Assessment of Potential Land Degradation in Akarsa Watershed, West Bengal, Using GIS and Multi-influencing Factor Technique

Senapati, Ujjal; Das, Tapan Kumar

doi:10.1007/978-3-030-23243-6_11

Cited by 16 publications

(3 citation statements)

References 44 publications

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“…Parmar et al (2021) [48] also conducted a study to assess land degradation vulnerability using the geospatial technique in the Kutch district of Gujarat, India, and the results revealed that 67% of the land area has high vulnerability to land degradation, and 27% of the area falls under the moderate class. Similarly, an assessment of potential land degradation using the geospatial technique and multi-influencing factor technique was carried by Senapati et al (2020) [49] in the Akarsa Watershed, West Bengal, and they also classified the study area into five land degraded zones. The analysis revealed that the very low to low categories of land degradation vulnerability covered almost half of the area of the watershed, and this portion of the study area is associated with good vegetative coverage with open forest, very low vegetative degradation, adequate rainfall (843.21-846 mm), and well-drained soils deep in nature with clayey texture.…”

Section: Discussionmentioning

confidence: 99%

Mapping of Land Degradation Vulnerability in the Semi-Arid Watershed of Rajasthan, India

et al. 2022

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Global soils are under extreme pressure from various threats due to population expansion, economic development, and climate change. Mapping of land degradation vulnerability (LDV) using geospatial techniques play a significant role and has great importance, especially in semi-arid climates for the management of natural resources in a sustainable manner. The present study was conducted to assess the spatial distribution of land degradation hotspots based on some important parameters such as land use/land cover (LULC), Normalized Difference Vegetation Index (NDVI), terrain characteristics (Topographic Wetness Index and Multi-Resolution Index of Valley Bottom Flatness), climatic parameters (land surface temperature and mean annual rainfall), and pedological attributes (soil texture and soil organic carbon) by using Analytical Hierarchical Process (AHP) and GIS techniques in the semi-arid region of the Bundi district, Rajasthan, India. Land surface temperature (LST) and NDVI products were derived from time-series Moderate-Resolution Imaging Spectroradiometer (MODIS) datasets, rainfall data products from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), terrain characteristics from Shuttle Radar Topography Mission (SRTM), LULC from Landsat 9, and pedological variables from legacy soil datasets. Weights derived for thematic layers from the AHP in the studied area were as follows: LULC (0.38) > NDVI (0.23) > ST (0.15) > LST (0.08) > TWI (0.06) > MAR (0.05) > SOC (0.03) > MRVBF (0.02). The consistency ratio (CR) for all studied parameters was <0.10, indicating the high accuracy of the AHP. The results show that about 20.52% and 23.54% of study area was under moderate and high to very high vulnerability of land degradation, respectively. Validation of LDV zones with the help of ultra-high-resolution Google Earth imageries indicates good agreement with the model outputs. The research aids in a better understanding of the influence of land degradation on long-term land management and development at the watershed level.

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Section: Discussionmentioning

confidence: 99%

Mapping of Land Degradation Vulnerability in the Semi-Arid Watershed of Rajasthan, India

et al. 2022

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“…Mientras que, con creciente precipitación el contenido de agua en el suelo es considerable Del mismo modo, Senapati & Das (2020), llevaron a cabo una evaluación de la posible degradación de la tierra, en la cual el análisis reveló que las categorías muy bajas a bajas de vulnerabilidad a la degradación de la tierra cubrían casi la mitad del área de la cuenca de investigación. Por el contrario, Parmar et al…”

Section: Revista De Investigación Científica Dekamu Agropecunclassified

Mapeo de la vulnerabilidad a la degradación de pastizales mediante AHP-GIS & RPAS en la microcuenca Pomacochas - Perú

