Pages that link to "Item:Q140356"
From geokb
The following pages link to Pardhasaradhi Teluguntla (Q140356):
Displayed 20 items.
- Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine (Q149744) (← links)
- New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification (Q150706) (← links)
- Hyperspectral Remote Sensing of Vegetation and Agricultural Crops (Q154516) (← links)
- Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data (Q238601) (← links)
- Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data (Q239245) (← links)
- Automated cropland mapping of continental Africa using Google Earth Engine cloud computing (Q239564) (← links)
- Inland valley wetland cultivation and preservation for africa’s green and blue revolution using multi-sensor remote sensing (Q254029) (← links)
- Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud (Q256362) (← links)
- Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA (Q258186) (← links)
- A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades (Q262107) (← links)
- Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system (Q263114) (← links)
- Hyperspectral remote sensing for terrestrial applications (Q264778) (← links)
- Crop water productivity from cloud-Based landsat helps assess California’s water savings (Q265225) (← links)
- A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform (Q273589) (← links)
- Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 Data on Google Earth Engine (Q274041) (← links)
- Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities (Q286818) (← links)
- Hyperspectral narrowband data propel gigantic leap in the earth remote sensing (Q298574) (← links)
- Data Supporting Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA (Q318892) (← links)
- PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season (Q325625) (← links)
- Download rates of the Global Food-Security-Support-Analysis Data at 30-m Resolution (GFSAD30) Cropland-Extent Products (Q326562) (← links)
