4.1. Land Cover Change Analysis
From Figure 7
, the degradation was mainly located in the areas near the administrative center of the prefecture government Mengzi and the administrative centers of the counties north of the Red River. The NOAA VIIRS night light data from May 2015 was used to overlay with the degradation data, which clearly shows the correlation between the degradation and the urban expansion. In the densely populated urban center areas, the vegetation cover of the cultivated land decreased significantly. This is inseparable from the urbanization of Honghe Prefecture.
The urbanization process of Honghe Prefecture is in synchronization with China’s rapid development. Rural people increasingly work in urban centers. When they earn enough money, they buy real estate from where they originated, which requires a great deal of land to build more apartments around the county center. The investments in real estate development and the urban infrastructure construction caused a sharp reduction in the cultivated land resources around the center, which is one of the important causes of land degradation in Honghe Prefecture, which is driven by the population growth and migration.
The fastest changing area is at the junction of Mengzi and Gejiu, which may be due to two reasons. First, the Honghe Prefecture government began to relocate in 2003, and there were a large number of factories and enterprises moving with the government agencies. Therefore, the demand for the land near the new administrative center of the government increased dramatically. Second, Gejiu is the tin capital of China, and Datun is one of the main producing areas of tin. With strong financial support, the government has planned the Datun New District. This area is changing rapidly with the two benefits of being close to the prefecture government and establishing a new district.
Google Earth was used to validate the land cover change. Figure 8
shows the image near G326 (China National Highway) at the junction of Mengzi and Gejiu on 10 November 2006, from which we can see that most of the area is cropland. In contrast, Figure 9
shows that man-made buildings became the main type of land cover in this area on 23 January 2015.
The urban expansion and the construction of the new functional areas directly and indirectly occupy a large number of land resources, which have become important factors in the land resources degradation in Honghe Prefecture. The driver of the land degradation in Chenggong District, Kunming City, Yunnan Province is similar to that of this region [41
]. The urban expansion of Honghe Prefecture mainly occupied croplands and grasslands around urban areas, a rule that also applies to the farming-pastoral ecotone of northern China [42
]. In the process of industrialization and urbanization of the Shazand Watershed in Iran, a large number of grasslands and rain-fed agricultural lands were converted into artificial areas [43
With the reduction of croplands and the continuous population growth, cutting shrubs and reclaiming grasslands became a measure to compensate for the reduction of croplands [44
]. A total of 6.47 km2
of forests and 2.23 km2
of grasslands in Honghe Prefecture were converted into croplands in 10 years. Unlike the practice of felling wood as fuel in Ethiopia [44
], coal is the main fuel in Honghe Prefecture. The deforestation in Tanzania is due to the energy demand for curing tobacco leaves [46
]. Honghe Prefecture is the second main tobacco producing area in Yunnan, where coal and electricity are mainly used for flue-cured tobacco.
Another area with significant changes is in the middle of Mile. It is distributed along a stripe pattern, which is consistent with the direction and location of the G80 National Highway, which was completed in 2012. Based on the above reasons, human land use is a dominant driver of the land degradation in Honghe Prefecture.
The largest increase in land improvement in the land cover change is from the conversion of grasslands to forests, with an area of 227.58 km2, accounting for 94.27% of the total improvement area of 241.42 km2, mainly distributed in Honghe (county), Lvchun, Shiping, Jianshui, and the south of Jinping. Most of these forests occur in remote mountainous areas in each county, which may be related to the Grain for Green Program (GGP) launched in China in 1999.
The GGP is the largest ecological restoration project in China and is closely related to land use and cover change (LUCC) [47
]. The project accelerated the process of national afforestation, and the forest coverage rates in the project areas increased by an average of more than four percentage points [48
]. An article of Nature Sustainability stated that China alone accounted for 25% of the global net increase in leaf area with only 6.6% of the global vegetated area from 2000 to 2017. The greening in China is from forests (42%) and croplands (32%) [49
]. This program underlines that government policy can play an important role in the modification of landscapes [45
Land expropriation is a significant source of revenue for municipal governments. To improve the government’s fiscal performance, the newly amended Land Administration Law grants greater autonomy to local governments over land conversions and farmland acquisitions. The new land policy will accelerate the conversion of good-quality farmlands into artificial areas, and the lost farmlands will be made up of grasslands and forests, aggravating land degradation and destroying the local ecosystem. The Honghe prefecture government should reduce the scale of conversion from cultivated land to construction land year by year, to protect high-quality arable land. They should also strengthen the water conservancy construction to improve the quality of land, use resources scientifically, stabilize the scale of the city, and cut down on the demand from the natural environment.
