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Bounoua, Lahouari

Publications and source records attributed to Bounoua, Lahouari.

At least 19 records

A Satellite Assessment of the Urban Heat Island in Morocco

Urban ecosystems interact with surroundings via land cover changes and their subsequent impact on surface temperature. In emerging countries, large urban agglomerations often form around cities, and only few studies have evaluated their impact. This study carries out the first ever large-scale assessment of urban heat island (UHI) and reflects on its mitigation in Morocco.The analysis reveals a well-defined UHI in urban-areas built within vegetated lands and an urban heat sink (UHS) in urban-areas built within arid regions. Both UHI and UHS amplitudes are higher during day than nighttime, emphasizing vegetation physiological activity. We show a monotonic increase in UHI amplitude with urban-area size. However, unlike previous studies, our analysis shows that as urban-areas built in desert-like environments grow in size, the UHS gradually decreases to ultimately turn into an UHI. On average, cities built within vegetation are warmer than rural fringe by 1.51°C during daytime. This suggests that daytime urban heating may exacerbate the potential climate warming. Our results also suggest that adapted trees constitute a natural cooling mechanism and should be part of urban heating mitigation in Morocco.

Urban Heat Sink↗

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

Management of Leshmaniases in the Era of Climate Change in Morocco

The proliferation of vector-borne diseases are predicted to increase in a changing climate and Leishmaniases, as a vector-borne diseases, are re-emerging diseases in several regions of the world. In Morocco, during the last decade, a sharp increase in cutaneous leishmaniases cases has been reported. Nevertheless, in Morocco, leishmaniases are a major public health problem, and little interest was given to climate change impacts on the distribution and spread of these diseases. As insect-borne diseases, the incidence and distribution of leishmaniases are influenced by environmental changes, but also by several socio-economic and cultural factors. From a biological point of view, environmental variables have effects on the survival of insect vectors and mammalian reservoirs, which, in turn, affects transmission. Here, we highlight the effects of climate change in Morocco and discuss its consequences on the epidemiology of leishmaniases to identify challenges and define targeted recommendations to fight this disease.

climate change↗

A Method for Mapping Future Urbanization in the United States

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Bounoua, Lahouari↗

Regional Impacts of Urbanization in the United States

We simulate the impact of impervious surface areas (ISA) on the U.S. local and regional climate. At a local scale, we find the urban area warmer than the surrounding vegetation in most cities, except in arid climate cities where urban temperature is cooler for much of the daytime. For all 9 regions studied, simulated results show that the growing season maximum surface temperature difference between urban and the dominant vegetation occurs around mid-day and is strongest in the northern regions. Regional temperature differences of 3.0 C, 3.4 C, and 3.9 C were simulated in the Northeast, Midwest, and Northwest, respectively. In these regions evaporative cooling, during the growing season, creates a stronger urban heat island (UHI). The UHI is less pronounced during winter when vegetation is dormant. Our results suggest that the ISA temperature is set by building material's characteristics and its departure from that of the surrounding vegetation is essentially driven by evaporative cooling. Except when rainfall is small, the highest surface runoff to precipitation ratios are simulated in most cities, especially when precipitation events occur as heavy downpours. In terms of photosynthesis, we provide a detailed distribution of maximum production in the U.S., a needed product for policy and urban planners.

Bounoua, Lahouari↗

Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers

In this paper, we assessed and compared land surface temperature (LST) in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2). We also evaluated the sensitivity of the models LST to different land cover types, fractions (percentages), and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI) mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.

Al-Hamdan, Mohammad Z.↗

Mapping Impact of Urbanization in the Continental U.S. From 2001-2020

We combine Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) products to create observation-based and scenario-based maps characterizing distant-past, recent-past, present, and near-future land cover and land use change in the continental United States at a 5km scale. These maps show the nature and impact of urbanization across the continental U.S. from 2001 to 2020 with focus on the relationship between population and urban growth and how it varies across the U.S. The influence of culture on urbanization characteristics are revealed in the results at city-scale, helping to provide insight into both past and projected urbanization trends.

Bounoua, Lahouari↗

Mapping Impact of Urbanization in the Continental U.S. from 2001 - 2020

We combine Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) products to create observation-based and scenario-based maps characterizing distant-past, recent-past, present, and near-future land cover and land use change in the continental United States at a 5km scale. These maps show the nature and impact of urbanization across the continental U.S. from 2001 to 2020 with focus on the relationship between population and urban growth and how it varies across the U.S. The influence of culture on urbanization characteristics are revealed in the results at city-scale, helping to provide insight into both past and projected urbanization trends.

