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.

Study of Ancient Land Boundaries at Tauric Chersonesos Using Satellite Images

2019 ◽  
Vol 25 (1) ◽  
pp. 44-58 ◽  
Author(s):  
Edgar A. Terekhin ◽  
Tatiana N. Smekalova
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Satellite Images ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Field Surveys ◽  
The 1960S ◽  
Better Than ◽  
Made In

Abstract The near chora (agricultural land) of Tauric Chersonesos was investigated using multiyear remote sensing data and field surveys. The boundaries of the land plots were studied with GIS (Geographic Information Systems) technology and an analysis of satellite images. Reliable reconstruction of the borders has been done for 231 plots (from a total of about 380), which is approximately 53% of the Chersonesean chora. During the last 50 years, most of the ancient land plots have been destroyed by modern buildings, roads, or forests. However, in the 1960s, a significant part of the chora was still preserved. Changes in preservation with time were studied with the aid of satellite images that were made in 1966 and 2015. During that period, it was found that the number of plots with almost-complete preservation decreased from 47 to 0. Those land plots whose preservation was better than 50% dropped from 104 to 4. A temporal map shows this decline in preservation. It was found that the areas of land plots could be determined accurately with satellite images; compared to field surveys, this accuracy was about 99%.

scholarly journals Watershed Health Changes based on Vegetated Land Cover in the Upper Citarum Watershed, West Java, Province, Indonesia

2021 ◽  
Vol 940 (1) ◽  
pp. 012045
Author(s):  
K Marko ◽  
D Sutjiningsih ◽  
E Kusratmoko
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
West Java ◽  
Health Changes ◽  
The North ◽  
Health Level ◽  
Watershed Health

Abstract The increase in built-up land and the decrease in vegetated land due to human activities have worsened watershed health from time to time. This study aims to assess the watershed’s health and changes every ten years based on the percentage of vegetated land cover except agricultural land in the Upper Citarum watershed, West Java. Land cover information was obtained from the processing of Landsat imagery in 1990, 2000, 2010, and 2020 based on remote sensing using the supervised classification method. The watershed health level is determined by calculating the percentage of vegetated land cover of 173 catchments. The results show that the area of the vegetated land cover decreased from 1990 to 2000, then increased from 2000 to 2010, and decreased again from 2010 to 2020. Changes in the area of vegetated land in each period of the year affect the health level of the watershed in a spatiotemporal manner. Although these changes occur in a fluctuating manner, the number of unhealthy catchments in the Upper Citarum watershed is increasing, especially in the Ci Kapundung sub-watershed in the north and Ci Sangkuy in the south.

scholarly journals Monitoring Changes to Arctic Vegetation and Glaciers at Ny-Ålesund, Svalbard, Based on Time Series Remote Sensing

2021 ◽  
Vol 13 (19) ◽  
pp. 3845
Author(s):  
Guangbo Ren ◽  
Jianbu Wang ◽  
Yunfei Lu ◽  
Peiqiang Wu ◽  
Xiaoqing Lu ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Time Series ◽  
High Latitude ◽  
Global Climate ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Coastal Regions ◽  
Average Annual Temperature

Climate change has profoundly affected global ecological security. The most vulnerable region on Earth is the high-latitude Arctic. Identifying the changes in vegetation coverage and glaciers in high-latitude Arctic coastal regions is important for understanding the process and impact of global climate change. Ny-Ålesund, the northern-most human settlement, is typical of these coastal regions and was used as a study site. Vegetation and glacier changes over the past 35 years were studied using time series remote sensing data from Landsat 5/7/8 acquired in 1985, 1989, 2000, 2011, 2015 and 2019. Site survey data in 2019, a digital elevation model from 2009 and meteorological data observed from 1985 to 2019 were also used. The vegetation in the Ny-Ålesund coastal zone showed a trend of declining and then increasing, with a breaking point in 2000. However, the area of vegetation with coverage greater than 30% increased over the whole study period, and the wetland moss area also increased, which may be caused by the accelerated melting of glaciers. Human activities were responsible for the decline in vegetation cover around Ny-Ålesund owing to the construction of the town and airport. Even in areas with vegetation coverage of only 13%, there were at least five species of high-latitude plants. The melting rate of five major glaciers in the study area accelerated, and approximately 82% of the reduction in glacier area occurred after 2000. The elevation of the lowest boundary of the five glaciers increased by 50–70 m. The increase in precipitation and the average annual temperature after 2000 explains the changes in both vegetation coverage and glaciers in the study period.

