CoChat
Sign Up
Cited by 45

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A framework for mapping vegetation over broad spatial extents: A technique to aid land management across jurisdictional boundaries

Haslem, Angie, Callister, Kate E., Avitabile, Sarah C., Griffioen, Peter A., Kelly, Luke T., Nimmo, Dale G., Spence-Bailey, Lisa M., Taylor, Rick S., Watson, Simon J., Brown, Lauren, Bennett, Andrew F., Clarke, Michael F.·2010·Landscape and Urban Planning
DOI 10.1016/j.landurbplan.2010.07.002
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1016/j.landurbplan.2010.07.002

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The area is geologically rich and filled with varied landforms, semi-arid vegetation communities, and high levels of endemism, which have been mapped and recorded at different times and scales.

    “The area is geologically rich and filled with varied landforms, semi-arid vegetation communities, and high levels of endemism, which have been mapped and recorded at different times and scales (Bowler & Magee 1978; Genty et al. 2003; Haslem et al. 2010; Hesse 2011; Westbrooke & Miller 1995).”

    From Exploratory GIS: modelling past land use and occupancy with functional connectivity, willandra lakes region world heritage area, NSW, australia (2022) · cites this paper as Haslem et al. 2010

  • The WLRWHA area is geologically rich and filled with varied landforms, semi-arid vegetation communities, and high levels of endemism, which have been mapped and recorded at different times and scales.

    “The area is geologically rich and filled with varied landforms, semi-arid vegetation communities, and high levels of endemism, which have been mapped and recorded at different times and scales (Bowler & Magee 1978; Genty et al. 2003; Haslem et al. 2010; Hesse 2011; Westbrooke & Miller 1995).”

    From Exploratory GIS: modelling past land use and occupancy with functional connectivity, willandra lakes region world heritage area, NSW, australia (2022) · cites this paper as Haslem et al. 2010

