## 3 Results
### Focus of the Studies
This indicates that the spatial arrangement of pixels is more important than their intensity values, as these arrangements can be described by measures of contrast, homogeneity, randomness, or variability, such as entropy or variance. The study by [PERSON] et al. [129] focused on diagnostic performance indicators such as depleted fraction, evapotranspiration, and crop water productivity to evaluate the performance of irrigated rice, aiming to identify areas with good and poor performance. The depleted fraction provides insights into water efficiency or losses from drainage or percolation. Their parameters were derived using the PySEBAL model driven by Landsat images to analyze spatiotemporal patterns. [PERSON] et al. [130] aimed to identify potential soil salinity areas by integrating Sentinel-2 with field measurements, employing two approaches: assessing salinity through the Salinity Index and monitoring vegetation behavior over eight growing seasons from 2016 to 2019 in the arid Niger River basin in rice fields. [PERSON] et al. [65] present the results of a soil mapping approach that combined multi-temporal RapidEye, Landsat imagery, along with ASTER Global DEM terrain derivatives and soil samples to enhance the availability of spatial soil information in rural West Africa. In 2022, [PERSON] et al. [69] demonstrated that both tree species diversity and tree cover in semi-arid parklands are crucial for food production and enhance food security, utilizing an integrated landscape approach with current RS data and advanced data analysis methods. They advocate for land management policies that acknowledge the importance of co-benefits within the agricultural landscape diversity-food security nexus. [PERSON] et al. [131] presented an approach for assessing land suitability for precision agriculture in Nigeria, combining field data on soil properties of plots with remotely sensed land use suitability. Twelve studies addressed retrieving plant parameters. [PERSON] et al. (2001) [82] investigated the effects crop residues and phosphorus application have on fallow vegetation after repeated millet cultivation in the Sahel, measuring residual effects on herbaceous dry matter two years post-experiment and evaluating an RS method for herbaceous dry matter estimation. Their findings indicate that soil amendment impacts on fallow vegetation have to be considered in analyzing agro-pastoral systems. In a separate study [PERSON] and [PERSON] [126] (2001) tested non-destructive methods for spatially estimating millet growth and yield. This involved testing aerial photography, georeferenced radiometric, and chlorophyll measurements in an experiment in Niger. [PERSON] et al. (2020) [123] employed the PySEBAL model to estimate actual evapotranspiration over large areas throughout the crop growing season for water resource management. [PERSON] et al. (2015) [125] used SWIR bands to detect dry season vegetation mass and cover fraction with a ground radiometer and MODIS data, which is a key parameter for forage, erosion, and fire risk assessment in semi-arid areas. [PERSON] et al. (2023) [122] analyzed growth vegetation anomalies pro duced by the crop monitors of the main early warning systems for the 2010 to 2020 period. As a comparative measure, they used NDVI-based vegetation anomaly indicators. The convergence of EO data streams, advancements in methodologies, and cloud computing infrastructure calls, according to [PERSON] et al. (2019) [124], for a paradigm shift in operational agricultural monitoring. They assessed whether the Sen2-Agri platform can be effectively applied to different cropping systems to provide essential agricultural information with high accuracy. Their outputs include monthly vegetation status indices, crop masks and crop type maps, with vegetation status being derived from NDVI and LAI. The LAI as a plant parameter is the subject of several studies: [PERSON] et al. (2004) [121] evaluated MODIS LAI and fAPAR against in situ measurements, and [PERSON] et al.