Remote sensing and GIS in identification of soil constraints for sustainable development in Bhilwara district, Rajasthan

被引:0
作者
N. K. Kalra
L. Singh
R. Kachhwah
D. C. Joshi
机构
[1] State Remote Sensing Application Centrre,
来源
Journal of the Indian Society of Remote Sensing | 2010年 / 38卷
关键词
Soil Constraints; IRS LISS III Remote sensing; GIS; Sustainable development;
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学科分类号
摘要
Soil is an integral part of ecosystem nurturing the biological system. Sustainable management of soil resources based on the consideration of constraints is the key to check land degradation and maintain productivity of biological system. To meet the objective remote sensing and GIS technology has been employed for identification of soil constraints in resource potential Bhilwara district. IRS LISS-III FCC images were interpreted for soil constraints using physiography soil approach, verified through field checking and laboratory analysis. On IRS LISS-III FCC images the salt affected soils of Kotri and Taswaria appeared in bright white to light grey tone, smooth texture with white mottles. These were also verified during ground truth and soil analysis for salinity (EC 2.90–3.32 dS m−1) and sodicity (pH 9.50–9.86 and ESP 17.60–19.05). Similarly on the LISS III FCC, constraints due to water erosion near Bir, Sareri and Vijaypura soil series were apparent in light grey to whitish tone, intercepted by medium grey streaks indicating streams and exposed sub-soil. The constraints due to shallow depth associated with rock out crops and hilly areas of Balda and Delwara series appeared in greenish grey tone and coarse texture. There was close relationship between image characteristics, field observation and analytical data.
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页码:279 / 290
页数:11
相关论文
共 3 条
[1]  
Eswaran H.(1992)Role of soil information in meeting the challenge of sustainable land management Journal of the Indian Society of Soil Science 40 6-24
[2]  
Kalra N.K.(1996)Potentiality of Landsat, SPOT and IRS satellite imagery for recognition of salt affected soils in Indian Arid zone International Journal of Remote Sensing 17 3001-3014
[3]  
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