Sunday, 21 July 2013

[ANFES] 2013-07-21 NRMI: This Issue: Terrestrial LiDAR and Urban Trees and Some Other Good Things


This Issue: Terrestrial LiDAR and Urban Trees and Some Other Good Things

BUT FIRST, WON’T YOU PLEASE HELP? Legacy Regression Programs Sought - Dr. Tim Gregoire, Yale University, writes. In 1958, Lew Grosenbaugh published a USDA Forest Service Occasional Paper 158 with the title "The elusive formula of best fit: a comprehensive new machine program". It was advertising a new service: a regression program written in Fortran to run on the IBM 704 Electronic Data Processing Machine. It would fit all possible regressions and could accommodate up to 9 "independent" variables and a maximum of 500 observations. This was superseded in 1967 by REX--Fortran-4 System, that Lew wrote about in USDA Forest Service Research paper PSW-44. Then concurrent with his ongoing development of 3P sampling, he developed "STX--Fortran-4 Program for estimates of tree populations from 3P sample-tree-measurements". An early reference is USDA Forest Service Research Paper PSW-13, Revised, published in 1967. Lew would famously, or infamously, install STX on university mainframes in person and without the aid of the local computer technicians. I believe Harold Burkhart recalls when he did so at Virginia Tech. Later, Jim Space put out STXMOD. I wonder whether there are any legacy versions of these programs still around. If you can assist, please contact Tim at

TERRESTRIAL LIDAR AND URBAN TREES. Luiz Octavio de Lima Pedreira was seeking data about the use of land-based LIDAR scanning to determine the volume of standing trees, with emphasis in street trees. Here are some sites that may be of interest. If you know of others, please contact Luiz at

Changok, Lim. 2007. Estimation of urban tree crown volume based on object-oriented approach and LIDAR data. Thesis. 87 p.

Garrity, Steven R. et al. 2012. Estimating plot-level tree structure in a deciduous forest by combining allometric equations, spatial wavelet analysis and airborne LiDAR, Remote Sensing Letters, 3:5, 443-451.

Lefsky, Michael A. et al. 2002? Lidar Remote Sensing for Ecosystem Studies. BioScience 52(1):19–30.

Lefsky, Michael; McHale, Melissa R. 2008. . Volume estimates of trees with complex architecture from terrestrial laser scanning. J. Appl. Remote Sens. 2(1). Abstract.

Lewis, P.; Hancock, S. 2007. LiDAR for vegetation applications. 29 p.

Lin, Yi et al. 2012. Tree Height Growth Measurement with Single-Scan Airborne, Static Terrestrial and Mobile Laser Scanning. Sensors (Basel) 12(9): 12798–12813.

McHale, M.R. et al. 2009. Urban forest biomass estimates: is it important to use allometric relationships developed specifically for urban trees. Urban Ecosyst 12:95–113.

Morales, D.J et al. 1983. Two methods of evaluating trees on residential sites. Journal of Arboriculture, 9(1): 21-24.

Miyamoto, Matt. 2010. Tips & Tricks for Creating Civil 3D Surfaces from LiDAR Data. 30 p.

Moskal, L. Monika et al.2010? Lidar Applications in Precision Forestry, 10 p.

Moskal, L. Monika; Zheng, Guang. 2012. Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest. Remote Sens. 4:1-20.

NiMeister, W. et al. 2010. Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing, J. Geophys. Res., 115,.

O’Beirne, Dara. 2012. Measuring the urban forest: comparing lidar derived tree heights to field measurements. Thesis. 55 p.

Popescu, Sorin C. et al. 2009? Expansion of Texas Land Use/Land Cover through Class Crosswalking and Lidar Parameterization of Arboreal Vegetation. 56 p.

Qiu, Fang. N.d. LiDAR and Hyperspectral Imagery Based Urban Tree Inventory. 50 slides.

Raber, Brian R. et al.2005. Lidar guidebook: concepts, project design, and practical applications. URISA. 64 p.

