scholarly journals USE OF REMOTE SENSING AND GIS FOR MODELING AND MAPPING THE SOIL SALINITY OF AGRICULTURAL LAND IN EL-FAYOUM GOVERNORATE, EGYPT

2021 ◽  
Vol 6 (4) ◽  
pp. 161-162
Author(s):  
F. E. Abu-Agwa ◽  
M. S. E. Amira ◽  
A. H. El-Nahry
Keyword(s):  
Remote Sensing ◽  
Soil Salinity ◽  
Agricultural Land ◽  
Remote Sensing And Gis ◽  
Fayoum Governorate

scholarly journals REMOTE SENSING AND GIS FOR LAND COVER CLASSIFICATION AND CHANGE DETECTION IN GAZIPUR SADAR, BANGLADESH DURING 1973-2017

2018 ◽  
Vol 5 (2) ◽  
pp. 215
Author(s):  
Md Arafat Hassan ◽  
Rakibul Islam ◽  
Rehnuma Mahjabin
Keyword(s):  
Remote Sensing ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Remote Sensing And Gis ◽  
Vegetation Coverage ◽  
Accurate Information ◽  
Sal Forest ◽  
Shed Light

This paper has been developed to capture the land coverage change in Gazipur Sadar Upazila with the help of remote sensing data of 44 years from 1973 to 2017. After acquiring the study area image of 1973, 1991, 2006 and 2017 supervised classification method has been used to get the accurate information from the satellite image and the whole outcome has been transformed into measurable unit (sq km) and graphs. The accuracy of land coverage was ranged from 85% to 89%. The outcome says that the acceleration of economic growth and pressure of huge population took a heavy toll on the vegetation coverage which decreased -199.7%. People are destroying vegetation coverage for building up settlements and infrastructure. In the year 2017, the map shows that the built-up area increased 312.9% for industry, settlement and agricultural purpose. Moreover agricultural land also drops down from 42% to 32%.  The rapid rate of decreasing vegetation coverage and small amount of existing vegetation coverage only 57 sq km (in 2017) is a red alert for the region. The Sal forest and other special flora species of that region is valuable resource for environment. This paper shed light on the fact that it is urgent to protect vegetation coverage so it will help the authority to make good policies and use other techniques to save vegetation coverage.

A Remote Sensing and GIS Integrated Study on Assessment of Change in Land Use and Loss of Agricultural Land due to Urbanization – A Case Study of Nashik City

2021 ◽  
Vol 9 (8) ◽  
pp. 3055-3063
Author(s):  
Dipti Bakare
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Rapid Change ◽  
Remote Sensing And Gis ◽  
Suitability Analysis ◽  
The World

Abstract: Urbanization may be a process having a serious impact ashore use characteristics. Basically, as an impression of urbanization, the world is observed with rapid change within the land use character of agricultural land. Generally, the agricultural land is employed for various development activities like industrial establishments, residential colonies and other urban infrastructure during the method of urbanization. it's necessary to possess a periodical assessment of land use change for the developing populated area , which helps to make a decision the longer term expansion strategies for the world. Nashik city is located in the state of Maharashtra in the western part of India. It is one of the most dynamic cities of India with a rapid growth rate due to migration from various parts of Maharashtra. The Nashik city is presently spread over an area of 264.15 sq. km. with a periodical increase in municipal corporation boundary during the last few decades. As a result of urbanization and expansion of municipal corporation limits, the city has undergone drastic changes in land use character. In this study, land-use change is quantified for the existing six zones of Nashik city during the last 30 years using remote sensing and GIS. The study has analysed the relationship between urban expansion and the loss of agricultural land because of an increase in a built-up area and other land use. The study present excellent scenario for land use change during the year 1991, 2001, 2011 and 2020. This can surely guide the development strategies for the study area of Nashik. Also the study can be extended for conducting a suitability analysis to assess future change of land use based on various criteria. Keywords: Land use, Remote sensing, GIS, Supervised classification, Urbanization, Agricultural land loss

scholarly journals Research and Application of Remote Sensing and GIS Technologies in Determining and Forecasting Land Use Changes by Markov Chain in Y Yen District - Nam Dinh Province

2016 ◽  
Vol 24 (3) ◽  
pp. 27-39 ◽  
Author(s):  
Giang Thi Le ◽  
Thuan Duc Nguyen ◽  
Vinh Quoc Tran
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Markov Chain ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing And Gis ◽  
Strong Impact ◽  
Gis Technology ◽  
New Directions ◽  
Residential Living

Abstract The land's natural resources are invaluable and a requisite for the existence and development of humans and other organisms on Earth. In recent years, under the strong impact of new directions in economic and social development, the demand for land has been increasing. The percentage of land used for residential living, transportation, irrigation and infrastructure tends to increase, while the share of agricultural land is continuously decreasing. Consequently, the allocation and efficient use of land is one of the most important concerns in order to enable sustainable development, environmental protection and ecology. Therefore, research to determine the volatility and changing trends in land use is necessary. This study uses remote sensing and GIS technology, combined with the Markov Chain to determine variation and forecast the changes in land use in the Y Yen district of the Nam Dinh province of Vietnam. This will create a basis for helping land managers grasp the situation in local land use management.

The use of remote sensing data to extract information from agricultural land with emphasis on soil salinity

Soil Research ◽  
2003 ◽  
Vol 41 (7) ◽  
pp. 1243 ◽  
Author(s):  
F. M. Howari
Keyword(s):  
Remote Sensing ◽  
Soil Salinity ◽  
Large Scale ◽  
Agricultural Land ◽  
Rio Grande Valley ◽  
Remote Sensing Data ◽  
Rio Grande ◽  
The United States ◽  
Sensing Data ◽  
Matching Techniques

The rapid growth of information technologies has provided exciting new sources of data, interpretation tools, and modelling techniques to soil research and education communities at all levels. This paper presents some examples of the capability of remote sensing data such as Landsat ETM+, airborne visible/infrared imaging spectrometer (AVIRIS), colour infrared aerial photos (CIR), and high-resolution field spectroradiometer (GER 3700) to extract surface information about soil salinity. The study used image processing techniques such as supervised classification, spectral extraction, and matching techniques to investigate types and occurrences of salts in the Rio Grande Valley on the United States–Mexico border. Soil salinity groups were established using soil physico-chemical properties and image elements (absorption-reflectivity profiles, band combinations, grey tones of the investigated images, and textures of soil and vegetation covers as they appear in images). The lack of vegetation or scattered vegetation on salt-affected soil (SAS) surfaces makes it possible to detect salt in several locations of the investigated area. The presented remote sensing datasets reveal the presence of gypsum and halite as the dominant salt crusts in the Rio Grande Valley. This information can help agricultural scientists and engineers to produce large-scale maps of salt-affected lands, which will help improve salinity management in watersheds and ecosystems.

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