Forests are associated with countrywide ecological security, and there are significant differences in the forests of different regions. Based on the DPSIR model, 25 indicators were selected from five dimensions to determine the index system, and the entropy-weighted TOPSIS method and gray correlation were applied to determine the index of western China’s forests. The spatial distribution map was used to observe the spatial changes of forests. The results show that first, Inner Mongolia (0.466) has the best forest ecological security status and Ningxia (0.124) has the worst forest resource status. Second, the first and most frequent correlation is the area of planted forests (I1). The last and most frequent correlation is sulfur dioxide emission (P2). Thirdly, Inner Mongolia and Szechwan belong to the high ecological safety–high economic level, Yunnan, Guangxi, and Tibet belong to the high ecological safety–low economic level, and Gansu and Guizhou belong to the low ecological safety–low economic level. The rest of the regions are classified in the low ecological security–high economic level. Fourth, the forest ecological security in western China has gradually become better, with the security index increasing from 0.417 to 0.469, with an average annual increase of 12.47%.

China’s forest ecological problems are becoming increasingly serious, especially in the Yangtze River Basin (YRB) area. The basin has rich species resources and a well-developed natural forest management and conservation policy. Taking the YRB as the object, we combine the DPSIRM model to build a forest evaluation system containing 6 criterion layers and 24 indicator layers. The entropy weight method-TOPSIS and ArcGIS were combined to assess the forest state and the distribution characteristics of the 11 regions. Furthermore, grey relational analysis (GRA) was used to study the influencing factors of forest status. The results are as follows: (1) the comprehensive index of the YRB forests increased by 192.66% during the study period. The forest status showed the stage characteristics of small climb, basic flatness, and significant improvement. (2) The forest status varied significantly among provinces (cities), with Tibet (0.483) in the best condition and Qinghai (0.103) in a worse condition. (3) Except for Tibet, the rest of the regions are more influenced by the extent of development of the economy. (4) The factor most strongly correlated with the YRB is the forest response (R) indicator.