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502 results in Remote sensing and GIS

Page 8 of 26

  • 4 - Image Fusion: Model Based Approach with Degradation Estimation

  • Manjunath V. Joshi, Kishor P. Upla
  • Book:
    Multi-resolution Image Fusion in Remote Sensing
    Published online:
    06 December 2018
    Print publication:
    24 January 2019, pp 80-139

  • Summary

    Recently, many researchers have attempted to solve the problem of multi-resolution image fusion by using model based approaches, with emphasis on improving the fused image quality and reducing color distortion [273, 121]. They model the low resolution (LR) MS image as a blurred and noisy version of its ideal high resolution (HR) fused image. Solving the problem of fusion by the model based approach is desirable since the aliasing present due to undersampling of the MS image can be taken care of while modelling. Fusion using the interpolation of MS images and edge-preserving filters as given in Chapter 3 do not consider the effect of aliasing which is due to undersampling of MS images. The aliasing in the acquired image causes distortion and, hence, there exists degradation in the LR MS image. In this chapter, we propose a model based approach in which a learning based method is used to obtain the required degradation matrix that accounts for aliasing. Using the proposed model, the final solution is obtained by considering the model as an inverse problem. The proposed approach uses sub-sampled as well as non sub-sampled contourlet transform based learning and a Markov random field (MRF) prior for regularizing the solution.

    Previous Works

    As stated earlier, many researchers have used the model based approach for fusion with the emphasis on improving fusion quality and reducing color distortion [6, 149, 105, 273, 143, 116, 283, 76, 121]. Aanaes et al. [6] have proposed a spectrally consistent method for pixel-level fusion based on the model of the imaging sensor. The fused image is obtained by optimizing an energy function consisting of a data term and a prior term by using pixel neighborhood regularization. Image fusion based on a restoration framework is suggested by Li and Leung [149] who modelled the LR MS image as a blurred and noisy version of its ideal. They also modelled the Pan image as a linear combination of true MS images. The final fused image was obtained by using a constrained least squares (CLS) framework. The same model with maximum a posteriori (MAP) framework was used by Hardie et al. and Zhang et al. [105, 273]. Hardie et al. [105] used the model based approach to enhance the hyper-spectral images using the Pan image.

  • 6 - Image Fusion: Application to Super-resolution of Natural Images

  • Manjunath V. Joshi, Kishor P. Upla
  • Book:
    Multi-resolution Image Fusion in Remote Sensing
    Published online:
    06 December 2018
    Print publication:
    24 January 2019, pp 180-202

  • Summary

    Increasing the spatial resolution of a given test image is of interest to the image processing community since the enhanced resolution of the image has better details when compared to the corresponding low resolution image. Super-resolution (SR) is an algorithmic approach in which a high spatial resolution image is obtained by using single/multiple low resolution observations or by using a database of LR–HR pairs. The linear image formation model discussed for image fusion in Chapter 4 is extended here to obtain an SR image for a given LR test observation. In the image fusion problem, the available Pan image was used in obtaining a high resolution fused image. Similar to the fusion problem, SR is also concerned with the enhancement of spatial resolution. However, we do not have a high resolution image such as a Pan image as an additional observation. Hence, we make use of a database of LR–HR pairs in order to obtain the SR for the given LR observation. Here, we use contourlet based learning to obtain the initial SR estimate which is then used in obtaining the degradation as well as the MRF parameter. Similar to the fusion problem discussed in Chapter 4, an MAP–MRF framework is used to obtain the final SR image. Note that we are not using the self-learning and sparse representation based approach proposed in Chapter 5 to obtain the fused image since the objective of this chapter is to illustrate a new approach for SR using the data model used in fusion.

