Unit Conversion Research Articles

Guidance on the conversion of gaseous emission units to standardized emission factors and recommendations for data reporting

Emissions of ammonia (NH3), nitrous oxide (N2O) and methane (CH4) from livestock production may be measured for different reasons and in consequence reported in a wide range of units. For the purpose of compiling national inventories of emissions of those gases, emissions from buildings and stores usually need to be expressed per animal or as a proportion of nitrogen (N) (NH3 and N2O) or volatile solids (VS) (CH4) excreted or stored. Much of the published data on gaseous emissions from livestock production is not reported in units that can be readily used for inventory compilation. This paper provides guidance for researchers wishing to convert a wide range of emission units into emission factors (EFs) and opens up opportunities for increased use of published data. We developed our methodology using reported emissions from housing and storage systems compiled from studies for the DATAMAN database so that we could convert reported emissions into agreed EFs referred to as 'required EFs' (RqEFs). Required EFs were either derived using data reported in the associated publication or estimated, using default data (e.g. annual N excretion by a particular type of livestock). The approach greatly increased the number of RqEFs. For example, the number of RqEFs of N2O-N from livestock buildings as a proportion of excreted N increased from 16 to 326, while the number of N2O RqEFs from manure stores as a proportion of stored N increased from 126 to 353. For two subsets of NH3-N emissions from livestock buildings and from slurry stores there were very good correlations between emissions estimated using the methodology we developed and reported emissions (R2 = 0.97 and 0.97, respectively). We include a list of recommended information for inclusion in publications reporting emissions that will enable other workers to utilize this methodology.

A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures.

Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three-dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x-ray CT scans. We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x-ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x-ray CT scans from two different scanners and compared results from high-dose and low-dose settings. Comparing our reconstructed proton CT images with images derived from x-ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae. Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low-dose treatment planning with reduced margins.

Low Intensity Beam Extraction Mode on the Protom Synchrotron for Proton Radiography Implementation

Proton radiography is one of the most important and actual areas of research that can significantly improve the quality and accuracy of proton therapy. Currently, the calculation of the proton range in patients receiving proton therapy is based on the conversion of Hounsfield CT units of the patient's tissues into the relative stopping power of protons. Proton radiography is able to reduce these uncertainties by directly measuring proton stopping power. The study demonstrates the possibility of Protom synchrotron-based proton therapy facilities to operate in a special mode which makes it possible to implement proton radiography. This work presents the status of the new low beam intensity extraction mode. The paper describes algorithms of low flux beam control, calibration procedures and experimental measurements. Measurements and calibration procedures were performed with certified Protom Faraday Cup, PTW Bragg Peak Chamber and specially designed experimental external.

Novel method of transpulmonary pressure measurement with an air-filled esophageal catheter

BackgroundThere is a strong rationale for proposing transpulmonary pressure-guided protective ventilation in acute respiratory distress syndrome. The reference esophageal balloon catheter method requires complex in vivo calibration, expertise and specific material order. A simple, inexpensive, accurate and reproducible method of measuring esophageal pressure would greatly facilitate the measure of transpulmonary pressure to individualize protective ventilation in the intensive care unit.ResultsWe propose an air-filled esophageal catheter method without balloon, using a disposable catheter that allows reproducible esophageal pressure measurements. We use a 49-cm-long 10 Fr thin suction catheter, positioned in the lower-third of the esophagus and connected to an air-filled disposable blood pressure transducer bound to the monitor and pressurized by an air-filled infusion bag. Only simple calibration by zeroing the transducer to atmospheric pressure and unit conversion from mmHg to cmH2O are required. We compared our method with the reference balloon catheter both ex vivo, using pressure chambers, and in vivo, in 15 consecutive mechanically ventilated patients. Esophageal-to-airway pressure change ratios during the dynamic occlusion test were close to one (1.03 ± 0.19 and 1.00 ± 0.16 in the controlled and assisted modes, respectively), validating the proper esophageal positioning. The Bland–Altman analysis revealed no bias of our method compared with the reference and good precision for inspiratory, expiratory and delta esophageal pressure measurements in both the controlled (largest bias −0.5 cmH2O [95% confidence interval: −0.9; −0.1] cmH2O; largest limits of agreement −3.5 to 2.5 cmH2O) and assisted modes (largest bias −0.3 [−2.6; 2.0] cmH2O). We observed a good repeatability (intra-observer, intraclass correlation coefficient, ICC: 0.89 [0.79; 0.96]) and reproducibility (inter-observer ICC: 0.89 [0.76; 0.96]) of esophageal measurements. The direct comparison with pleural pressure in two patients and spectral analysis by Fourier transform confirmed the reliability of the air-filled catheter-derived esophageal pressure as an accurate surrogate of pleural pressure. A calculator for transpulmonary pressures is available online.ConclusionsWe propose a simple, minimally invasive, inexpensive and reproducible method for esophageal pressure monitoring with an air-filled esophageal catheter without balloon. It holds the promise of widespread bedside use of transpulmonary pressure-guided protective ventilation in ICU patients.