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 37

  1. Bach, 2006, Accuracy and congruency of three different digital land-use maps, Landscape Urban Plan., 78, 289, 10.1016/j.landurbplan.2005.09.004 · DOI
  2. Barker, 2005, Census of South Australian vascular plants, J. Adelaide Bot. Gard. Suppl., 1
  3. Başkent, 2007, Spatial and temporal dynamics of land use pattern in Turkey: a case study in İnegöl, Landscape Urban Plan., 81, 316, 10.1016/j.landurbplan.2007.01.007 · DOI
  4. Bennett, 2007, Mammals of the mallee region, Victoria: past, present and future, Proc. R. Soc. Victoria, 118, 259
  5. Brody, 2003, Evaluating ecosystem management capabilities at the local level in Florida: identifying policy gaps using geographic information systems, Environ. Manag., 32, 661, 10.1007/s00267-003-3035-1 · DOI
  6. Caldwell, 1970, The ecosystem as a criterion for public land policy, Nat. Resour. J., 10, 203
  7. Cihlar, 2000, Land cover mapping of large areas from satellites: status and research priorities, Int. J. Remote Sens., 21, 1093, 10.1080/014311600210092 · DOI
  8. Cook, 1996, Use of air-borne gamma radiometric data for soil mapping, Aust. J. Soil Res., 34, 183, 10.1071/SR9960183 · DOI
  9. Congalton, 1991, A review of assessing the accuracy of classifications of remotely sensed data, Remote Sens. Environ., 37, 35, 10.1016/0034-4257(91)90048-B · DOI
  10. Congalton, 2001, Accuracy assessment and validation of remotely sensed and other spatial information, Int. J. Wildland Fire, 10, 321, 10.1071/WF01031 · DOI
  11. Crumpacker, 1988, A preliminary assessment of the status of major terrestrial and wetland ecosystems on Federal and Indian lands in the United States, Conserv. Biol., 2, 103, 10.1111/j.1523-1739.1988.tb00339.x · DOI
  12. Cunningham, 2009, A robust technique for mapping vegetation condition across a major river system, Ecosystems, 12, 207, 10.1007/s10021-008-9218-0 · DOI
  13. Eva, 2004, A land cover map of South America, Global Change Biol., 10, 731, 10.1111/j.1529-8817.2003.00774.x · DOI
  14. Foody, 1997, An evaluation of some factors affecting the accuracy of classification by an artificial neural network, Int. J. Remote Sens., 18, 799, 10.1080/014311697218764 · DOI
  15. Fuller, 1998, Countryside survey from ground and space: different perspectives, complementary results, J. Environ. Manag., 54, 101, 10.1006/jema.1998.0213 · DOI
  16. Hansen, 2000, A comparison of the IGBP DISCover and University of Maryland 1km global land cover products, Int. J. Remote Sens., 21, 1365, 10.1080/014311600210218 · DOI
  17. Herold, 2008, Some challenges in global land cover mapping: an assessment of agreement and accuracy in existing 1km datasets, Remote Sens. Environ., 112, 2538, 10.1016/j.rse.2007.11.013 · DOI
  18. Hobbs, 1989, Classification of vegetation in the Western Australian wheatbelt using Landsat Mss data, Vegetatio, 80, 91, 10.1007/BF00048035 · DOI
  19. Hooper, 1997, The effects of plant composition and diversity on ecosystem processes, Science, 277, 1302, 10.1126/science.277.5330.1302 · DOI · Paper page
  20. Huang, 2006, Land cover classification optimized to detect areas at risk of desertification in North China based on SPOT VEGETATION imagery, J. Arid Environ., 67, 308, 10.1016/j.jaridenv.2006.02.016 · DOI
  21. Keith, 2008, A protocol for assessment and integration of vegetation maps, with an application to spatial data sets from south-eastern Australia, Austral Ecol., 33, 761, 10.1111/j.1442-9993.2008.01844.x · DOI
  22. Kozak, 2008, European forest cover mapping with high resolution satellite data: the Carpathians case study, Int. J. Appl. Earth Obs., 10, 44, 10.1016/j.jag.2007.04.003 · DOI
  23. Linderman, 2004, Using artificial neural networks to map the spatial distribution of understorey bamboo from remote sensing data, Int. J. Remote Sens., 25, 1685, 10.1080/01431160310001598971 · DOI
  24. Margules, 2000, Systematic conservation planning, Nature, 405, 243, 10.1038/35012251 · DOI · Paper page
  25. Marvin, 2009, A novel, web-based, ecosystem mapping tool using expert opinion, Nat. Area J., 29, 281, 10.3375/043.029.0307 · DOI
  26. Mayaux, 2002, Large-scale vegetation maps derived from the combined L-band GRFM and C-band CAMP wide area radar mosaics of Central Africa, Int. J. Remote Sens., 23, 1261, 10.1080/01431160110092894 · DOI
  27. Nimmo, 2008, Range extension of the Millewa Skink Hemiergis millewae in the Murray-Sunset National Park, Victoria, Victorian Nat., 125, 110
  28. Özesmi, 2006, Methodological issues in building, training, and testing artificial neural networks in ecological applications, Ecol. Model., 195, 83, 10.1016/j.ecolmodel.2005.11.012 · DOI
  29. Pressey, 2000, Using abiotic data for conservation assessments over extensive regions: quantitative methods applied across New South Wales, Australia, Biol. Conserv., 96, 55, 10.1016/S0006-3207(00)00050-1 · DOI
  30. Scardi, 1996, Artificial neural networks as empirical models for estimating phytoplankton production, Mar. Ecol.—Prog. Ser., 139, 289, 10.3354/meps139289 · DOI
  31. Smith, 2007, Multi-scale survey by sample-based field methods and remote sensing: a comparison of UK experience with European environmental assessments, Landscape Urban Plan., 79, 170, 10.1016/j.landurbplan.2006.02.011 · DOI
  32. Taylor, 1993, Connectivity is a vital element of landscape structure, Oikos, 68, 571, 10.2307/3544927 · DOI · Paper page
  33. Thackway, 2007, Vegetation information for improved natural resource management in Australia, Landscape Urban Plan., 79, 127, 10.1016/j.landurbplan.2006.02.003 · DOI
  34. Thogmartin, 2004, Commentary: a cautionary tale regarding use of the National Land Cover Dataset 1992, Wildlife Soc. B, 32, 970, 10.2193/0091-7648(2004)032[0970:CACTRU]2.0.CO;2 · DOI
  35. Tucker, 1979, Red and photographic infrared linear combinations for monitoring vegetation, Remote Sens. Environ., 8, 127, 10.1016/0034-4257(79)90013-0 · DOI
  36. Van Eetvelde, 2009, A stepwise multi-scaled landscape typology and characterisation for trans-regional integration, applied on the federal state of Belgium, Landscape Urban Plan., 91, 160, 10.1016/j.landurbplan.2008.12.008 · DOI
  37. Westbrooke, 1998, The vegetation of the Scotia 1: 100000 map sheet, western New South Wales, Cunninghamia, 5, 665

Cited by

Sorted by citations

Metadata

Authors
Haslem, A., Callister, K. E., Avitabile, S. C., Griffioen, P. A., Kelly, L. T., Nimmo, D. G., Spence-Bailey, L. M., Taylor, R. S., Watson, S. J., Brown, L., Bennett, A. F., & Clarke, M. F.
Venue
Landscape and Urban Planning
Publisher
Elsevier BV
Published
2010-09
Volume
97
Issue
4
Pages
296-305
ISSN
0169-2046
DOI
10.1016/j.landurbplan.2010.07.002
Cited by
45
References
1
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review