Automatic building detection from satellite images using spectral graph theory

Zakharov, A. A.; Tuzhilkin, Alexei; Zhiznyakov, A. L.

doi:10.1109/meacs.2015.7414937

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…With higher accuracy, the high resolution satellite image contains more precise information to detect the target with smaller sizes, such as buildings and ships [36], [37].…”

Section: Satellite Imagesmentioning

confidence: 99%

Weather Visibility Prediction Based on Multimodal Fusion

Zhang

Chen

et al. 2019

IEEE Access

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Visibility affects all forms of traffic: roads, sailing, and aviation. Visibility prediction is meaningful in guiding production and life. Different from weather prediction, which relies solely on atmosphere factors, the factors that affect meteorological visibility are more complicated, such as the air pollution caused by factory exhaust emission. However, the current prediction of visibility is mostly based on the numerical prediction method similar to the weather prediction. We proposed a method using multimodal fusion to build a weather visibility prediction system in this paper. An advanced numerical prediction model and a method for emission detection were used to build a multimodal fusion visibility prediction system. We used the most advanced regression algorithm, XGBoost, and LightGBM, to train the fusion model for numerical prediction. Through the estimation of factory emission by the traditional detector in the satellite image, we propose to add the result of estimation based on Landsat-8 satellite images to assist the prediction. By testing our numerical model in atmosphere data of various meteorological observation stations in Beijing-Tianjin-Hebei region from 2002 to 2018, our numerical prediction model turns out to be more accurate than other existing methods, and after fusing with emission detection method, the accuracy of our visibility prediction system has been further improved.

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“…With higher accuracy, the high resolution satellite image contains more precise information to detect the target with smaller sizes, such as buildings and ships [36], [37].…”

Section: Satellite Imagesmentioning

confidence: 99%

Weather Visibility Prediction Based on Multimodal Fusion

Zhang

Chen

et al. 2019

IEEE Access

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“…LiDAR technology automatically extracted building footprints and segment out the rooftop planes but this technology is very expensive and everyone could not afford to do that. Using Spectral Graph theory [22], automatic building detection has been done but that's also done over the USA dataset. Moreover, the houses in the USA have slanted rooftops whereas in India the rooftops are planes.…”

Section: Related Workmentioning

confidence: 99%

Solar Potential Analysis of Rooftops Using Satellite Imagery

Kumar

2018

Preprint

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Solar energy is one of the most important sources of renewable energy and the cleanest form of energy. In India, where solar energy could produce power around trillion kilowatt hours in a year, we are producing only power of around in gigawatts only. Many people are not aware of the solar potential of their rooftop and hence they always think that installing solar panels is very much expensive. In this work, we introduce an approach through which we can generate a report remotely that provides the amount of solar potential of a building using only its latitude and longitude. We further evaluated various types of rooftops to make our solution more robust. We also provide an approximate area of rooftop that can be used for solar panels placement and a visual analysis of how solar panels can be placed to maximize the output of solar power at a location.

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“…The key role of operator is to identify rooftops of the buildings, defining the walls and borders which is tedious and expensive work. Manually marking of buildings in the aerial or satellite image has certain limitations [1]. It is possible to render buildings visible from various angles as they may not have an exact articulation.…”

Section: Introductionmentioning

confidence: 99%

A Gabor Filter-Based Protocol for Automated Image-Based Building Detection

et al. 2021

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Detecting buildings from high-resolution satellite imagery is beneficial in mapping, environmental preparation, disaster management, military planning, urban planning and research purposes. Differentiating buildings from the images is possible however, it may be a time-consuming or complicated process. Therefore, the high-resolution imagery from satellites needs to be automated to detect the buildings. Additionally, buildings exhibit several different characteristics, and their appearance in these images is unplanned. Moreover, buildings in the metropolitan environment are typically crowded and complicated. Therefore, it is challenging to identify the building and hard to locate them. To resolve this situation, a novel probabilistic method has been suggested using local features and probabilistic approaches. A local feature extraction technique was implemented, which was used to calculate the probability density function. The locations in the image were represented as joint probability distributions and were used to estimate their probability distribution function (pdf). The density of building locations in the image was extracted. Kernel density distribution was also used to find the density flow for different metropolitan cities such as Sydney (Australia), Tokyo (Japan), and Mumbai (India), which is useful for distribution intensity and pattern of facility point f interest (POI). The purpose system can detect buildings/rooftops and to test our system, we choose some crops with panchromatic high-resolution satellite images from Australia and our results looks promising with high efficiency and minimal computational time for feature extraction. We were able to detect buildings with shadows and building without shadows in 0.4468 (seconds) and 0.5126 (seconds) respectively.

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Automatic building detection from satellite images using spectral graph theory

Cited by 10 publications

References 15 publications

Weather Visibility Prediction Based on Multimodal Fusion

Weather Visibility Prediction Based on Multimodal Fusion

Solar Potential Analysis of Rooftops Using Satellite Imagery

A Gabor Filter-Based Protocol for Automated Image-Based Building Detection

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