Researchers have explored various methods used to recover the spatiotemporal patterns of the long-term historical forestland cover before the existence of remote sensing satellites, which can be summarized in the following three aspects. The first is the forest area reconstruction method, which relies on statistical yearbook or literature to reconstruct the area change characteristics of forestland. For example, Esser
et al. (
1999) estimated the changes in FC in Europe from 1000 to 1850. Based on historical documents and statistical yearbook, some studies have conducted both qualitative and quantitative research on the area of historical forests of China (Lin,
1983; Shi,
1991; Fan and Dong,
2001) or America (Clawson,
1979). Based on historical documents of Qing Dynasty, He
et al. (
2007) combined modern statistical methods and changes in woodlands and population trends; they reconstructed a provincial forestland dataset with a time scale of 50 years starting in 1700. By analyzing historical literature, previous potential vegetation restoration, and driving forces, Ye
et al. (
2009) reconstructed the forest and grassland cover of each county in Northeast China over the past 300 years. The second method involves spatial pattern reconstruction using a model to recover forestland cover patterns. With the forest area as the limitation of the amount or rate of forest in grid units, this method uses environmental factors affected forestland distribution to establish the forest distribution potential suitability, and then construct a spatial-grid allocation model and quantitatively reconstruct the distribution pattern of forestland. For example, Kaplan
et al. (
2009) used population as a substitute factor to create gridded forestland data with a spatial resolution of 5′×5′ in the 1000 years prior to European industrialization through the interaction between agriculture and forestry. Steyaert and Knox (
2008) used county-level forest statistics as an area control factor, combined with land cover, potential vegetation, and soil data to generate a gridded product of land cover with a spatial resolution of 20 km in the eastern United States in 1650-1992. Liu and Tian (
2010) and Tian
et al. (
2014) generated the spatial patterns of historical cropland, forestland, and built-up land in China and India, respectively. By assuming that the interaction between cropland and forestland as well as assuming the spatial pattern of historical forest did not exceed the outer boundary of the potential natural forest vegetation, Li
et al. (
2014) and He
et al. (
2014) reconstructed forest in the past 300 years with a spatial resolution of 10 km in northeast and southwest China, respectively. Based on the above approach, He
et al. (
2015) further gridded China’s forest spatial pattern since 1700 using a temporal resolution of 20 years and a spatial resolution of 10 km. By comprehensively considering the behavioral characteristics of the individual in converting forestland for agricultural land and farming, cutting down forests for lumber and timber, Yang
et al. (
2018) constructed a forest distribution reconstruction model. That study reconstructed China’s gridded forestland dataset in 1661-1952 with a spatial resolution of 1 km. The third method involves image or map-based extraction of land use. Using high-precision atlases (e.g., historical thematic maps and topographic maps), after location registration, vectorization, and attribute correction, the long-term historical patterns of change in forestland use can be directly reconstructed. Ciupa
et al. (
2016) used historical maps, soil maps, and a digital elevation to model the FC changes occurring in the Holy Cross Mountains from 1800-2011. Based on digital forest maps or black and white orthophoto maps produced in 1868-2005, Cervera
et al. (
2020) reconstructed the forest distribution pattern in the Mediterranean area. Brandolini
et al. (
2020) modeled the landscape pattern of the Upper Rhone Valley in the past 200 years based on historical maps and GIS technology. Szypula (
2020) adopted paleotopographic maps to recover the land use patterns of the Upper Silesian Industrial Region in 1890-2014. Chen
et al. (
2019) have reconstructed Taiwan’s land cover changes during 1904-2015 by means of historical maps and satellite images at a grid of 500 m. Among the above methods, the map extraction method has recently been widely used to recover historical land use information based on first-hand dataset. If the quality of an atlas data source is reliable, the reconstructed land use information will contain high spatiotemporal resolution as well as being reliable. This method has become widely used by the academic community (Jiang,
2015; Han
et al.,
2016; Wan
et al.,
2018).