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Earth Observation, Remote Sensing and Geoscientific Ground Investigations for Archaeological and Heritage Research

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ISBN: 9783039211937 / 9783039211944 Year: Pages: 304 DOI: 10.3390/books978-3-03921-194-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

This book collects 15 papers written by renowned scholars from across the globe that showcase the forefront research in Earth observation (EO), remote sensing (RS), and geoscientific ground investigations to study archaeological records and cultural heritage.Archaeologists, anthropologists, geographers, remote sensing, and archaeometry experts share their methodologies relying on a wealth of techniques and data including, but not limited to: very high resolution satellite images from optical and radar space-borne sensors, air-borne surveys, geographic information systems (GIS), archaeological fieldwork, and historical maps.A couple of the contributions highlight the value of noninvasive and nondestructive laboratory analyses (e.g., neutron diffraction) to reconstruct ancient manufacturing technologies, and of geological ground investigations to corroborate hypotheses of historical events that shaped cultural landscapes.Case studies encompass famous UNESCO World Heritage Sites (e.g., the Nasca Lines in Peru), remote and yet-to-discover archaeological areas in tropical forests in central America, European countries, south Asian changing landscapes, and environments which are arid nowadays but were probably full of woody vegetation in the past.Finally, the reader can learn about the state-of-the-art of education initiatives to train site managers in the use of space technologies in support of their activities, and can understand the legal aspects involved in the application of EO and RS to address current challenges of African heritage preservation.

Keywords

analytic hierarchy process (AHP) --- archaeology --- predictive model --- tumuli --- remote sensing --- multi-criteria --- Saharan Morocco --- airborne laser scanning --- orthophotographs --- archaeological survey --- field reconnaissance --- Arran --- national archaeological mapping programme --- synthetic aperture radar --- subsurface imaging --- microwave penetration --- archaeology --- arid environments --- remote sensing --- Oman --- e-learning --- Earth observation --- education --- capacity development --- cultural and natural heritage --- UNESCO --- photogrammetry --- RPAS --- UAV --- Peru --- geoglyph Pista --- mapping --- drones --- remote sensing --- free satellite imagery --- GoogleEarth --- Bing Maps --- archaeological fieldwork --- arid environments --- basalt desert --- landscape accessibility --- Harra --- Jordan --- archaeological landscapes --- settlements --- historical maps --- Survey of India --- Archaeological Survey of India --- heritage --- colonial studies --- remote sensing --- historical landscapes --- landscape archaeology --- settlements --- colonial studies --- river morphology --- Indus --- floods --- remote sensing --- satellite --- Sentinel-2 --- surface survey --- Roman archaeology --- Sumerian pottery --- neutron techniques --- neutron diffraction --- chemometric analysis --- Mega El Niño --- pampa of Nazca --- Cuenca Pisco --- Rio Grande de Nazca --- grain-size --- volcaniclastic layer --- stratigraphy --- petrography --- Lidar --- GIS --- Mesoamerica --- Archaeology --- Caves --- Landscape --- Ritual --- Visualization --- Maya --- Belize --- Sacred --- automated detection --- OBIA --- LiDAR --- Difference Map --- field monument --- Burial Mound --- Motte-and-Bailey castle --- Ridge and Furrow --- space law --- disaster and conservation management --- Geographic Information System (GIS) --- international boundaries --- Africa --- Cameroon-Nigeria Mixed Commission --- satellite imagery --- Boundary Demarcation --- international law --- relict boundaries --- Earth Observation --- remote sensing --- optical --- SAR --- drone --- airborne LiDAR --- GIS --- OBIA --- neutron diffraction --- archaeological prospection --- pattern recognition --- archaeometry --- geological mapping

Solar Radiation, Modelling and Remote Sensing

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ISBN: 9783039210046 / 9783039210053 Year: Pages: 230 DOI: 10.3390/books978-3-03921-005-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-06-26 08:44:06
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Accurate solar radiation knowledge and its characterization on the Earth’s surface are of high interest in many aspects of environmental and engineering sciences. Modeling of solar irradiance from satellite imagery has become the most widely used method for retrieving solar irradiance information under total sky conditions, particularly in the solar energy community. Solar radiation modeling, forecasting, and characterization continue to be broad areas of study, research, and development in the scientific community. This Special Issue contains a small sample of the current activities in this field. Both the environmental and climatology community, as the solar energy world, share a great interest in improving modeling tools and capabilities for obtaining more reliable and accurate knowledge of solar irradiance components worldwide. The work presented in this Special Issue also remarks on the significant role that remote sensing technologies play in retrieving and forecasting solar radiation information.

