# Understanding Forest Health with Remote Sensing-Part II--A Review of Approaches and Data Models
## 2 Trends in Close-Range RS Approaches for Assessing FH
### Radar
\begin{table}
\begin{tabular}{p{85.4 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Application** & **Example Studies** & **Main Findings** \\ \hline Deforestation & [173] & Shuttle Imaging Radar (SIR) L-band better than C-band. Multiple polarizations required to detect intermediate Amazon deforestation classes. \\ \cline{2-3}  & [174] & Airborne L- and P-bands better than X- and C- bands in classifying selective logging classes. Image texture also beneficial. Identified a need for multi-temporal data to discriminate disturbed/logged areas from temporally stable forest classes. \\ \cline{2-3}  & [175] & PALSAR L-band object-based classification of forest and deforestation classes in Indonesia for 4 successive years. Markov chain analysis applied in future scenarios modelling of potential deforestation areas to aid in reducing rates of deforestation. \\ \hline  & [176] & Above ground biomass (AGB) (avg. 78 t/ha) for 3 classes (non-forest, shrub and forest) in disturbed forests of Laos using PALSAR L-band. High RMSE (42\%-52%) but similar to a model using AVNIR optical data, the latter being more difficult to obtain due to the persistent cloud cover. \\ \cline{2-3}  & [177; 178; 179] & Improved AGB modelling with higher saturation threshold using: (1) Cross-polarized (HV) data; (2) P-band that penetrates deeper into the canopy; (3) Shorter-to-longer wavelength backscatter ratio (e.g., C/L); (4) Averages of multi-temporal images to reduce moisture/ rain effects. \\ \cline{2-3} Forest degradation: Estimation of forest structure parameters & [180; 181] & AGB loss estimation: (1) Relation between 2007 PALSAR HV L-band backscatter and AGB in a forest-savannah of Africa applied to 1996 JERS-1 HH L-band data to estimate biomass and detect areas of biomass loss. \\ \cline{2-3}  & [180; 181] & Concluded that better consistency and calibration between data types is needed to conduct such temporal analysis; (2) Multi-temporal canopy height derived from SRTM C-band InSAR and IceSAT GLAS LiDAR used in allometric equations to estimate biomass and biomass loss in mangrove forest due to hypersaline soils caused by anthropogenic hydrological changes. \\ \cline{2-3}  & [182] & Leaf Area Index (LAI): VV/HH ratio (and additional VV terms for dry forests with stronger trunk response) derived from Envisat ASAR C-band images to estimate LAI in boreal and subarctic forests. \\ \cline{2-3}  & [183] & Forest density: Six incoherent decomposition techniques compared using RADARSAT-2 data in forests in India. Support Vector Machine (SVM) classification of the decomposition parameters produced 70\%-90\% accuracy for 3 forest density classes. \\ \hline  & [184] & Greater backscatter in burned areas. \\ \cline{2-3}  & [185] & Burn severity and surface roughness in an Alaska forest were the strongest factors affecting ERS-1 C-band VV backscatter. Relationship was strongest when surface moisture variations were minimal. \\ \cline{2-3} Fire impacts & [186] & Ratio of pre- to post-fire backscatter in a given polarization related to a temperate forest burn intensity index. Dry period cross-polarized data performed best. \\ \cline{2-3}  & [187] & Individual PALSAR polarimetric, phase, and decomposition parameters distinguished Amazon burn classes if area burned 3 or more times. More subtle burn discrimination achieved with multiple variable models, particularly those with phase and power metrics. \\ \cline{2-3}  & [173] & Flooded forest class mapped based on dead trees producing high double bounce scattering and a large (120\({}^{\circ}\)) phase difference between HH- and VV-polarized returns at both C- and L-band. \\ \cline{2-3} Inundation & [188] & Effects of incident angle on RADARSAT-1 C-band backscatter evaluated in flooded forests of North Carolina. Moderate angles detected inundation best during both leaf-off and leaf-on periods. \\ \cline{2-3}  & [189] & InSAR data generated from PALSAR L-band and RADARSAT-1 C-band data to determine flooding levels in Louisiana swamp forests. HH best single polarization.