Rentsch, M et al. 2011. Extraction of Non-forest Trees for Biomass Assessment Based on Airborne and Terrestrial LiDAR Data. Photogrammetric Image Analysis Lecture Notes in Computer Science Volume 6952: 121-132. Page 1.

Sheridan, Ryan D. 2011. Modeling plot-level biomass and volume using airborne and terrestrial Llidar measurements. Thesis. 117 p.

Shrestha, R.; Wynne, R.H. 2912. Estimating Biophysical Parameters of Individual Trees in an Urban Environment Using Small Footprint Discrete-Return Imaging Lidar. Remote Sens. 2012, 4, 484-508.

Tian, X. et al. 2011. Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data, Remote Sensing of Environment 115: 2330-2341.

Vazirabad, Yashar Fallah; Karslioglu, Mahmut Onur.2911. Lidar for Biomass Estimation.. 25 p.

Vonderach, Christian, et al. 2012. Terrestrial laser scanning for estimating urban tree volume and carbon content. International Journal of Remote Sensing 33(21): 6652-6667. Abstract.

Young, C. Bryan. 2013. Assessing LiDAR Elevation Data for KDOT Applications. Report No. K-TRAN: KU-10-8 ▪ FINAL REPORT. 24 p.


Real, R., et al. 2013. Estimating how inflated or obscured effects of climate affect forecasted species distribution. PLoS ONE 8(1):e53646.

Redpath, S.M., et al. 2013. Understanding and managing conservation conflicts. Trends Ecol. Evol. 28(2):100-109.

Reich, Robin M. et al. 2008. An innovative approach to inventory and monitoring of natural resources in the Mexican State of Jalisco. Environ. Monit. Assess 146:383-396. 1st page.

Reymer, Arthur, et al. n.d. Low Altitude Remote Sensing with UAS. TNO Feature Article

Rick, T.C.; Lockwood, R. 2013. Integrating paleobiology, archeology, and history to inform biological conservation. Conserv. Biol. 27(1):45-54.

Roach, K.A. 2013. Texas water wars: how politics and scientific uncertainty influence environmental flow decision-making in the Lone Star state. Biodivers. Conserv. 22(3):545-565. Abstract.

Robarts, R.D., et al. 2013. The State of knowledge about wetlands and their future under aspects of global climate change: the situation in Russia. Aquat. Sci. 75(1):27-38. Page 1.

Rocha-Santos, L.; Talora, D.C. 2012. Recovery of Atlantic Rainforest areas altered by distinct land-use histories in northeastern Brazil. Trop. Conserv. Sci. 5(4):475-494.

Rodríguez, A., et al. 2012. The eye in the sky: combined use of unmanned aerial systems and GPS data loggers for ecological research and conservation of small birds. PLoS ONE 7(12):e50336.

Romero, D., et al. 2013. Comparative assessment of different methods for using land-cover variables for distribution modelling of Salamandra salamandra longirotris. Environ. Conserv. 40(1):48-59. Summary

Ronconi, R.A., et al. 2012. The role of seabirds in Marine Protected Area identification, delineation, and monitoring: Introduction and synthesis. Biol. Conserv. 156:1-4.

Runting, R.K., et al. Does more mean less? The value of information for conservation planning under sea level rise. Global Change Biol. 19(2):352-363. Abstract.

Safeguarding Personally Identifiable Information in the Federal Government. 16 p.

Santangeli, A., et al. 2013. Integrating multi-source forest inventory and animal survey data to assess nationwide distribution and habitat correlates of the Siberian flying squirrel. Biol. Conserv. 157:31-38. Abstract.

Sartori, A.A.D., et al.. 2012. Weighted linear combination of a GIS environment in the definition of priority areas for connectivity among forest fragments. Rev. Arvore 36(6):1079-1090. Abstract.

Sawyer, Geoff; de Vries, Marc. 2012. About GMES and Data: Geese and Golden Eggs – Study of the economic benfits of a free and open data policy for Sentinel Satellite Data. Final Report. 80 p. From Artur Gil, Applied GIS RS List.