Keywords

Himawari-8/Advanced Meteorological Imager (Himawari-8/AHI) --- Geostationary Korea Multi-Purse Satellite/Advanced Meteorological Imager (GK-2A/AMI) --- broadband albedo at the top of the atmosphere (TOA albedo) --- reflected shortwave radiation at the top of the atmosphere (RSR) --- Clouds and the Earth Radiant Energy System (CERES) --- surface solar radiation --- remote sensing --- validation --- India --- solar radiation trends --- Solis scheme --- clear sky --- radiation model --- radiative transfer --- high turbidity --- water vapor --- solar radiation --- understory light condition --- forest canopy --- subcanopy light regime --- PAR --- shortwave radiation --- light attenuation --- remote sensing --- solar irradiance --- nowcasting --- AMESIS --- MSG --- SEVIRI --- radiance --- brightness temperature --- motion vector field --- photosynthetically active radiation --- global horizontal irradiance --- clustering analysis --- Kato bands --- solar irradiance --- MSG --- SEVIRI --- HRV --- AMESIS --- solar radiation --- global horizontal irradiance --- satellite-derived dataset --- validation --- solar energy --- aerosol impact --- earth observation --- clear sky index --- solar irradiance --- downward shortwave radiation --- global horizontal irradiance --- solar variability --- cloud categories --- GOES satellites --- evapotranspiration --- insolation --- surface energy balance --- data fusion --- water resource management --- California Delta --- solar radiation --- radiative transfer --- solar energy systems --- solar radiation forecasting

Google Earth Engine Applications

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ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2019-04-25 16:37:17
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In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Keywords

Google Earth Engine --- NDVI --- vegetation index --- Landsat --- remote sensing --- phenology --- surface reflectance --- cropland mapping --- cropland areas --- 30-m --- Landsat-8 --- Sentinel-2 --- Random Forest --- Support Vector Machines --- segmentation --- RHSeg --- Google Earth Engine --- Africa --- remote sensing --- semi-arid --- ecosystem assessment --- land use change --- image classification --- seasonal vegetation --- carbon cycle --- Google Earth Engine --- crop yield --- gross primary productivity (GPP) --- data fusion --- Landsat --- MODIS --- MODIS --- Random Forest --- pasture mapping --- Brazilian pasturelands dynamics --- Google Earth Engine --- crop classification --- multi-classifier --- cloud computing --- time series --- high spatial resolution --- BACI --- Enhanced Vegetation Index --- Google Earth Engine --- cloud-based geo-processing --- satellite-derived bathymetry --- image composition --- pseudo-invariant features --- sun glint correction --- empirical --- spatial error --- Google Earth Engine --- low cost in situ --- Sentinel-2 --- Mediterranean --- burn severity --- change detection --- Landsat --- dNBR --- RdNBR --- RBR --- composite burn index (CBI) --- MTBS --- lower mekong basin --- landsat collection --- suspended sediment concentration --- online application --- google earth engine --- Landsat --- Google Earth Engine --- protected area --- forest and land use mapping --- machine learning classification --- China --- temporal compositing --- image time series --- multitemporal analysis --- change detection --- cloud masking --- Landsat-8 --- Google Earth Engine (GEE) --- Google Earth Engine --- LAI --- FVC --- FAPAR --- CWC --- plant traits --- random forests --- PROSAIL --- small-scale mining --- industrial mining --- google engine --- image classification --- land-use cover change --- seagrass --- habitat mapping --- image composition --- machine learning --- support vector machines --- Google Earth Engine --- Sentinel-2 --- Aegean --- Ionian --- global scale --- soil moisture --- Soil Moisture Ocean Salinity --- Soil Moisture Active Passive --- Google Earth Engine --- drought --- cloud computing --- remote sensing --- snow hydrology --- water resources --- Google Earth Engine --- user assessment --- MODIS --- snow cover --- flood --- disaster prevention --- emergency response --- decision making --- Google Earth Engine --- land cover --- deforestation --- Brazilian Amazon --- Bayesian statistics --- BULC-U --- Mato Grosso --- spatial resolution --- Landsat --- GlobCover --- SDG --- surface urban heat island --- Geo Big Data --- Google Earth Engine --- global monitoring service --- Google Earth Engine --- web portal --- satellite imagery --- trends --- earth observation --- wetland --- Google Earth Engine --- Sentinel-1 --- Sentinel-2 --- random forest --- cloud computing --- geo-big data --- cloud computing --- big data analytics --- long term monitoring --- data archival --- early warning systems

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MDPI - Multidisciplinary Digital Publishing Institute (3)


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eng (3)


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2019 (3)