Land Use/Land Cover Change Detection using Geoinformatics in Gurugram District, Haryana, India
Anuj Goyal1, Mukta Sharma2, Dapinder Deep Singh3
1Mr. Anuj Goyal, Research Scholar, IKG Punjab Technical University, Jalandhar, Punjab, India Assistant Professor, Department of Civil Engineering, GLA University Mathura, U.P, India.
2Dr. Mukta Sharma: Assistant Professor, Department of Civil Engineering, IKGPTU Khunnimajra-140301, Punjab, India.
3Mr. Dapinder Deep Sigh: Research Scholar, IKG Punjab Technical University, Jalandhar, India.
Manuscript received on 08 March 2019 | Revised Manuscript received on 15 March 2019 | Manuscript published on 30 July 2019 | PP: 3753-3755 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3388078219/19©BEIESP | DOI: 10.35940/ijrte.B3388.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The district Gurugram in the state Haryana has seen significant extension & development during the last few years. In this paper, the change in land-use/cover has been estimated with time range of 2007 – 2017 and the change detection was quantified. The land-use/cover data generated through satellite imagery has been classified into five major classes i.e., (i) Built-up land (ii) Water Bodies (iii) Barren Land (iv) Agricultural Land (v) Vegetation. The investigation was helped out through Geoinformatics approach by using IRS-P6-LISS-III sensor of 2007 and IRS-P6-LISS-IV sensor of 2017. Observing of land-use/spread mirrored that changes were more noteworthy in degree over the time range of 10 years in the land under various classes. The most sensational changes are the increase in built-up land and barren land. Apart from this decrease in agricultural, water bodies and vegetation cover area also. Results demonstrates an expansive change in the territory of various land use classifications amid the period from 2007 to 2017.The agriculture land covering an area of about 55.27% in 2007 reduced to 43.42% in 2017. The built up area increased from 15.97 % in 2007 to 30.23 in 2017. The barren land area increased from 6.45 % in 2007 to 16.97 in 2017 The Water bodies decreased from 4.65 % in 2007 to 1.05 % in 2017. The vegetation area has also decreased from 17.66 % in 2007 to 8.33 % in 2017. Urban extension and various anthropogenic exercises have brought genuine misfortunes of agricultural land, vegetation and water bodies.
Keywords: Change Detection, GIS, Landuse/Land Cover, LISS-III, LISS-IV, Remote Sensing.
Scope of the Article: Remote Sensing