A Geographical Analysis of Resource Utilization and Its Impact on Landuse Pattern in Perambalur District Using Geo-Spatial Technology

P. Manivel¹, S. M. Kumar¹, A. Vetrivel¹, S. Vimal¹ and P Thirumalai^1,

¹Department of Geography, Government Arts College (Autonomous), Kumbakonam (Affiliated to Bharathidasan University, Thiruchirappalli), Tamil Nadu, India

Cite this paper:
P. Manivel, S. M. Kumar, A. Vetrivel, S. Vimal and P Thirumalai. A Geographical Analysis of Resource Utilization and Its Impact on Landuse Pattern in Perambalur District Using Geo-Spatial Technology. Applied Ecology and Environmental Sciences. 2021; 9(7):626-632. doi: 10.12691/aees-9-7-1

Abstract

The objectives of this paper are to simulate the location of the land use change due to the open mining activities from the cement industries. In this study first we estimate the existing land use distribution with the help of remote sensing data. Remote sensing technology reduces cost and time to a great extent with better accuracy to that of conventional surveying. To analysis the land cover above the sand stone with lime stone and clay as shown in the geology map and overlay this region on the land use map and crop the region and estimation given land use area going for the open mining in the study area. The existing land use, its spatial distribution and changes are essential pre-requisite for planning and land management strategies hold key for development of any region. The study of land use is necessary for proper utilization of land resources of a region.

Keywords:
land use land degradation biodiversity resource utilization

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References:

