Results 1 to 10 of about 1,186,895 (272)

Valid model-free spatial prediction. [PDF]

J Am Stat Assoc, 2023
Predicting the response at an unobserved location is a fundamental problem in spatial statistics. Given the difficulty in modeling spatial dependence, especially in non-stationary cases, model-based prediction intervals are at risk of misspecification bias that can negatively affect their validity.
Mao H, Martin R, Reich BJ.
europepmc   +5 more sources

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16 [PDF]

Geoscientific Model Development, 2022
A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications.
P. C. Campbell, P. C. Campbell, Y. Tang, Y. Tang, P. Lee, P. Lee, B. Baker, D. Tong, D. Tong, R. Saylor, A. Stein, J. Huang, J. Huang, H.-C. Huang, H.-C. Huang, E. Strobach, E. Strobach, J. McQueen, L. Pan, L. Pan, I. Stajner, J. Sims, J. Tirado-Delgado, J. Tirado-Delgado, Y. Jung, F. Yang, T. L. Spero, R. C. Gilliam   +27 more
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SPATIAL PREDICTION OF THE CONTENT OF CARBONATE MINERALS AND GYPSUM AND ITS RELATIONSHIP TO THE FORMATION OF HEAT ISLANDS USING THERMAL IMAGING [PDF]

مجلة الأنبار للعلوم الزراعية, 2021
The study area was chosen to the south of a Haditha lake. It is located between longitudes 41º 42 '02 "and 42º 27 03" E, and between longitude 34º 02 24 "and 34º 32 08" N, Western desert region at borders of Al-Anbar Governorate in ...
S. Al-Juraysi, Q. Al-Obeidi
doaj   +1 more source

Improving the Spatial Prediction of Soil Organic Carbon Content Using Phenological Factors: A Case Study in the Middle and Upper Reaches of Heihe River Basin, China

Remote Sensing, 2023
The accurate mapping of soil organic carbon (SOC) distribution is important for carbon sequestration and land management strategies, contributing to mitigating climate change and ensuring agricultural productivity.
Xinyu Liu, Jian Wang, Xiaodong Song
doaj   +1 more source

Spatial Interpolation Techniques to Map Rainfall in Southeast Brazil

Revista Brasileira de Meteorologia, 2022
The prediction, as well as the estimation of precipitation, is one of the challenges of the scientific community in the world, due to the high spatial and seasonal variability of this meteorological element. For this purpose, methodologies that allow the
Lucas Eduardo de Oliveira Aparecido, Jose Reinaldo da Silva Cabral de Moraes, Rafael Fausto de Lima, Guilherme Botega Torsoni   +3 more
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Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study

ISPRS International Journal of Geo-Information, 2022
Mapping of landslides, conducted in 2021 by the Geological Survey of Denmark and Greenland (GEUS), revealed 3202 landslides in Denmark, indicating that they might pose a bigger problem than previously acknowledged.
Angelina Ageenko, Lærke Christina Hansen, Kevin Lundholm Lyng, Lars Bodum, Jamal Jokar Arsanjani   +4 more
doaj   +1 more source

Spatial prediction of physical and chemical properties of soil using optical satellite imagery: a state-of-the-art hybridization of deep learning algorithm

Frontiers in Environmental Science, 2023
This research aimed to predict soil’s physical and chemical properties with a state-of-the-art hybrid model based on deep learning algorithms and optical satellite images in a region in the north of Iran.
Fatemeh Sadat Hosseini, Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi, Mohammad Jamshidi   +4 more
doaj   +1 more source

Mapping Rice Paddy Distribution Using Remote Sensing by Coupling Deep Learning with Phenological Characteristics

Remote Sensing, 2021
Two main approaches are used in mapping rice paddy distribution from remote sensing images: phenological methods or machine learning methods. The phenological methods can map rice paddy distribution in a simple way but with limited accuracy.
A-Xing Zhu, Fang-He Zhao, Hao-Bo Pan, Jun-Zhi Liu   +3 more
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Spatial Prediction and Mapping of Gully Erosion Susceptibility Using Machine Learning Techniques in a Degraded Semi-Arid Region of Kenya

Land, 2023
This study aimed at (i) developing, evaluating and comparing the performance of support vector machines (SVM), boosted regression trees (BRT), random forest (RF) and logistic regression (LR) models in mapping gully erosion susceptibility, and (ii ...
Kennedy Were, Syphyline Kebeney, Harrison Churu, James Mumo Mutio, Ruth Njoroge, Denis Mugaa, Boniface Alkamoi, Wilson Ng’etich, Bal Ram Singh   +8 more
doaj   +1 more source

Geoparcel-Based Spatial Prediction Method for Grassland Fractional Vegetation Cover Mapping

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Grassland resources guarantee the balance of ecosystems and the sustainable development of animal husbandry. Spatial information is essential for grass resource management in pastoral areas, which can be extracted quickly on a large-scale by using remote
Tianjun Wu, Jiancheng Luo, Lijing Gao, Yingwei Sun, Yingpin Yang, Ya'nan Zhou, Wen Dong, Xin Zhang   +7 more
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