scholarly journals Geoecological assessment of the state of postagrogenic lands of the Moscow village soviet council of the Republic of Khakassia on the basis of remote sensing data

2020 ◽  
Vol 149 ◽  
pp. 03006 ◽  
Author(s):  
Ekaterina V. Pavlova ◽  
Anastasiia I. Volkova ◽  
Ekaterina A. Demina
Keyword(s):  
Remote Sensing ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Point Of View ◽  
Economic Point ◽  
Fallow Lands ◽  
Village Council ◽  
Qualitative State ◽  
The Republic ◽  
Map Scale

Currently, the consequences which take place in Khakassia expansion of tree-shrub vegetation on fallow lands have not been properly assessed neither from an ecological nor economic point of view. Based on the analysis of the agricultural map scale 1: 100 000 decoding images Landsat 4–5, 7, 8 and Sentinel 1, and 2, as well as subsatellite ground researches were carried out the identification, the description and assessment of the qualitative state of postagrogenic lands of Khakassia exposed to the processes of overgrowth of tree-shrub vegetation. As an example, this article analyzes the processes of overgrowth of agricultural land on the example of the territory of the Moscow village council of Ust-Abakan district. A geoinformation project of spatial distribution of postagrogenic lands within the Moscow village council of Ust-Abakan district of Khakassia was developed. The results of the research showed that in the studied area in the structure of agricultural land 67204 hectares of land belongs to the fallows located at different stages of recovery of which 77 % exposed to overgrowth processes. The obtained data indicate the need for the formation of management decisions in the field of land use.

scholarly journals A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe

2019 ◽  
Vol 11 (23) ◽  
pp. 2759 ◽  
Author(s):  
Tomáš Goga ◽  
Ján Feranec ◽  
Tomáš Bucha ◽  
Miloš Rusnák ◽  
Ivan Sačkov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
World Literature ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Field Research ◽  
Radar Data ◽  
Expert Assessment ◽  
Biomass Estimation ◽  
Agricultural Abandonment ◽  
Expert Analysis

This study aims to analyze and assess studies published from 1992 to 2019 and listed in the Web of Science (WOS) and Current Contents (CC) databases, and to identify agricultural abandonment by application of remote sensing (RS) optical and microwave data. We selected 73 studies by applying structured queries in a field tag form and Boolean operators in the WOS portal and by expert analysis. An expert assessment yielded the topical picture concerning the definitions and criteria for the identification of abandoned agricultural land (AAL). The analysis also showed the absence of similar field research, which serves not only for validation, but also for understanding the process of agricultural abandonment. The benefit of the fusion of optical and radar data, which supports the application of Sentinel-1 and Sentinel-2 data, is also evident. Knowledge attained from the literary sources indicated that there exists, in the world literature, a well-covered problem of abandonment identification or biomass estimation, as well as missing works dealing with the assessment of the natural accretion of biomass in AAL.

Determination of Drought Threshold for Agricultural Land-use using Satellite Image Analysis Techniques

2020 ◽  
Author(s):  
Jieun Kim ◽  
Jaehyung Yu ◽  
Sang Kee Seo ◽  
Jin-Hee Baek ◽  
Byung Chil Jeon
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Near Infrared ◽  
Agricultural Land ◽  
Irrigation Management ◽  
Satellite Image ◽  
Agricultural Drought ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Eastern Area

<p>The climate change causes major problems in natural disasters such as storms and droughts and has significant impacts on agricultural activities. Especially, global warming changed crops cultivated causing changes in agricultural land-use, and droughts along with land-use change accompanied serious problems in irrigation management. Moreover, it is very problematic to detect drought impacted areas with field survey and it burdens irrigation management. In South Korea, drought in 2012 occurred in western area while 2015 drought occurred in eastern area. The drought cycle in Korea is irregular but the drought frequency has shown an increasing pattern. Remote sensing approaches has been used as a solution to detect drought areas in agricultural land-use and many approaches has been introduced for drought monitoring. This study introduces remote sensing approaches to detect agricultural drought by calculation of local threshold associated with agricultural land-use. We used Landsat-8 satellite images for drought and non-drought years, and Vegetation Health Index(VHI) was calculated using red, near-infrared, and thermal-infrared bands. The comparative analysis of VHI values for the same agricultural land-use between drought year and non-drought year derived the threshold values for each type of land-use. The results showed very effective detection of drought impacted areas showing distinctive differences in VHI value distributions between drought and non-drought years.</p>

Sign in / Sign up

Export Citation Format

Share Document