Topic
Satellite imagery
About: Satellite imagery is a research topic. Over the lifetime, 6189 publications have been published within this topic receiving 134551 citations. The topic is also known as: satellite photography.
Papers published on a yearly basis
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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.
Abstract: Preface. Part I: Foundations. History and Scope of Remote Sensing. Electromagentic Radiation. Part II: Image Acquisition. Photographic Sensors. Digital Data. Image Interpretation. Land Observation Satellites. Active Microwave and Lidar. Thermal Radiation. Image Resolution. Part III: Analysis. Preprocessing. Image Classification. Field Data. Accuracy Assessment. Hyperspectral Remote Sensing. Part IV: Applications. Geographic Information Systems. Plant Sciences. Earth Sciences. Hydrospheric Sciences. Land Use and Land Cover. Global Remote Sensing.
3,445 citations
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TL;DR: In this article, the status and distribution of global mangroves using recently available Global Land Survey (GLS) data and the Landsat archive was mapped using hybrid supervised and unsupervised digital image classification techniques.
Abstract: Aim Our scientific understanding of the extent and distribution of mangrove forests of the world is inadequate. The available global mangrove databases, compiled using disparate geospatial data sources and national statistics, need to be improved.Here,we mapped the status and distributions of global mangroves using recently available Global Land Survey (GLS) data and the Landsat archive. Methods We interpreted approximately 1000 Landsat scenes using hybrid supervised and unsupervised digital image classification techniques. Each image was normalized for variation in solar angle and earth‐sun distance by converting the digital number values to the top-of-the-atmosphere reflectance. Ground truth data and existing maps and databases were used to select training samples and also for iterative labelling. Results were validated using existing GIS data and the published literature to map ‘true mangroves’. Results The total area of mangroves in the year 2000 was 137,760 km 2 in 118 countries and territories in the tropical and subtropical regions of the world. Approximately 75% of world’s mangroves are found in just 15 countries, and only 6.9% are protected under the existing protected areas network (IUCN I-IV). Our study confirms earlier findings that the biogeographic distribution of mangroves is generallyconfinedtothetropicalandsubtropicalregionsandthelargestpercentage of mangroves is found between 5° N and 5° S latitude. Main conclusions We report that the remaining area of mangrove forest in the world is less than previously thought. Our estimate is 12.3% smaller than the most recent estimate by the Food and Agriculture Organization (FAO) of the United Nations.We present the most comprehensive, globally consistent and highest resolution (30 m) global mangrove database ever created.We developed and used better mapping techniques and data sources and mapped mangroves with better spatial and thematic details than previous studies.
2,261 citations
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South Dakota State University1, Natural Resources Canada2, United States Geological Survey3, Boston University4, University of Idaho5, United States Department of Agriculture6, Goddard Space Flight Center7, University of Colorado Boulder8, University of Massachusetts Boston9, Rochester Institute of Technology10, University of California, Los Angeles11, United States Forest Service12, Agricultural Research Service13, Humboldt University of Berlin14, Desert Research Institute15, University of Maryland, College Park16, University of Nebraska–Lincoln17, Geoscience Australia18, Virginia Tech19
TL;DR: Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared as mentioned in this paper.
1,697 citations
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TL;DR: In this paper, the spatial structure of images as a function of spatial resolution is measured for selecting the appropriate scale for remote sensing, and graphs are obtained by imaging the scene at fine resolution and then collapsing the image to successively coarser resolutions while calculating the local variance.
1,277 citations
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TL;DR: A new Automated Water Extraction Index (AWEI) is introduced improving classification accuracy in areas that include shadow and dark surfaces that other classification methods often fail to classify correctly, using Landsat 5 TM images of several water bodies.
1,158 citations