Warren et al., 2022 - Google Patents
Validation of the USPED erosion and deposition model at Schofield Barracks, O 'ahu, Hawai 'iWarren et al., 2022
View PDF- Document ID
- 4400395238397060026
- Author
- Warren S
- Ruzycki T
- Publication year
- Publication venue
- Pacific Science
External Links
Snippet
Soil erosion has been recognized as a significant environmental issue in the United States for over 200 years. Numerous attempts have been made to predict and quantify the phenomenon, yet significant issues remain that hinder the accuracy and effectiveness of …
- 230000003628 erosive 0 title abstract description 50
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ashiagbor et al. | Modeling soil erosion using RUSLE and GIS tools | |
Segura et al. | Potential impacts of climate change on soil erosion vulnerability across the conterminous United States | |
Doulabian et al. | Projected climate change impacts on soil erosion over Iran | |
Karamesouti et al. | Erosion rate predictions from PESERA and RUSLE at a Mediterranean site before and after a wildfire: Comparison & implications | |
Rahman et al. | Assessing regional environmental quality by integrated use of remote sensing, GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration | |
Adediji et al. | Assessment of revised universal soil loss equation (RUSLE) in Katsina area, Katsina state of Nigeria using remote sensing (RS) and geographic information system (GIS) | |
Mosbahi et al. | Assessment of soil erosion risk using SWAT model | |
Mohamed et al. | Land cover classification and change detection analysis of Qaroun and Wadi El-Rayyan lakes using multi-temporal remotely sensed imagery | |
Thomas et al. | Suitability of spaceborne digital elevation models of different scales in topographic analysis: an example from Kerala, India | |
Young et al. | Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using 137Cs in two US Midwest agricultural fields | |
Abu Hammad | Watershed erosion risk assessment and management utilizing revised universal soil loss equation‐geographic information systems in the Mediterranean environments | |
Warren et al. | Validation of the USPED erosion and deposition model at Schofield Barracks, O ‘ahu, Hawai ‘i | |
Van Leeuwen et al. | Physically based hydrological modelling of inland excess water | |
Panidi et al. | Application of phyto-indication and radiocesium indicative methods for microrelief mapping | |
Harmon et al. | r. sim. terrain 1.0: a landscape evolution model with dynamic hydrology | |
Warren et al. | Validation of the unit stream power erosion and deposition (USPED) model at Yakima Training Center, Washington | |
Thomsen et al. | Monitoring vegetation dynamics at a tidal marsh restoration site: integrating field methods, remote sensing and modeling | |
Coulibaly et al. | Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire | |
Duulatov et al. | Assessing the potential of soil erosion in Kyrgyzstan based on RUSLE, integrated with remote sensing | |
Vujačić et al. | Initial results of comparative assessment of soil erosion intensity using Wintero model: A Case Study Of Polimlje And Shirindareh Drainage Basins | |
Fiener et al. | Soil organic carbon patterns under different land uses in South India | |
Kumar | Geospatial approach in modeling soil erosion processes in predicting soil erosion and nutrient loss in hilly and mountainous landscape | |
Rodrigues Neto et al. | Soil loss modelling by the intero model-erosion potential method in the machado river basin, Minas Gerais, Brazil. | |
Singh et al. | Possibility of spatial estimation of soil erosion using Revised Universal Soil Loss Equation model and generalized additive model in post‐hard coal mining spoil heap | |
Warren et al. | Validation of the Unit Stream Power Erosion and Deposition (USPED) model at Fort Hood, Texas |