Silva-López,

Vázquez Pérez,

Zabaleta-Santisteban

2023

dekamuagropec

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En Perú, realizar un monitoreo de pastizales es cada vez más esencial para apoyar a los productores agropecuarios y fortalecer nuevas políticas públicas enmarcadas a un manejo sostenible a nivel de cuencas hidrográficas. En esta investigación se buscó mapear la vulnerabilidad a la degradación de pastizales en la microcuenca de Pomacochas, Amazonas − Perú. Para ello, se utilizaron criterios (NDVI, precipitación, MOS, textura del suelo, pH y pendiente). También, basado en consulta a expertos y el Proceso de Jerarquía Analítica (AHP), se sopeso la importancia de los criterios. Luego, se generó el mapa de aptitud del territorio para evaluar la vulnerabilidad de pastizales mediante superposición ponderada de los mapas de criterios. NDVI fue el criterio más importante, mientras que, la pendiente del terreno fue el menos importante. El modelado basado en AHP y SIG muestra que alrededor de 4012.08 km2 (62.98%) del área total de estudio se encuentran en la categoría “ligeramente vulnerable” (C3) a la degradación de pastizales. Asimismo, se validó los resultados mediante cuatro parcelas de validación empleando imágenes de un Aeronave Piloteada Remotamente (RPA). El estudio brindará apoyo para la toma de decisiones en torno al manejo de los pastizales en microcuencas.

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“…Each variable is weighted depending on its direct and indirect strength, and subclasses are assigned based on a literature evaluation (relative relationship) and autistic behavior. Both most important and small influencing factor is given a weightage of 1.0 and 0.5, respectively (Magesh et al 2012a,b;Senapati and Das. 2020).…”

Section: Multi-influencing Factor (Mif) Techniquementioning

confidence: 99%

GIS-based comparative assessment of groundwater potential zone using MIF and AHP techniques in Cooch Behar district, West Bengal

Senapati

Das

2022

Appl Water Sci

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Global warming, change in climate and rapid growth of population have put a huge strain on the world's groundwater resources. The use of excess groundwater has created a drop in the water table. Increased use of groundwater for agriculture in agro-based areas increases the demand for groundwater. The current study has been conducted in Cooch Behar, an agro-based remote district of North Bengal in the Indian state of West Bengal, where the use of high groundwater in agriculture has reduced groundwater levels. Comparative assessment of Multi-Influencing Factor (MIF) and Analytical Hierarchy Process (AHP) techniques has been used to create a perspective mapping of groundwater potential zone for the research region. Land use and land cover (LULC), rainfall, soil texture, geomorphology, lithology, drainage density, Normalized Differential Vegetation Index (NDVI), and Topographic Wetness Index (TWI) have been used to create the map. The MIF and AHP techniques have been used for Groundwater Potential Zones (GPZ) mapping. Output GPZ has been classified into 5 classes, i.e., very poor, poor, moderate, good, and excellent. MIF technique shows that the groundwater potential classes are covering 9% (285 km2), 21% (67 km2), 30% (944 km2), 27% (837 km2) and 13% (410 km2) of the study area, respectively, whereas the output GPZ from AHP technique shows that the groundwater potential classes are covering 8% (271 km2), 15% (508 km2), 24% (813 km2), 33% (1118 km2) and 20% (677 km2), respectively. Finally, the maps have been verified using groundwater fluctuation data through Receivers Operating Characteristic curve (ROC). The MIF technique's Area Under Curve (AUC) score is 76.5%, while the AHP technique reveals 88.9% accuracy. Both techniques for assessing and monitoring GPZ have been accurate and reasonable. Thus, this type of research is reliable for a more appropriate framework for swiftly analyzing groundwater recharge and directing the location of artificial recharge structures and other groundwater management operations of agricultural-based areas.

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Assessment of Potential Land Degradation in Akarsa Watershed, West Bengal, Using GIS and Multi-influencing Factor Technique

Cited by 16 publications

References 44 publications

Mapping of Land Degradation Vulnerability in the Semi-Arid Watershed of Rajasthan, India

Mapping of Land Degradation Vulnerability in the Semi-Arid Watershed of Rajasthan, India

Mapeo de la vulnerabilidad a la degradación de pastizales mediante AHP-GIS & RPAS en la microcuenca Pomacochas - Perú

GIS-based comparative assessment of groundwater potential zone using MIF and AHP techniques in Cooch Behar district, West Bengal

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