Estimation of Vegetation and Land Use Changes Using Remote Sensing Techniques and Geographical Information System (Case Study: Roodab Plain, Sabzevar City)

Journal of Rangeland Science

مقاله 2، دوره 4، شماره 1، فروردین 2014، صفحه 1-13   

نوع مقاله: Research and Full Length Article

نویسندگان

Ali Ariapour^{* 1}؛ Abolghasem Dadrasi Sabzevar²؛ Sara Toloee³

¹Department of Natural Resource, College of Range Management, Boroujerd Branch, Islamic Azad University, Boroujerd,

²Faculty Member of Research Agriculture and Natural Resources Center of Razavi Khorasan

³Rangeland Management Engineering, Islamic Azad University, Boroujerd Branch

چکیده

Land use may be regarded as one of the most important factors affecting the
environment with respect to human activities. So far, destroying the rangelands and
changing them into the waste lands and poor rangelands has been proposed as the most
significant variations of land use done by human beings. This paper has been conducted to
evaluate the variations of vegetation percentage and land uses in Barabad-Darook village
with the area of 1522.99 km2 in Sabzevar city during 1987-2007. Thus, using satellitebased
images of TM and ETM+, the most appropriate band composition has been selected
and a mapping of vegetation cover and land use was provided through maximum
likelihood algorithms to correct the errors of geometer and radiometer highlights. At last,
the accuracy of extracted maps was to be determined by the means of overall accuracy test
and Kappa coefficient in order to achieve the validation of research process. Results
indicate that waste lands have been increased from 84.75 to 89.49 and third-rated
rangelands have been reduced from 6.85 to 4.14 percent. On the other hand, first-rated
rangelands were reduced from 0.03 to 0.01 percent which covers 5170791.45 m2 of total
area in the district. Also, the results show that irrigated agricultural lands are to be
decreased from 6.53 to 0.07 percent. In total, due to improper exploitations of regional
water resources and vegetation cover, land uses have been changed into fallow and waste
lands leading to the decrease in the percentage cover of high quality rangelands. Research
findings demonstrate that considering the accepted accuracy, new remote sensing
technology can be applied to exactly estimate the area changes of land use and vegetation.

