Assessing and Mapping Forest Landscape Quality in China

Abstract

Forest landscape plays a critical role in the resource management and recreational planning of forest destinations. An assessment of forest landscape quality (FLQ) could reflect the distribution of landscape resources, hence identifying the hotpots and areas with high visual quality and protection values. The objective of this study is to propose, for the first time, a methodology for assessing FLQ at the national level. Based on China's forestry inventory database, the paper identified landform patterns and vegetative patterns as determinants (including 12 indicators) to establish an evaluation index system, and further implemented and mapped FLQ using the ArcGIS Engine platform. Results show high mountain ranges and tropical areas in China often have a high-quality forest landscape, while low FLQ scores are found in low mountains and foothills. The distribution of the four FLQ levels indicates most forest areas are featured with mediocre-or low-quality landscape values, and the differences of FLQ among different forest types are obvious. Furthermore, there is a relatively low correlation between the total forest area and the area of high-quality forest landscape. Overall, this study could contribute to enriching the existing assessment system for FLQ and to guiding the planning, policy development, and decision-making for China's forestry administration.

Urban Ecological Corridor Network Construction: An Integration of the Least Cost Path Model and the InVEST Model

“…The same as in previous studies, the degradation of cropland and forest caused by urban expansion was more severe [36]. The forest landscape in the alpine mountains and tropical regions of China is of high quality and positively correlated with the forest area [32]. The degree of habitat degradation of the Taihu Lake Basin has increased significantly over the past 30 years, especially in the construction of farmland for landscape heterogeneity [1].…”

“…These factors are habitat elements, geophysical landscape, and human disturbance [32,34]. According to the relative importance, we rounded each weight to four decimal places [32,37]. With the average inconsistency value of 0.06, the matrix analysis confirmed the consistency and reliability of the expert judgment [34].…”

“…We divided land use into six categories of 12 types ( Figure 2): water (4), built-up land (5), unused land (6), grassland (11,12), forest land (21)(22)(23)(24), and cropland (31)(32)(33). The water and cropland were the main types of landscapes in Wuhan.…”

“…AHP is a mature method to determine the weight of influence factors, especially for a multilevel and multifactor index system [31,32]. In this study, we invited 10 experts with more than 12 years of research experience in the fields of forestry, ecology, and landscape planning.…”

“…Based on expert assessments and literature reviews, we developed three factors ( Tables 3 and 4) that influenced the cost surface. These factors are habitat elements, geophysical landscape, and human disturbance [32,34]. According to the relative importance, we rounded each weight to four decimal places [32,37].…”