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A 30-m annual corn residue coverage dataset from 2013 to 2021 in Northeast China
Crop residue cover plays a key role in the protection of black soil by covering the soil in the non-growing season against wind erosion and chop**...
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Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau
Check dams on the Chinese Loess Plateau (CLP) have captured billions of tons of eroded sediment, substantially reducing sediment load in the Yellow...
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The BELSAR dataset: Mono- and bistatic full-pol L-band SAR for agriculture and hydrology
The BELSAR dataset consists of high-resolution multitemporal airborne mono- and bistatic fully-polarimetric synthetic aperture radar (SAR) data in...
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SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US
Soil moisture plays a key role in controlling land-atmosphere interactions, with implications for water resources, agriculture, climate, and...
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An RFI-suppressed SMOS L-band multi-angular brightness temperature dataset spanning over a decade (since 2010)
The Soil Moisture Ocean Salinity (SMOS) was the first mission providing L-band multi-angular brightness temperature (TB) at the global scale....
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A new high-resolution global topographic factor dataset calculated based on SRTM
Topography is an important factor affecting soil erosion and is measured as a combination of the slope length and slope steepness (LS-factor) in...
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Dataset of the suitability of major food crops in Africa under climate change
Understanding the extent and adapting to the impacts of climate change in the agriculture sector in Africa requires robust data on which technical...
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An experimental dataset on yields of pulses across Europe
Future European agriculture should achieve high productivity while limiting its impact on the environment. Legume-supported crop rotations could...
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An improved global vegetation health index dataset in detecting vegetation drought
Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic...
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SDFC dataset: a large-scale benchmark dataset for hyperspectral image classification
Hyperspectral image (HSI) classification plays an important role in a wide range of remote sensing applications in military and civilian fields....
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AgEvidence: a dataset to explore agro-ecological effects of conservation agriculture
Conservation agriculture (CA) is a set of principles thought to be able to enhance crop productivity while minimizing impacts on the environment. The...
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Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy
The air in the Lombardy region, Italy, is one of the most polluted in Europe because of limited air circulation and high emission levels. There is a...
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A global dataset for the production and usage of cereal residues in the period 1997–2021
Crop residue management plays an important role in determining agricultural greenhouse gas emissions and related changes in soil carbon stocks....
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Machine Learning Methods for Predicting Soil Compression Index
The compression index is an important consideration when figuring out how fine-grained soil settles. The compression index is determined from the...
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Effects of straw return on soil carbon sequestration, soil nutrients and rice yield of in acidic farmland soil of Southern China
Straw return was extensively applied owing to its multiple positive impacts on improving soil fertility, impeding soil degradation, enhancing soil...
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Soil quality index as a tool to assess biochars soil quality improvement in a heavy metal-contaminated soil
The assessment of soil quality improvement provided by biochars is complex and rarely examined. In this work, soil quality indices (SQIs) were...
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The Arctic Plant Aboveground Biomass Synthesis Dataset
Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant...
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A high-precision oasis dataset for China from remote sensing images
High-resolution oasis maps are imperative for understanding ecological and socio-economic development of arid regions. However, due to the late...
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Enhancing the accuracy of digital soil map** using the surface and subsurface soil characteristics as continuous diagnostic layers
Digital soil map** relies on relating soils to a particular set of covariates, which capture inherent soil spatial variation. In digital map** of...
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Predicting wetland soil properties using machine learning, geophysics, and soil measurement data
PurposeMachine learning models can improve the prediction of spatial variation of wetland soil properties, such as soil moisture content (SMC) and...
