Monitoring Land Use/Land Cover Changes Around Damietta Promontory, Egypt, Using RS/GIS

Esmail, Mohammed; Masria, Ali; Negm, Abdelazim

doi:10.1016/j.proeng.2016.07.515

Cited by 30 publications

(11 citation statements)

References 3 publications

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“…The samples were equally distributed and scattered over the study area. The maximum likelihood (MLH) supervised method was used to classify the multispectral images [24]. Before the classification, created a new subset of the images and training samples data were selected with the region of interest (ROI) to classify the land cover changes assessment.…”

Section: Methodsmentioning

confidence: 99%

Land Covers Change Assessment After Small Dam’s Construction Based on the Satellite Data

et al. 2019

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The small dams were constructed in the study area for storing the rainwater. The present study was conducted to assess the impact of small dams on the LCC (Land Cover Change) in Nangarparkar, Pakistan based on the satellite data. The ENVI (Environment for Visualizing Images) software was used for classification of the four year’s images and three classes viz. water, vegetation, and soil were taken for detection of LCC. The MLH (Maximum Likelihood) supervised method was used to classify the multispectral satellite images. The classified results of the classes were found different each year before and after dam construction. Average results of the two years before dam’s construction revealed that water availability, vegetation cover and soil cover was 3.02%, 18.52%, and 32.30% respectively. However, after the dam construction, the water availability, vegetation cover and soil cover was 8.49%, 34.33%, and 17.15% respectively. Overall results revealed that water availability and vegetation cover were increased by 5.47 % and 15.18% respectively while soil cover decreased 15.15% after the construction of dams. Hence, based on the results, it is confirmed that the constructions of small dams have a direct and indirect positive impact on the land cover changes and it can play an important role in the resettlement of the communities of the arid areas.

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Section: Methodsmentioning

confidence: 99%

Land Covers Change Assessment After Small Dam’s Construction Based on the Satellite Data

et al. 2019

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“…• Geodata: Includes All Satellite Images from Lanasat, Which Obtained from United States Geological Survey (USGS) As Shown in The Table (1), And Aerial Photos That Obtained by Using " Google Earth Pro" Application, Which Contained an Archive of Aerial Photos "Image History", And It Was Used the Aerial Photos for The Years (1985,1990,1995,2000,2005,2010,2015,2019) (Alsaleh, 2010). In The Study, A Supervised Classification of Satellite Images Was Performed, Then Assessment of Classification Accuracy Was Done On the Classified Images by Kappa Index and Confusion Matrix (Keshtkar Et Al., 2017;Esmail Et Al., 2016) -Change in land use for the university district during the period between 2010 and 2015. This stage was marked by the influx of thousands of syrian refugees in 2011, the population of the district reached (743980 people) in the year 2015, of whom (339202 people) 46% were non-jordanians).…”

Section: Study Area University District-ammanmentioning

confidence: 99%

Detecting Land Use Change in The Jordan University District During the Period of (1985-2019) Using GIS and Remote Sensing

Salameh¹,

Al-Sagarat

2021

ijbass

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This study aimed to evaluate the changes in usage patterns of lands in Jordan University district for the period (1985-2019), demonstrate the impact of natural factors, humans, in the use of change, and identify the trend of urbanization. To achieve the study objectives, the analytical method, descriptive method, and historical method were used, it also relied on Landsat satellite images, images by Google Earth Pro, and metadata serving the subject of study. The study findings demonstrated the changing in the land use due to increasing urban lands by 12.5% during the study period, decreasing agricultural lands by –40%, decreasing rangeland by -49%, decreasing barren lands by -42.6%, and decreasing forest area by -50.5%. The study used logistic regression, to predict the usage area of urban and agriculture aspects, and it is demonstrated increasing the urban land by (110823donums) of the district's area, and decreasing the agriculture lands by 2029.

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“…For example, several researches show that good scenery is an important criterion for site selection in building development and, therefore, it adds an economic value to the property values. For these and many other reasons, management of coastal landscapes is a complex issue due to inherent biophysical diversity of ecological systems and competing demands of land uses (Aguilar, Ano, Valera, & Sanchez, 2006;Alphan & Guvensoy, 2016;Basnou et al, 2013;Esmail, Ali, & Negm, 2016;Hossen & Negm, 2016;Parcerisas et al, 2012;Zitti, Ferrara, Perini, Carlucci, & Salvati, 2015).…”

Section: Modelling Of Future Developmentmentioning

confidence: 99%

Quantitative Approach for Complementary Analysis of a Touristic Coastal Landscape: The Case of Erdemli (Mersin), Turkey.

Alphan¹

2020

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Monitoring Land Use/Land Cover Changes Around Damietta Promontory, Egypt, Using RS/GIS

Cited by 30 publications

References 3 publications

Land Covers Change Assessment After Small Dam’s Construction Based on the Satellite Data

Land Covers Change Assessment After Small Dam’s Construction Based on the Satellite Data

Detecting Land Use Change in The Jordan University District During the Period of (1985-2019) Using GIS and Remote Sensing

Quantitative Approach for Complementary Analysis of a Touristic Coastal Landscape: The Case of Erdemli (Mersin), Turkey.

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