Classification and change detection of built-up lands from Landsat-7 ETM+ and Landsat-8 OLI/TIRS imageries: A comparative assessment of various spectral indices

Estoque, Ronald C.; Murayama, Yuji

doi:10.1016/j.ecolind.2015.03.037

Cited by 173 publications

(95 citation statements)

References 38 publications

(62 reference statements)

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“…This satellite has two earth imaging sensors on-board: the OLI and the Thermal Infrared Sensor (TIRS) [26]. The Landsat 5 and 8 images were processed using single-band extraction methods, false color composite, geometric correction and finally forming standard false color images of the Qin-Ba mountainous area (Figure 2).…”

Section: Data Collection and Analysismentioning

confidence: 99%

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Cai

Sun

et al. 2016

Sustainability

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Abstract:The Qin-Ba Ecological Functional Zone is a component of China's ecological security pattern designed to protect the regional ecosystem and maintain biodiversity. However, due to the impact of mining and urban encroachment, the plight of a sustainable ecosystem in the Qin-Ba mountainous area is deteriorating. This paper has used a remote sensing and geographic information system (GIS) to examine the impacts of mining and urban encroachment on the environment in the Qin-Ba mountainous area. The results indicate that the total mined area in 2013 was 22 km 2 and is predicted to escalate. Results also show that the ecosystems in Fengxian County, Shaanxi Province and Baokang County, Hubei Province were most severely affected by mining. Urbanization in the Qin-Ba mountainous area has seen an increase of 85.58 km 2 in urban land use from 2010 to 2013. In addition, infrastructure development including airport construction, tourism resorts and real estate development in the Qin-Ba mountainous area has intensified environmental and biodiversity disturbances since large areas of forest have been cleared. Our results should provide insight and assistance to city planners and government officials in making informed decisions.

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Section: Data Collection and Analysismentioning

confidence: 99%

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Cai

Sun

et al. 2016

Sustainability

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“…Temporal patterns of urban land expansion for each province and for the whole study [47]; GLCM mean is the mean value of the gray level co-occurrence matrix and is widely used in textural features extraction, calculated by the gray scale value of the images [48]. Elevation and slope are calculated from ASTER GDEM V1 data; NDWI is the Normalized Difference Water Index, calculated from bands three and five of Landsat OLI [49]; NDBI is the Normalized Difference Build-up Index, calculated from bands five and six of Landsat OLI [50]; and EVI/Phenology is Enhanced Vegetation Index varied in time, calculated from bands one, four, and five of Landsat OLI [51].…”

Section: Calculation Of Growth Ratementioning

confidence: 99%

Quantifying Urban Land Sprawl and its Driving Forces in Northeast China from 1990 to 2015

et al. 2018

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Drastic urbanization has resulted in numerous problems worldwide, and many studies were devoted to individual cities. There is an urgent need to quantify urbanization patterns and illustrate their driving forces in the regional area on a large scale over a longer time period. This study produced a land cover dataset to characterize sequential urban land expansion in Northeast China from 1990 to 2015 using object-based backdating classification and calculating the expansion index. The drivers were investigated using Pearson correlation analysis and the multiple linear stepwise regression model. The results revealed that the total area of urban land increased by 43.15% from 1990 to 2015, mainly in the middle part of the study area, and especially in the coastal area of Liaoning. Liaoning had the fastest growth rate, while Heilongjiang showed a decrease in growth rate rankings. Urban land expanded northward and southward within Harbin City, towards the west and east within Changchun City, and relatively equally in all directions within Shenyang City. Expansion patterns changed from edge expansion (42%) to outlying expansion (47%). Urban land of Liaoning and the Eastern Inner Mongolia Autonomous region expanded with similar patterns as the entire area, but that of Heilongjiang grew in an opposite pattern, and Jilin maintained outlying major expansion. The influence of factors on urban land sprawl varied temporally. Tertiary industry product, gross domestic product, secondary industry product, total population and urban population were driving factors of urban land sprawl in Northeast China from 1990 to 2015. This research provides quantitative methods for better understanding urban land dynamics and devising feasible strategies for sustainable urban development.

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“…Based on the same principle, the UI was designed to detect updated information about the conditions of urban areas from satellite images in the NIR and SWIR2 channels (Equation (5)) [47]. Two Vis-based indices, i.e., the VgNIR-BI and the VrNIR-BI, were proposed as techniques for extracting the built-up areas from the visible green and red channels, respectively, in combination with the NIR channel (Equations (6) and (7)) [6]. …”

Section: Comparison With Other Methodologiesmentioning

confidence: 99%

“…As a key place of material and energy input, transformation and output, built-up areas have a higher population density and various social-environmental problems when compared to their surroundings [2][3][4]. Knowledge about the extent and pattern of built-up areas can provide the necessary information for expansion monitoring, environmental change and risk assessment, and disaster management and government decision-making [5,6] in built-up areas. …”

Section: Introductionmentioning

confidence: 99%

A Strategy of Rapid Extraction of Built-Up Area Using Multi-Seasonal Landsat-8 Thermal Infrared Band 10 Images

et al. 2017

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Abstract:Recently, studies have focused more attention on surface feature extraction using thermal infrared remote sensing (TIRS) as supplementary materials. Innovatively, in this paper, using three-date (winter, early spring, and end of spring) TIRS Band 10 images of Landsat-8, we proposed an empirical normalized difference of a seasonal brightness temperature index (NDSTI) for enhancing a built-up area based on the contrast heat emission seasonal response of a built-up area to solar radiation, and adopted a decision tree classification method for the rapidly accurate extraction of the built-up area. Four study areas, including one major experimental study area (Tangshan) and three verification areas (Minqin, Laizhou, and Yugan) in different climate zones, respectively, were used to empirically establish the overall strategy system, then we specified constrained conditions of this strategy. Moreover, we compared the NDSTI to the current built-up indices, respectively, for extracting the built-up area. The results showed that (1) the new index (NDSTI) exploited the seasonal thermal characteristic variation between the built-up area and other covers in the time series analysis, helping achieve more accurate built-up area extraction than other spectral indices; (2) this strategy could effectively realize rapid built-up area extraction with generally satisfied overall accuracy (over 80%), and was especially excellent in Tangshan and Laizhou; however, (3) it may be constrained by climate patterns and other surface characteristics, which need to be improved from the view of the results of Minqin and Yugan. In summary, the method developed in this study has the potential and advantage to extract the built-up area rapidly from the multi-seasonal thermal infrared remote sensing data. It could be an operative tool for long-term monitoring of built-up areas efficiently and for more applications of thermal infrared images in the future.

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Classification and change detection of built-up lands from Landsat-7 ETM+ and Landsat-8 OLI/TIRS imageries: A comparative assessment of various spectral indices

Cited by 173 publications

References 38 publications

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Quantifying Urban Land Sprawl and its Driving Forces in Northeast China from 1990 to 2015

A Strategy of Rapid Extraction of Built-Up Area Using Multi-Seasonal Landsat-8 Thermal Infrared Band 10 Images

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