Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 3838-3847 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2020.911.459 Land Use Land Cover Classification and Mapping using Geospatial Techniques in Ganderbal District, J & K, India Shiba Zahoor*, Akhlaq Amin Wani, T. H. Masoodi, M. A. Islam, Asif Ali Gatoo and S. A. Gangoo Faculty of Forestry, Benhama - Ganderbal, SKUAST-K, Shalimar, Srinagar-UT of Jammu and Kashmir, India *Corresponding author ABSTRACT Mapping of land use land cover (LULC) rehearses in the Himalayas is indispensable for K e yw or ds sustainable development, planning and management of resources. In light of remote sensing (RS) and geographic information system (GIS) techniques, the study is an Land use Land endeavor to map LULC patterns of district Ganderbal of Kashmir Himalaya for the year cover, 2018. Images from Landsat-8 (OLI) were used to extricate land cover maps. The study Remote sensing, GIS, region was delineated through visual image interpretation technique into 10 Kashmir Landuse/Landcover classes viz, forest, forest scrub, grassland, snow, wasteland, Himal ayas agriculture, TOF, built-up, water body and wetland. LULC map (2018) so generated revealed that among all the LULC classes, forest occupied maximum area of the map i.e. 33.96 % while as wetland with an area of 1.35 % occupied minimum portion of the map. Article Info The LULC map was likewise validated using ground truth points. The overall classification accuracy of LULC map came out to be 90.14 % with kappa coefficient of Accepted: 0.8897. The outcomes of the study could be used as a spatial standard to illuminate land 04 October 2020 management and strategy choices made by organizers, specialists, environmentalists and Available Online: different stakeholders for sustainable LULC management in the district Ganderbal of the 10 November 2020 Kashmir Himalaya. Introduction benchmark necessity for sustainable management and planning of natural assets The capability of satellite based data as a (Read and Lam, 2002). Exact and opportune basis for producing significant information for land cover maps play a vital role in different LULC is at this point broadly perceived areas of the developing world including land (Lambin et al., 2003; Yuanet al., 2005; Saadat use planning, food security, modeling of et al., 2011), albeit starting endeavors were hydrology, and planning and management of made since mid seventies for application of natural resources. The investigation of various interpretation procedures in LULC conveyance of land cover is significant for mapping (Anderson, 1976). The significance legitimate comprehension of the earth’s key of exploring LULC and their effects is a qualities and processes, including profitability 3838 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 3838-3847 of land, the variety of plant and animal Despite the fact that, there has been an species, and the biogeochemical cycles (Giri, expansion in LULC information bases using 2012). Foresters use land cover maps to create distinctive remote sensing procedures, there harvest management plans in a sustainable exists incredible variety nearby and scale of manner, coordinate biodiversity protection, study, purpose of mapping, classification and take part in climate finance activities like plans, types of mapping, and precision REDD+ (Reducing Emissions from appraisal. Sustainable LULC is vital not just Deforestation and forest degradation and the for the sustained livelihood of 115 million role of conservation, sustainable management Himalayan individuals, yet in addition a lot of forests and enhancement of forest carbon more individuals living in the adjoining Indo- stocks) in developing nations (Hall et al., Gangetic region have been sorely affected due 2011; Potapov et al., 2019). to quickened erosion because of wrong land- use rehearses in the Himalaya (Semwal et al., Land use land cover has been mapped from 2004). different sources like geographical maps, soil study associations, and statistical data and so In the present study multi-temporal satellite on; yet these are helpful for explicit purposes images of Landsat-8 (OLI) have been utilized only and are not truly reliable. However, with to map the LULC classes of district the advent of remote sensing technology, Ganderbal for the year 2018. With expanding every one of these issues have been cleared scale of human induced change and effects on out beating all the restrictions and have lead climate, it has gotten critical to have land to honest and speedy portrayal of the real assets inventory of the district. There have world in the most ideal manner. The advent of been restricted endeavors to examine the the free U.S. Landsat data strategy, the LULC and inventory of assets in the study longest running file, has frequently assisted region (Mehraj, 2018). Thusly, to address this with catching the most crucial human paucity of