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RISS 인기검색어
- 검색키워드
- 저자 : Pandey Kamal (검색결과 3 건)
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Time-series analysis of open data for studying urban heat island phenomenon: a geospatial approach
Rao Priyanka,Singh Abhishek,Pandey Kamal 대한공간정보학회 2021 Spatial Information Research Vol.29 No.6
Urbanization is increasing with a faster pace in almost all the cities of India, which has somehow prompted the anthropogenic activities eventually influencing the environment in this climate change scenario. This has led to the more prominent urban heat island (UHI) effect in urban areas, significantly raising the surface temperature of urban built-up. To focus on this issue, a spatio-temporal analysis of UHI over the Jaipur site of Rajasthan has been performed using moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) and MODIS Normalized Difference Vegetation Index (NDVI) for 16 years i.e., from 2003 to 2018 wherein NDVI has been used to analyze the status of vegetation in the urban and non-urban area w.r.t. UHI phenomenon. Study of UHI phenomenon has been done by computing the difference of mean LST between urban area and urban periphery (at a buffer distance of 2 km from urban boundary) both for day and night time. The difference of LST day time observed between urban and non-urban (buffer) is 0.06 C in May, 2003 and 0.51 C in May, 2018 whereas, difference of LST night time between urban and area surrounding to urban is 0.58 C in May, 2003 and 1.41 C in May, 2018. From the quantitative analysis of land use land cover it has been observed that there is a rapid increase of urban area from 63% in 2003 to 69% in 2018 and vegetation cover decreased from 36% in 2003 to 31% in 2018. The percentage decrease of vegetation cover from 2003 to 2018 is 5% and the percentage increase in urban area is 6% which is still continuing at an even faster rate. Data preparation tasks can be greatly minimized by using analysis ready open data available in the public domain for carrying out such studies. The approach followed in the study will assist researchers to carry out a quick spatio-temporal analysis for the identification of areas susceptible to increasing variability of LST. Also, it provides a basis to understand and manage urban stress, one of the major causes of unalterable damages to the environment.
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A Abhinav,VA Chethan,Shruti Pancholi,P Danuta Mohan,Shaik Mohammed Rayyan,Kamal Pandey 대한공간정보학회 2022 Spatial Information Research Vol.30 No.4
Infrastructure plays a vital role in the growth, performance, and alleviating poverty of a country. India is the second-largest producer of agriculture, requires proper infrastructure like roads, storage facilities, etc. which makes the development, location, and the number of cold storages vital in reducing the expenditure for the farmers as well as ensuring food security. Kolar district, situated in the South-eastern part of Karnataka is a leading producer of fruits and vegetables and faces a shortage of proper infrastructure for agriculture. An attempt is done to use geospatial technologies for analyzing the existing cold storage facilities in the district. The study reveals that the district faces a severe shortage of cold storage and is not evenly distributed which makes the farmer travel long distances to the nearest such facility. The spatial clustering-based approach is used to propose locations for new cold storage facilities. The study reveals that the study area requires a total of 50 new cold storage distributed throughout the district and proposed cold storage facilities will reduce the maximum distance to the nearest cold storage from 50.97 km to 13.98 km.
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Investigating water quality of an urban water body using ground and space observations
Kumar Manish,Kumar Mukesh,Denis Derrick Mario,Verma Om Prakash,Mahato Lakhan Lal,Pandey Kamal 대한공간정보학회 2021 Spatial Information Research Vol.29 No.6
Satellite based water quality monitoring and assessment is a thrust area of research. Present study focuses on use of space observations and ground data for assessment of spatial pattern in water quality parameters of an urban water body in Gorakhpur city of Uttar Pradesh, India. Water quality parameters namely, pH, Total Dissolved Solid, Turbidity, Total Hardness, Dissolved Oxygen and Biological Oxygen Demand were measured from the spatially distributed samples collected from the lake. Multiple linear regression models were developed using Landsat-8 OLI data and water quality sampling data to estimate the spatial patterns. It was observed that all the water quality parameters are significantly correlated with the radiance values of the Landsat-8 OLI sensor. Results of the regression model indicate a good agreement between the measured and estimated value of all the water quality parameters i.e., 82%, 70%, 90%, 66%, 84% and 79% respectively. Also, water quality maps when validated with lab tested value showed 71%, 62%, 71%, 55%, 75% and 86% accuracy. This study provides an effective and quick approach for mapping and planning of surface water (Lake) in urban areas with acceptable level of accuracy.
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