کلیدواژه‌ها

land use؛ Land cover change detection؛ Remote Sensing؛ GIS

مراجع

Afshinnia, M., 1993. Statistical Methods and
Their Application in Science. Atta Press, vol. 1,
No. 19: 622 pages. (In Persian).
Ahani, H., 2006. Evaluation of Water Dangers
using Geographical Information System and
Harvesting Techniques, Global Model in Rahim
Abad. FasaAgriculture College, Shiraz
University. (In Persian).
Ahani, H., Ghorbani, A., Rastegar Moghadam,
M., Falah Shamsi, R. and Baghernejad, M.,
2009. Evaluation of Land Use Changes using
Satellite Images. Agriculture Science and
Natural Resources Jour., Vol. 16. (In Persian).
Anderson, J. E. and Holte, R. E., 1981.
Vegetation Development over 25 years without
Grazing on Sagebrush Dominated Rangeland in
Southeastern ldaho. Range Management Jour.,
34:25-29.
Apan, A., 1997. Land Cover Mapping for
Tropical Forest Rehabilitation Planning using
Remotely Sensed Data. International Jour.
Remote Sensing, 18(5): 1029-149.
Arokhi, S. V., Niazi, I., 2000. Comparison of
Different Change Detection Techniques of Land
Use and Vegetation using RS, GIS (case study:
DarehShahr, Ilam province). Remotely Sensing
Jour., vol. 1, No. 1: 61-77. (In Persian).
Arzani, H., 1994. Aspects of Estimating Shortterm and Long-term Rangeland Carrying
Capacity. Ph.D. thesis, University ofNew south
Wales.
Buffington, L. C. and Herbel, C. H., 1965.
Vegetation Changes on a Semi-desert Grassland
and Rangeland from 1963 to 1985, 35:139-164.
Chavez, P. S., Berlin, G. L. and Sowers, L. B.,
1982. Statistical Methods for Selecting Landsat
Mss Raito. Jour. Applied Photogrammetric
Engineering, 8(1): 23-30.
Dellepiane, S. G. and P. C., Smith, 1999. Quality
Assessment of Image Classification Algorithms
for Land Cover Mapping: A review and a
proposal for a cost-based approach.
International Jour. Remote Sensing, 20(8):
1461-1486.
Dontree, S., 2003. Land Use Dynamics from
Multi -temporal Remotely Sensed Date, Case
Study: Northern Thailand. Proceedings of Map
in Malaysia.
ENVI User‘s Guide, 2008. Copyright ITT Visual
Information Solutions, Registered in the United
States Patent and Trademark Office, 459 pages.
Simpo PDF Merge and Split Unregistered Version - http://www.simpopdf.com
J. of Range. Sci., 2013, Vol. 4, No. 1 Estimation of …/12
Feizizade, B. V. M. and Mirrahimi, H., 2007.
Change Detection of Tabriz Landscape using
Object-oriented Methods and Urban GIS. (In
Persian).
Foody, G. M., 1992. Compensation for Chance
Agreement in Image Classification for
Assessment. Photogrammetric Engineering and
Remote Sensing, 58: 1459-1460.
Ghorbani, A. D., Tiver, B. F. and Brien, C., 2006.
Biological Soil Crusts Classification using
Ground –levelSpectra. Proceeding of the 27th
Asian Remote Sensing Conference,
Ulaanbaatar, Mongol.
Ghorbani, A., 2007. Terrestrial Survey and
Remotely-sensed Methods for Detecting the
Biological Soil Crust Components of Rangeland
Conditions. The School of Natural and Built
Environment, Ph.D. Thesis, University of South
Australia, Australia.
Hennessy, J. T. R., Gibbens, P., Tromble, J. M.
and M. Cardenas, 1983. Vegetation Changes
from 1935 to 1980 in Massachusetts Dunelands
and Former Grasslands of Southern New
Mexico. Range Management Jour., 36(8): 370-
374.
Hosseini, S. Z. S., Khaje-Al-Din, J., Azarnivand,
H., Farahpour, M. and Khalilpour, S. E., 2007.
Estimation and Mapping of Vegetation Rate of
Rangelands by Processing Sensing ETM+
Images. Rangeland Science Jour., vol. 1, No. 1:
pp 79-90. (In Persian).
Jensen, T. J. R., 2005. Introductory Digital Image
Processing: a Remote Sensing Perspective.
Englewood Cliffs, NJ: Prentice-Hall.
Khalaghi, S., 2006. Change Detection of Caspian
Coast, Human Science and Literature College.
Tabriz University. (In Persian).
Lefsky, M. A. and Cohen, W. B., 2003. Selection
of Remotely Sensed Data, InM. A., Wulder and
S. E., Franklin(Eds.). Remote Sensing of Forest
Environments: Concepts and Casestudies, pp13-
46, Kluwer Academic Publishers, Boston, USA.
Lu, D., and Weng, Q., 2007. A Survey of Image
Classification Methods and Techniques for
Improving Classification Performance.
International Jour. Remote Sensing, 28(5): 823-
870.
Mather, P. M., 2005. Computer processing of
remotely-sensed images. 3rd Ed, John Wiley
&Sons, Ltd., p: 319.
O‘Connor, T. G. and Roux, P. W., 1995.
Vegetation changes in a Semi-arid Grassy
Dwarf Shrub-landsin Karoo, SouthAfrica:
Influences of Rainfall Variability and Grazing
by Sheep. Jour. Applied Ecology, 32(2): 612-
626.
Singh, A., 1998. Digital Change Detection
Techniques Using Remotely Sensed Data.
International Jour. Remote sensing, 10(1):
1989-2003.
Sneva, F. A., Rittenhouse, L. R. and Tueller, P.
T., 1980. Forty-year Inside and Outside, pp: 10-
12.
Tipanaiat, U. and Nitin, K. T., 2003. A Satellitebased Monitoring of Changes in Mangroves in
Krabi, Thailand. Proceedings of map Asia
conference, Malaysia.
Ustine, S. L., 2004. Remote Sensing for Natural
Resource Management and Environmental
Monitoring.3rd Ed., pp: 522, John Wiley &
Sons, Inc., Hoboken, New Jersey.
West, N. E., Provenza, D., Johnson, P. S. and
Owens, K., 1984. Vegetation Changes after 13-
year Livestock Grazing Exclusion on Sagebrush
Semi-desertin West Central Utah. Range
Management Jour., 31(3): 262-267.