Google Earth Engine Applications
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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Book Chapter |
| Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2019
|
| Subjects: | |
| Online Access: | Get Fullteks DOAB: description of the publication |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 06359naaaa2201693uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_48756 | ||
| 005 | 20210211 | ||
| 020 | |a books978-3-03897-885-5 | ||
| 020 | |a 9783038978855 | ||
| 020 | |a 9783038978848 | ||
| 024 | 7 | |a 10.3390/books978-3-03897-885-5 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 100 | 1 | |a Mutanga, Onisimo |4 auth | |
| 700 | 1 | |a Kumar, Lalit |4 auth | |
| 245 | 1 | 0 | |a Google Earth Engine Applications |
| 260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2019 | ||
| 300 | |a 1 electronic resource (420 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a global monitoring service | ||
| 653 | |a suspended sediment concentration | ||
| 653 | |a image classification | ||
| 653 | |a empirical | ||
| 653 | |a Soil Moisture Active Passive | ||
| 653 | |a data archival | ||
| 653 | |a water resources | ||
| 653 | |a GlobCover | ||
| 653 | |a dNBR | ||
| 653 | |a satellite imagery | ||
| 653 | |a SDG | ||
| 653 | |a cloud-based geo-processing | ||
| 653 | |a spatial resolution | ||
| 653 | |a land use change | ||
| 653 | |a MTBS | ||
| 653 | |a global scale | ||
| 653 | |a landsat collection | ||
| 653 | |a Geo Big Data | ||
| 653 | |a trends | ||
| 653 | |a FAPAR | ||
| 653 | |a vegetation index | ||
| 653 | |a pseudo-invariant features | ||
| 653 | |a emergency response | ||
| 653 | |a RBR | ||
| 653 | |a BULC-U | ||
| 653 | |a Africa | ||
| 653 | |a Brazilian pasturelands dynamics | ||
| 653 | |a Enhanced Vegetation Index | ||
| 653 | |a geo-big data | ||
| 653 | |a multitemporal analysis | ||
| 653 | |a flood | ||
| 653 | |a early warning systems | ||
| 653 | |a low cost in situ | ||
| 653 | |a web portal | ||
| 653 | |a composite burn index (CBI) | ||
| 653 | |a small-scale mining | ||
| 653 | |a snow hydrology | ||
| 653 | |a RdNBR | ||
| 653 | |a seasonal vegetation | ||
| 653 | |a burn severity | ||
| 653 | |a random forests | ||
| 653 | |a land-use cover change | ||
| 653 | |a random forest | ||
| 653 | |a Support Vector Machines | ||
| 653 | |a lower mekong basin | ||
| 653 | |a CWC | ||
| 653 | |a Random Forest | ||
| 653 | |a crop yield | ||
| 653 | |a Landsat-8 | ||
| 653 | |a sun glint correction | ||
| 653 | |a protected area | ||
| 653 | |a cropland areas | ||
| 653 | |a disaster prevention | ||
| 653 | |a gross primary productivity (GPP) | ||
| 653 | |a segmentation | ||
| 653 | |a high spatial resolution | ||
| 653 | |a satellite-derived bathymetry | ||
| 653 | |a Aegean | ||
| 653 | |a Brazilian Amazon | ||
| 653 | |a image composition | ||
| 653 | |a pasture mapping | ||
| 653 | |a carbon cycle | ||
| 653 | |a machine learning | ||
| 653 | |a earth observation | ||
| 653 | |a ecosystem assessment | ||
| 653 | |a Mato Grosso | ||
| 653 | |a FVC | ||
| 653 | |a image time series | ||
| 653 | |a LAI | ||
| 653 | |a semi-arid | ||
| 653 | |a google engine | ||
| 653 | |a spatial error | ||
| 653 | |a Ionian | ||
| 653 | |a forest and land use mapping | ||
| 653 | |a snow cover | ||
| 653 | |a long term monitoring | ||
| 653 | |a RHSeg | ||
| 653 | |a online application | ||
| 653 | |a land cover | ||
| 653 | |a PROSAIL | ||
| 653 | |a support vector machines | ||
| 653 | |a seagrass | ||
| 653 | |a wetland | ||
| 653 | |a Sentinel-1 | ||
| 653 | |a Sentinel-2 | ||
| 653 | |a surface reflectance | ||
| 653 | |a user assessment | ||
| 653 | |a remote sensing | ||
| 653 | |a multi-classifier | ||
| 653 | |a time series | ||
| 653 | |a machine learning classification | ||
| 653 | |a deforestation | ||
| 653 | |a Google Earth Engine | ||
| 653 | |a decision making | ||
| 653 | |a cropland mapping | ||
| 653 | |a change detection | ||
| 653 | |a google earth engine | ||
| 653 | |a industrial mining | ||
| 653 | |a data fusion | ||
| 653 | |a cloud masking | ||
| 653 | |a Google Earth Engine (GEE) | ||
| 653 | |a NDVI | ||
| 653 | |a Bayesian statistics | ||
| 653 | |a China | ||
| 653 | |a cloud computing | ||
| 653 | |a plant traits | ||
| 653 | |a Soil Moisture Ocean Salinity | ||
| 653 | |a soil moisture | ||
| 653 | |a big data analytics | ||
| 653 | |a Landsat | ||
| 653 | |a phenology | ||
| 653 | |a 30-m | ||
| 653 | |a MODIS | ||
| 653 | |a habitat mapping | ||
| 653 | |a Mediterranean | ||
| 653 | |a temporal compositing | ||
| 653 | |a drought | ||
| 653 | |a surface urban heat island | ||
| 653 | |a BACI | ||
| 653 | |a crop classification | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/1262 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/48756 |7 0 |z DOAB: description of the publication |