Change detection study of Kuwait City and environs using multi-temporal Landsat Thematic Mapper data

Kwarteng, Andy Y.; Chavez, Pat S.

doi:10.1080/014311698215162

Cited by 92 publications

(60 citation statements)

References 4 publications

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“…Many publications illustrate the automatic or semi-automatic spectral analysis of medium to high spatial resolution data, e.g., Landsat TM, SPOT HRV. Spectrally derived land cover classifications are further enhanced by visual interpretation of either airphoto, or more recently, of very fine spatial resolution (VHR) optical satellite imagery, e.g., IKONOS or Quickbird [11][12][13][14][15][16]. Other methodologies have made use of vegetation indices or developed built-up indices derived from multispectral Landsat TM data [17][18][19].…”

Section: Applying Remote Sensing Imagery For Urban and Population Stumentioning

confidence: 99%

Population Growth and Its Expression in Spatial Built-up Patterns: The Sana’a, Yemen Case Study

Zeug

Eckert²

2010

Remote Sensing

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Abstract:In light of rapid global urbanisation, monitoring and mapping of urban and population growth is of great importance. Population growth in Sana'a was investigated for this reason. The capital of the Republic of Yemen is a rapidly growing middle sized city where the population doubles almost every ten years. Satellite data from four different sensors were used to explore urban growth in Sana'a between 1989 and 2007, assisted by topographic maps and cadastral vector data. The analysis was conducted by delineating the built-up areas from the various optical satellite data, applying a fuzzy-rule-based composition of anisotropic textural measures and interactive thresholding. The resulting datasets were used to analyse urban growth and changes in built-up density per district, qualitatively as well as quantitatively, using a geographic information system. The built-up area increased by 87 % between 1989 and 2007. Built-up density has increased in all areas, but particularly in the northern and southern suburban districts, also reflecting the natural barrier of surrounding mountain ranges. Based on long-term population figures, geometric population growth was assumed. This hypothesis was used together with census data for 1994 and 2004 to estimate population figures for 1989 and 2007, resulting in overall growth of about 240%. By joining population figures to district boundaries, the spatial patterns of population distribution and growth were examined. Further, urban built-up growth and population changes over time were brought into relation in order to investigate OPEN ACCESSRemote Sensing 2010, 2 1015 changes in population density per built-up area. Population densities increased in all districts, with the greatest density change in the peripheral areas towards the North. The results reflect the pressure on the city's infrastructure and natural resources and could contribute to sustainable urban planning in the city of Sana'a.

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Section: Applying Remote Sensing Imagery For Urban and Population Stumentioning

confidence: 99%

Population Growth and Its Expression in Spatial Built-up Patterns: The Sana’a, Yemen Case Study

Zeug

Eckert²

2010

Remote Sensing

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“…The images comprised both of high surface brightness (light, white) and low surface brightness (dark, black) areas.In images with two distinct light and dark areas, the use of normal contrast stretching techniques, such as linear stretching and edge enhancement, to simultaneously enhance the local details in both regions do not yield satisfactory results (Chavez 1984). Such conditions are typically observed in arid environment, where the spectral reflections are dominated by high values from the bright soil and vegetation (Kwarteng and Chavez 1998). Principal Component Analysis (PCA) In multi-band remote sensing images, the bands are the original variable.…”

Section: Data Settings and Pre-processingmentioning

confidence: 99%

Impact Analysis of Oil Pollution using Change Detection Techniques in Kuwait

Shafiullah¹

2016

IJEAB

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“…Our methodology makes use of Landsat 7 Enhanced Thematic Mapper Plus (ETMþ) imagery, available at 30 m spatial resolution ( [56]; available for download at: http://earthexplorer.usgs.gov), which has previously been found to have utility in desert areas [47,57]. One minor limitation of the Landsat 7 ETMþ sensor is that the Scan-Line-Corrector is off (SLC-off) owing to a technical malfunction, causing approximately 22% of data from any given Landsat 7 ETMþ image to be lost [58]; 'striping' of missing data is apparent in the images.…”

Section: (B) Satellite Datamentioning

confidence: 99%

Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from space

Duncan

Kretz

Wegmann

et al. 2014

Phil. Trans. R. Soc. B

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Deserts are among the most poorly monitored and understood biomes in the world, with evidence suggesting that their biodiversity is declining fast. Oil exploration and exploitation can constitute an important threat to fragmented and remnant desert biodiversity, yet little is known about where and how intensively such developments are taking place. This lack of information hinders local efforts to adequately buffer and protect desert wildlife against encroachment from anthropogenic activity. Here, we investigate the use of freely available satellite imagery for the detection of features associated with oil exploration in the African Sahelo-Saharan region. We demonstrate how texture analyses combined with Landsat data can be employed to detect ground-validated exploration sites in Algeria and Niger. Our results show that site detection via supervised image classification and prediction is generally accurate. One surprising outcome of our analyses is the relatively high level of site omission errors in Niger (43%), which appears to be due to non-detection of potentially small-scale, temporary exploration activity: we believe the repeated implementation of our framework could reduce the severity of potential methodological limitations. Overall, our study provides a methodological basis for the mapping of anthropogenic threats associated with oil exploitation that can be conducted across desert regions.

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Change detection study of Kuwait City and environs using multi-temporal Landsat Thematic Mapper data

Cited by 92 publications

References 4 publications

Population Growth and Its Expression in Spatial Built-up Patterns: The Sana’a, Yemen Case Study

Population Growth and Its Expression in Spatial Built-up Patterns: The Sana’a, Yemen Case Study

Impact Analysis of Oil Pollution using Change Detection Techniques in Kuwait

Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from space

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