2018
DOI: 10.4236/jgis.2018.101003
|View full text |Cite
|
Sign up to set email alerts
|

Application of Remote Sensing Techniques and Geographic Information Systems to Analyze Land Surface Temperature in Response to Land Use/Land Cover Change in Greater Cairo Region, Egypt

Abstract: The Greater Cairo Region (GCR), Egypt has experienced rapid urban expansion and broad development over the past several decades. Due to such development, this region faces many environmental consequences. In order to mitigate such consequences, it is essential to examine the historical change to measure the urban sprawl of GCR, and its effect on land surface temperature (LST). The objective of this study is to fulfill this goal. It does so by generating land use/land cover (LULC) maps derived from Landsat 5 TM… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

3
35
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
5
3
1
1

Relationship

3
7

Authors

Journals

citations
Cited by 65 publications
(38 citation statements)
references
References 53 publications
3
35
0
Order By: Relevance
“…Cross tabulation analysis and post classification comparison were applied to evaluate the quantity of temporal conversions and nature of changes from one land cover category to another in land use maps of 1992 and 2011 [61][62][63]. In the UWBDR, a comparison of land use maps for the years 1992 and 2011 indicated that the most significant changes occurred in three classes: developed urban, planted, and forest ( Figure 5).…”
Section: Changes In Land Use Characteristicsmentioning
confidence: 99%
“…Cross tabulation analysis and post classification comparison were applied to evaluate the quantity of temporal conversions and nature of changes from one land cover category to another in land use maps of 1992 and 2011 [61][62][63]. In the UWBDR, a comparison of land use maps for the years 1992 and 2011 indicated that the most significant changes occurred in three classes: developed urban, planted, and forest ( Figure 5).…”
Section: Changes In Land Use Characteristicsmentioning
confidence: 99%
“…Using the Landsat imagery as a reference, 90 points were used to compare features interpreted on the imageries and their corresponding output in the classification. The point comparison detected the correctly classified pixels, pixels assigned to a certain class that did not belong to it (commission errors) and pixels that belong to one class but are included into other classes (omission errors) (Tran et al 2017, Aboelnour, Engel 2018. The overall accuracy was then computed using the following expression:…”
Section: Image Classificationmentioning
confidence: 99%
“…Statistics for change detection from the land-use maps have been obtained over time (1992 and 2011) for this research through the thematic overlay of the classified land-use maps using pixel-by-pixel cross-tabulation analysis. This was used to evaluate the "from-to" change detection matrix table that shows the major gains and losses in each category [55][56][57].…”
Section: Land-use Change Detectionmentioning
confidence: 99%