Schoenmaker, Annelie. 2011. Community remote sensing legal issues, 13 p.

Senior, M.J.M., et al. 2013. Trait-dependent declines of species following conversion of rain forest to oil palm plantations. Biodivers. Conserv. 22(1):253-268. Page 1

Senseman, Gary M. et al. 1995. Accuracy Assessment of the Discrete Classification of Remotely-Sensed Digital Data for Landcover Mapping. EN 95/04. 31 p.

Slonecker, E. Terrence et al. 1998, Emerging Legal and Ethical Issues in Advanced Remote Sensing Technology. . Photogrammetric Engineering & Remote Sensing 64(9):. 589-595.

Squillace, Mark. 2013. Draft Forest Planning Rule: Public comment ideas. Red Lodge Clearinghouse.

Staff. 2013. Will we need to water the forests? SmallTownPapers News Service

Taylor, S.E. et al. 2002? Precision forestry: operational tactics for today and tomorrow. 6 p.

Taylor, Steven E. et al. 2006? Precision forestry in the southeast U.S. 18 p

Thompson, I. D., et al. 2013. An operational framework for defining and monitoring forest degradation. Ecology and Society 18(2): 20.

Thompson, Kenneth P. 2007, A political history of U.S. commercial remote sensing, 1984-2007: conflict, collaboration, and the role of knowledge in the high-tech world of earth observation satellites. Dissertation. 322 p.

Tian, J. et al. 2013 .Region-based automatic building and forest change detection on Cartosat-1 stereo imagery. ISPRS Journal of Photogrammetry and Remote Sensing 79: 226-239. Abstract.

Toral, Patel et al. 2013. Predicting Future Conflict under REDD+ Implementation. Forests 4(2): 343-363.

 KEEPING UP-TO-DATE – PRODUCTS, NEWSLETTERS, EMAIL LISTS, JOURNALS. See also,, and Directory of Open Access Journals.

InfoSylva – Issue no. 13/2013 is now available at


30 October – 1 November 2013. Introduction to Wetland Remote Sensing & Mapping. Lafayette, Louisiana, USA. Cost $400. Details from Ashley Kidd –

4 - 6 November 2013. Advanced Wetland Photo-Interpretation. Lafayette, Louisiana, USA Cost $400. Details from Ashley Kidd –

12-16 May 2014. Third International Climate Change Adaptation Conference 2014 (Adaptation Futures 2014). Fortaleza - Ceará Brazil. Details at . From Artur Gil, Applied GIS RS List.

MOVING AHEAD – OPPORTUNITIES – See also: Scholarships-Positions, Forestry, Arboriculture, Agriculture, Agronomy & Natural Resource Management Jobs at, Riley Guide to Agriculture, Forestry, & Farming Jobs, Finding Your Dream Job in Natural Resources, The Job Seekers Guide for International and Environmental Careers and Scholarship Listing

NEXT ISSUE - Feasibility Analysis of Paris polyphylla (Satuwa) in Private and Community Forests

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>    URL:  CV:   Publications:   Skype: forestgyde   

Sunday, 14 July 2013

[ANFES] 2013-07-14 NRMI: This Issue: Condors and Wind Turbines and Some Other Good Things


This Issue: Condors and Wind Turbines and Some Other Good Things

CONDORS AND WIND TURBINES – This past May, there was some discussion on one of the lists regarding the threat of wind turbines to condors. Here are some sites that may be of interest.

Anon. 2010. Improving Methods for Estimating Fatality of Birds and Bats at Wind Energy Facilities in California. California Energy Commission Grant Award Number PIR-08-028. 22 p.

Anon. 2012. Bird Collision with Wind Turbine. Avian Voices. Video of bird being killed by wind turbine.

Arnett, Edward B. et al. 2008. Patterns of Bat Fatalities at Wind Energy Facilities in North America. Journal of Wildlife Management 72(1):61–78.

Associated Press. 2012. Lawsuit says wind energy industry hurts condors.