An automated data cleaning method for Electronic Health Records by incorporating clinical knowledge

BackgroundThe use of Electronic Health Records (EHR) data in clinical research is incredibly increasing, but the abundancy of data resources raises the challenge of data cleaning. It can save time if the data cleaning can be done automatically. In addition, the automated data cleaning tools for data in other domains often process all variables uniformly, meaning that they cannot serve well for clinical data, as there is variable-specific information that needs to be considered. This paper proposes an automated data cleaning method for EHR data with clinical knowledge taken into consideration.MethodsWe used EHR data collected from primary care in Flanders, Belgium during 1994–2015. We constructed a Clinical Knowledge Database to store all the variable-specific information that is necessary for data cleaning. We applied Fuzzy search to automatically detect and replace the wrongly spelled units, and performed the unit conversion following the variable-specific conversion formula. Then the numeric values were corrected and outliers were detected considering the clinical knowledge. In total, 52 clinical variables were cleaned, and the percentage of missing values (completeness) and percentage of values within the normal range (correctness) before and after the cleaning process were compared.ResultsAll variables were 100% complete before data cleaning. 42 variables had a drop of less than 1% in the percentage of missing values and 9 variables declined by 1–10%. Only 1 variable experienced large decline in completeness (13.36%). All variables had more than 50% values within the normal range after cleaning, of which 43 variables had a percentage higher than 70%.ConclusionsWe propose a general method for clinical variables, which achieves high automation and is capable to deal with large-scale data. This method largely improved the efficiency to clean the data and removed the technical barriers for non-technical people.

Disentangling Doppler modulation, aberration and the temperature dipole in the CMB

An observer in relative motion to the Cosmic Microwave Background (CMB) rest frame is sensitive to both aberration and Doppler effects. Both effects introduce similar but non-identical off-diagonal couplings in the spherical harmonic coefficients. The CMB temperature dipole may have additional contributions from an intrinsic component, which in turn produces different aberration and Doppler couplings. Moreover, the standard conversion from intensity measurements into temperature also introduces spurious Doppler-like couplings. In order to learn about the intrinsic dipole it is therefore important to measure both aberration and Doppler couplings in an independent manner while also removing the spurious contributions from unit conversion, which are degenerate with the dipole. Here we present a pipeline to measure the Doppler and aberration signal independently from each other and from the dipole itself. We also consider realistic beaming, noise and mask effects. Our pipeline results in independent and unbiased estimators which have uncertainties only ~20% larger than the simple theoretical expectations. We discuss the achievable precision in each measurement for Planck 2018, and also forecast them for future ground-based experiments with the Simons Observatory and CMB-S4. An alternative pipeline is presented in order to cross-check results and improve robustness.

Generating pseudo-computerized tomography (P-CT) scan images from magnetic resonance imaging (MRI) images using machine learning algorithms based on fuzzy theory for radiotherapy treatment planning.

The substitution of computerized tomography (CT) with magnetic resonance imaging (MRI) has been investigated for external radiotherapy treatment planning. The present study aims to use pseudo-CT (P-CT) images created by MRI images to calculate the dose distribution for facilitating the treatment planning process. In this work, following image segmentation with a fuzzy clustering algorithm, an adaptive neuro-fuzzy algorithm was utilized to design the Hounsfield unit (HU) conversion model based on the features vector of MRI images. The model was generated on the set of extracted features from the gray-level co-occurrence matrices and the gray-level run-length matrices for 14 arbitrarily selected patients with brain malady. The performance of the algorithm was investigated on blind datasets through dose-volume histogram and isodose curve evaluations, using the RayPlan treatment planning system (TPS), along with the gamma analysis and statistical indices. In the proposed approach, the mean absolute error within the range of 45.4 HU was found among the test data. Also, the relative dose difference between the planning target volume region of the CT and the P-CT was 0.5%, and the best gamma pass rate for 3%/3mm was 97.2%. The proposed method provides a satisfactory average error rate for the generation of P-CT data in the different parts of the brain region from a collection of MRI series. Also, dosimetric parameters evaluation shows good agreement between reference CT and related P-CT images.

