Spatial resolution of remotely sensed imagery A review paper

Forshaw, M; Haskell, Arnold L.; Miller, P. F.; Stanley, David; Townshend, J. R. G.

doi:10.1080/01431168308948568

Cited by 58 publications

(19 citation statements)

References 5 publications

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“…Consequently, considering the four-dimensional spectroscopy scale scheme, spatial resolution is equal to the elementary pixel size of a remotely sensed image and spatial extent corresponds to the total area covered within an image swath. These spatial parameters are functions of the digital matrix of the spectral sensor and the 'instantaneous field of view' (IFOV) given by the optical system, flight altitude, and its flight velocity, respectively (Forshaw et al, 1983).…”

Section: Scale Definitions and Parameters In Imaging Spectroscopymentioning

confidence: 99%

Scaling dimensions in spectroscopy of soil and vegetation

Malenovský

Bartholomeus

Júnior

et al. 2007

International Journal of Applied Earth Observation and Geoinfor

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Section: Scale Definitions and Parameters In Imaging Spectroscopymentioning

confidence: 99%

Scaling dimensions in spectroscopy of soil and vegetation

Malenovský

Bartholomeus

Júnior

et al. 2007

International Journal of Applied Earth Observation and Geoinfor

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“…In fact, no single quantitative definition of spatial resolution exists. Several definitions have been proposed, based on, for example, the geometrical properties of the sensor (such as instantaneous field of view), the ability to separate point targets (point spread function), the ability to measure periodicity of repetitive targets (modulation transfer function) and the ability to measure spectral properties of small objects (effective resolution element) (Townshend 1981, Forshaw et al 1983, Cracknell 1998, Fisher 1998. In general terms, spatial resolution refers to the spatial detail of remotely sensed imagery.…”

Section: Spatial Variabilitymentioning

confidence: 99%

On scales and dynamics in observing the environment

Aplin

2006

International Journal of Remote Sensing

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Natural and anthropogenic processes at the Earth's surface operate at a range of spatial and temporal scales. Different scales of observation are required to match the spatial scales of the processes under observation. At the same time, the temporal sampling rate of the observing systems must be reconciled with the dynamics of the processes observed. Bringing together these issues requires insight, innovation and, inevitably, compromise. This paper reviews spatial and temporal considerations in remote sensing and introduces the papers in this Special Issue on 'Scales and Dynamics in Observing the Environment'. The review comprises three main sections. The first section focuses on spatial variability in remote sensing, while the second section focuses on temporal variability in remote sensing. The third section links these two issues, focusing on the interplay of space and time in remote sensing. The review is primarily theoretical, explaining spatial and temporal properties of remote sensing and remotely sensed phenomena. Where appropriate, however, practical examples are included to demonstrate how remote sensing is used in environmental applications. Following the review, the papers included in the Special Issue are introduced, outlining their significance in the context of 'Scales and Dynamics in Observing the Environment'.

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“…There are numerous definitions of the term scale (Lam & Quattrochi 1992;Ruddell & Wentz 2009;Wu & Li 2009). Throughout this thesis, when discussing remote sensing data, it is defined as the measurement scale or resolution, which refers to the smallest distinguishable part of an object (Forshaw et al 1983), or the degree of detail, or the sampling unit. On the other hand, when dealing with mangrove spatial ecology, the term scale refers to the operational scale, which is the spatial (or temporal) extent at which processes operate in the environment (Cao & Lam 1997;Wu & Li 2009).…”

Section: Scale Issues In Remote Sensing and Ecologymentioning

confidence: 99%

“…Although image pixel size is not identical to the image spatial resolution (Forshaw et al 1983;Warner et al 2009), for the sake of simplicity they are used to represent the actual sampling size of the image datasets explored in this thesis.…”

Section: Scale Issues In Remote Sensing and Ecologymentioning

confidence: 99%

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Remote sensing for multi-scale mangrove mapping

Kamal¹

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Understanding the relationships between the size of mangrove vegetation features and the optimum image pixel size required to map these features is essential to support effective mapping and monitoring activities in this environment. Currently mangroves are under pressure from anthropogenic and natural disturbances, and up-to-date and accurate spatial information is required to support their management. Addressing ecological problems at the correct spatial scale is essential in mangrove environments. There is a lack of knowledge on the types and biophysical properties of mangroves, which can be mapped at different image spatial resolutions. This thesis integrated the spatial and temporal dimension of remote sensing data into a spatio-temporal continuum of mangrove ecology and developed guidelines for multi-scale image-based mangrove mapping. Three objectives were addressed to achieve the aim: (1) characterising mangrove spatial structure to produce an optimum pixel resolution scheme for image-based mangrove mapping; (2) assessing the applicability of the scheme to selected images for mangrove composition and leaf area index (LAI) mapping; and (3) developing guidelines for multi-scale mangrove mapping. The research sites were located in Moreton Bay, Australia, and Karimunjawa Island, Indonesia. Landsat TM, ALOS AVNIR-2, and WorldView-2 images were used for both sites; with additional LiDAR data and a very high-spatial resolution aerial photograph for Moreton Bay.After two introductory chapters, chapter three focused on the development of a method for estimating the optimum pixel size to map different sizes of mangrove features accurately. The extent of dominant mangrove structural features including tree/shrub crowns, canopy gaps and vegetation formation or community, could be detected using semi-variogram analysis applied to image datasets with different spatial resolutions. The findings showed a gradual loss of mangrove information detail with increasing pixel size. Specific mangrove features could be optimally mapped from a specific pixel size and spectral bands or indices. A pixel size of ≤ 2 m was suitable for mapping canopy and inter-canopy-related features within mangrove vegetation features (such as shrub crown, canopy gaps and single tree crowns), while a pixel size of ≥ 4 m was appropriate for mapping mangrove vegetation formation, communities and larger mangrove features. An optimum pixel resolution scheme was produced for mangrove mapping that served as a basis for an inversion approach to map mangrove features using remote sensing image datasets.Chapters 4 and 5 focused on the application of the optimum pixel size scheme to the selected images with different spatial resolutions, to map mangrove composition and LAI, respectively.Object-based image analysis successfully produced mangrove composition maps at discrete spatial ii scales. The findings suggested that the accuracy of the maps was a result of the interaction between the image spatial resolution, the scale of the targeted objects and t...

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Spatial resolution of remotely sensed imagery A review paper

Cited by 58 publications

References 5 publications

Scaling dimensions in spectroscopy of soil and vegetation

Scaling dimensions in spectroscopy of soil and vegetation

On scales and dynamics in observing the environment

Remote sensing for multi-scale mangrove mapping

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