Baerwald, Erin et al. 2008. A Large-Scale Mitigation Experiment to Reduce Bat Fatalities at Wind Energy Facilities. Management and Conservation Note

Baerwald, Erin et al. 2009. A Large-Scale Mitigation Experiment to Reduce Bat Fatalities at Wind Energy Facilities. Journal of Wildlife Management 73(7):1077-1081.

Bird and Bat Monitoring Program for Glace Bay Lingan Wind Power Ltd. 10 p.

BLM. 2012. Avian and Bat Protection Plan for the Ocotillo Wind Energy Facility. Appendix 16. 87 p.

Burger, James. 2013. Wind energy company could be required to track, protect condors. The Bakersfield Californian.

California Bat Working Group. 2006. Guidelines for assessing and minimizing impacts to bats at wind energy development sites in California. 20 p.

Clarke, Chris. 2013. Killing a Condor is Okay at Wind Project, Fed Say in About-Face Move. Rewire. From Denise Boggs, Appeal List

Cryan, Paul M. 2012? Wind Turbines as Landscape Impediments to the Migratory Connectivity of Bats. Environmental Law.

Dillon Consulting Limited. 2011. Bird and Bat Environmental Effects Monitoring Plan: McLean’s Mountain Wind Farm. 20 p.

Drake, David et al. 2012. Regional Analysis of Wind Turbine-caused Bat and Bird Fatality. Final Report. 35 p.

Ellison, L.E., 2012, Bats and wind energy—A literature synthesis and annotated bibliography: U.S. Geological Survey Open-File Report 2012–1110, 57 p.

Farley, Robert. 2010. Checking George Will on birds and wind turbines.

Hoexter, Michael. 2012. Condors and Wind Turbines: Green-vs-Green Conflict Revisited. Green Thoughts.

Illinois Dept.Natural Resources. 2007 The Possible Effects of Wind Energy on Illinois Birds and Bats. 20 p.

Johnson, Greg et al. 2003. Avian and Bat Mortality During the First Year of Operation at the Klondike Phase I Wind Project, Sherman County, Oregon. Prepared for:Northwestern Wind Power. 17 p.

Johnson, Greg; Howlin, Shay.2011. California Condor Risk Assessment for the North Sky River Wind Energy Project, Kern County, California. Draft Report. Prepared for CH@MHill. 25 p.

Jokimäki, Ari. 2011. Papers on bird and bat mortality caused by wind power. AGW Observer.

Korner-Nievergelt, Fränzi et al. 2011. A new method to determine bird and bat fatality at wind energy turbines from carcass searches. Wildlife Biology 17(4):350-363.

Kunz, Thomas H. et al. 2009. Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. The Ecological Society of America.14 p.

Lausen, Cori et al. 2010 update. APPENDIX 5. Bats and Wind Turbines. Pre-siting and pre-construction survey protocols. 14 p.

Layton, Julia, n.d. Do wind turbines kill birds?. How stuff works. 4 p.

Loew, S.S., et al. 2013. Re-evaluation of collision risk at wind farms. Biol. Conserv. 157:432.

New Wind Power Rules to Protect Birds and Bats

New York State Department of Environmental Conservation. 2009. Guidelines for conducting bird and bat studies at commercial wind energy projects. 31 p.

Nicholson, Charles P. et al. 2005. Assessment and prediction of bird and bat mortality at wind energy facilities in the Southeastern United States. Final Report. Tennessee Valley Authority, Knoxville, TN. 65 p.

NWCC 2010. Wind Turbine Interactions with Birds, Bats, and their Habitats: A Summary of Research Results and Priority Questions. National Wind Coordinating Collaborative. 8 p.

Rydell, Jens et al. 2012. The effect of wind power on birds and bats – A synthesis. The Swedish Environmental Protection Agency 152 p.

Samuel, Molly. 2012. Birds and Blades: Are Condors and Wind Turbines Compatible? KQED Climate Watch. No California condors have yet had a run-in with a turbine.