Bounoua, Lahouari↗

Modeling Impact of Urbanization in US Cities Using Simple Biosphere Model SiB2

We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products, as well as climate drivers from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) in a Simple Biosphere land surface model (SiB2) to assess the impact of urbanization in continental USA (excluding Alaska and Hawaii). More than 300 cities and their surrounding suburban and rural areas are defined in this study to characterize the impact of urbanization on surface climate including surface energy, carbon budget, and water balance. These analyses reveal an uneven impact of urbanization across the continent that should inform upon policy options for improving urban growth including heat mitigation and energy use, carbon sequestration and flood prevention.

Zhang, Ping↗

Mapping Impact of Urbanization in the Continental U.S. from 2001-2020

Data fusion, from Landsat and MODIS, was used to characterize US buildup and to derive a plausible 2020 impervious surface area (ISA) projection based on observed rates of ISA change as a function of population from 2006 to 2011. The analysis shows that urbanization in the U.S. implicitly includes a cultural character whereby depending on the region, cities are either built horizontally with large ISA per capita or vertically with a minimal spatial footprint. This cultural character can also be forced by land availability, topography and inland water. In other regions, cities seem to have adapted to their population growth and adjusted their ISA use per capita.

ISA↗

Modeling the Urban Impact on Semiarid Surface Climate: A Case Study in Marrakech, Morocco

We combine Landsat and MODIS data in the Simple Biosphere Model to assess the impact of urbanization on surface climate in a semiarid city in North Africa. The model simulates highest temperatures in urban class, with spring average maximum temperature differences to other land cover classes ranging between 1.6 C and 6.0 C. During summer, these maximum temperature differences are smallest (0.5 C) with barelands and highest (8.3 C) with irrigated lawns. This excess heating is simulated above and beyond a seasonal temperature average of about 30 C during spring and 44 C during summer. On annual mean, a full urbanization scenario decreases the carbon fixation by 0.13 MtC and increases the daytime mean surface temperature by 1.3 C. This may boost the city energy consumption by 5.72%. Under a 'smart growth' scenario, whereby the city expands on barelands to cover 50% of the study region and all remaining barelands converted to orchards, the carbon fixation is enhanced by 0.04 MtC with a small daytime temperature increase of 0.2 C. Our results indicate that vegetation can mitigate the urban heating. The hydrological cycle indicates that highest ratio of surface runoff to precipitation (43.8%) occurs in urban areas, versus only 16.7 % for all cover types combined.

Lachir, Asia↗

Mapping Biophysical Parameters for Land Surface Modeling over the Continental US Using MODIS and Landsat

In terms of the space cities occupy, urbanization appears as a minor land transformation. However, it permanently modifies land's ecological functions, altering its carbon, energy, and water fluxes. It is therefore necessary to develop a land cover characterization at fine spatial and temporal scales to capture urbanization's effects on surface fluxes. We develop a series of biophysical vegetation parameters such as the fraction of photosynthetically active radiation, leaf area index, vegetation greenness fraction, and roughness length over the continental US using MODIS and Landsat products for 2001. A 13-class land cover map was developed at a climate modeling grid (CMG) merging the 500mMODIS land cover and the 30m impervious surface area from the National Land Cover Database. The landscape subgrid heterogeneity was preserved using fractions of each class from the 500 m and 30 m into the CMG. Biophysical parameters were computed using the 8-day composite Normalized Difference Vegetation Index produced by the North American Carbon Program. In addition to urban impact assessments, this dataset is useful for the computation of surface fluxes in land, vegetation, and urban models and is expected to be widely used in different land cover and land use change applications.

