Mapping the forests and their spatiotemporal changes in the Yellow River Basin (Gansu section) in China from 2008 to 2018 - Quanfu Niu; Mingzhi Liu; Bo Liu; Gang Wang; Zhenyu Wang; Xiujie Liu; Weiming Cheng; Kegong Li (European Journal of Remote Sensing)
Efficient and precise extraction of forest information is crucial for assessing the effectiveness of ecological projects and informing ecological policy adjustments in the Gansu section of the Yellow River Basin, China. Utilizing PALSAR (Phased Array L-band Synthetic Aperture Radar) and Landsat data, this study gathered forest/non-forest samples and formulated classification rules using the backscatter coefficients from PALSAR’s HH, HV, HH-HV, and HH/HV polarizations to generate monthly 30-meter forest data. These results were further refined using Landsat’s NDVImax and B7max indices. Our findings are as follows: The forest/non-forest data extracted from PALSAR and Landsat aligns more closely with publicly available forest data, achieving an overall accuracy of 95.4% and a Kappa coefficient of 0.87, which demonstrates the reliability and accuracy of our extraction method. Driven by ecological engineering projects and climate factors, the forest area has expanded significantly, from 13,200 square kilometers in 2008 to 19,800 square kilometers in 2018, with an average annual growth rate of 5%. Approximately 94.09% of the forest area is located at elevations up to 3,500 meters, with stable and increasing forest types predominantly found on the northern and western slopes, spanning elevations between 3,000 and 3,500 meters and slopes ranging from 20° to 35°. Our study provides valuable insights into regions characterized by rugged terrain and low forest density.