1. Introduction
Vegetation, as the core component of the terrestrial ecosystem, is the link between the atmosphere, soil, water, and other natural factors in the ecosystem. It plays an important role in soil and water conservation, climate regulation, and the stability of the ecological environment [
1,
2,
3]. Vegetation change is easily affected by climate. Under the trend of global warming, it has important theoretical value and there are application prospects to study the vegetation distribution, growth status, and vegetation structure response to meteorological factors [
4,
5,
6]. With the continuous development and maturity of remote sensing technology, vegetation remote sensing data has become a key data source for monitoring global and regional land cover change. The Normalized Difference vegetation index (NDVI) is the most commonly used indicator to characterize vegetation growth status and coverage, and it is widely used in the study of vegetation change and its driving factors [
7,
8,
9].
The middle reaches of the Yangtze River (MRYR), including Hunan Province, Hubei Province, and Jiangxi Province, is the core area of the development of the Yangtze River economic belt, and also the key area of China’s “two screens and three belts” ecological security strategy. The region has important ecological functions such as water conservation and regulation, biodiversity protection, and basin ecological security. It plays an important role in the ecological security and ecosystem stability of China and even East Asia [
10]. In recent years, due to the impact of climate change and human activities, the ecological environment of the region has been deteriorating, and the problem of ecosystem degradation is becoming increasingly prominent, which poses a serious threat to the water resource conditions, ecological security, and sustainable development of the social economy of the region and the whole Yangtze River Basin [
11]. The change of vegetation ecosystem in the MRYR has not only attracted the attention of scholars at home and abroad, but has also been highly valued by the Chinese government [
12].
In 2005, China plans to invest USD 1134.94 million to start 22 ecological protection projects, including returning grazing land to grassland, returning farmland to forests, and harnessing ecologically deteriorated land [
13,
14]. According to the results of the Eighth National Forest Inventory (2009–2013), China’s plantation area was 69.33 million ha, accounting for 36% of the forests area and for 17% of the national forests volume, and the plantation scale ranks first in the world [
15,
16]. The results of the Ninth National Forest Inventory (2014–2019) showed that the area of plantations (5.02 million ha) is larger than that of natural forests (5 million ha) in some provinces of the MRYR, but the volume was lower than that of natural forests (180.65 million m
3 of plantations; 226.51 million m
3 of natural forests) [
17]. The community structure of plantations and natural forests was usually different, the composition of plantations was relatively single, and the ecological stability was fragile [
18,
19]. Many scholars have studied the differences of community structure and soil components of plantations at the stand scale, but there are few studies on the differences of landscape patterns and vegetation dynamics between plantations and natural forests [
20,
21,
22]. Analyzing the dynamic changes of land use types and vegetation in the MRYR before and after the implementation of ecological projects, especially the differences of dynamic changes of vegetation between plantations and natural forests and evaluating and measuring the effect of ecological protection projects, could provide an important scientific basis for evaluating the ecological benefits of ecological projects and guiding the construction and layout of plantations projects.
Vegetation is very sensitive to climate change [
23,
24]. At present, scholars at home and abroad have carried out a significant amount of research on the impact of climate on vegetation change [
25]. In previous studies, many researchers used correlation analysis, multiple linear regression, and other methods to reveal that precipitation and temperature were the main meteorological factors affecting vegetation change [
3,
26,
27,
28]. However, there were also relevant studies concluding that vegetation changes were not only related to precipitation and temperature, but also that other meteorological factors (such as sunshine hours and relative humidity) had different effects on vegetation change [
29,
30,
31]. The slow process of vegetation growth determined that the responses of vegetation change to meteorological factors had a certain lag and cumulative effect [
32]. The responses of vegetation to meteorological factors had spatial heterogeneity in different spatial scales and vegetation types [
26,
33,
34,
35]. The results showed that NDVI was increasing year by year. The Yangtze River Basin is rich in water and the heat condition is the limiting factor affecting vegetation growth [
36]. Yi et al. studied the responses of vegetation to climate change in the MRYR and pointed out that vegetation had an obvious time lag to climate change. But at present, there have been few studies comparing the dynamic characteristics of NDVI and its responses to climate change between plantations and natural forests in the same region [
37]. Understanding and revealing the internal relationship between different vegetation types and meteorological factors is of great significance for regional ecological protection and management [
38].