4.2. Land Productivity Analysis
According to our results, the changes in land productivity occurred mainly in the forests, the grasslands, and the croplands. Degradation or improvement mainly occurred within the same land class. The overall trend showed that, regardless of the land cover class, the area of improvement was greater than the area of degradation (Table 10
), which indicates that the land productivity improved over time. This is consistent with the changes in the characteristics of the three land cover classes in China during the same period as derived by Wang Zhen et al. [50
]. In recent years, the Chinese government attached great importance to environmental protection. Through returning farmland to forests, returning grazing land to grasslands, and the development and use of desert areas, the vegetation coverage indices of all land cover classes increased significantly.
Although there is a lag in the response of the NDVI to the temperature and precipitation in the Red River Basin [51
], the lag time is less than 1 year. The lag effect can be reduced or eliminated by calculating the average annual NDVI each year from 2005 to 2012 and the 2013–2015 average value. However, geological disasters caused by rainfall may cause sharp changes in the local NDVI value. The degradation of the land productivity in Jinping mainly occurred on the top of the mountain over 2000 m above sea level. Disasters caused by rainfall may be the main cause of ecological degradation in high-altitude areas [52
]. The special geographical environment and complex geological structure of Honghe Prefecture and even Yunnan Province, coupled with the unreasonable exploitation and utilization by human beings, brought more frequent natural disasters. In particular, since the 1990s, the collapses, landslides, and debris flows in Yunnan Province have shown an increasing trend, causing huge losses [53
As the area distribution of land productivity degradation north of the Red River overlapped very well with the night light data, we infer that this is related to the distribution of the county centers. These areas also have densely distributed agricultural land and populations [54
]. In addition, the degradation of southeast Mile is also significant. Since 2005, we used remote sensing data to monitor the planting distribution of the cash crops north of the Red River. We found that the cash crops tended to shift from low to high altitudes, and from the basins to the slopes and mountains.
Cash crops with a smaller average area, in particular Panax notoginseng
and the greenhouse vegetables, might be the cause of land productivity degradation in the grasslands, the forests, and the croplands. Panax notoginseng
prefers shaded environments, distributed in the forests or the grasslands, and is often covered with black plastic nets (Figure 10
). Figure 11
and Figure 12
show images of the same area in Luxi County before and after planting Panax notoginseng
in Google Earth. Greenhouse vegetables are mainly distributed in the fields and covered with polyethylene films, which affect the NDVI acquired from the satellite images. Panax notoginseng
and vegetables are cultivated in small fields covered with thin films and shade nets, which will lead to a lower assessment of the land productivity. In addition, climate change and geological factors can also result in the NPP degradation of irrigated farmland [43
The NDVI decreased in areas with high economic development near administrative centers. In contrast, the NDVI increased significantly in the areas with low human activities [55
]. Benefiting from the implementation of the GGP, forests and grasslands in the remote areas were well protected. An upward trend of NDVI indicates that the implementation of ecological projects effectively improved the regional environment [54
4.4. SDG 15.3.1 Indicator Land Degradation
According to the principle of “One Out, All Out”, the result of the SDG 15.3.1 land degradation can be extracted by merging the degradation areas of the three sub-indicators. From these data tables (Table 6
, Table 7
, Table 8
and Table 9
), we concluded that there was an overlap among the degradation areas of the sub-indicators. Among the three sub-indicators, the area of land productivity degradation was the largest, which accounted for 98.7% of the total SDG 15.3.1 land degradation area. Land productivity degradation mainly occurs internally, which indicates the need for good plans to protect the forests and the grasslands, as well as crop planting programs to prevent further degradation.
As one of the important factors of human activities, urbanization is the dominant driver of land cover degradation in Honghe Prefecture, and road construction and mining development have directly occupied croplands, grasslands, and forests. Mining development also consumes a great deal of water resources, which indirectly leads to a change in vegetation [61
]. According to our field survey, urbanization and population migration in Honghe Prefecture did not cause land abandonment, which was observed in Srpska [62
]. Despite the residents’ great demand for croplands, they still responded to the national policies and converted part of the croplands into grasslands and forests.
Land degradation shows obvious urban–rural differences. Urban land degradation is serious; however, the land in rural areas demonstrated a clear trend of improvement. Serious land degradation occurred in Mengzi, Gejiu, Kaiyuan, Mile, and Jianshui, which are in the top 100 counties of west China with better economic development, while the area of land improvement in the national-level poverty-stricken counties, such as Yuanyang, Honghe, and Jinping, is limited.
Comparing the land degradation results is difficult due to the different methods and evaluative indicators employed and the lack of uniform standards [63
]. The guidance provided by UNCCD and the SDG implementation of Trends.Earth are conducive to the unification of methods and parameters among different countries and regions. This will improve the consistency of assessing land degradation for reporting on SDG indicator 15.3.1. We used the recommend datasets in Honghe Prefecture. LUCC datasets with the highest possible precision, high-spatial-resolution NDVI datasets, and detailed SOC datasets are encouraged to be used for land degradation as they will improve the accuracy of reports on SDG indicator 15.3.1.