# Remote Sensing Technologies for Monitoring Argane Forest Stands: A Comprehensive Review
## 4 Remote Sensing Applications
### Drought Stress Monitoring  
Drought, a severe climatic condition marked by prolonged periods of water deficiency due to an imbalance in water resources, is considered one of the most complex and poorly comprehended natural phenomena. In recent decades, the study of drought has intensified due to its escalating frequency and consequential losses [159]. It is typically categorized into four types: agricultural droughts, meteorological droughts, hydrological droughts, and economic and social droughts [138; 160], leading to diminished vegetation, crop yields, and land degradation [161]. Meteorological drought arises from decreased precipitation, whereas agricultural drought involves inadequate water availability in soil for plant growth. Hydrological drought indicates a deficit in streamflow supply, while socioeconomic drought is characterized by an insufficient water supply to meet the demand for economic activities, affected by the drought conditions [162; 163; 160]. Numerous drought indices have been developed using diverse remote sensing data across various fields. Monitoring drought conditions involves the extensive use of these indices, which measure deviations in hydrologic processes [164]. Remote-sensing-based drought indicators are extensively employed in crop drought monitoring due to their effectiveness [138], especially in regions with limited access to meteorological stations [160; 165; 166]. These drought indices utilize distinct methods to quantify and analyze drought phenomena, each with varying requirements for remote sensing data, thereby providing valuable insights into this critical environmental challenge. Remote sensing also offers significant advantages for large-scale, real-time  
Figure 5: Key performance metrics for crop yield prediction algorithms. monitoring compared to traditional meteorological stations [138]. Prominent drought indicators include the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI), Standardized Precipitation Index (SPI), Soil Moisture Condition Index (SMCI), and Evapotranspiration Condition Index (ETCI). These indices vary in their methodologies and data requirements, providing nuanced perspectives on drought severity and impacts across different landscapes. The VCI, as generalized by [136], serves as a robust indicator of moisture deficiency, distinct from the NDVI, by separating near-term climate effects from enduring biological signals [167]. It scales NDVI values from 0 to 1, using minimum and maximum thresholds, making it crucial indicator for evaluating drought impacts on agricultural areas [168]. Complementarily, the Temperature Condition Index (TCI), formulated by [137] under NOAA's oversight in the United States, uses land surface temperature (LST) to assess vegetation stress from elevated temperature and humidity levels. Numerous studies have highlighted its positive correlation with VCI, making it valuable for monitoring drought events [160, 161, 168, 169]. Building upon this correlation, [PERSON] [135] introduced the Vegetation Health Index (VHI) by integrating VCI and TCI for agricultural drought detection. The PCI is a condition index that provides insights into weather conditions [162], while SPI, originally proposed by [170], identifies and tracks local droughs based on long-term precipitation data, typically spanning 3, 6, or 12 months, requiring at least 30 years of precipitation dataset [171]. It remains one of the most widely used drought indices globally. SMCI tracks soil moisture dynamics and is particularly suited for monitoring drought duration and impact across large geographical territories [163, 166, 172]. It has shown strong correlations with short-term SPI [160] and VCI indices [172]. The Evapotranspiration Condition Index (ETCI) significantly influences agriculture and water resource management, reflecting crop water deficits level in agricultural zones [173]. It is valuable for assessing vegetation's efficient use of available water resources.