The Influence of Data Density and Integration on Forest Canopy Cover Mapping Using Sentinel-1 and Sentinel-2 Time Series in Mediterranean Oak Forests

Spatial effects analysis of natural forest canopy cover based on spaceborne LiDAR and geostatistics

Because of the high cost of manual surveys, the analysis of spatial change of forest structure at the regional scale faces a difficult challenge. Spaceborne LiDAR can provide global scale sampling and observation. Taking this opportunity, dense natural forest canopy cover (NFCC) observations obtained by combining spaceborne LiDAR data, plot survey, and machine learning algorithm were used as spatial attributes to analyze the spatial effects of NFCC. Specifically, based on ATL08 (Land and Vegetation Height) product generated from Ice, Cloud and land Elevation Satellite-2/Advanced Topographic Laser Altimeter System (ICESat-2/ATLAS) data and 80 measured plots, the NFCC values located at the LiDAR's footprint locations were predicted by the ML model. Based on the predicted NFCC, the spatial effects of NFCC were analyzed by Moran's I and semi-variogram. The results showed that (1) the Random Forest (RF) model had the strongest predicted performance among the built ML models (R2=0.75, RMSE=0.09); (2) the NFCC had a positive spatial correlation (Moran's I = 0.36), that is, the CC of adjacent natural forest footprints had similar trends or values, belonged to the spatial agglomeration distribution; the spatial variation was described by the exponential model (C0 = 0.12×10-2, C = 0.77×10-2, A0 = 10200 m); (3) topographic factors had significant effects on NFCC, among which elevation was the largest, slope was the second, and aspect was the least; (4) the NFCC spatial distribution obtained by SGCS was in great agreement with the footprint NFCC (R2 = 0.59). The predictions generated from the RF model constructed using ATL08 data offer a dependable data source for the spatial effects analysis.

Impact of Iran's Forest Nationalization Law on Forest Cover Changes over Six Decades: A Case Study of a Zagros Sparse Coppice Oak Forest

Forest nationalization policies in developing countries have often led to a reduction in local forest ownership rights and short- or long-term exploitative behaviors of stakeholders. The purpose of this research is to quantify the effect of Iran's Forest Nationalization Law (FNL) in a part of Zagros Forest over a 68-year time period (1955-2022) using 1955 historical aerial photos, 1968 Corona spy satellite photography, and classification of multi-temporal Landsat satellite images. A past classification change detection technique was used to identify the extent and the pattern of land use changes in time. For this purpose, six periods were defined, to cover the time before and after the implementation of FNL. A 0.27% deforestation trend was identified over the period after the FNL. Dense and open forested area has decreased from 7175.62 ha and 68,927.46 ha in 1955 to 5664.26 ha and 59,223.38 ha in 2022. The FNL brought decisive changes in the legal and forest management systems at the state level, mainly by giving their ownership to the state. Accordingly, the FNL and the related conservation plans have not fully succeeded in protecting, rehabilitating, recovering, and developing the sparse Zagros Forest ecosystems, as their most important goals.