[1]	Angelis, C. F., Freitas, C. C., Valeriano, D. M., & Dutra, L. V. (2002).Multitemporal analysis of land-use/land-cover JERS-1 backscatter inthe Brazilian Tropical Rainforest. Int. J. Remote Sens., 23(7), 1231-1240.
[2]	Anjee Reddy.M. 2001, II edition, Remote Sensing and Geographical information system. B.S Publication.
[3]	Asner, G. P., Bustamante, M. M. C., & Townsend, A. R. (2003). Scaledependence of biophysical structure in deforested areas bordering theTapajo´s National Forest, Central Amazon. Remote Sens. Environ., 87, 507-520.
[4]	Asner, G. P., Keller, M., Pereira, R., & Zweede, J. C. (2002). Remotesensing of selective logging in Amazonia: Assessing limitations basedon detailed field observations, Landsat ETM+ and textural analysis.Remote Sens. Environ., 80(3), 483-496.
[5]	Asner, G. P., Townsend, A. R., & Bustamante, M. C. (1999). Spectrometryof pasture condition and biogeochemistry in the Central Amazon. Geophys.Res. Lett., 26(17), 2769-2772.
[6]	Biggs, T. W., Dunne, T., Domingues, T. F., & Martinelli, L. A. (2002).Relative influence of natural watershed properties and human disturbanceon stream solute concentrations in the southwestern BrazilianAmazon basin. Water Resour. Res., 38(8), 1150.
[7]	Brown, I. F., Martinelli, L. A., Thomas, W. W., Moreira, M. Z., Ferreira, C. A. C., & Victoria, R. A. (1995). Uncertainty in the biomass ofAmazonian forests: An example from Rondonia, Brazil. For. Ecol.Manag., 175-189.
[8]	Cardille, J. A., & Foley, J. A. (2003). Agricultural land-use change inBrazilian Amazoˆnia between 1980 and 1995: Evidence from IntegratedSatellite and Census data. Remote Sens. Environ., 551-562.
[9]	de Moraes, J. F. L., Seyler, F., Cerri, C., & Volkoff, B. (1998). Land-cover mapping and carbon pools estimates in Rondonia, Brazil. Int. J. Remote Sens., 19(5), 921-934.
[10]	Hansen, M. C., Defries, R. S., Townshend, J. R. G., & Sohlberg, R. (2000). Global land-cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens., 21(6-7), 1331-1364.
[11]	Hess, L. L., Melack, J. M., Filoso, S., & Wang, Y. (1995). Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar. IEEE Trans. Geosci. Remote Sens., 33(4), 896-904.
[12]	Houghton, R. A., Lawrence, K. T., Hackler, J. L., & Brown, S. (2001). The spatial distribution of forest biomass in the Brazilian Amazon: A comparison of estimates. Glob. Chang. Biol., 7(7), 731-746.
[13]	Johnson, C. M., Zarin, D. J., & Johnson, A. H. (2000). Post-disturbance aboveground biomass accumulation in global secondary forests: Climate, soil texture, and forest-type effects. Ecology, 81(5), 1395-1401.
[14]	Khanna , Dr.V.K. Guptha. 2001. Economic and Commercial Geography. Sultan Chand and Sons publication.
[15]	Kimes, D. S., Nelson, R. F., Salas, W. A., & Skole, D. L. (1999). Mapping secondary tropical forest and forest age from SPOT HRV data. Int. J. Remote Sens., 20(18), 3625-3640.
[16]	Lean, J., & Rowntree, P. (1993). A GCM simulation of the impact of Amazonian deforestation on climate using an improved canopy representation. Q. J. R. Meteorol. Soc., 119, 509-530.
[17]	Lillisand . C, Keifer, 1994, III edition, Remote Sensing and Image Interpretation. Library of Congress Cateloguing.
[18]	Lu, D., Moran, E., Batistella, M. (2003). Linear mixture model applied to Amazonian vegetation classification. Remote Sens. Environ., 87, 456-469.
[19]	Lucas, R. M., Honzak, M., Curran, P. J., Foody, G. M., Milnes, R., Brown, T., & Amaral, S. (2000). Mapping the regional extent of tropical forest regeneration stages in the Brazilian Legal Amazon using NOAA AVHRR data. Int. J. Remote Sens., 21(15), 2855-2881.
[20]	Malingreau, J. P., & Tucker, C. J. (1990). Ranching in the Amazon region: Large-scale changes observed by AVHRR. Int. J. Remote Sens., 11(2), 187-189.
[21]	Moran, E. F., Brondizio, E. S., Tucker, J. M., da Silva-Forsberg, M. C., McCracken, S., & Falesi, I. (2000). Effects of soil fertility and land-use on forest succession in Amazoˆnia. For. Ecol. Manag., 139, 93-108.
[22]	Nelson, R. F., Kimes, D. S., Salas, W. A., & Routhier, M. (2000). Secondary forest age and tropical forest biomass estimation using Thematic Mapper imagery. Bioscience, 50(5), 419-431.
[23]	Nepstad, D. C., Verissimo, J. A., Alencar, A., Nobre, C., Lima, E., Lefebvre, P., Schlesinger, P., Potter, C., Moutinho, P., Mendoza, E., Cochrane, M., & Brooks, V. (1999). Large-scale impoverishment of Amazonian forests by logging and fire. Nature, 398, 505-508.
[24]	Numata, I., Soares, J. V., Roberts, D. A., Leonidas, F. C., Chadwick, O. A., & Batista, G.T. (2003). Relationships among soil fertility dynamics and remotely sensed measures across pasture chronosequences in Rondoˆnia, Brazil. Remote Sens. Environ., 87, 446-455.
[25]	Oliveira, P. S., & Marquis, R. J. (Eds.) (2002). The Cerrados of Brazil— ecology and natural history of a neotropical Savanna. New York, NY, USA: Columbia University Press.
[26]	Pereira, R., Zweede, J., Asner, G. P., & Keller, M. (2002). Forest canopy damage and recovery in reduced-impact and conventional selective logging in Eastern Para, Brazil. For. Ecol. Manag., 168, 77-89.
[27]	Potter, C. S., Randerson, J. T., Field, C. B., Matson, P.A, Vitousek, P. M., Mooney, H. A., & Klooster, S. A. (1993). Terrestrial ecosystem production: A process model based on global satellite and surface data. Glob. Biogeochem. Cycles, 7(4), 811-841.
[28]	Prithvish Nag, K. Kudrat. 1998. Digital Remote Sensing. Concept publishing company.
[29]	Richey, J. E., Melack, J. M., Aufdenkampe, A. K., Ballester, V. M., Hess, L. L. (2002). Outgassing from Amazonian rivers and wetlands as a large tropical source of atmospheric CO2. Nature, 416, 617-620.
[30]	Yuan. F, 2008. Land cover change and Environmental Impact.