LULC baseline data set, the aim of exercises on the surface of Earth throughout the study is to generate land use land cover the previous 40 years (Kennedy et al., 2014). map of the Ganderbal district in the state of Landsat, in terms of frequency and coverage Jammu and Kashmir, India for the legitimate stays an ideal answer for viable capture and investigation of land use and its pattern, the evaluation where and when significant natural reason and its impact on the environment and and human-induced changes have happened, humanity. by demonstrating fundamental identification of on-going alterations (Kennedy et al., 2014; Materials and Methods Wulder et al., 2015). Study area The Himalayan region, in spite of being wealthy in terms of biodiversity, has The present study was conducted in district predetermined number of key examinations Ganderbal of Jammu and Kashmir, India (Sharma and Chettri, 2005), making it hard to which lies in the central part of Kashmir, comprehend and likewise plan resource situated on the geographical coordinates of usage, developmental needs, and protection 34o08′0′′N 74o35′0′′E to 34o28′0′′N 75o30′0′′E endeavors. This area is frequently viewed as at a normal elevation of 1,619 meters above data inadequate with earlier mapping mean sea level (Figure 1). The region endeavors being irregular, conflicting, and encounters both temperate and sub-alpine also difficult to reach (Uddin et al., 2014). conditions and is notable for inordinate yearly 3839 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 3838-3847 precipitation of 700 mm and temperature landuse, geology, availability and so forth of varying from 50 C to 200 C. The temperature various LULC types in Ganderbal district. generally falls underneath freezing point The data so obtained was valuable in deciding during winter. The relative humidity stays the nature of mapping to be done and the high and differs from 40% to 86%. Almost number of LULC classes to be outlined. 70% area of the locale is sloping and semi- hilly covered with green forests and a few Generation of LULC map (2018): Mapping areas stay out of reach for a long while during of satellite data was doe through mapping winter. The total geographical area of the software (ArcGIS) at 1:20000 mapping scale. locale is 39,304 ha of which 10949 ha area is The satellite data was delineated into various under forest, 3161 ha of land is under barren LULC types as follows: and uncultivable land, 5758 ha of land is under non-agricultural use, 1790 ha of land is Forest ii. Forest scrub iii. Grassland iv. under grazing and permanent pastures, Agriculture v. Built-up vi. Wetland vii. TOF cultivable waste land is 973 ha and net area viii. Water body ix. Snow x. Wasteland sown is 16673 ha (Anonymous, 2011). Accuracy Assessment of LULC map: The Data source: Multi-temporal Landsat-8 accuracy of LULC map produced was (OLI) imageries of 2018, image processing surveyed on the ground through ground truth software (ERDAS Imagine) and mapping points. The following information was software (ArcGIS) were utilized for mapping gathered from the ground truth points for LULC classes of the chosen study area. All accuracy appraisal: the images were taken from NRSC (National Remote Sensing Centre) Hyderabad, India. Latitude ii. Longitude iii. Altitude (m) iv. Agriculture v. Aspect vi. Slope % vii. Methodology Dominant species viii. Village ix. Block x. Tehsil The point by point procedure for the study is as per the following: Validation of LULC map: The producer’s accuracy and overall accuracy of the LULC Procurement of satellite data: Satellite data map was generated utilizing error matrix and was acquired from National Remote Sensing based on these accuracies KAPPA (khat Centre (NRSC) Hyderabad. coefficient) was additionally determined. User’s Accuracy is a measure of error of Pre-processing of satellite data: The satellite commission and Producer’s accuracy is a data acquired was preprocessed for making a measure of error of omission. KAPPA False Color Composite (FCC) with the ideal analysis is a discrete multivariate technique band combinations by using image processing utilized in accuracy evaluation (Congalton et software. Various image enhancement al., 1983). techniques were additionally used for better No. of correctly classified pixels in each category Producer’s accuracy = interpretation of various Landuse/Landcover Total No. of validation points used for that category (column total) (LULC) types in district Ganderbal. No. of correctly classified pixels in each category User’s accuracy = Preliminary survey of the study area: Total No. of validation points used for that category (row total) Preliminary review was carried out in the study region to get the prior information about 3840 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 3838-3847 No. of correctly classified pixels Overall accuracy = occupied maximum area of the map i.e.