Hassan Bazzi

AgroParisTech

The radar-backscattering coefficient (σ⁰) depends on surface characteristics and instrumental parameters (wavelength, polarization, and incidence angle). For Sentinel-1 (S1), with incidence angles ranging from 25° to 45°, σ⁰ for similar targets typically differs by a few dB depending on their localization in the S1 swath. Overcoming this angular de...

Management practices that increase the surface albedo of cultivated land could mitigate climate change, with similar effectiveness to practices that reduce greenhouse gas emissions or favor natural CO2 sequestration. Yet, the efficiency of such practices is barely quantified. In this study, we quantified the impacts of seven different management pr...

Several approaches based on process-based, statistical or economic models have been developed and are currently used by market analysts and governmental agencies to forecast agricultural yields and commodity prices at the national and global scales. However, these models require input data that are often difficult to obtain before crop harvest and...

Natural gas is the primary fuel used in U.S. residences, yet little is known about its consumption patterns and drivers. We use daily county-level gas consumption data to assess the spatial patterns of the relationships and the sensitivities of gas consumption to outdoor air temperature across U.S. households. We fitted linear-plus-plateau function...

Heat and drought events are increasing in frequency and intensity, posing significant risks to natural and agricultural areas with uncertain effects on the net ecosystem CO2 exchange (NEE). We modified the Vegetation Photosynthesis and Respiration Model to include soil moisture impacts on the gross ecosystem exchange (GEE) and respiration (RECO) fl...

This study investigates the potential of Sentinel-1 (S1) multi-temporal data for the early-season mapping of the rapeseed crop. Additionally, we explore the effectiveness of limiting the portion of a considered time series to map rapeseed fields. To this end, we conducted a quantitative analysis to assess several temporal windows (periods) spanning...

In Europe, the heterogeneous features of crop systems with majority of small to medium sized agricultural holdings, and diversity of crop rotations, require high-resolution information to estimate cropland Net Ecosystem Exchange (NEE) and its two main components of Gross Ecosystem Exchange (GEE) and the Ecosystem Respiration (R ECO). In this contex...

Citation: Bazzi, H.; Baghdadi, N.; Nino, P.; Napoli, R.; Najem, S.; Zribi, M.; Vaudour, E. Retrieving Soil Moisture from Sentinel-1: Limitations over Certain Crops and Sensitivity to the First Soil Thin Layer. Water 2024, 16, 40. https://doi.org/10.3390/ Abstract: This paper presents a comparison between the Sentinel-1 (S1)/Sentinel-2 (S2)-derived...

This study aims to enhance rapeseed field detection accuracy using Sentinel-1 (S1) time series data and addressing challenges in collecting ground samples. The proposed solutions include model transfer between years without retraining and secondly, developing models with limited training samples. The research evaluates the performance of Random For...

Soil moisture maps are essential for hydrological, agricultural and risk assessment applications. To best meet these requirements, it is essential to develop soil moisture products at high spatial resolution, which is now made possible using the free Sentinel-1 (S1) SAR (Synthetic Aperture Radar) data. Some soil moisture retrieval techniques using...

Soil moisture maps are essential for hydrological, agricultural and risk assessment applications. To best meet these requirements, it is essential to develop soil moisture products at high spatial resolution which is now made possible using the free Sentinel-1 (S1) SAR (Synthetic Aperture Radar) data. Some soil moisture retrieval techniques using S...

Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestation. Recent advances in deep learning techniques, coupled with the vast amount of spaceborne remote sensing data offer an unprecedented opportunity to map canopy height at...

Very high-resolution (∼10–100 m) surface soil moisture (SM) observations are important for applications in agriculture, among other purposes. This is the original goal of the S2MP (Sentinel-1/Sentinel-2-Derived Soil Moisture Product) algorithm, which was designed to retrieve surface SM at the agricultural plot scale by simultaneously using Sentinel...

Cover crops are intermediary crops planted in between two main cash crops. They play a role in limiting nitrate leaching into ground water. Currently, there is no database pertaining to cover crops despite their importance. The development period of cover crop is characterized by a dense cloud cover in Europe, which obstructs land surface monitorin...

Irrigation monitoring is of great importance in agricultural water management to guarantee better water use efficiency, especially under changing climatic conditions and water scarcity. This study presents a detailed assessment of the potential of the Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to detect irrigation events at the plot scale....

High-resolution (HR) surface soil moisture (SM) observations are important for applications in hydrology and agriculture, among other purposes. For instance, the S2MP (Sentinel-1/Sentinel-2 derived Soil Moisture Product) algorithm was designed to retrieve surface SM at agricultural plot scale using simultaneously Sentinel-1 (S1) backscatter coeffic...

Comprehensive knowledge about irrigation timing is crucial for water resource management. This paper presents a comparative analysis between C- and L-band Synthetic Aperture Radar (SAR) data for the detection of irrigation events. The analysis was performed using C-band time series data derived from the Sentinel-1 (S1) satellite and two L-band imag...

Accurate information about the irrigated surface is essential to help assess the impact of irrigation on water consumption, the hydrological cycle and regional climate. In this study, we compare recently developed operational and spatially transferrable classification models proposed for irrigation mapping. The first model suggests the use of spati...

