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http://krishi.icar.gov.in/jspui/handle/123456789/72092
Title: | Geospatial Modelling for Delineation of Crop Management Zones Using Local Terrain Attributes and Soil Properties |
Other Titles: | Not Available |
Authors: | Roomesh Kumar Jena Siladitya Bandyopadhyay Upendra Kumar Pradhan Pravash Chandra Moharana Nirmal Kumar Gulshan Kumar Sharma Partha Deb Roy Dibakar Ghosh Prasenjit Ray Shelton Padua Sundaram Ramachandran Bachaspati Das Surendra Kumar Singh Sanjay Kumar Ray Amnah Mohammed Alsuhaibani Ahmed Gaber Akbar Hossain |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Institute of Water Management ICAR::National Bureau of Soil Survey and Land Use Planning ICAR::Indian Agricultural Statistics Research Institute ICAR::Indian Institute of Soil and Water Conservation ICAR::Indian Agricultural Research Institute ICAR::Central Marine Fisheries Research Institute ICAR::Indian Institute of Horticultural Research ICAR::Central Coastal Agricultural Research Institute |
Published/ Complete Date: | 2022-04-27 |
Project Code: | Not Available |
Keywords: | management zone digital soil mapping environmental covariates possibilistic fuzzy c-means clustering geographically weighted principal component analysis |
Publisher: | MDPI |
Citation: | Jena, R.K.; Bandyopadhyay, S.; Pradhan, U.K.; Moharana, P.C.; Kumar, N.; Sharma, G.K.; Roy, P.D.; Ghosh, D.; Ray, P.; Padua, S.; et al. Geospatial Modelling for Delineation of Crop Management Zones Using Local Terrain Attributes and Soil Properties. Remote Sens. 2022, 14, 2101. https://doi.org/10.3390/ rs14092101 |
Series/Report no.: | Not Available; |
Abstract/Description: | Defining nutrient management zones (MZs) is crucial for the implementation of sitespecific management. The determination of MZs is based on several factors, including crop, soil, climate, and terrain characteristics. This study aims to delineate MZs by means of geostatistical and fuzzy clustering algorithms considering remotely sensed and laboratory data and, subsequently, to compare the zone maps in the north-eastern Himalayan region of India. For this study, 896 grid-wise representative soil samples (0–25 cm depth) were collected from the study area (1615 km2). The soils were analysed for soil reaction (pH), soil organic carbon and available macro (N, P and K) and micronutrients (Fe, Mn, Zn and Cu). The predicted soil maps were developed using regression kriging, where 28 digital elevation model-derived terrain attributes and two vegetation derivatives were used as environmental covariates. The coefficient of determination (R2) and root mean square error were used to evaluate the model’s performance. The predicted soil parameters were accurate, and regression kriging identified the highest variability for the majority of the soil variables. Further, to define the management zones, the geographically weighted principal component analysis and possibilistic fuzzy c-means clustering method were employed, based on which the optimum clusters were identified by employing fuzzy performance index and normalized classification entropy. The management zones were constructed considering the total pixel points of 30 m spatial resolution (17, 86,985 data points). The area was divided into four distinct zones, which could be differently managed. MZ 1 covers the maximum (43.3%), followed by MZ 2 (29.4%), MZ 3 (27.0%) and MZ 4 (0.3%). The MZs map thus would not only serve as a guide for judicious location-specific nutrient management, but would also help the policymakers to bring sustainable changes in the north-eastern Himalayan region of India. |
Description: | Not Available |
ISSN: | 2072-4292 |
Type(s) of content: | Article |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Remote Sensing |
Journal Type: | research paper |
NAAS Rating: | 10.85 |
Impact Factor: | 4.85 |
Volume No.: | 14 |
Page Number: | 2101 |
Name of the Division/Regional Station: | Statistical Genetics |
Source, DOI or any other URL: | https://doi.org/10.3390/rs14092101 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/72092 |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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remotesensing-14-02101-v3.pdf | 5.24 MB | Adobe PDF | View/Open |
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