Journal ArticleDOI
Determining uncertainties and their propagation in dynamic change detection based on classified remotely-sensed images
Wenzhong Shi,Manfred Ehlers +1 more
TLDR
An approach to determine uncertainties and their propagation in dynamic change detection based on classified remotely-sensed images and a visualization technique, using 3-D and colour, was developed to present uncertainties.Abstract:
This paper provides an approach to determine uncertainties and their propagation in dynamic change detection based on classified remotely-sensed images. First, the uncertainties of a classified image using maximum likelihood (ML) classification are determined. The probability vectors which are generated during the maximum likelihood classification are used as uncertainty indicators. Secondly, the uncertainty propagation of classified multi-date images is described using mathematical language for problem description. Based on this mathematical formulation, two techniques were used to calculate the uncertainty propagation. One is based on the product rule in probability theory and the other is based on a certainty factor model with probabilistic interpretation. Thirdly, a visualization technique, using 3-D and colour, was developed to present uncertainties.read more
Citations
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Remote sensing of tropical forest environments: Towards the monitoring of environmental resources for sustainable development
TL;DR: In this paper, the potential to derive indicators of sustainable resource use from satellite remote sensing is discussed, focusing on indicators related to land cover condition and type in tropical forest environments, including the mapping of forest cover, estimation of biomass and biodiversity as well as the impacts of extreme events such as drought on the forest.
Journal ArticleDOI
Land Cover Change Detection Techniques: Very-High-Resolution Optical Images: A Review
Journal ArticleDOI
National forest carbon inventories: policy needs and assessment capacity
TL;DR: In this paper, the authors provide an overview for policy makers about approaches to forest carbon inventories, paying particular attention to the contributions of remote sensing technologies, and discuss the tradeoffs between information cost, accuracy, precision, transparency and timeliness that need to be balanced in long-term monitoring of forest carbon.
Journal ArticleDOI
Quantifying Land Use Change in Zhejiang Coastal Region, China Using Multi-Temporal Landsat TM/ETM+ Images
TL;DR: Landsat Thematic Mapper (TM) and enhanced thematic mapper plus (ETM+) images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes (LUCC) in the Zhejiang coastal region with a stratified unsupervised classification technique in conjunction with visual interpretation and to attempt an identification of the socioeconomic driving forces as mentioned in this paper.
Journal ArticleDOI
Land Cover Change Detection Techniques: Very-high-resolution optical images: A review
TL;DR: In this paper , very high-resolution (VHR) remote sensing images can capture details of a ground object and offer an opportunity to detect land cover changes in detail, which is an important application of Earth observation data because it provides insights into environmental health, global warming, and city management.
References
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Book
Remote Sensing Digital Image Analysis: An Introduction
TL;DR: In this paper, the authors present an introduction to quantitative evaluation of satellite and aircraft derived from remotely retrieved data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations.
Journal ArticleDOI
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TL;DR: The history and scope of remote sensing is described in detail in this paper, where the authors present a detailed overview of the field of Remote Sensing and its application in agriculture, land use and land cover.
Journal Article
A coefficient of agreement as a measure of thematic classification accuracy.
TL;DR: In this article, a conditional coefficient of agreement for individual categories is compared to other methods for expressing category accuracy which have already been published in remote sensing literature, such as a Coefficient of Agreement as a Measure of Thematic Classification Accuracy.
Journal Article
Assessing Landsat classification accuracy using discrete multivariate analysis statistical techniques.
TL;DR: In this paper, Card et al. presented three different techniques to evaluate the accuracy of land-cover classifications from Landsat digital image y, and then analyzed using three techniques: discrete multivariate analysis, contingency table analysis, and multivariable comparison between matrices.