Biophysical↗

Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

Land Surface Temperature↗

Linking Climate to Incidence of Zoonotic Cutaneous Leishmaniasis (L. major) in Pre-Saharan North Africa

Shifts in surface climate may have changed the dynamic of zoonotic cutaneous leishmaniasis (ZCL) in the pre-Saharan zones of North Africa. Caused by Leishmania major, this form multiplies in the body of rodents serving as reservoirs of the disease. The parasite is then transmitted to human hosts by the bite of a Phlebotomine sand fly (Diptera: Psychodidae) that was previously fed by biting an infected reservoir. We examine the seasonal and interannual dynamics of the incidence of this ZCL as a function of surface climate indicators in two regions covering a large area of the semi-arid Pre-Saharan North Africa. Results suggest that in this area, changes in climate may have initiated a trophic cascade that resulted in an increase in ZCL incidence. We find the correlation between the rainy season precipitation and the same year Normalized Difference Vegetation Index (NDVI) to be strong for both regions while the number of cases of ZCL incidence lags the precipitation and NDVI by 2 years. The zoonotic cutaneous leishmaniasis seasonal dynamic appears to be controlled by minimum temperatures and presents a 2-month lag between the reported infection date and the presumed date when the infection actually occurred. The decadal increase in the number of ZCL occurrence in the region suggests that changes in climate increased minimum temperatures sufficiently and created conditions suitable for endemicity that did not previously exist. We also find that temperatures above a critical range suppress ZCL incidence by limiting the vector's reproductive activity.

NDIV↗

Radiative and Physiological Effects of Increased CO2: How Does This Interaction Affect Climate?

Several climate models indicate that in a 2xCO2 environment, temperature and precipitation would increase and runoff would increase faster than precipitation. These models, however, did not allow the vegetation to increase its leaf density as a response to the physiological effects of increased CO2 and consequent changes in climate. Other assessments included these interactions but did not account for the vegetation downregulation to reduce plant's photosynthetic activity and as such resulted in a weak vegetation negative response. When we combine these interactions in climate simulations with 2xCO2, the associated increase in precipitation contributes primarily to increase evapotranspiration rather than surface runoff, consistent with observations, and results in an additional cooling effect not fully accounted for in previous 2xCO2 simulations. By accelerating the water cycle, this feedback slows but does not alleviate the projected warming, reducing the land surface warming by 0.6 C. Compared to previous studies, these results imply that long term negative feedback from CO2-induced increases in vegetation density could reduce temperature following a stabilization of CO2 concentration.

Bounoua, Lahouari↗

Global Night-Time Lights for Observing Human Activity

We present a concept for a small satellite mission to make systematic, global observations of night-time lights with spatial resolution suitable for discerning the extent, type and density of human settlements. The observations will also allow better understanding of fine scale fossil fuel CO2 emission distribution. The NASA Earth Science Decadal Survey recommends more focus on direct observations of human influence on the Earth system. The most dramatic and compelling observations of human presence on the Earth are the night light observations taken by the Defence Meteorological System Program (DMSP) Operational Linescan System (OLS). Beyond delineating the footprint of human presence, night light data, when assembled and evaluated with complementary data sets, can determine the fine scale spatial distribution of global fossil fuel CO2 emissions. Understanding fossil fuel carbon emissions is critical to understanding the entire carbon cycle, and especially the carbon exchange between terrestrial and oceanic systems.

Hipskind, Stephen R.↗

Relationships Between Seed Weight, Germination Potential and Biochemical Reserves of Maritime Pine in Morocco: Elements for Tree Seedlings Improvement

Selection of quality seeds in breeding programs can significantly improve seedling productivity. Germination and biochemical analyses on seeds from ten natural populations of maritime pine (Pinus pinaster Ait.) in Morocco reveals significant differences among populations in seed weight, germination characters and protein content in both dry seeds and megagametophytes. During germination, the mobilization of protein content in megagametophyte is significantly different among populations than sugar content. A strong positive correlation between the germination capacity and the protein content in both dry seeds and megagametophytes indicates that the best populations in term of germination capacity may also be the richest in protein content. The present study finds that seed weight is not a good indicator for quality seed selection, nor is it recommended to increase the degree of germinability. Our results suggest that the pine population in southern Morocco might have adapted to drought conditions as it is characterized by heavy seed weight and lower speed of protein content mobilization in megagametophyte compared to northern populations growing in temperate climate.

Wahid, Nadya↗

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship with development intensity, size, and ecological setting for more than 3000 urban settlements globally. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby nonurban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to ensure objective intercomparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass shrubs biomes; and only a weak UHI or sometimes an urban heat sink (UHS) in cities in arid and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) with the difference in vegetation density between urban and rural zones represented by the MODIS normalized difference vegetation index (NDVI). Globally averaged, the daytime UHI amplitude for all settlements is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers compared with 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude, with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variance is explained by ISA for urban settlements within forests at mid to high latitudes. This percentage will increase to more than 80% when only settlements in the US are examined.

Zhang, Ping↗