## 3 Results
### Focus of the Studies
\begin{table}
\begin{tabular}{c c c c c} \hline
**Study Focus** & **Category** & **Main Findings and Remote Sensing Potential** & **Challenges** & **Sources** \\ \hline \multirow{8}{*}{Crop Monitoring} & \multirow{4}{*}{Agricultural Productivity} & Estimating crop yields in a heterogenous small-scale agricultural landscape & Limited reference data for assessing accuracy of satellite-based estimates; high spatial variability & [7,33,67,80,81,95,96,97,98,106] \\  & & & & high spatial variability \\ \cline{2-5}  & \multirow{2}{*}{Crop-Type Mapping} & \multirow{2}{*}{Crop-Type Mapping} & Combining optical and SAR data and a variety of methods for multi-sensor data analysis & Heterogeneity, accuracy of final products; reference data scarcity & [11,25,34,45,47,61,62,64,70,71,86,100,107,108,109,110,111,112,113,114,115] \\  & & & & \\ \cline{2-5}  & \multirow{2}{*}{Plant Parameters} & LAI, soil amendments, vegetation monitoring, evapotranspiration, chlorophyll, etc. & Large within and between field variations in yield, LAI, chlorophyll, etc. & [12,82,119,110,111,112,113,114,115,116,117,118] \\ \cline{2-5}  & \multirow{2}{*}{Field Characteristics} & Derivation of field boundaries, soil moisture and type & Small feature extraction; limitations of Proxy Use & [4,29,65,69,129,130,131] \\ \cline{2-5}  & \multirow{2}{*}{Management Detection} & Water management performance; timing, impact and responses of crop management & Sustainability monitoring, reference data, data variability within fields & [1,10,37,38,77,87,132,132,133,134,135,136,137,138,139,140,141,142,143,144,145] \\ \hline \multirow{8}{*}{Agroforestry} & \multirow{2}{*}{Cocoa and Palm Oil} & Accurate mapping of cocoa and palm oil plantation including encroached areas & Limited reference data and reference data refinement & [22,46,78,88,90,143,144,145,146,147,148,149] \\  & & Fruit tree disease surveillance system & Lack of validation data & [40,146,147,148,149] \\ \cline{2-5}  & \multirow{2}{*}{Above Ground Biomass in Agroforestry systems} & Spatially explicit AGB estimates for reporting reduction emission efforts & Site complexity, poor-quality reference data, spectral variability within the same class and mixed pixels from fragmented landscapes & [79,89,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168] \\ \cline{2-5}  & \multirow{2}{*}{Semi-arid Parklands} & Mapping agroforestry parklands and their influence on crop yields & Upscaling individual tree level to landscape level (diversity of tree species and mix of crop types) & [68,85,153,154,155,156,157,158,159,161,162,163,164,165,166,167,168] \\ \hline \multirow{8}{*}{LULUC (with crop focus)} & \multirow{2}{*}{Data Consistency} & Improved accuracy (data fusion and very high-res.) & Lack of consistent LULUC maps & [30,158,159,150,151,152,154,155,156,157,158,159,160,161,162,163,164,165] \\ \cline{2-5}  & \multirow{2}{*}{Classification Accuracy} & Supporting decision-making for multiple objectives & Low agreement among RS datasets & [18,32,43,66,84,160,161,162,163,164,165,166,167,168] \\ \cline{2-5}  & \multirow{2}{*}{Mapping Approaches} & Diverse and new methodologies and various data integration for improved mapping of LULUC & Similar phenological signatures complicate mapping & [73,166,167,168] \\ \cline{1-1} \cline{2-5}  & & & & \\ \end{tabular}
\end{table} 
Table 2: Overview Table summarizing the main findings, RS potential, and remaining challenges for each research focus category.