Comprehensive Analysis of Landform and Land Use/ Land Cover Mapping of Waghora Watershed Using Sentinal-2B and SRTM-DEM Data

Yagani Sinha *

Department of Soil Science and Agricultural Chemistry, Indira Gandhi Krishi Vishwavidyalaya, Raipur, 492012, India.

K.K. Sahu

Department of Soil Science and Agricultural Chemistry, Indira Gandhi Krishi Vishwavidyalaya, Raipur, 492012, India.

Rajeev Srivastava

ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur-440 033, India.

M.S.S. Nagaraju

ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur-440 033, India.

S.S. Porte

Department of Soil Science and Agricultural Chemistry, Indira Gandhi Krishi Vishwavidyalaya, Raipur, 492012, India.

R.R. Saxena

Department of Soil Science and Agricultural Chemistry, Indira Gandhi Krishi Vishwavidyalaya, Raipur, 492012, India.

*Author to whom correspondence should be addressed.


Abstract

This paper aims to integrate the use of high spectral resolution a remote sensing data of Sentinel-2B imagery along with the Digital Elevation Model (DEM) derived from the SRTM stereo data to delineate the landforms and analyze the land use and land cover in Waghora watershed, Sausar tehsil, Chhindwara district, situated on basaltic terrain in northern Deccan plateau. A 30 m resolution DEM of the study area was generated, capturing terrain parameters like elevation, slope, aspect, hillshade, and drainage. Sentinel-2B (10 m) images from two seasons were collected FCC (false colour composite) and were prepared by ARCGIS software. combination of Sentinel-2B imagery, SRTM-DEM data, and ground truth verifications to delineate eight major landforms in the studied area. Slope information, extracted from high-resolution DEMs, reveals 4 distinct slope classes. The landforms, including Plateau, Escarpment, Foot Slope, Upper Pediment, Lower Pediment, Valley, Interfluve, and Mound, are characterized based on visual interpretation and geological context. Each landform exhibits unique features, elevation ranges, and dominant land use/cover types, such as single crop cultivation, forest, or degraded land. This detailed terrain analysis aids in land-use planning and environmental management initiatives. The land use/land cover analysis utilizes Sentinel-2B data to identify five classes: degraded forest, double crop, single crop, orchard, and land with and without scrubs. Dense forest dominates 24.2% of the watershed, while double crop and single crop lands cover 36.7% and 24.2% respectively. Orchards occupy a minimal 0.8% of the area, and wastelands account for 5.7%. The relationship between landforms, slope, and land use/cover reveals dominant forestation on steep escarpments, while valleys and interfluves support double cropping due to gentle slopes and depositional processesThe study elucidated connections to examine diverse biophysical phenomena. It highlights the effectiveness of employing SRTM-DEM and Sentinel-2B imagery for analyzing geomorphic characteristics and mapping land use/land cover, offering significant perspectives for land management and planning approaches.

Keywords: Landform, landuse/land cover, slope, ArcGIS, Sentinel-2B, SRTM-DEM


How to Cite

Sinha, Y., Sahu, K., Srivastava, R., Nagaraju, M., Porte, S., & Saxena, R. (2024). Comprehensive Analysis of Landform and Land Use/ Land Cover Mapping of Waghora Watershed Using Sentinal-2B and SRTM-DEM Data. Asian Journal of Soil Science and Plant Nutrition, 10(2), 403–412. https://doi.org/10.9734/ajsspn/2024/v10i2298

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References

Alomran AI, McCullagh MJ. Evaluation of adequacy of DEM level-1 as an alternative to level-2: in a context of a case study for radiometric normalization of desert bare soil in Saudi Arabia. In Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII. 2008; 7110:313-329

Katusiime J, Schütt B. Linking land tenure and integrated watershed management—A review. Sustainability. 2020;12(4):1667.

3.Yan K, Di Baldassarre G, Solomatine DP, Schumann GJ. A review of low‐cost space‐borne data for flood modelling: topography, flood extent and water level. Hydrological processes. 2015; 29(15): 3368-87.

Mashimbye ZE, de Clercq WP, Van Niekerk A. An evaluation of digital elevation models (DEMs) for delineating land components. Geoderma. 2014; 213:312-9.

Teske R, Giasson E, Bagatini T. Comparison of the use of digital elevation models in digital mapping of soils of Dois Irmãos, RS, Brazil. Revista Brasileira de Ciência do Solo. 2014; 38:1367-76.

Sheetal K, Biswas U, Ahmad M, Kumar S. Integrated Approach for Land Resource Management through Remote Sensing and GIS - A Case Study of Keolari Block, Seoni District (Madhya Pradesh), India. International Journal for Research in Applied Science & Engineering Technology (IJRASET) 2019; 7:2321-9653

Delalay, Marie & Tiwari, Varun & Ziegler, Alan & Gopal, Vik & Passy, Paul. (2019). Land-use and land-cover classification using Sentinel-2 data and machine-learning algorithms: Operational method and its implementation for a mountainous area of Nepal. Journal of Applied Remote Sensing. 13. 1. 10.1117/1.JRS. 13.014530.

Phiri D, Simwanda M, Salekin S, Nyirenda VR, Murayama Y, Ranagalage M. Sentinel-2 data for land cover/use mapping: A review. Remote Sensing. 2020;12(14): 2291.

Chang Y, Hou K, Li X, Zhang Y, Chen P. Review of land use and land cover change research progress. InIOP Conference Series: Earth and Environmental Science. 2018;113: 012087.

Izakovičová Z, Špulerová J, Petrovič F. Integrated approach to sustainable land use management. Environments. 2018; 5(3):37.

Sahu N, Obireddy GP, Kumar N, Nagaraju MS, Srivastava RA, Singh SK. Characterization of landforms and land use/land cover in basaltic terrain using IRS-P6 LISS-IV and Cartosat-1 DEM data: a case study. Agropedology. 2014;24(2): 166-78.

Martínez S, Mollicone D. From land cover to land use: A methodology to assess land use from remote sensing data. Remote Sensing. 2012;4(4):1024-45.

Reddy GPO, Maji AK. Delineation and characterization of geomorphological features in a part of lower Maharashtra metamorphic plateau using IRS-ID LISS-III data. Journal of the Indian Society of Remote Sensing. 2003; 31(4): 241-250

Nagaraju MSS, Kumar N, Srivastava R, Das SN. Cadastral-level soil mapping in basaltic terrain using Cartosat-1-derived products. International Journal of Remote Sensing. 2014; 35(10): 3764–3781.