Remotely sensed soil moisture products showed sensitivity to vegetation cover density and soil typology at regional dryland level. In these regions, drought monitoring is significantly performed using soil moisture index and rainfall data. Recently, rainfall and soil moisture observations have increasingly become available. This has hampered scientific progress as regards characterization of land surface processes not just in meteorology. The purpose of this study was to investigate the relationship between a newly developed precipitation dataset, SM2RAIN (Advanced SCATterometer (SM2RAIN-ASCAT), and NDVI (eMODIS-TERRA) in monitoring drought events over diverse rangeland regions of Morocco. Results indicated that the highest polynomial correlation coefficient and the lowest root mean square error (RMSE) between SM2RAIN-ASCAT and NDVI were found in a 10-year period from 2007 to 2017 in all rangelands (R = 0.81; RMSE = 0.05). This relationship was strong for degraded rangeland, where there were strong positive correlation coefficients for NDVI and SM2RAIN (R = 0.99). High correlations were found for sparse and moderate correlations for shrub rangeland (R = 0.82 and 0.61, respectively). The anomalies maps showed a very good similarity between SM2RAIN and Normalized Difference Vegetation Index (NDVI) data. The results revealed that the SM2RAIN-ASCAT and NDVI product could accurately predict drought events in arid and semi-arid rangelands.
We studied the effectiveness of SPIRITS processing software used to monitor drought. In this article, we propose practice steps and we prove that ecological modeling can be available with remote sensing data on a larger scale (for any place in the world) with SPIRITS. The studies summarize some important analyses of remote sensing time series at high temporal and medium spatial resolution. The Software for the Processing and Interpretation of Remotely sensed Image Time Series (SPIRITS) is a stand-alone flexible analysis environment created to facilitate the processing and analysis of large image time series and ultimately for providing clear information about vegetation status in various graphical formats to ecological modeling. The examples of operational analyses are taken from several recent drought monitoring articles. We conclude with considerations on SPIRITS use also in view of data processing requirements imposed by the coming generation of remote sensing products at high spatial and temporal resolution, such as those provided by the Sentinel sensors of the European Copernicus program.
Recently, pastoral ecosystem has been strongly studied by naturalists. However, phytoecological research must focus on species richness and enhance these ecosystems. The main objective of this research is to prove that the Moroccan pastoral ecosystem is very rich in terms of soil biodiversity and plant formations. In such areas, some pastoral plants maintain the physicochemical characteristics of soil. The field experiment was based on Braun-Blanquet sampling method with 90 surveys. The vegetation surveys carried out during the spring of the 2014–2018 period showed that there were 30 families, 23 orders, and 99 plant species (47 perennial species and 52 annual or biennial species). Of the 99 species inventoried, 14 species are very rare (RR) (14% of the total flora), six are rare (R), five are suspected rare (R?), three species are extinct or of doubtful presence (??), two are vulnerable (or seem to be), in decline, and could become rare in the short term (V), and one is a suspected very rare taxon (RR?). Investigation of life forms based on Raunkiaer method showed that there were various plants in different life forms. Among them, terophytes (47%) and 2% phanerophytes had the highest and the lowest plant species, respectively. This work led us to discover six species (Atractylis cancellata, Carduus pycnocephalus, Scorzonera angustifolia, Telephium sphaerospermum, Teucrium luteum, and Androsace maxima) and five types of rangeland in eastern Morocco. Chorology results showed a high proportion of Mediterranean biogeographic species in the study area, with a percentage of 35%. North African species followed the Mediterranean, with 14%. Euro-Mediterranean species constituted the major flora in the arid regions and played a significant role in the Mediterranean rangelands with 8%. The percentage of North African and Eurasian species was 6%, followed by North African and Asian species forming 4% of the total species. Eurasian, Paleo temperate, and Mediterranean Asian species had the same percentage (3%). The remains represented a low percentage, but contributed to the diversity and the richness of phytogeographic potential in the rangelands of eastern Morocco.
L’amélioration de l’état de la végétation et de la fertilité des sols est une préoccupation majeure pour une réhabilitation réussie dans les parcours dégradés. Cette étude examine l’impact de la mise en repos, de la technique de conservation de l’eau et du sol (CES) et de la plantation fourragère sur le recouvrement de la végétation, la phytomasse, la valeur énergétique de la phytomasse (UF. ha-1), le pH, la matière organique (MO), le phosphore assimilable (P), le calcaire total (CaT), le potassium échangeable (K), le sodium échangeable (Na) et la conductivité électrique (CE) dans cinq sites différents. Les résultats montrent que ces techniques permettent de restaurer les parcours steppiques en induisant une dynamique positive de la végétation et du sol. Ainsi, la mise en repos, la technique de CES et la plantation d’Atriplex nummularia ont entraîné une accumulation de la matière organique dans les sols et ont amélioré le recouvrement, la phytomasse et la valeur énergétique de la végétation avec des valeurs allant jusqu’à 85 %, 2,84 t. ha-1 et 931 UF. ha-1 respectivement. Par contre, le site en pâturage libre est marqué par une phytomasse inférieure à 0,31 t. ha-1, correspondant à une valeur énergétique inférieure à 46 UF. ha-1, et par un recouvrement végétal inférieur à 6 %. Ce site est marqué aussi par des taux du sodium échangeable (Na) et de conductivité électrique (CE) élevés avec des valeurs moyennes de 463,65 mg. kg-1 et 4,66 mS.cm-1 respectivement.
Working in the virtual world is different to real experiment in field. Nowadays, with remote sensing and new analysis programs we can assure a quick response and with less costs. The problem is efficiency of these methods and formulation of an exact response with low errors to manage an environmental risk. The objective of this article is to ask question about performance of some tools in this decision making in Morocco. The study uses (Test 1: TaylorFit Multivariate Polynomial Regressions (MPR); Test 2: SAS Neural Network (NN) to modeling relationship between European Center for Medium-Range Weather Forecasts dataset and NDVI eMODIS-TERRA at arid Eastern Morocco. The results revealed that the both test could accurately predict future scenario of water stress and livstock production decrease. The experience shows that virtual work with Artificial Intelligence is the future of ecological modeling and rapid decision-making in case of natural disasters.
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