Climate change will exacerbate environmental threats, which will, in turn, affect agricultural production patterns. This study addresses the feasibility of using Sentinel-2 (S2) optical remote sensing data to map the consequences of heatwaves on vineyard plots. The proposed method to map damaged and undamaged vineyards is based on the use of an int...

The climate change and the increase in the global population are putting more pressure on natural resources in order to satisfy the global food requirement. To fulfill the increasing food demand, the global agricultural intensification is mainly based on increasing the resource use especially water. Irrigation is the primary source of freshwater co...

In this study, we present an operational methodology for mapping irrigated areas at plot scale, which overcomes the limitation of terrain data availability, using Sentinel-1 (S1) C-band SAR (synthetic-aperture radar) and Sentinel-2 (S2) optical time series. The method was performed over a study site located near Orléans city of north-central France...

Surface soil moisture (SSM) is a key variable for many environmental studies, including hydrology and agriculture. Synthetic aperture radar (SAR) data in the C-band are widely used nowadays to estimate SSM since the Sentinel-1 provides free-of-charge C-band SAR images at high spatial resolution with high revisit time, whereas the use of L-band is l...

Le Pôle thématique national des surfaces continentales Theia a pour objectif d’accroître l’utilisation par la communauté scientifique et les acteurs publics de la donnée spatiale en complémentarité d’autres types de données, notamment les données in situ et aéroportées. Depuis quelques années, Theia, met à disposition des acteurs publics nationaux,...

Better management of water consumption and irrigation schedule in irrigated agriculture is essential in order to save water resources, especially at regional scales and under changing climatic conditions. In the context of water management, the aim of this study is to monitor irrigation activities by detecting the irrigation episodes at plot scale...

Short-term freeze/thaw cycles, which mostly occur in the northern hemisphere across the majority of land surfaces, are reported to cause severe economic losses over broad areas of Europe and North America. Therefore, in order to assess the extent of frost damage in the agricultural sector, the objective of this study is to build an operational appr...

Irrigation plays a significant role in agricultural production in order to meet the global food requirement under changing climatic conditions. To fulfill the high demand for food with an ever-increasing global population, better planning of irrigation is required. Therefore, more focus is being set on the assessment of irrigation performance for i...

In the context of monitoring and assessment of water consumption in the agricultural sector, the objective of this study is to build an operational approach capable of detecting irrigation events at plot scale in a near real-time scenario using Sentinel-1 (S1) data. The proposed approach is a decision tree-based method relying on the change detecti...

This letter proposes a deep learning model to deal with the spatial transfer challenge for the mapping of irrigated areas through the analysis of Sentinel-1 data. First, a convolutional neural network (CNN) model called "Teacher Model" is trained on a source geographical area characterized by a huge volume of samples. Then, this model is transferre...

This paper presents a comparison between the Sentinel-1/Sentinel-2-derived soil moisture product at plot scale (S2MP) and the new Copernicus surface soil moisture (C-SSM) product at 1-km scale over a wide region in southern France. In this study, both products were first evaluated using in situ measurements obtained by the calibrated time delay ref...

Mapping irrigated plots is essential for better water resource management. Today, the free and open access Sentinel-1 (S1) and Sentinel-2 (S2) data with high revisit time offers a powerful tool for irrigation mapping at plot scale. Up to date, few studies have used S1 and S2 data to provide approaches for mapping irrigated plots. This study propose...

This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Aperture Radar) time series over the Camargue region, Southern France. First, the temporal behavior of the SAR backscattering coefficient over 832 plots containing different crop types was analyzed. Through this analysis, the rice cultivation was identifie...

The objective of this paper is to present an analysis of Sentinel-1 derived surface soil moisture maps (S1-SSM) produced with high spatial resolution (at plot scale) and a revisit time of six days for the Occitanie region located in the South of France as a function of precipitation data, in order to investigate the potential of S1-SSM maps for det...

This paper assesses the potential of Synthetic Aperture Radar (SAR) in the C and L bands to penetrate into the canopy cover of wheat, maize and grasslands. For wheat and grasslands, the sensitivity of the C and L bands to in situ surface soil moisture (SSM) was first studied according to three levels of the Normalized Difference Vegetation Index (N...

The objective of this paper is to evaluate the potential of Sentinel-1 Synthetic Aperture Radar “SAR” data (C-band) for monitoring agricultural frozen soils. First, investigations were conducted from simulated radar signal data using a SAR backscattering model combined with a dielectric mixing model. Then, Sentinel-1 images acquired at a study site...

The purpose of this study is to analyze the potential of Sentinel-1 C-band SAR data in VV polarization for estimating the surface roughness (Hrms) over bare agricultural soils. An inversion technique based on Multi-Layer Perceptron neural networks is used. It involves two steps. First, a neural network (NN) is used for estimating the soil moisture...

This chapter shows how to map the surface soil moisture over agricultural plots and grasslands using the free and open-source software quantum geographic information system (QGIS), by coupling radar (synthetic aperture radar (SAR)) and optical images acquired at high spatial resolution (~10 m x 10 m). The chapter describes the implementation of QGI...

Soil moisture mapping at a high spatial resolution is very important for several applications in hydrology, agriculture and risk assessment. With the arrival of the free Sentinel data at high spatial and temporal resolutions, the development of soil moisture products that can better meet the needs of users is now possible. In this context, the main...