La présente étude a pour objectif de contribuer au suivi de la désertification au nord d’Algérie par l’utilisation des capteurs MODIS (MODerate resolution Imaging Spectroradiometer) de TERRA. A cet effet, certains paramètres géophysiques (albédo "R0", indice de végétation "NDVI" et température de surface "TS") sont produits régulièrement et couvrent la période de 2000 à 2005. Les combinaisons de ces paramètres deux à deux en particulier R0 -TS ; NDVI-TS et NDVI-R0 ont permis respectivement la caractérisation de l'état hydrique et de l'état de la végétation.La synthèse de l'ensemble des résultats sous un système d’information géographique (SIG), ainsi que leurs confrontations avec d'autres types de données ont permis de dresser des cartes de la sensibilité à la désertification selon cinq degrés (très bon état, bon état, état critique, état dégradé et état très dégradé). Ces résultats montrent qu’environ 75 % des parcours steppiques sont désertifiés ou au seuil de la désertification.

The present paper reports on an investigation to monitor the drought status in Algerian forest covered areas with satellite Earth observations because ground data are scarce and hard to collect. The main goal of this study is to map surface energy fluxes with remote sensing data, based on a simplified algorithm to solve the energy balance equation on each data pixel. Cultivated areas, forest cover and a large water surface were included in the investigated surfaces. The input parameters involve remotely sensed data in the visible, near infrared and thermal infrared. The surface energy fluxes are estimated by expressing the partitioning of energy available at the surface between the sensible heat flux (H) and the latent heat flux (LE) through the evaporative fraction (Λ) according to the S-SEBI (Simplified Surface Energy Balance Index) concept. The method is applicable under the assumptions of constant atmospheric conditions and sufficient wet and dry pixels over a Landsat 7 image. The results are analyzed and discussed considering instantaneous latent heat flux at the data acquisition time. The results confirm the relationships between albedo (r₀), the surface temperature (T₀) and the evaporative fraction. The method provides estimates of air temperature and LE close to reference measurements. The estimate of latent heat flux and other variables are comparable to those of previous studies. Their comparison with other methods shows reasonable agreement. This approach has demonstrated its simplicity and the fact that remote sensing data alone is sufficient; it could be very promising in areas where data are scarce and difficult to collect.

A new approach of the modified method of the analysis of innovative trends (ITA) was applied to the categories of maximum daily rains coming from 41 pluviometric stations of Macta (North West Algeria) for the period 1970-2010. Six categories of maximum daily rainfall were considered: light: 0–4 mm/day (A); mild to moderate: 4–16 mm/day (B); moderate-heavy: 16–32 mm/day (C₁); heavy: 32–64 mm/day (C₂); heavy torrential: 64–128 mm/day (D₁); and torrential: greater than or equal to 128 mm/day (D₂). The results show that during the second period (1990-2010), the increasing trends were detected in the middle categories B (most frequent: 20.78%), C₁ (17.85%), C₂ (20.21%) and D₁ (4.92%). In addition, migratory movements and rainy events towards the higher categories were detected (in particular towards C₁ (8.84%)). These results show the increase in extreme rains in the Macta watershed during the period (1990-2010).

Obtaining evapotranspiration and surface energy fluxes with remotely sensed data to improve agricultural water management

Accurate spatio-temporal estimation of evapotranspiration (ET) and surface energy fluxes is crucial for many agro-environmental applications, including the determination of water balance, irrigation scheduling, agro-ecological zoning, simulation of global changes in land use and forecasting crop yields. Remote sensing based energy balance models are presently most suitable for estimating ET at both temporal and spatial scales. This study presents an intercomparison of ET maps over the Habra plain in western Algeria obtained with two different models: Ts/VI trapezoid (Surface temperature/Vegetation Index Trapezoid Model) and SEBAL (Surface Energy Balance Algorithm for Land). Ts/VI trapezoid is the most used model, due to its simplicity, ease of use, few data input requirements and relatively high accuracy. It allows estimating ET directly by using the Priestley-Taylor equation. Whereas SEBAL allows estimating ET as the residual term of the energy balance equation, by using a rather complex hot and cold pixel based contextual approach to internally calibrate sensible heat flux through an iterative approach. The data set consists of four Landsat-8 OLI/TIRS images acquired on 2018-2019 and some ground measurements. In conclusion, the results show that SEBAL and Ts/VI trapezoid models provide comparable outputs and suggest that both the two models are suitable approaches for ET mapping over agricultural areas where ground measurements are scarce or difficult to collect.