    Related Work

    The low cost and ease of operation have significantly contributed to the growing popularity of digital imaging systems. Low cost cameras are fitted with low precision optics and lesser density detectors. Images captured using such a camera suffer from the drawback of reduced spatial resolution compared to traditional film cameras. Images captured using a camera fitted with high precision optics and image sensors comprising high density detectors provide better details that are essential in many imaging applications such as medical imaging, remote sensing and surveillance. However, the cost of such a camera is prohibitively high and obtaining a high resolution image is an important concern in many commercial applications requiring HR imaging. Images captured using a low cost camera represent the under-sampled images of a scene containing aliasing, blur and noise.

Multi-resolution Image Fusion in Remote Sensing
  • Manjunath V. Joshi, Kishor P. Upla
  • Published online:
    06 December 2018
    Print publication:
    24 January 2019
  • Written in an easy-to-follow approach, the text will help the readers to understand the techniques and applications of image fusion for remotely sensed multi-spectral images. It covers important multi-resolution fusion concepts along with the state-of-the-art methods including super resolution and multi stage guided filters. It includes in depth analysis on degradation estimation, Gabor Prior and Markov Random Field (MRF) Prior. Concepts such as guided filter and difference of Gaussian are discussed comprehensively. Novel techniques in multi-resolution fusion by making use of regularization are explained in detail. It also includes different quality assessment measures used in testing the quality of fusion. Real-life applications and plenty of multi-resolution images are provided in the text for enhanced learning.

  • 2 - Introduction to Remote Sensing for Conservation Practitioners

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 26-53

  • Summary

    This introductory chapter guides the reader through the concept of remote sensing with a specific focus on the interests and needs of the conservation community. It begins with a brief history and key milestones in remote sensing, and then provides a technical overview. The reader is introduced to the basic physics of electromagnetic radiation and how it interacts with the Earth surface and atmosphere. This is followed by a description of satellite and sensor characteristics and the various processing steps required to obtain geometrically and radiometrically corrected images. The key to making satellite images useful is the process of turning raw pixel data into information; thus common data processing methods as well as some of the derived products used by authors in the following chapters of this book are presented. The ultimate aim of this chapter is to stimulate the interest of the non-remote sensing specialist by explaining key remote sensing concepts in a clear and simple manner, with the goal of serving as a foundation for the case study chapters. 

  • 3 - Satellite Remote Sensing for the Conservation of East Asia’s Coastal Wetlands

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 54-81

  • Summary

    The use of remote sensing for assessing long-term changes of wetlands has provided essential information on the distribution and status of wetlands around the world. High resolution global maps of wetland extent now include water cover, water bodies, mangroves and many other wetland types. Yet our knowledge of the distribution and extent of tidal flats, a fringing ecosystem that occurs between land and sea, remains surprisingly poor. The process of regular tidal inundation renders tidal flats fully exposed only at low tide and completely unobservable at high tide, which has severely limited our ability to observe tidal flats with satellites. Therefore, fundamental information such as the global distribution of tidal flats and how they have changed over time remains largely unknown at anything other than local scales. This chapter introduces a satellite remote sensing project that overcame this limitation to develop high resolution maps of the intertidal zone using the full Landsat Archive images. The project was initiated to contribute to solving a fundamental conservation problem: identifying the cause of the ongoing collapse of migratory shorebird populations in the East Asian-Australasian Flyway. This migration is one of the world’s largest bird movements, involving millions of individuals. By developing a time series of tidal flat extent in the Yellow Sea region of East Asia, a critical staging site for millions of migratory shorebirds, we discovered that more than two-thirds of tidal flats had disappeared over a 50 year period. The high-resolution maps and the detection of alarmingly high rates of habitat loss have catalysed a range of conservation actions since 2012, demonstrating that data gathered with satellite remote sensing can have significant and lasting influence on conservation actions.

