Land cover

Land cover surrounding Madison, Wisconsin. Fields are shaded yellow and brown, water blue, and urban surfaces red.

Land cover is the physical material at the land surface of Earth. Land covers include flora, concrete, built structures, bare ground, and temporary water. Earth cover is the expression used by ecologist Frederick Edward Clements that has its closest modern equivalent being vegetation.[1]: 52  The expression continues to be used by the United States Bureau of Land Management.[2]

There are two primary methods for capturing information on land cover: field survey, and analysis of remotely sensed imagery.[3] Land change models can be built from these types of data to assess changes in land cover over time.

One of the major land cover issues (as with all natural resource inventories) is that every survey defines similarly named categories in different ways. For instance, there are many definitions of "forest"—sometimes within the same organisation—that may or may not incorporate a number of different forest features (e.g., stand height, canopy cover, strip width, inclusion of grasses, and rates of growth for timber production).[4] Areas without trees may be classified as forest cover "if the intention is to re-plant" (UK and Ireland), while areas with many trees may not be labelled as forest "if the trees are not growing fast enough" (Norway and Finland).

Distinction from "land use"

"Land cover" is distinct from "land use", despite the two terms often being used interchangeably. Land use is a description of how people utilize the land and of socio-economic activity. Urban and agricultural land uses are two of the most commonly known land use classes. At any one point or place, there may be multiple and alternate land uses, the specification of which may have a political dimension. The origins of the "land cover/land use" couplet and the implications of their confusion are discussed in Fisher et al. (2005).[5]

Types

Land cover by IGBP with 17 classes. Class definition[6] Color Code[7]
  Water
  Evergreen Broadleaf forest
  Deciduous Needleleaf Forest
  Deciduous Broadleaf Forest
  Closed Shrubland
  Open Shrubland
  Woody Savannas
  Savannas
  Permanent Wetlands
  Urban and Built-Up
  Cropland/Natural Vegetation Mosaic
  Snow and Ice
  Barren or Sparsely Vegetated

Following table is Land Cover statistics by Food and Agriculture Organization (FAO) with 14 classes.

Land Cover[8][9] (million ha = 10 000 km2)
FAO code type[10] 1992 2001 2015 share change fm 92 note
[6970] Artificial surfaces (including urban and associated areas) 26.04 34.33 55.40 0.37% 29.35
[6971] Herbaceous crops 1,716.22 1,749.58 1,712.15 11.50% -4.06 Arable land
[6972] Woody crops 162.86 181.32 199.90 1.34% 37.04 Arable land
[6973] Multiple or layered crops Arable land
[6974] Tree-covered areas 4,434.92 4,393.70 4,335.00 29.11% -99.93 large decrease
[6975] Mangroves 18.06 18.39 18.74 0.13% 0.67
[6976] Shrub-covered areas 1,685.00 1,669.65 1,627.34 10.93% -57.66 large decrease
[6977] Shrubs and/or herbaceous vegetation, aquatic or regularly flooded 202.61 194.77 185.39 1.24% -17.23
[6978] Sparsely natural vegetated areas 891.78 878.69 868.07 5.83% -23.71
[6979] Terrestrial barren land 2,001.25 2,000.87 1,884.00 12.65% -117.25 large decrease
[6980] Permanent snow and glaciers 78.59 84.32 84.29 0.57% 5.70
[6981] Inland water bodies 432.60 435.00 444.57 2.98% 11.97
[6982] Coastal water bodies and intertidal areas
[6983] Grassland 1,793.65 1,806.50 1,801.14 12.09% 7.50
Total Land Mass 14,893.91 100%

Mapping

Process of land cover mapping using TM images[11]

Land cover change detection using remote sensing and geospatial data provides baseline information for assessing the climate change impacts on habitats and biodiversity, as well as natural resources, in the target areas. Land cover change detection and mapping is a key component of interdisciplinary land change science, which uses it to determine the consequences of land change on climate.

Application of land cover mapping

See also

References

  1. ^ Makers of American Botany, Harry Baker Humphrey, Ronald Press Company, Library of Congress Card Number 61-18435
  2. ^ "Susitna MOA Earth Cover Classification" (PDF). BlM-Alaska Technical Report 44. Bureau of Land Management. September 2002. Archived from the original (PDF) on 23 September 2015. Retrieved 15 June 2015.
  3. ^ Cracknell, Matthew J.; Reading, Anya M. (February 2014). "Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information". Computers & Geosciences. 63: 22–33. Bibcode:2014CG.....63...22C. doi:10.1016/j.cageo.2013.10.008. ISSN 0098-3004.
  4. ^ Horning, Ned; Robinson, Julie A .; Sterling, Eleanor J.; Turner, Woody; Spector, Sacha (2010). "Measuring and Monitoring Land Cover, Land use, and Vegetation Characteristics". Remote Sensing for Ecology and Conservation: A Handbook of Techniques. Oxford University Press.
  5. ^ Fisher, P., Comber, A. and Wadsworth, R.. 2005. Land Use and Land Cover: Contradiction or Complement. In Fisher, P. and Unwin, D. (Eds.). Re-Presenting GIS. John Wiley & Sons. https://www.wiley.com/en-ca/Re+Presenting+GIS+-p-9780470848470
  6. ^ The IGBP Land Cover Classification
  7. ^ The Land Processes Distributed Active Archive Center (LP DAAC) MODIS/Terra Land Cover Types Yearly L3 Global 0.05Deg CMG (MOD12C1)
  8. ^ FAO Agri-Environmental Indicators / Land cover
  9. ^ values are from CCI_LC(Climate Change Initiative Land Cover) by European Space Agency
  10. ^ FAO Dataset Information: Land Cover Title Abstract Supplemental see Table 1. SEEA CF/AFF land cover classes and corresponding LCC classifiers, page 2,3,4
  11. ^ Uddin, Kabir; Shrestha, Him Lal; Murthy, M. S. R.; Bajracharya, Birendra; Shrestha, Basanta; Gilani, Hammad; Pradhan, Sudip; Dangol, Bikash (2015-01-15). "Development of 2010 national land cover database for the Nepal". Journal of Environmental Management. Land Cover/Land Use Change (LC/LUC) and Environmental Impacts in South Asia. 148: 82–90. Bibcode:2015JEnvM.148...82U. doi:10.1016/j.jenvman.2014.07.047. ISSN 0301-4797. PMID 25181944.

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