Schwartz, Susan Savitt ed. 2004. Proceedings of the Wind Energy and Birds/Bats Workshop: Understanding and Resolving Bird and Bat Impacts. 18-19 May 2004. Washington, DC. 132 p.

Sibley, David. 2010. Causes of Bird Mortality. Sibley Guides – Identification of North American birds and trees.

Smallwood, K. Shawn. 2013. Comparing Bird and Bat Fatality-Rate Estimates Among North American Wind-Energy Projects. Wildlife Society Bulletin; DOI: 10.1002/wsb.260. Abstract. From Denise Boggs, Appeal List

Stantec Consulting Services, Inc.2012. Avian and Bat Protection Plan for the Buckeye Wind Power Project, Champaign County, Ohio. Prepared for EverPower Wind Holdings, Inc.102 p.

Stolz, Chritstopher. 2012. Condors may stand in way of growing wind power industry.

Sutter, Crissy. et al. 2912. Condor detection and alerting system. 20 slides.

The Bats and Wind Energy Cooperative Charter (revised May 2012). 15 p.

Thorngate, Nellie. 2007. Presence and movements of California condors near proposed wind turbines. Final report prepared for HI Harvey and Associates. 21 p.

Warren-Hicks, William et al. 2013. Improving methods for estimating fatality of birds and bats at wind energy facilities. California Energy Commission. 136 p.

Wiegand, Jim. 2009. Wind turbines are killing condors. Opinions – Industrial Wind Action Group. Abstract.

Woody, Todd. 2012. Revival of Iconic California Condor Threatens State's Wind Farm Boom. Forbes. 4 p.

FEEDBACK - SMALL BIOMASS GREEN WEIGHT TO DRY WEIGHT CONVERSION (Re NRM for 30 June 2013) George Wooten, Appeal list, writes “Many of the biomass conversion methods cited use remote sensing for inventory, followed by converting the area of each forest type to an estimate of biomass. For calculating woody biomass this calculation is problematic. Many biomass calculations were designed for purposes other than wood production, and so there are few published figures to accurately factor the percentage of wood and non-wood, even if the forest type is known. In addition, this method does not account for changing amounts of wood at different successional stages. An alternative method that averages the growth rate over time is to use mean annual increment figures for dominant trees. This eliminates the need to factor out non-woody growth and also puts the answer in terms of what the sustaining yield might be - a yearly basis rather than simply what one might get from a single harvest. This method is described in: Wooten, George; Demyan, Dave. 2007+ Woody biomass availability calculations for the Methow Valley, Washington a second approximation. Floradora Farms.15 p. Results are comparable within a factor of about 2 to two other methods - one determined from biomass sale receipts and another determined by measuring the amount of non-harvestable remainder found in slash piles.” Thanks for the feedback George.


Macqueen, Duncan. 2013. Landscapes for public goods: multifunctional mosaics are fairer by far. IIED. 4 p.

Manley, P.N et al. 2006. Multiple species inventory and monitoring technical guide. Gen. Tech. Rep. WO-73. Washington, DC: U.S. Department of Agriculture, Forest Service, Washington Office. 204 p.

Marion, Jeffrey L. 1991. Developing a natural resource inventory and monitoring program for visitor impacts on recreation sites: a procedural manual. 67 p.

Martin, Chester et al. 2008. Natural Resources Level One Inventories: What are the Needs and Process for Corps Projects?  ERDC TN-EMRRP-EM-04. 13 p.

MDNR. 2004? Water Quality and Wildlife Habitat in Pine Stands on Delmarva, Maryland Department of Natural Resources. 4 p.

Minimum Security Standards for Electronic Information (2013)

Mohd-Azlan, J.; Engkamat, L. 2013. Camera trapping and conservation in Lanjak Entimau Wildlife Sanctuary, Sarawak, Borneo. Raffles Bull. Zool. 61(1):397-405

Morrison, Michael L.; Marcot, Bruce G. 1995. An evaluation of resource inventory and monitoring program used in national forest planning. Environmental Management 19(1): 147-156. Abstract.