Remote sensing data can be used to identify vegetation types, mainly using the differences of spectrum, texture, and other characteristics of different vegetation types. Texture can be understood as the spatial change and repetition of image gray, or the repeated local patterns (texture units) and their arrangement rules in the image. Haralick first proposed the gray level co-occurrence moment (GLCM) [
39]. This method uses a spatial co-occurrence matrix to calculate the relationship between pixel values and uses these values to calculate the second-order statistical properties of the matrix. GLCM is a widely used texture statistical analysis method and texture measurement technology. In the MRYR in China, plantations usually have single biodiversity and exist in patches of one or two plant species, such as Masson Pine, Chinese fir, and Chinese thuja. Compared with natural forests, this kind of plantation has more regular texture characteristics. Similarly, the plantations in eastern Thailand also have special texture features, which makes it possible to use texture features to identify their distribution law [
40]. In southern Africa, the texture features of vegetation are used to identify invasive species [
41]. At present, the GLCM has been widely used in image retrieval and classification, and it has greatly improved the accuracy of image retrieval and classification [
42].
In this study, Hubei Province, Hunan Province, and Jiangxi Province in the MRYR are taken as the research objects, and four Landsat TM/ETM/OLI remote sensing images in 1999, 2005, 2010, and 2015 are taken as the basic data source. Based on the GLCM and spectral features, the neural network supervised classification method was used to classify the land use types in the study area, and the forest land was further divided into artificial forest and natural forest for analysis. Our specific objectives are: (1) to analyze the temporal and spatial change characteristics of land use (including natural forest and plantation) in the study area from 1999 to 2015; (2) to investigate the characteristics and evolution trends of NDVI of different vegetation types in the MRYR; (3) to analyze the relationship between meteorological factors and NDVI at interannual and monthly scales. This study reveals the dynamic changes of land use/cover types and the response mechanism of vegetation to climate change in the MRYR, especially natural forests and plantations. Our research can provide a scientific reference for regional ecological environment construction and protection measures.
2. Study Area
The MRYR includes Hubei Province, Jiangxi Province, and Hunan Province (24°25’ N–33°16′ N, 108°24′ E–118°23′ E), with a total area of 564,600 km
2 (
Figure 1). There are flat plains, hills, and steep mountains in this area. In the long process of development, traditional agriculture, forestry, and fishery production and splendid cultural and artistic landscape have formed in this area, which has had an important impact on the local land use [
43,
44]. The area over the general terrain is mountainous. The terrain is high in the west and low in the east, and the average altitude is approximately 1497 m [
36]. The MRYR is rich in forest resources. In 2018, there were 174.38 million permanent residents in the MRYR, accounting for 12.7% of Chinese total population. The annual gross regional product (GDP) reached USD 1479.50 billion, accounting for 10.9% of the Chinese total GDP [
45].
The plantations in the study area have a simple diversity of species, often consisting of one or two species of trees, such as
Chinese fir,
Masson pine, and
Chinese thuja, etc. (
Figure 1a–c). The natural forest is rich in plant diversity, mainly composed of
Cinnamomum,
Ligustrum, and
Koelreuteria, etc. (
Figure 1d–f). The vegetation under these plantations is relatively uniform and has regular texture characteristics, which are different from natural forests.
5. Discussion
From 1999 to 2015, the land use types in the study area changed significantly. The landscape proportion of built-up land increased by 8.21%, the cropland decreased by 4.36%, and the forestland increased slightly, but the proportion of natural forests decreased. Other scholars’ research showed that the built-up land in the Yangtze River Delta had increased by 8.68% in the past 10 years, which was similar to the research results of this study [
64]. In other urban agglomerations, such as the Pearl River Delta, the built-up land increased by 9.98% in the past 16 years, and the cropland and forestland decreased by 7.12% and 2.26%, respectively [
65]. Cropland was the first type of land use to be occupied in the process of urbanization [
66,
67]. The irregular expansion of urban scale would inevitably lead to the transformation of the agricultural landscape. In the period of rapid urbanization, every 1% economic growth will occupy about 200 km
2 of cropland, which is about eight times that of the land occupied by 1% economic growth in Japan. By the end of 2010, the total amount of cropland in China was less than 1.22 × 10
6 km
2, which was close to the red line of 1.20 × 10
6 km
2 of cropland in China [
68]. The importance of basic farmland protection should be paid attention to by relevant departments.
