Tracking Reforestation in the Loess Plateau, China after the “Grain for Green” Project through Integrating PALSAR and Landsat Imagery

Abstract

An unprecedented reforestation process happened in the Loess Plateau, China due to the ecological restoration project ‘Grain for Green Project’, which has affected regional carbon and water cycles as well as brought climate feedbacks. Accurately mapping the area and spatial distribution of emerged forests in the Loess Plateau over time is essential for forest management but a very challenging task. Here we investigated the changes of forests in the Loess Plateau after the forest reconstruction project. First, we used a pixel and rule-based algorithm to identify and map the annual forests from 2007 to 2017 in the Loess Plateau by integrating 30 m Landsat data and 25 m resolution PALSAR data in this study. Then, we carried out the accuracy assessment and comparison with several existing forest products. The overall accuracy (OA) and Kappa coefficient of the resultant map, were about 91% and 0.77 in 2010, higher than those of the other forest products (FROM-GLC, GlobeLand30, GLCF-VCF, JAXA, and OU-FDL) with OA ranging from 83.57% to 87.96% and Kappa coefficients from 0.52 to 0.68. Based on the annual forest maps, we found forest area in the Loess Plateau has increased by around 15,000 km2 from 2007 to 2017. This study clearly demonstrates the advantages of data fusion between PALSAR and Landsat images for monitoring forest cover dynamics in the Loess Plateau, and the resultant forest maps with lower uncertainty would contribute to the regional forest management.

Land‐Use Intensity Reversed the Role of Cropland in Ecological Restoration Over the World's Most Severe Soil Erosion Region

“…LAI data attest to an obvious increase in vegetation greening on the LP during 1995-2015 (increase rate: 0.008 m 2 m −2 yr −1 ), and the area of a new leaf was increased by 1.23 × 10 5 km 2 . Several previous studies confirm this vegetation greening trend (Wang et al, 2015;Zhou et al, 2019). Overall, the above results can be attributed to large-scale vegetation restoration projects, intensified agriculture, and climate factor (Kou et al, 2021;Schwarzel et al, 2020).…”

Comparing the long‐term effects of artificial and natural vegetation restoration strategies: A case‐study of Wuqi and its adjacent counties in northern China

“…We found that the proportion of artificial restoration in Wuqi was the highest of all areas within the study region, which is supported by previous research. For instance, Sun et al (2015) and Liu et al (2020) found that the area and investment involved in the GFGP in northern Shaanxi were much higher than the average for the Loess Plateau; Liu et al (2020) and Zhou et al (2019) reported that the implementation intensity of the GFGP in Yan'an was significantly greater than that in Yulin and that it was even higher in Wuqi. The GFGP is a top-down regulatory policy (Meyer et al, 2018;Zhang et al, 2008), and the annual tasks for the GFGP are transmitted stepwise along with administrative levels (Xu & Zhang, 2021).…”

A comparative study of forest extraction methods in the yellow river basin (Gansu section) based on multi-source remote sensing data

“…However, most previous studies have focused on areas with dense forest vegetation. [6] This study aims to explore the applicability of forest information acquisition methods based on decision-level fusion and feature-level fusion of multi-source remote sensing data in areas with low forest coverage and scattered vegetation. Select the Yellow River Basin (Gansu Section) as the research object, compare and verify the accuracy of the classification results of the two methods, and obtain a high-precision forest information extraction method suitable for this research area, which is an evaluation of the ecological engineering effect of the Yellow River Basin (Gansu Section) A high-precision basic data collection method is provided.…”