Development of length standard phantom for length measurement correction in x-ray image.

Specific tissue lengths or volumes in x-ray images are measured for diagnostic and therapeutic purposes. Measurements are used to make clinical decisions; however, the accuracy of these measurements has not been studied. In this study, based on the sources of uncertainty, an SI-traceable length standard phantom and an x-ray imaging system calibration method are proposed. The uncertainty in the length of the fabricated standard phantom is determined using a toolmaker's microscope. The sources of uncertainty in an x-ray imaging system, such as magnification, pixel-to-millimeter unit conversion, and penumbra effect, are considered, and the lengths of the phantom before and after imaging system calibration were compared. The maximum deviation of length measurements with and without calibration is (-0.11 ± 0.10) and (-3.37 ± 0.15) mm (k = 2, 95% level of confidence), respectively. The proposed phantom and calibration method can be used for calibrating x-ray images and obtaining their length correction values. Furthermore, length correction values are expected to be useful for diagnosis and treatment planning, where precise length measurements are essential.

Introducing GloRiSe – a global database on river sediment composition

Abstract. Rivers transport dissolved and solid loads from terrestrial realms to the oceans and between inland reservoirs, representing major mass fluxes on Earth's surface. The composition of river water and sediment provides clues to a plethora of Earth and environmental processes, including weathering, erosion, nutrient and carbon cycling, environmental pollution, reservoir exchange, and tectonic cycles. While there are documented, publicly available databases for riverine dissolved and suspended nutrients, there is no openly accessible, georeferenced database for riverine suspended sediment composition. Here, we present a globally representative set of 2828 suspended and bed sediment compositional measurements from 1683 locations around the globe. This database, named Global River Sediments (GloRiSe) version 1.1, includes major, minor and trace elements, along with mineralogical data, and provides time series for some sites. Each observation is complemented by metadata describing geographic location, sampling date and time, sample treatment, and measurement details, which allows for grouping and selection of observations, as well as for interoperability with external data sources, and improves interpretability. Information on references, unit conversion and references makes the database comprehensible. Notably, the close to globe-spanning extent of this compilation allows the derivation of data-driven, spatially resolved global-scale conclusions about the role of rivers and processes related to them within the Earth system. GloRiSe version 1.1 can be downloaded from Zenodo (https://doi.org/10.5281/zenodo.4485795, Müller et al., 2021) and GitHub (https://github.com/GerritMuller/GloRiSe, last access: 26 May 2021), where updates with adapted version numbers will become available, along with a technical documentation and an example calculation in the form of MATLAB scripts, which calculate the sediment-flux-weighted major element composition of the annual riverine suspended sediment export to the ocean and related uncertainties.

A Novel Approach of Unit Conversion in the Lattice Boltzmann Method

The lattice Boltzmann method (LBM) is an alternative method to the conventional computational fluid dynamic (CFD) methods. It gained popularity due to its simplicity in coding and dealing with a complex fluid flow such as the multiphase flow. The method is based on the kinetic theory, which is mesoscopic scale. Hence, applying the LBM method for macroscopic problems requires a proper conversion from the physical scale (conventional units) to the mesoscopic scale (lattice units) and vice versa. The Buckingham π theorem and the principle of corresponding states are the popular methods used for data reductions and unit conversion processes in the LBM. Nevertheless, those methods have some issues, such as difficulty in converting specific quantities, such as thermo-physical properties. The current work uses a novel dimensional analysis method systematically for mapping properties’ units between scales. Moreover, the approach has the flexibility in selecting parameters to ensure the stability of the method of solution. Several benchmark examples are used to evaluate the feasibility and accuracy of the proposed approach. In conclusion, the proposed approach showed the flexibility of the mapping between meso-scale to macro-scales and vice versa on solid bases rather than ad-hoc methods.

Characterisation, definition, and measurement issues of the middle class in sub-Saharan Africa

ABSTRACT In this study, we evaluate how both the definition of middle class and the dataset considered affect the estimated size of the middle class in sub-Saharan Africa. By considering the feasibility of a single definition of a middle class for all African countries based on the World Bank’s PovcalNet database, we estimate the size of this segment for a selection of countries. As part of the regional analysis, we follow with a country and city case study for Kenya and Nairobi. In the case study, to show the complexity and dynamics involved in the measurement at a more disaggregated level, we add the dynamic of currency unit conversion. This statistical assessment, as an investigation into the accuracy of past and current estimates of the middle class in sub-Saharan Africa, is helpful for both assessing the growth of the middle class on the continent and its potential to attract foreign investment.

Pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for timeseries aggregation, downscaling and unit conversion. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

Anti-SARS-CoV-2 Antibody Levels Measured by the AdviseDx SARS-CoV-2 Assay Are Concordant with Previously Available Serologic Assays but Are Not Fully Predictive of Sterilizing Immunity.

ABSTRACTWith the availability of widespread SARS-CoV-2 vaccination, high-throughput quantitative anti-spike protein serological testing will likely become increasingly important. Here, we investigated the performance characteristics of the recently FDA-authorized semiquantitative anti-spike protein AdviseDx SARS-CoV-2 IgG II assay compared to the FDA-authorized anti-nucleocapsid protein Abbott Architect SARS-CoV-2 IgG, Roche Elecsys anti-SARS-CoV-2-S, EuroImmun anti-SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA), and GenScript surrogate virus neutralization assays and examined the humoral response associated with vaccination, natural protection, and vaccine breakthrough infection. The AdviseDx assay had a clinical sensitivity at 14 days after symptom onset or 10 days after PCR detection of 95.6% (65/68; 95% confidence interval [CI], 87.8 to 98.8%), with two discrepant individuals seroconverting shortly thereafter. The AdviseDx assay demonstrated 100% positive percent agreement with the four other assays examined using the same symptom onset or PCR detection cutoffs. Using a recently available WHO international standard for anti-SARS-CoV-2 antibody, we provide assay unit conversion factors to international units for each of the assays examined. We performed a longitudinal survey of healthy vaccinated individuals, finding that median AdviseDx immunoglobulin levels peaked 7 weeks after first vaccine dose at approximately 4,000 IU/ml. Intriguingly, among the five assays examined, there was no significant difference in antigen binding level or neutralizing activity between two seropositive patients protected against SARS-CoV-2 infection in a previously described fishing vessel outbreak and five health care workers who experienced vaccine breakthrough of SARS-CoV-2 infection, all with variants of concern. These findings suggest that protection against SARS-CoV-2 infection cannot currently be predicted exclusively using in vitro antibody assays against wild-type SARS-CoV-2 spike. Further work is required to establish protective correlates for SARS-CoV-2 infection.

Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

Evaluation of the quality of irrigation water using the Agriwater software

Since water is an increasingly limited resource, having methods for evaluating its quality is necessary to ensure an adequate and sustainableuse for human consumption, agriculture and industry. The aim of this work was to describe agriwater software for evaluating the quality of irrigation water. The software consisted of the following stages: a) development of a database capable of hosting all the information stored in the software; b) conversion of chemical units; c) indexes calculation; and d) evaluation of performance and efficiency in data processing. The Agriwater software converts measuring units of ions to mg L-1, meq L-1 and mmol L-1, calculating the following water quality indexes: sodium absorption ratio, effective salinity, potential salinity and chloride toxicity. The result is Agriwater software, a professional tool that can handle, analyze and evaluate thousands of data in seconds in an intuitive and simple way.

Design and evaluation of an application-based pharmaceutical calculations review module

Background and purposeTo describe the design of an application-based calculations review module, determine retention of skills learned in a calculations course, determine student ability to identify information necessary to solve calculations, and evaluate student perceptions. Educational activity and settingThree student cohorts completed the calculations application-based review module. All students passed a required pharmaceutical calculations course previously (17 months prior for Cohort 1 and nine months prior for Cohorts 2 and 3). The activity included seven themed stations each with three questions. Each question was categorized by calculation type. Students utilized stock bottles and patient chart information to solve problems. For select stations, necessary information was missing, and students had to request it. Each student completed an activity evaluation form. FindingsTwo hundred ninety students completed the module (90, 102, and 98 in Cohorts 1, 2, and 3, respectively). Two hundred eighty students (97%) completed the activity assessment form. The overall average score was 85.1%, which did not differ significantly among the cohorts. Cohort 1 performed significantly lower on dosage, unit conversion, ratio, and milliosmole calculations. Almost all (96.4%) students agreed the activity reinforced lecture material, and 90% agreed the activity improved their ability to perform in future pharmacy practice. Participating students scored significantly higher on a pre-graduation math skills assessment. SummarySome calculation types, such as dosage, unit conversion, ratio, and milliosmoles may warrant more closely spaced reinforcement activities in the curriculum. Inclusion of the review module was associated with increased knowledge retention.