In the past 17 years, the NDVI of vegetation in the MRYR showed an overall upward trend (improvement area accounted for more than 3/4) (
Figure 3 and
Table 4). This is consistent with the research results of the NDVI change trend of different scales in Hubei Province [
69], Hunan Province [
70], Jiangxi Province [
71], and the Yangtze River Basin [
72]. The annual mean NDVI values of the Yangtze River Delta, Pearl River Delta, and other coastal urban agglomerations are mostly between 0.3 and 0.5. Compared with them, the NDVI in the MRYR was relatively high. First, from 2004 to 2005, the climate of each province in the study area was abnormal, which showed that the winter lasted for a long time, the temperature was extremely low, and the phenomenon of “late spring cold” appeared in spring, which led to the extremely poor growth of winter vegetation and the sharp decline of NDVI. Second, from 2010 to 2011, the NDVI of vegetation decreased in all seasons, which was due to the serious impact on vegetation growth caused by the large-scale drought in this year. At the same time, it can be seen that the impact of drought on natural forest has a certain lag and is smaller than other vegetation types, which also shows that the stability of natural forest ecosystems is stronger to a certain extent [
73]. The stand structure of mature plantations in China was single and the regulation capacity of the ecosystem was low. The average volume was only 71.55 m
3, which is only 41% of mature natural forests. It can be seen that there was still much room for improvement of plantations in the study area, and its ecosystem service function should be improved to ensure the sustainable and healthy growth of plantations.
In addition, different spatial resolutions of NDVI would definitely lead to different research results. In this paper, Landsat images with a resolution of 30 m were used to obtain the boundary of different land uses/land cover, and 1 km NDVI was used to depict the dynamic change of land cover, which had certain limitations. In the future, open resources with a higher resolution such as 250 m and 500 m could be considered, and Landsat images data with a resolution of 30 m could also be used to calculate and obtain NDVI values to further study the vegetation dynamic changes in the middle reaches of the Yangtze River.
Nemani et al. and Liu et al. considered that hydrothermal climate conditions were the driving factors affecting the spatial pattern of land vegetation cover [
20,
74]. This study showed that relative humidity was the main climatic factor affecting the growth of different vegetation types in the study area in terms of interannual variation, and the partial correlation analysis between relative humidity and NDVI of each vegetation type showed a significant negative correlation. In addition, the correlation between cropland and precipitation was significant (
R = 0.149,
p < 0.05). This was consistent with the research results regarding the response of vegetation NDVI to climate in east China and its surrounding areas [
75,
76,
77]. The reason for this might be that the precipitation in the study area was rich enough to meet the needs of vegetation growth, and the difference of heat was the main driving factor for the difference of NDVI. The results showed that the sunshine hours in January, August, and December had significant positive effects on the vegetation growth of natural forests, while the rainfall and relative humidity in January, May, August, and December had negative effects on the vegetation growth. NDVI was positively correlated with precipitation in summer and autumn, negatively correlated with precipitation in spring, and positively correlated with sunshine hours. It showed that moderate precipitation could promote the growth of crops, and high humidity would inhibit the growth of crops and vegetation. In addition, each meteorological factor had an obvious lag effect on NDVI. This was consistent with the results confirmed by Bao et al. from global, regional, and other multi-scale studies, and the feedback of vegetation cover on climate change has a certain lag effect [
78].
6. Conclusions
With the urbanization process in the MRYR in the past 17 years, on the one hand, the area was greatly disturbed by human activities, with the rapid growth of built-up land and the sharp decline of cropland. On the other hand, the implementation of Chinese ecological protection projects (grain to green, construction of Yangtze River shelterbelt, etc.) and the promulgation of various management policies played a great role in the ecological protection of the MRYR. Forestland is the main part of the land use/cover types (more than 50%), and it was increasing in the period, but it is worth noting that the area of natural forests has decreased (about one tenth), and the proportion of plantations continues to increase. From 1999 to 2015, the vegetation situation in the MRYR gradually improved, especially the natural forests, accounting for 45.39%. The area with an unclear future change trend of plantations accounted for the highest proportion (more than half). According to the relationship between climate factors and vegetation growth, relative humidity had significant negative effects on NDVI (p < 0.05), especially on cropland. On the inter-monthly scale, climate factors (temperature, precipitation, relative humidity, and sunshine hours) had significant lag effects on natural forests and plantations. Sunshine hours promoted vegetation growth positively, while relative humidity had negative effects. Although the overall development trend of forestland in the study area was good, natural forests and plantations were facing problems, respectively. We should protect natural forests and prevent the loss of those with strong ecosystem services and replace those that do not with plantations with a single species diversity.