Hyperspectral Remote Sensing of Urban Areas

Hardin, Perry J.; Hardin, Andrew

doi:10.1111/gec3.12017

Cited by 24 publications

(8 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Especially in the past decade there has been a steady growth in the development and availability of new sensors able to better cope with the challenges outlined above. Two technologies that have made remarkable contributions are hyperspectral remote sensing, also referred to as imaging spectroscopy, and Light Detection And Ranging (LiDAR) [9][10][11]. As opposed to broadband multispectral sensors, hyperspectral sensors tend to extensively cover both the VNIR and SWIR regions with a high number (ranging from tens to hundreds) of narrowly defined spectral bands, allowing them to capture even subtle spectral features, strongly improving the ability to discriminate different materials and in some cases even material conditions [10].…”

Section: Introductionmentioning

confidence: 99%

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Priem

Canters

2016

Remote Sensing

View full text Add to dashboard Cite

Land cover mapping of the urban environment by means of remote sensing remains a distinct challenge due to the strong spectral heterogeneity and geometric complexity of urban scenes. Airborne imaging spectroscopy and laser altimetry have each made remarkable contributions to urban mapping but synergistic use of these relatively recent data sources in an urban context is still largely underexplored. In this study a synergistic workflow is presented to cope with the strong diversity of materials in urban areas, as well as with the presence of shadow. A high-resolution APEX hyperspectral image and a discrete waveform LiDAR dataset covering the Eastern part of Brussels were made available for this research. Firstly, a novel shadow detection method based on LiDAR intensity-APEX brightness thresholding is proposed and compared to commonly used approaches for shadow detection. A combination of intensity-brightness thresholding with DSM model-based shadow detection is shown to be an efficient approach for shadow mask delineation. To deal with spectral similarity of different types of urban materials and spectral distortion induced by shadow cover, supervised classification of shaded and sunlit areas is combined with iterative LiDAR post-classification correction. Results indicate that height, slope and roughness features contribute to improved classification accuracies in descending order of importance. Results of this study illustrate the potential of synergistic application of hyperspectral imagery and LiDAR for urban land cover mapping.

show abstract

Section: Introductionmentioning

confidence: 99%

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Priem

Canters

2016

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Ref. [17] presented a review of latest advances made in recent years in both the technological part and with respect to the processing of hyperspectral observations in the field of urban forests. Typical applications include mapping of surfaces covered with trees, transport network planning, studying urban heat islands, and measurement of vegetation stress, etc.…”

Section: Systems For Tree Stress Detection Based On Imagerymentioning

confidence: 99%

Remote Sensing to Detect and Monitor Trees in Various Environments: Case Studies in Chile

Staub¹

2018

Recent Advances and Applications in Remote Sensing

View full text Add to dashboard Cite

Today, the presence of green areas in cities plays an important role for the well-being of its inhabitants and its sustainable development. Modern cities need green spaces for environmental, psychological, esthetic, economic, and social reasons. In this meaning, Chilean cities, although Chile is still considered by the United Nations 1 as a developing economy, are no exception. Given the importance of this common good, it is necessary to optimize its permanent care. An incident factor in the deterioration of vegetation in urban and rural areas is stress, which can be of biotic or abiotic origin. One way to systematize care of trees is by the application of multispectral sensors and modern digital image processing. Once plantations or trees are spectrally characterized, one can proceed to develop plant health mitigation programs. This article shows the potential of remote sensing for tree stress detection, in the central south of Chile. Focus is given on rural areas as forestry for the Chilean economy is of great importance. These approaches can easily be adapted to urban scenarios.

show abstract

“…Hyperspectral images comprise a rich of data, but interpreting them needs a sympathetic of exactly what ground materials properties that can try to measure, and how relate to the measurements essentially made by the hyperspectral sensor. Imaging spectrometers are instruments which used for producing hyperspectral images [2]. The ratio of reflected energy to incident energy as a function of wavelength is called spectral reflectance.…”

Section: Introductionmentioning

confidence: 99%

Classification of Hyperspectral Remote Sensing for Production Minerals Mapping Using Geological Map and Geomatics Techniques

Jaber¹,

2018

IJET

View full text Add to dashboard Cite

The classification of hyperspectral images is an interesting job since the data dimension is huge for conventional classification procedures; normally several hundreds of spectral bands are attained for each image. These spectral bands can supported very rich spectral data of each pixel to find objects material .The objective of this research is to classify hyperspectral images for detection and production of detailed minerals mapping using geological map and Environment for Visualizing Images (ENVI) software. In this research, ASTER data and geological map have been used. Some techniques on these data are used such as enhancement, matching (linking), De-correlation, Band Ratio, stacking image and classification. The results showed that comparison of the two classification results showed the classification of stack image with the aspect and the slope provide more information than classification of ASTER image alone. Also, using ENVI software to generate 3D surface views.It concluded that capability of hyperspectral and its differentiation with multispectral data to extract detailed features from ASTER image.

show abstract

Hyperspectral Remote Sensing of Urban Areas

Cited by 24 publications

References 79 publications

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Remote Sensing to Detect and Monitor Trees in Various Environments: Case Studies in Chile

Classification of Hyperspectral Remote Sensing for Production Minerals Mapping Using Geological Map and Geomatics Techniques

Contact Info

Product

Resources

About