A Modified and Enhanced Normalized built-up Index using Multispectral and Thermal Bands

Azmi, Rida; Alami, Omar Bachir; Saadane, Abd Errahim; Kacimi, Ilias; Chafiq, Tarik

doi:10.17485/ijst/2016/v9i28/87405

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…The Normalized Difference Building Index (NDBI) [59] and the soil index (SI) [60] were utilized as composite indicators of dryness in the research region since bare soil and urban development land play a significant part in the cause of the study area's dryness. The calculation of the NDBI is shown in Equation ( 3).…”

Section: Remote Sensing Ecological Monitoring Indicatorsmentioning

confidence: 99%

Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau

Shi,

Lin,

Jing

et al. 2023

Sustainability

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Ecosystems in arid and semi-arid areas are delicate and prone to different erosive effects. Monitoring and evaluating the environmental ecological condition in such areas contribute to the governance and restoration of the ecosystem. Remote sensing ecological indices (RSEIs) are widely used as a method for environmental monitoring and have been extensively applied in various regions. This study selects the arid and semi-arid Loess Plateau as the research area, in response to existing research on ecological monitoring that predominantly uses vegetation indices as monitoring indicators for greenness factors. A fluorescence remote sensing ecological index (SRSEI) is constructed by using monthly synthesized sun-induced chlorophyll fluorescence data during the vegetation growth period as a new component for greenness and combining it with MODIS product data. The study generates the RSEI and SRSEI for the research area spanning from 2001 to 2021. The study compares and analyzes the differences between the two indices and explores the evolution patterns of the ecosystem quality in the Loess Plateau over a 21-year period. The results indicate consistent and positively correlated linear fitting trend changes in the RSEI and SRSEI for the research area between 2001 and 2021. The newly constructed ecological index exhibits a higher correlation with rainfall data, and it shows a more significant decrease in magnitude during drought occurrences, indicating a faster and stronger response of the new index to drought in the research area. The largest proportions are found in the research area’s regions with both substantial and minor improvements, pointing to an upward tendency in the Loess Plateau’s ecosystem development. The newly constructed environmental index can effectively evaluate the quality of the ecosystem in the research area.

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Section: Remote Sensing Ecological Monitoring Indicatorsmentioning

confidence: 99%

Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau

Shi,

Lin,

Jing

et al. 2023

Sustainability

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“…6). OA, CE and OE are computed by comparing the number of false and true negatives with the number of false and true positives (Azmi, Bachir Alami, Errahim Saadane, Kacimi, & Chafiq, 2016).…”

Section: Qualitative Accuracy Assessmentmentioning

confidence: 99%

Remote sensing-based mapping of the destruction to Aleppo during the Syrian Civil War between 2011 and 2017

Lubin

Saleem

2019

Applied Geography

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Accurate assessment of damage caused by conflict can be difficult to determine from ground-based surveys, particularly in the context of violence and unsafe conditions. Earth Observation data provides a non-invasive method for rapid damage assessment over wide geographic areas. In this study we use Landsat Imagery captured between 2011 and 2017 to assess the damage in Aleppo, Syria caused by conflict during the Syrian Civil War. Extracting temporal changes in urban environments is complex and the capabilities of traditional spectral-based methodologies are limited. We examined the effectiveness of the Gray-Level Co-Occurrence Matrix (GLCM) and two texture-based metrics (correlation and homogeneity) at classifying changes in reflectance characteristics within urban environments caused by building damage and consequent changes in surface orientation. Homogeneity was a more effective texture measure than correlation (overall accuracy of 79% vs 50%). Results indicated that between 45% and 57% of Aleppo was damaged during the study period, including up to 57% of former rebel held areas and between 34% and 46% of government areas and their surrounds. We used SPOT-6 imagery for accuracy assessment. Damage to Aleppo has yet to be fully quantified and several parts of the city remain unsafe and inaccessible. The results of this study highlight the potential offered by texture analysis for mapping damage to urban areas with freely available imagery and can be readily applied to natural disasters such as earthquakes and the aftermath of extreme weather events.

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Performance testing of selected spectral indices in automated extraction of impervious built-up surface features using Resourcesat LISS-III image

et al. 2020

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A Modified and Enhanced Normalized built-up Index using Multispectral and Thermal Bands

Cited by 4 publications

References 27 publications

Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau

Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau

Remote sensing-based mapping of the destruction to Aleppo during the Syrian Civil War between 2011 and 2017

Performance testing of selected spectral indices in automated extraction of impervious built-up surface features using Resourcesat LISS-III image

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