Most, William Brock; Weissman, Steven. 2012. Trees and Power Lines: Minimizing Conflicts between Electric Power Infrastructure and the Urban Forest. Berkeley Law Issue Brief. 28 p.

Murphy, Glen. 2009. New Sensor Technologies for Forest Data Collection. IUFRO Division 4.01 Conference – Mount Gambier, South Australia 17 – 20 August 2009. Meeting Multiple Demands for Forest Information: New Technologies in Forest Data Gathering. 30 p.

National Park Service. 2008. Data management guidelines for inventory and monitoring networks. Natural Resource Report NPS/NRPC/NRR—2008/035. National Park Service, Fort Collins, Colorado. 126 p.

Nemec, K.T.; Raudsepp-Hearne, C. 2013. The use of geographic information systems to map and assess ecosystem services. Biodivers. Conserv. 22(1):1-15. Page 1

Nghiem, N. 2013. Biodiversity conservation attitudes and policy tools for promoting biodiversity in tropical planted forests. Biodivers. Conserv. 22(2):373-403. Page 1.

Norris, Thomas D. 2003. The Seven Attributes of an Effective Records Management Program.  

NRCS.2006. Chapter 4 Inventorying and Monitoring Grazing Land Resources. National Range and Pasture Handbook. 84 p.

O’Dell, T, et al. 2005. Northern Colorado Plateau Inventory and Monitoring Network, Vital Signs Monitoring Plan, National Park Service, Inventory and Monitoring Network, Moab, UT. 174 p. plus appendices.

O'Connell, M. 2013. Spatial ecology and conservation. Ecol. Inform. 14:1.

Olofsson, P., et al. 2013. Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment 129: 122-131. Abstract.

OMB. N.d. Management of Federal Information Resources. Circular Nol. A-130

Packman, C.E., et al.. 2013. Rapid loss of Cambodia's grasslands. Conserv. Biol. 27(2):245-247.

Pan, Y., et al. 2012. Ecological consequences of changing fuelwood consumption patterns in remote villages of northwestern China. Appl. Ecol. Env. Res. 10(3):207-222

Parks, S.A., et al. 2013. Effects of weighting schemes on the identification of wildlife corridors generated with least-cost methods. Conserv. Biol. 27(1):145-154.

Peerbhay, Kabir et al. 2013. Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu–Natal, South Africa. ISPRS Journal of Photogrammetry and Remote Sensing 79:19-28. Abstract.

Pereira, H.M., et al. 2013. Essential biodiversity variables. Science 339(6117):277-278.

Petursdottir, T., et al. 2013. An evaluation of the short-term progress of restoration combining ecological assessment and public perception. Restor. Ecol. 21(1):75-85

Powell, L.A. 2012. Common-interest community agreements on private lands provide opportunity and scale for wildlife management. Anim. Biodivers. Conserv. 35(2):295-306. Abstract.

Preiss, Benjamin. 2013. Lasers check the pulse of Wombat Forest. WAtoday

 KEEPING UP-TO-DATE – PRODUCTS, NEWSLETTERS, EMAIL LISTS, JOURNALS. See also,, and Directory of Open Access Journals.

Forest Information Billboard - Issue 2, June 2013 is now available at From Nelson Wong, IFL.

Transparent Forests – ESA Project

IUFRO News, Volume 42, Double Issue 6&7, 2013 - Download PDF from  Imprint:


 MOVING AHEAD – OPPORTUNITIES – See also: Scholarships-Positions, Forestry, Arboriculture, Agriculture, Agronomy & Natural Resource Management Jobs at, Riley Guide to Agriculture, Forestry, & Farming Jobs, Finding Your Dream Job in Natural Resources, The Job Seekers Guide for International and Environmental Careers and Scholarship Listing

NEXT ISSUE - Terrestrial LiDAR and Urban Trees

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>    URL:  CV:   Publications:   Skype: forestgyde   


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