  • 4 - Global Forest Maps in Support of Conservation Monitoring

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 82-118

  • Summary

    Forest habitat loss is a preeminent threat to numerous species, including all four chimpanzee (Pan troglodytes) sub-species. The chimpanzee range spans approximately 2.3 million km2, making ground surveys of habitat condition intractable. Remotely sensed data is well-suited to quantify rates and map the spatial patterns of forest cover loss over large areas. Open access to the Landsat data archive and the proliferation of high performance computing has enabled annual forest loss to be mapped at the 30-m resolution for the entire globe. Here, we discuss a partnership between the Jane Goodall Institute (JGI) and the University of Maryland Department of Geographical Sciences to leverage recent advances in remote sensing with the aim of monitoring chimpanzee habitats across their range to support conservation action. We present two case studies using two methods to monitor habitat change. First, we use a simple method that quantifies forest loss area within the chimpanzee range and in protected areas between 2001 and 2014. The second study describes the development of a model that incorporates several environmental variables derived from satellite imagery to produce a map of relative habitat suitability that can be updated as new imagery becomes available. Resulting data from both methods are used to create Key Ecological Attributes (KEAs) that are incorporated into Jane Goodall Institute’s Decision Support System (DSS). The DSS allows managers to aggregate multi-source spatial data into management units that enable them to better visualise the relative status of chimpanzee habitats and make better-informed decisions to increase the likely success of conservation actions over time.

  • 8 - Lessons Learned from WhaleWatch

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 229-273

  • Summary

    Blue whales (Balaenoptera musculus) are currently listed as Endangered on the International Union for Conservation of Nature’s (IUCN) Red List. Collisions with ships are an ongoing threat to their recovery. The goal of the WhaleWatch project was to create a near real-time tool predicting whale occurrence and densities in US West Coast waters to identify high-use areas and help reduce whale mortality from ship strikes. We combined remotely sensed environmental data and satellite telemetry of blue whales to create a habitat preference model and near real-time tool. During the development of WhaleWatch, several key lessons were learned: the importance of end user involvement in product development; the requirement of large telemetry data sets to describe species distributions over multiple years; the critical need for satellite-derived environmental data to develop the habitat model and to operationalise predictions based on current ocean conditions; the relevance of assessing biological realism versus statistical model fit in habitat models; the value of evaluating model performance using independent data sets; and the benefit of automation to improve sustainability beyond the lifetime of the initial development project. These near real-time tools will require regular evaluation and updating in response to changes in climate that alter the relationships between ocean conditions and marine species habitat use.

  • 10 - Operational Conservation Remote Sensing

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 301-317

  • Summary

    In this final chapter, we identify and discuss shared themes and lessons learned from the preceding six case study chapters and one organisational perspective chapter. Commonalities were (i) collaboration, (ii) free, open, and accessible data, (iii) spatial and temporal resolution of satellite observations, (iv) types of satellite observations used, (v) building and enabling remote sensing capacity, (vi) customised tool development and visualisations, (vii) integrating in situ and Earth observations, and (viii) a role for serendipity. We then provide our perspective on the future of conservation remote sensing.

  • 7 - Predicting Mule Deer Harvests in Real Time

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 194-228

  • Summary

    Ungulates are an important group of species across the world that have strong ecological impacts on terrestrial vegetation and food-webs, as well as being economically valued for recreational hunting, bushmeat, and impacts on agriculture. Consequently, it would be useful to predict their population dynamics ahead of time for many management and conservation applications, yet there are almost no cases of prediction being used to guide management of these key species. In the case of recreational harvest, wildlife managers across the world are often faced with setting harvest quotas of ungulates one or two years before harvest implementation. These lags between determining the harvest quotas and the actual harvest period can often induce undesirable population oscillations of game species. This can also have consequences for other aspects of the ecosystem, including threatened or declining species. Here, we illustrate a predictive harvest management model applied to improving the harvest of mule deer, an economically and ecologically important ungulate across the state of Idaho, USA. Previously developed predictive models of key population parameters such as overwinter fawn survival were developed that linked to remotely sensed measures of vegetation productivity and snow cover from the MODIS platform. Models of these demographic rates were then included in an integrated population model that could forecast overwinter survival in late autumn when hunting seasons are set in Idaho. These models enabled managers to adjust their harvest quotas for the subsequent autumn based on readily available remotely sensed data in real-time. We demonstrate the improvements to harvest management of mule deer by comparing what harvests would have been with and without remotely sensed data. We also provide lessons for the necessary management and operational conditions that needed to be present in the Idaho Department of Fish and Game to enable such a successful, centralised, prediction system with recommendations for other management and conservation agencies. In conclusion, remote sensing measures of terrestrial environmental conditions can be a powerful tool to improve the management of ungulates worldwide.

