-and-Management.html. From Artur Gil, Applied GIS RS List.
OR/WA/CA USFS Forest Inventory and Analysis temporary seasonal positions. The Pacific Northwest Research Station's Resource Monitoring and Assessment Program, Forest Inventory and Analysis (FIA) is conducting outreach for at least two seasonal temporary (not to exceed 1039 hours) Data Collection Field Crew Members GS-462-5 or 6 (highest priority location of hires will be Klamath Falls, Oregon and La Grande, Oregon). We will be filling these positions through national Open Continuous Recruitment (OCR) announcements which are currently open on the USAJOBS website. If you are interested in being considered for this opportunity you must apply online through USAJOBS. Interested parties can apply immediately! - https://www.usajobs.gov ANNOUNCEMENT # TEMPOCR-462-5-RES-DT https://www.usajobs.gov/GetJob/ViewDetails/340074400 and TEMPOCR-0462-6-RES-DT https://www.usajobs.gov/GetJob/ViewDetails/339917400 For more information about the vacancies and the duties of the job please contact: Jane Terzibashian firstname.lastname@example.org. From Shirley Cromwell, USFS.
NEXT ISSUE – LiDAR and Forest Inventory (Part 1 of 2)
Pay It Forward – Cheers, Gyde
-- H. Gyde Lund Forest Information Services 6238 Settlers Trail Place Gainesville, VA 20155-1374 USA Tel: +1-703-743-1755 Email: gyde<at>comcast.net URL: http://www.forestinfoservices.com CV: http://home.comcast.net/~gyde/cv.html. Publications: http://home.comcast.net/~gyde/lundpub.htm. Skype: forestgyde