Characterization of laser beams: theory and application in laser-assisted bonding process

The International Organization for Standardization (ISO), in collaboration with the academic community, has developed and published a comprehensive system of standards for the characterization of optical components and laser beams. Our study offers a pedagogical introduction to the theory and application of laser beam characterization in accordance with ISO 13694:2018 and ISO 11145:2018. The characterizing parameters of each ISO standard are presented, defined mathematically, and explained in detail through the use of a minimum working example. A laser beam applied to an actual industrial process [laser-assisted bonding (LAB) process in the semiconductor packaging industry] is thoroughly analyzed to help the reader understand and interpret the characterizing results. Background noise correction and unit conversion methods are also discussed. We target researchers new to the field of laser beam analysis who want the acquire background knowledge, as well as more experienced researchers who want to implement their own laser beam analysis software and propose new definitions for their specific application. Although our study deals with only two ISO standards, the methods covered in our study can be easily applied to other norms that fit the reader’s application. Our study should not be treated as a full review of the LAB process nor of the beam profiling instruments and measurement principles. These are only mentioned to enhance the reader’s learning experience.

Exploring the impact of the COVID-19 pandemic on cardiac surgical services: A scoping review.

Cardiac surgery was severely affected by the COVID‐19 pandemic. Reallocation of resources, conversion of surgical intensive care units and wards to COVID‐19 facilities, increased risk of nosocomial transmission to cardiac surgery patients, lead to reduced accessibility, quality, and affordability of health care facilities to cardiac surgery patients. Increasing the mortality and morbidity rate among such patients. Cardiac patients are at an increased risk to develop a severe illness if infected by COVID‐19 and are associated with a high mortality rate. Therefore, measures had to be taken to reduce the spread of the virus. Various approaches such as the hubs and the spokes centers, or parallel system were enforced. Elective surgeries were postponed while urgent surgeries were prioritized. Use of personal protective equipments and surgeries performed by only senior surgeons became necessary. Surgical trainees were also affected as limited training opportunities deprived them of the experience required to complete their fellowship. Some of the trainees were reallocated to COVID‐19 wards, while others invested their time in research opportunities. Online platforms were used for teaching, meetings, and workshops across the globe. Although some efforts have been made to reduce the impact of the pandemic, more research and innovation is required.

Simulation-Based Analysis of Hydrometallurgical Processes. Case Study: Small-Scale Gold Mining in Ecuador

In this work, two hydrometallurgical processes for gold recovery are explored for a small-scale gold mining case study located at Ponce Enriquez, Azuay, Ecuador. The hydrometallurgical systems consider the use of sodium cyanide and sodium thiosulfate as leaching agents, with and without the incorporation of a subsystem for residual mercury removal. The proposed processes are modelled using the commercial simulator PRO/II interconnected with a Python scientific computing environment for performing stochastic simulations. Monte Carlo simulations, in which the conversion of the main units and the prices of gold vary following a random uniform distribution, permit observing the effects of these uncertainties on key recovery and economic indicators. The results facilitate the correlation between the inputs and outputs of interest as well as the visualization of the outputs variability for an adequate assessment of the systems under study by following a technical and social responsibility approach.

Mutations Spatiales Du Paysage Et Prospective Territoriale Dans Le Secteur Habité De La Commune De Karimama Au Nord Bénin

Abstract Remote sensing is very requested over last years for land-use and land cover monitoring at several spatial levels. ¶But beyond this stake, it plays a significant role in spatial planning while bringing answers to the environmental concerns. This study aims to analyze the landscape changes and to predict the future land-use changes in the inhabited sector of the of Karimama common, for a sustainable spatial planning. The methodological approach used is based on remote sensing technics, which allowed to make Landsat image processing of the years 1988;¶2003 and 2018 with Envi 5.3 software. ¶A predictive modeling was carried out starting from the extension Land Change Modeler available on IDRISI to generate the future probabilities of these changes. ¶The obtained results show that over the thirty last years, the landscape area has considerably changed. It ¶is is observed a crucial anthropization phenomenon caused by a conversion of the forest units into crop and fallow areas. ¶In addition, the inhabited sector of the commune is in full change, in particular the easily flooded zones of plain formerly occupied by the forest galleries and shrubby raised savannas, were transformed into marshy zones under the effect of the natural risks. ¶The prospective analysis carried out on the data shows that if no measurement of installation is taken, the two evoked tendencies will continue until 2033 and are likely to compromise the regional planning.¶ Key words : Remote sensing; Spatial changes¶S; R¶S¶egional planning; ¶Karimama, Benin