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3 Geomatics, Landmanagement and Landscape

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Use of remote sensing as an indicator of the urban heat island effect: the case of the municipality of Guelma (north-east of Algeria)

100%

Khallef B.

Geomatics, Landmanagement and Landscape

2023

tom no. 3

61--72

The main objective of this study is to show which of the LST-NDVI and LST-NDBI relationships can determine the most accurate index that can be used as an indicator of the effects of urban heat islands in the municipality of Guelma, using Landsat data. 8 OLI/TIRS and the geographic information system. The application of the calculation formulas made it possible to extract the Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built up Index (NDBI) of the municipality of Guelma for the four seasons of 2019. This calculation led to the determination of the relationship between all three indicators. The results obtained show a strong correlation between the LST and the NDBI for the four seasons of the year. They suggest that the NDBI is an accurate indicator of the heat island effect in Guelma. This indicator can serve as a tool for future urban planning by those in charge of this department. However, there is currently and urgent need to strengthen strategies for reducing the effects of urban heat islands in order to preserve the quality of urban life of the inhabitants and by setting up emergency programs.

Assessment of the quality of the ecological environment of an area with tourist potential using the remote sensing ecological index: Case of El Kala National Park (Algeria)

51%

Karima C. , Zennir R. , Khallef B.

Geomatics, Landmanagement and Landscape

2024

tom no. 2

31--52

The assessment of the ecological quality of the environment in El Kala National Park plays an important role in the protection and management of its tourist potential in the face of ecological constraints that have arisen. The present study is based on the use of remote sensing data; its main objective is to analyze the ecological quality in a protected area using the remote sensing ecological index which is based on the calculation of vegetation indices based on Landsat images taken in 2013 and 2023. This observation period shows that the values of drought, temperature, and humidity in the study area increased while the greenness values decreased. The RSEI index was calculated using principal component analysis of the fourth indicators (NDVI, WET, NDBSI, and LST) which made it possible to quantitatively analyze, monitor, and dynamically evaluate changes in the ecological quality of the environment in this park over the past 10 years. The results obtained show that the spatio-temporal distribution of the ecological quality of the environment of the park experienced a downward trend from 2013 to 2023 with a regression rate of -10.16% for the classes of good and excellent quality ecological. This study is considered a reference for the formulation of measures aimed at protecting the quality of the environment in El Kala National Park, and also a database to determine monitoring indicators for sites characterized by significant tourism potential.

A study of vegetation cover dynamics using landsat images: case of the beni haroun watershed (Algeria)

51%

Roukia N. , Abdelaziz L. , Khallef B.

Geomatics, Landmanagement and Landscape

2023

tom no. 4

315--328

Conducting a diachronic study of vegetation cover helps to assess its transformations over a period of time, allowing for a comprehensive assessment of the factors influencing these transformations. The purpose of this research is to analyze the vegetation cover spatio-temporal changes within Beni Haroun watershed, located in the northeast region of Algeria. Based on remote sensing data, two satellite images for the years 2009 and 2020 from Landsat 7 ETM+ and Landsat 8 OLI/TIRS were downloaded. The Normalized Difference Vegetation Index was employed to remotely detect and monitor the changes of the vegetation cover. It was calculated for both chosen dates, and the results were classified into four classes (no vegetation, sparse vegetation, moderate vegetation, dense vegetation), each representing a different vegetation density. The obtained maps showed a regression of the vegetation cover. The NDVI values have decreased from 0.77 in 2009 to 0.58 in 2020. Spatial patterns in the classified NDVI maps illustrated reduced vegetation cover demonstrated by an expansion of the no vegetation class: 35,3479 ha in 2009 and 56,7916 ha in 2020. The final map of the change detection depicted a predominance of the negative change throughout Beni Haroun watershed, in consequence of various controlling factors, including climate and human interventions.