  • 6 - Ecosystem Functioning Observations for Assessing Conservation in the Doñana National Park, Spain

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 164-193

  • Summary

    Climate change is predicted to have major repercussions for the preservation of ecosystems and has already led to significant changes in terrestrial productivity and water availability. In order to preserve ecosystems, and the benefits and goods that they provide, managers, decision-makers, and stakeholders require precise and easily accessible information on ecosystem functioning. In Doñana National Park (Spain), we have developed an observatory for producing and transferring information to stakeholders on carbon and water balance based on freely available remote sensing data. The simple and intuitive graphics developed helped managers to gain a synoptic overview of the stability of ecosystems following a perturbation and also assist with monitoring the direct consequences of management practices on vegetation productivity and water demand. The working framework and the tools developed in Doñana National Park are already being incorporated in other protected areas, promoting the ability of additional locations to implement adaptive management strategies, with the goal of mitigating the consequences of climate change on ecosystem integrity.

  • 5 - Wildfire Monitoring with Satellite Remote Sensing in Support of Conservation

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 119-163

  • Summary

    This chapter finds its rationale in the key ecological role fire plays on ecosystems and biodiversity. In particular, it focuses on the use of satellite information to improve habitat monitoring in protected areas. Conservation practitioners need this information to meet their goals and improve management effectiveness. To address these needs, the European Commission worked in collaboration with conservation institutions and protected areas in Africa to build two systems for the distribution of satellite-based information to support conservation and decision making. The first system, the Fire Monitoring Tool, is a stand-alone web portal which provides near-real time information of fire activity based on the Moderate Resolution Imaging Spectroradiometer (MODIS). The tool provides specific ecological indicators about fire in the world protected areas. Whereas the second system, the eStation, is a network of servers receiving EO-based products, including wildfire, used for protected area ecological assessment, but also national and regional environmental monitoring. The benefits provided by the systems are described in two case studies in Tanzania and Niger. The examples show how park ecologists have improved habitat monitoring and conservation efforts in the protected areas and how this can be repeated in other conservation areas. 

  • Preface

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp xi-xv

  • Summary

    Satellite images of Earth capture the imagination. They not only capture the beauty of the planet but also how humans are changing it. Conservation scientists have realized this, and the field of conservation remote sensing exploits the potential of satellite images for biodiversity conservation. Here, we expand this brief introduction to conservation remote sensing, and provide the rational for this book. By collating examples of where satellite remote sensing is being used in an operational way to inform conservation management, we aim to stimulate collaborations that will deliver projects that use satellite remote sensing in an operational way to inform conservation management.

  • 1 - A Brief Introduction to Conservation and Conservation Remote Sensing

  • Edited by Allison K. Leidner, National Aeronautics and Space Administration, Washington DC, Graeme M. Buchanan
  • Book:
    Satellite Remote Sensing for Conservation Action
    Published online:
    23 July 2018
    Print publication:
    16 August 2018, pp 1-25

  • Summary

    This chapter provides a primer on conservation and conservation science to provide some context for the rest of the book. It is well established that the world’s biodiversity is under pressure from humans. The modern conservation movement was established to respond to these pressures. Sound science should be used to inform conservation decision making in order to utilise the limited resources available to conservation effectively. The potential of satellite remote sensing to contribute to conservation is established. The use of satellite remote sensing in peer reviewed papers has steadily been increasing over recent years, but until recently there remained a feeling that these papers were not being turned into practical applications that provided scientific data to inform decision making in an on going, operational way. This chapter concludes by briefly describing how the case studies have met this need.

Page 8 of 26