Determining Wheat Crop Acreage Based on Remote Sensing and GIS Technique in Jabalpur, India

2021 ◽  
pp. 63-69
Author(s):  
Umakant Rawat ◽  
Ankit Yadav ◽  
P. S. Pawar ◽  
Aniket Rajput ◽  
Devendra Vasht ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing And Gis ◽  
Wheat Crop ◽  
Crop Acreage ◽  
Gis Technique

scholarly journals Land Use/Land Cover Change Detection Study Using Remote Sensing and GIS Technique in Puthimari River Basin-A Transboundary Basin Between Bhutan and India

2021 ◽  
pp. 26-34
Author(s):  
Swapnali Barman ◽  
Jaivir Tyagi ◽  
Waikhom Rahul Singh
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
River Basin ◽  
Remote Sensing And Gis ◽  
Rural Settlement ◽  
Land Use Land Cover ◽  
Dense Vegetation ◽  
Gis Technique

Using remote sensing and GIS technique, we analyse the change detection of different land use/land cover (LULC) types that has taken place in Puthimari river basin during a two-decade period from 1999 to 2019. Supervised classification method with maximum likelihood algorithm have been applied to prepare the LULC maps. The LULC change detection has been performed employing a post-classification detection method. Puthimari is a north bank sub-catchment of River Brahmaputra, the northern part of which falls in Bhutan and the rest falls in the Assam state of India. The primary LULC types of the basin are, dense vegetation which is predominant in the upper catchment, crop land and rural settlement. Thus, five different classes have been considered for the analysis, viz., dense vegetation, water bodies, silted water, cropland and rural settlement. The results showed that the rural settlement and water bodies in the basin increased by 42.70% and 30.31% from 1999 to 2019. However, dense vegetation, silted water and cropland decreased by 9.24%, 27.47% and 28.10% during these two decades.

scholarly journals Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India)

2021 ◽  
pp. 88-94
Author(s):  
Umakant Rawat ◽  
Ankit Yadav ◽  
P.S. Pawar ◽  
Aniket Rajput ◽  
Devendra Vasht ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Unsupervised Classification ◽  
Good Choice ◽  
Madhya Pradesh ◽  
Wheat Crop ◽  
Kappa Statistics ◽  
Crop Acreage ◽  
Spectral Bands ◽  
Sentinel 2

Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing.

scholarly journals Soil Organic Carbon Stocks Assessment in Uttarakhand State using Remote Sensing and GIS Technique

2019 ◽  
Vol 8 (01) ◽  
pp. 1646-1658 ◽  
Author(s):  
Nitin Surendra Singh Gahlod ◽  
Navneet Jaryal ◽  
Mallikarjun Roodagi ◽  
Sanjay A. Dhale ◽  
Devinder Kumar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Remote Sensing And Gis ◽  
Carbon Stocks ◽  
Soil Organic Carbon Stocks ◽  
Gis Technique

scholarly journals Historical Morphodynamics Assessment in Bridge Areas using Remote Sensing and GIS Techniques

2019 ◽  
Vol 5 (11) ◽  
pp. 2515-2524 ◽  
Author(s):  
Myint Myat Oo ◽  
Cho Cho Thin Kyi ◽  
Win Win Zin
Keyword(s):  
Remote Sensing ◽  
Google Earth ◽  
Remote Sensing And Gis ◽  
Channel Migration ◽  
Gis Techniques ◽  
Deposition Area ◽  
Gis Technique ◽  
Bridge Inspections ◽  
Landsat Satellite ◽  
Planning And Construction

Currently the Ministry of Construction is responsible for planning and construction of bridges across the country but remote sensing and satellite data are not widely used in the Ministry’s routine process. Although the inspection and monitoring are carried out by the conventional methods, the remote sensing and GIS techniques are available as an alternative way with time and cost saving. From this study, the channel migration in the locations of Ayeyarwady bridges will be analyzed and mapped by identifying temporal changes of channels. Google Earth Engine is used as the primary application in this study and surface water extraction from historical Landsat satellite imagery is done by GEE. River centerline processing and erosion-deposition area identifications are carried out by GIS technique. Study period of each bridge is between 1987 and 2017. Bo Myat Tun Bridge and Ayeyarwady Bridge (Pakokku) are toped in the list with highest migration and erosion-deposition rate according to the study. The goal of this study is to assist the bridge inspections and channel monitoring works by means of remote sensing and GIS techniques which are currently undertaking by Ministry of Construction with conventional techniques.

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