Sampling design optimization for soil mapping with random forest
Abstract Machine learning techniques are widely employed to generate digital soil maps.
The map accuracy is partly determined by the number and spatial locations of the …
The map accuracy is partly determined by the number and spatial locations of the …
Improving daily stochastic streamflow prediction: Comparison of novel hybrid data-mining algorithms
In the current paper, the efficiency of three new standalone data-mining algorithms [M5
Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid algorithms of …
Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid algorithms of …
Spatial biases of information influence global estimates of soil respiration: How can we improve global predictions?
Soil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of
the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The …
the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The …
Mountain riverine floods in Ecuador: Issues, challenges, and opportunities
Increasing urbanization and development along rivers, together with climate change,
exacerbate future flood risk in Ecuador. Current policy strategies in the highlands greatly …
exacerbate future flood risk in Ecuador. Current policy strategies in the highlands greatly …
How to compare sampling designs for mapping?
AMJC Wadoux, DJ Brus - European Journal of Soil Science, 2021 - Wiley Online Library
If a map is constructed through prediction with a statistical or non‐statistical model, the
sampling design used for selecting the sample on which the model is fitted plays a key role …
sampling design used for selecting the sample on which the model is fitted plays a key role …
[PDF][PDF] Determinación de las épocas lluviosas y secas en la ciudad de Chachapoyas para el periodo de 2014-2018
El estudio de las precipitaciones, permite definir e implementar estrategias en diferentes
zonas. El objetivo de esta investigación fue conocer la variabilidad de las precipitaciones en …
zonas. El objetivo de esta investigación fue conocer la variabilidad de las precipitaciones en …
Improving hourly precipitation estimates for flash flood modeling in data-scarce andean-amazon basins: An integrative framework based on machine learning and …
JE Chancay, EF Espitia-Sarmiento - Remote Sensing, 2021 - mdpi.com
Accurate estimation of spatiotemporal precipitation dynamics is crucial for flash flood
forecasting; however, it is still a challenge in Andean-Amazon sub-basins due to the lack of …
forecasting; however, it is still a challenge in Andean-Amazon sub-basins due to the lack of …
Large-scale precipitation monitoring network re-design using ground and satellite datasets: coupled application of geostatistics and meta-heuristic optimization …
Precipitation is a key constituent of the water cycle and its accurate measurement is
essential for a wide range of hydroclimatic studies. Although advances in technology have …
essential for a wide range of hydroclimatic studies. Although advances in technology have …
Assessing the impact of sampling strategy in random forest-based predicting of soil nutrients: a study case from northern Morocco
In this work, we tested different combinations of sampling strategies, random sampling and
conditioned Latin Hypercube sampling (cLHS)] and sample ratios (10%= 147 and 25 …
conditioned Latin Hypercube sampling (cLHS)] and sample ratios (10%= 147 and 25 …
Spatio-temporal rainfall trend and homogeneity analysis in flood prone area: case study of Odaw river basin-Ghana
Accurately forecasting rainfall trends is vital for the socio-economic development of a nation.
Observed daily rainfall data from the Ghana Meteorological Agency (GMet) spanning 1980 …
Observed daily rainfall data from the Ghana Meteorological Agency (GMet) spanning 1980 …